9th International Conference on ICT for Sustainable Development: Full Schedule

Authors - Poonam Sachin Kadlag, Jatinderkumar R Saini, Deepali Prakash Suryavanshi
Abstract - A study was conducted to assess teacher trainees' sentiments on the key parameters of the Teacher Education Programme curriculum. Interviews with 10 principals from Teacher Education Institutions identified five key parameters integral to curriculum evaluation: Digital Tools, Pedagogical Techniques, Special Education, Interdisciplinary Learning and Active Learning. The study used Vosviewer to identify 228 research studies and PRISMA model to filter the related reviews. The study used Azure Machine Learning tools to conduct sentiment analysis of the feedback from 521 teacher trainees across 52 TEIs in Maharashtra, India, using bilingual Google Forms and NLP techniques to analyse textual data and identify polarity. The result shows the curriculum's positive aspects align with current educational trends, demonstrating the program's commitment to preparing educators for evolving teaching methods.

Paper Presenter

Deepali Prakash Suryavanshi

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Design and Evaluation Of Smart Energy Management System For EV Applications

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Suhas M, B Sahithi Reddy, Ashwini N, Medini S Kalkur, Jyothi TN, Venugopal N
Abstract - Electric vehicles (EVs) have emerged as a promising solution to address environmental concerns and reduce reliance on fossil fuels. However, the performance and longevity of EVs are heavily dependent on the effectiveness of their battery management systems (BMS). A smart BMS plays a crucial role in optimizing battery performance, ensuring safety, and extending battery life. This paper delves into the design and implementation of a smart BMS for EV applications. The proposed BMS incorporates advanced algorithms and techniques to accurately monitor and control battery parameters. The system utilizes real-time data acquisition and processing to optimize charging and discharging strategies, ensuring efficient energy utilization and extending battery lifespan. The proposed method employs the Unscented Kalman Filter(UKF) algorithm to estimate State of Charge (SOC) based on the battery’s real-time voltage ,current, and temperature measurements . The Voltage, Current and Temperature parameters are utilized to capture the nonlinear behavior of the battery, accounting for the variations in battery performance under different operating conditions. A simulation study is conducted, and its results demonstrate the effectiveness of the UKF-based SOC estimation method. The same approach is used in the hardware implementation. This paper provides insights into high-frequency transformer design, potentially useful for Arduino system power supply construction, and suggests future research on battery management system integration for improved efficiency and accuracy.

Paper Presenter

Ashwini N

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Enabling a Sustainable Shift: Consumer Drivers for Bio-plastic Coffee Cup Usage in India

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Abdul Rehman Shaik, Ishaq Ahamed S, Alka T A, Suresh M
Abstract - The study is an exploration of bioplastic coffee cup usage in India with a focus on environmental sustainability. This research aims not only to identify but also to comprehensively analyze the critical drivers that influence the bioplastic coffee cup usage as an alternative to traditional cups by reviewing literature, and the perceptions of regular coffee cup users. Using Grey Influence Analysis (GINA), the research aims to reveal and quantify the complex connections among these identified factors. The study urgency lies in the increase in the concern for environmental sustainability, and plastic pollution. Bioplastic from renewable sources is a better way to reduce plastic consumption. The burning of the Indian population is another rationale for doing this exploration. The data is collected from 21 coffee consumers who use bioplastic coffee cups regularly and the collected data is analyzed with the help of GINA. The study tries to uncover and quantify the major influencing factors and their influence. The findings and future research topics of this study will provide insights to the policymakers, food industry practitioners, sustainable advocates, entrepreneurs, and researchers for policy framing, and further research. The study is important and relevant in the sustainability context as well as the growing discussion on the circular economy.

Paper Presenter

Ishaq Ahamed S

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Enhancing Advanced Technology for Baby Supervision System

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Murugesan M, Mounish kumar P, Shofiya A, Vasanth A
Abstract - Intelligent Smart cradle tracking childcare is necessary, parenting has become more difficult in the modern day, especially for working women. Monitoring their child's health is becoming more and more difficult for parents. The smart infant system, which is based on the Internet of Things, has fixed the baby monitoring issues and is providing parents with real-time notifications. The suggested setup incorporates all required Intelligent Smart tracking functions, including multiple sensor cry detection, identify wet surface by wet sensor and ambient temperature and humidity measurements. Controllers linked to the Internet send sensor data to the server. Parents are able to keep an eye on their child's cot activities. They can also monitor the humidity and temperature of the space in real time. By employing the Intelligent Smart tracking system, working parents may better manage their time and provide for their infants at the same time. If an aberrant conduct is discovered, a message is delivered to the parents IOT application so they may respond appropriately, also we added a new feature called sms alert to handle the absence of viewing the web application.

Paper Presenter

Vasanth A

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Impact of Informal Learning on Employee Engagement: A study among Indian professionals

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Halin Manoj, Nanda S, Rhea Rajendran, Vandana Madhavan
Abstract - This study aims to assess employee perceptions of informal learning opportunities within an organization, including their accessibility, relevance, impact on development, and overall satisfaction, alongside general workplace sentiment regarding recognition and growth opportunities. Informal learning is of great importance, given its prominent role in employee performance improvement. Compared to traditional training, the enhanced interactions between employees and the presence of flexible learning and information-sharing options contribute immensely to informal employee learning. This plays a major role in improving employee performance and engagement. For this study, data was collected through surveys distributed to Indian professionals across various industries to gather insights into how management supports informal learning practices. The survey employed random sampling to explore the application of informal learning skills in work contexts and identify prevalent challenges respondents face. The data analysis revealed a positive relationship between employee engagement and opportunities for informal learning through interaction with coworkers and supervisors. Additionally, a sense of value, support for informal learning, work enablement, and social support impacted the strength of relationships between informal learning practices and employee engagement.

Paper Presenter

Halin Manoj

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Optimising Life Expectancy Rate Using Different Regression Models

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Rishav Prajapati, Harsh Sharma, Rohan Gupta, Parneeta Dhaliwal
Abstract - As we all know in the present the life expectancy rate for rich nations is becoming better as compared to that for poor countries, to measure the impact of various parameters on the rate of life expectancy. We are working on analyzing the “Kumar Rajarshi “Life Expectancy (WHO) dataset. the dataset consists of various attributes through which we can find better results in poor countries. The measure of life expectancy provides very crucial information about health at a given population level, that can be used to apply in government policies to help its people in the best way. The research paper aims to make people grow in a more comfortable zone than their earlier generations.

Paper Presenter

Rishav Prajapati

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Optimizing the User Experience for Beauty E-commerce in India

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Aishwarya S Raj, Anitia Sam, Govind U, Parvathy Venugopal
Abstract - Purpose: The aim of this study is to examine the user experience (UX) of mobile applications and websites related to beauty in India. It seeks to ascertain how well these platforms meet the demands of the nation's consumers of beauty products. Design, Methodology, and Approach: This study uses a qualitative methodology, with questionnaires serving as the main means of gathering data. A sample of Indian users of beauty products who regularly use online beauty platforms were given surveys. The poll was centered on how users interacted with different features, such as search capabilities, product details, comparison tools, checkout procedures, and order monitoring. Findings: Study highlights the main advantages and disadvantages of Indian beauty platforms' user experiences. The results show which areas these platforms perform exceptionally well in satisfying user needs: Convenience: Compared to conventional brick-and-mortar establishments, online buying is a convenient option. Product assortment: Compared to physical stores, beauty platforms offer a greater assortment of products. But the study also identifies opportunities for development: Search Functionality: Users may have difficulty locating particular products due to restricted search features or a lack of efficient filters. Product Information: Product descriptions may be vague or devoid of information regarding ingredients, advantages, or how to use them. Comparison Tools: It's possible that platforms don't provide users with sufficient comparison tools to quickly assess the features and costs of various products. Research Restrictions/Implications: Because this study relies on self-reported survey data, bias may be present. Furthermore, it's possible that the sample size is not representative of all Indian consumers of cosmetic products. Notwithstanding these drawbacks, the study offers insightful information on the online beauty platforms' user experience in the Indian market. Practical Implications: The research's conclusions have applications for Indian beauty e-commerce companies. These companies can improve their platforms in a number of ways by comprehending the requirements and problems of their users: Improve search capabilities by adding sophisticated filtering choices. Give thorough product details, such as ingredient lists and in-depth descriptions. Provide strong comparative tools to help consumers make well-informed purchases.

Paper Presenter

Aishwarya S Raj

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Surveying Advancements of 5G Technology and Network Evolution with MEC Integration

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Shreya Devagiri, Vijayalakshmi M
Abstract - The rapid progress of fifth-generation (5G) technology has transformed the networking and telecommunications field, introducing unprecedented data rates, low latency, and the capability to unlock innovative applications. This paper emphasizes the importance of ongoing evolution, with a specific focus on achieving seamless mobility and integrating Multi-Access Edge Computing (MEC) into 5G networks. To address these requirements, our research conducts an extensive survey, exploring various issues that arise in 5G networks and presenting state-of-the-art solutions. We thoroughly investigate challenges such as network congestion and security vulnerabilities to provide a comprehensive view of the current situation. The article underscores the significance of MEC integration in enhancing 5G capabilities, enabling efficient computation and data processing at the network edge. Additionally, we outline a roadmap for future research, suggesting possible directions for study and development to address emerging problems. This research provides crucial insights into the current status of 5G networks and serves as a roadmap for future initiatives aimed at maximizing the performance, flexibility, and security of 5G technologies.

Paper Presenter

Shreya Devagiri

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Unraveling the Foundations: Exploring Blockchain Technology and its Security Challenges

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Shailender Kumar Vats, Prasadu Peddi, Prashant Vats
Abstract - Blockchain technology has emerged as a revolutionary concept with transformative potential across various industries. Its decentralized and immutable nature offers promising solutions to longstanding issues in data management, finance, supply chain, and beyond. However, alongside its promise, blockchain also presents significant security concerns that must be addressed to fully harness its benefits. This research paper provides an introductory exploration of blockchain technology, delving into its fundamental principles and mechanisms. Additionally, it examines the multifaceted security challenges inherent in blockchain systems, including issues related to consensus mechanisms, smart contracts, privacy, scalability, and regulatory compliance. By comprehensively understanding both the potential and the risks associated with blockchain technology, stakeholders can make informed decisions to navigate this evolving landscape effectively.

Paper Presenter

Prashant Vats

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

V2V2I VANET Data Offloading Path Using Reinforcement Learning

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Raneena Raoof, Santhameena S
Abstract - The importance of Vehicle-Ad Hoc Networks (VANETs) lies in their ability to improve traffic monitoring, enhance road safety, and provide in-car infotainment. However, these networks face significant challenges, such as frequent disconnections between vehicles due to high mobility, limited bandwidth, roadside obstructions, and a scarcity of roadside units. Effective routing becomes a critical aspect in addressing these issues. In this paper, a novel approach utilizing a reinforcement learning strategy based on the Q-learning algorithm is presented. The objective is to use RL to enable vehicles to establish and maintain a stable connection even in the presence of multiple roadside units, thereby mitigating the problem of frequent disconnections. This innovative solution aims to enhance the overall performance of VANETs, & hence contributing to more seamless and efficient V2V2I communication among vehicles on the road.

Paper Presenter

Raneena Raoof

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Assessing the effective utilization of LMS in Higher Education

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Arjun B Raj, Sudani Sai Himavanth, Rojalin Patri
Abstract - The purpose of the study is to identify the underutilized parameters and to focus on the areas for improvement regarding LMS in higher education. The fuzzy logic approach has been used to assess the effective utilization of Learning management systems in higher education. A sample size of 20 is taken from each faculty and student group. The finding suggests that twelve attributes have been underutilized. Some of these attributes include server performance, ease of content upload, etc. The study shows that the current effectiveness of LMS is showing “Moderately effective”. The study only focussed on higher education like educational universities, and higher education schools regarding the utility of LMS in higher education.

Paper Presenter

Arjun B Raj

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Consumer awareness and willingness towards Smart Home Automation

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Rahul Dhaigude, Ruby Chanda
Abstract - This study delves into the realm of home automation, leveraging technology for streamlined household tasks, emphasizing efficiency and security. Current trends encompass ecosystem expansion, voice control, energy efficiency, and a strong focus on security. However, the study identifies significant challenges, particularly in the domain of data security and privacy, prompting academic discourse on encryption, privacy concerns, and regulatory compliance. Examining responses from 62 questionnaire respondents, the study sheds light on issues such as device heterogeneity, communication protocol standardization, and the imperative need for user awareness. Despite these challenges, the home automation sector presents lucrative opportunities, as evident from consumer willingness to invest in smart home devices. Overcoming barriers requires collaborative efforts, innovative solutions, and an approach aligned with user demands for accessible and affordable technology.

Paper Presenter

Rahul Dhaigude

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

DeepVerify: Ensuring Authenticity through Deepfake and Liveness Analysis

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Devanshi Shah, Rachit Shah, Yash Bhadania, Priteshkumar Prajapati, Parth Shah, Dharmendrasinh Rathod
Abstract - With technology advancing, Deep Fake AI techniques make manipulating faces in images and videos easy, notably through precise swapping to create an authentic appearance. Therefore, this research aims to create fake images using traditional and generative adversarial networks (GAN) methods. Additionally, manually generated datasets are incorporated into existing datasets, and using four deep learning algorithms from Convolution Neural Networks (CNN), they are trained and tested to improve accuracy across different datasets. As per outcomes, the ResNet algorithm results in superior accuracy between 98.93% and 99.38% in all three datasets. It has been integrated into an application developed to verify the authenticity of uploaded images. Furthermore, the research introduces an anti-spoofing technique to verify the authenticity of individuals during video calls. It uses real, publicly available videos and images to create composite videos where the maximum portion of the face remains legitimate and only synchronized lips are AI-generated, making it difficult to differentiate between fake and real video. Hence, the anti-spoofing mechanism analyzes the person’s liveliness when the camera is activated, distinguishing between genuine communication and scripted playback. Nevertheless, this experimental study aims to enhance detection accuracy by training and testing datasets of deepfake images and videos, ultimately improving security performance and robustness. These advancements are integrated into an application, enabling users to verify the genuineness of individuals in both images and video calls.

Paper Presenter

Yash Bhadania

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Driving Sustainability: The Impact of Green Supply Chain Management Practices on the Indian Automotive Industry

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Akhil Krishnan, Darshan Muralidharan, Harikrishnan R
Abstract - The paper emphasizes the implementation of the green supply chain management (GSCM) strategies in the Indian auto industry, emphasizing particularly the society of Indian automobile manufacturers (SIAM) and relevant government policies. The literary review is an inclusive view of the welfare position that can be attained by incorporating the GSCM strategies to several subjects like for example the productivity and the top performance of the industry. One will compare documents between SIAM's reports covering production, domestic sales and exports from the years 2003 to 2023 to be able to outline the trends with regards to sustainable supply chains. The results of this storm, in general, show a significant increase in manufacturing and sales volume combined with a tightening and implementation of green projects which both SIAM and governing bodies are spearheading. In summary, the application of effective industry policies by SIAM and the government have greatly helped maintain sustainability growth in automotive without its competitiveness being jeopardized. Top of the list lies the development of study data collection instruments through which one can obtain a deeper insight into the headway that is made by firms in the track of implementing GSCM and will advise how they can be better equipped through some tailored intervention plans and policy measures.

Paper Presenter

Akhil Krishnan

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Enhancing Phishing Website Detection through Multi-Classifier Integration and Comparative Analysis of Data Mining Techniques

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Rahul Dhaigude, Ruby Chanda
Abstract - Phishing, a prevalent cyber-criminal activity, poses significant threats to individuals and organizations by luring users into disclosing sensitive information through deceptive means. This research aims to address the challenges of phishing website detection by conducting a comprehensive comparative analysis of various data mining techniques and feature selection methods. Furthermore, the study proposes the development of a multi-classifier integration model to bolster the detection process and mitigate the risk posed by phishing URLs. By leveraging multiple classification techniques, including feature selection, the proposed model seeks to enhance the accuracy and efficiency of identifying malicious websites. The ultimate goal is to identify the most suitable algorithm for classification, thereby fortifying defenses against phishing attacks and safeguarding critical data in an increasingly internet-driven society.

Paper Presenter

Rahul Dhaigude

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Error Confinement Mechanism in CAN Bus

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Bhagyashree Kinnal, Prerana.B.Hubli, Nalini.C.Iyer
Abstract - A controller area network (CAN) bus connects all ECUs in contemporary automobiles, allowing them to communicate and carry out tasks. Modern automobiles’ increased connectivity and complexity have raised serious questions about their security, though. Because they employ a broadcast communication technique and lack authentication, CANs are especially vulnerable to attacks using message injection. The controller area network (CAN) in automobiles is an extremely useful tool for both attack and defense. The purpose of the bus-off attack is to put an electronic control unit (ECU) in the bus-off state and use the fault confinement of the CAN to prevent it from using the bus. The paper presents a simulation framework for Controller Area Network(CAN) utilizing the MCP2515 CAN controller. To simulate real-world situations, the program introduces error simulation. Error states are divided into three categories: ACTIVE, PASSIVE, and BUS OFF. Error state transitions are based on the error counter, which is used to track and react to errors. Furthermore, the program includes error recovery mechanisms that demonstrate how to reset the MCP2515 and get it back to normal operation if it encounters a BUS OFF state.

Paper Presenter

Prerana.B.Hubli

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Generative AI for Predicting Employee Engagement in HR Analytics: A Bibliometric Analysis

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Reena Lenka, Ruby Chanda
Abstract - In recent years, generative artificial intelligence (AI) has emerged as a powerful tool that has the potential to revolutionize HR analytics by offering innovative solutions to predict and enhance employee engagement. The study Generative AI for Predicting Employee Engagement in HR Analytics was done to focus on the fact that generative AI can help HR managers improve employee engagement. To identify the research gap and investigate the context for future GenAI research, this study, which delves into current research articles in Generative AI, HR management, and employee engagement, conducts a thorough bibliometric and thematic analysis to integrate findings from both modern academic research fields and business application spheres. By identifying key trends, seminal studies, and gaps in the literature, this analysis aims to shed light on the evolution and potential future directions of research in this emerging domain. The study concludes with recommendations for more research, highlighting the significance of fusing technological know-how with a human-centered perspective.

Paper Presenter

Reena Lenka

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Lane Keeping Assistance System

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Narra Alekya, Rashmi Koppad, Prabha.C.Nissimagoudar, Gireesha H.M, Nalini .C.Iyer
Abstract - Lane Keeping Assist Systems (LKAS) play a pivotal role in modern driver assistance. This paper presents a Lane Keeping Assist System utilizing sensor fusion and computer vision for accurate lane detection and corrective steering. The system’s architecture and control strategies are analyzed through simulations and real-world testing, addressing challenges like adverse weather conditions. User studies demonstrate positive effects on driver behavior and safety. This research contributes insights into LKAS design, implementation, and user impact, advancing autonomous driving technology.

Paper Presenter

Narra Alekya

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Need a Guide by my Side not a Sage on Stage: Chat GPT in Learning

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Pradnya Vishwas Chitrao, Pravin Kumar Bhoyar, Rajiv Divekar
Abstract - The main focus of the third decade of the twenty-first century has been the debate surrounding students' use of Chat GPT for academic purposes. The most recent debate began when the start-up Open AI revealed Chat GPT algorithms in November 2022 (which stands for "Generalized Pretrained Transformer" algorithms). Artificial intelligence (AI) is used by Chat GPT to generate outlines and academic writings in answer to prompts. Many academics fear that Chat GPT may undermine the core purpose of higher education because of its amazing potential. There is concern that it will eradicate pupils' mental endeavours, ultimately leading to the death of creativity and a lot of plagiarism Through interviews, this study attempts to learn what MBA students think about using Chat GPT and the manner in which it should be used to overcome its ill effects. It also looks for ways that teachers might use AI tools to enhance the learning experience. Additionally, the study makes use of secondary materials. This report is significant since many prestigious colleges are prohibiting students from using AI in their submissions, and businesses are turning to using different AI gadgets to streamline their work processes and save down on labor. Additionally, it is anticipated that the study will provide light on how teachers might best apply recent advances in AI to enhance the learning process.

Paper Presenter

Pradnya Vishwas Chitrao

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Sight Sense: Enhancing Independence with AI & ML Driven Smart Glasses for the Blind Community

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Sakshi Katakwar, Deepak Sharma, Pankajkumar Anawade, Shailesh Gahane
Abstract - Individuals with physical disabilities and visual impairments may experience difficulty getting around independently and overcoming various challenges in their everyday lives. Using computer vision and artificial intelligence, physically and visually challenged people may do their main duties on their own, without assistance from others. This study uses a transformer encoder–decoder to provide users with auditory feedback based on sound categories like humans, animals, automobiles, etc. This gadget consists of an output device, a unit that processes data, a pair of glasses, and an obstacle-sensing module installed in the middle. The processing unit comprises an output unit, a control module, and an ultrasonic sensor for obstacle detection. These ultrasound smart glasses for blind individuals are inexpensive, lightweight, portable, and simple to operate. The goal is to leverage the wearable design format's advantages to help with various everyday chores. The difficulty of creating a tool for the visually handicapped is not a new one. However, the field of creating computer-assisted tools is still in its infancy. In this research, we suggest a novel approach that adds certain additional features to help the blind person while combining the essential elements of several useful approaches. These types of innovations are thought to be a way to inspire blind students to finish their education despite all of their challenges. The major goal is to help blind individuals communicate by creating a new method of text reading for them. The glasses employed a variety of technologies, including Google Translate, to carry out their functions. The glasses do have several shortcomings, though, such as the need to improve their look to make them more wearer-friendly and compact.

Paper Presenter

Deepak Sharma

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Batch Size Optimization in CNN Models for Chest X-ray Image Analysis: An Analytical Investigation

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Prabira Kumar Sethy, Raman Sahu, Preesat Biswas, Akshay Shirole, Santi Kumari Behera
Abstract - This study deviates from the norm by examining the impact of batch size on CNN models that have been trained to analyse thoracic X-ray images. To analyse the NIH Chest X-ray dataset, we implemented two optimisation techniques, namely stochastic gradient descent with momentum (SGDM) and adaptive moment estimation (ADAM), in addition to 18 distinct CNN models. Following a thorough examination of the impacts associated with batch sizes ranging from 16 to 1024, the researchers determined that a batch size of 512 yielded the highest performance for the majority of CNN models. By elucidating the intricate relationship between batch size and model performance, our exhaustive analytical investigation elucidates the complex dynamics underpinning CNNs using chest X-ray analysis as a case study. The findings shed light on the advantages of a specific sample size and contribute to our understanding of how this parameter impacts the accuracy and efficacy of convolutional neural network (CNN) models in the classification of medical images. Academics and practitioners can use our findings to enhance the performance of CNN in medical image analysis by effectively managing the intricate interplay between sample size and optimisation methods, as suggested by our findings.

Paper Presenter

Prabira Kumar Sethy

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

DIGITAL DARSHAN: A NEW PERSCPECTIVE OF PILGRIMAGE TOURISM DURING ONGOING PANDEMIC

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Deepanjali Mishra
Abstract - Covid 19, also known as Novel Coronavirus had its origin in a Chinese province called Hubei, in a wet market in the year 2019. This became so fatal that it got spread to all the countries of the world. I the first wave the countries which got affected were Ital, USA and India got affected in the second wave. Covid 19 caused havoc and destruction of lives. The countries which ws affected most during the first wave were Italy, USA etc and India got affected most in the second wave. Looking into the safet of the citizens, the governments imposed worldwide lockdown which forbade people from coming out of their homes. The summers which were spent on visiting pilgrimage sites in order to enhance their spirituality was paralyzed. It was during this time that people used to visit the shrines like Vaishno Devi temple in Katra, Amarnath Yatra was initiated during the holy moth of Sawan and after the Supreme court verdict on Shri ram temple people had started visiting Ayodhya. This led to a huge loss in the economy of the country. India is a country which is rich in its cultural heritage. It is said that there are 13 festivals in 12 months. So after the lockdown the festivals like Navratri, Ram Navami and Sawan kawar yatra could not be celebrated in the temples because of the restrictions imposed on them. Therefore the government of India decided to start with online aartis and facilated e -darshans of Mata Vaishno Devi during Navratri and Baba Barfani of Amarnath. The artis of Baba Amarnath is being continued on television and the devotees are getting darshans of Mahadev directly from the shrine as well as the daily aartis twice whole of Sawan. In the month of July Rath Yatra was telecast live from Puri which enabled people all over the world to have darshan of Mahaprabhu Shri Jagannath’s journey to his aunt’s house along with his siblings live on television. Therefore this paper is an attempt to analyse the problems created to the tourism industry due to Covid-19 and bring out the concept of having e- darshans of the shrines directly from the temples. The paper also would propose to discuss on the impact of spirituality of the devotees after the e- darshans.

Paper Presenter

Deepanjali Mishra

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Exploration of Historical and Modern Perspective on Hand Gesture Recognition with AI and ML

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Prem Shah, Mansi Patel, Himani Shah, Preet Patel, Sachi Joshi, Mohini Darji, Upesh Patel, Adey Purohit
Abstract - The aim of this paper is to delve into an important aspect of HCI (human-computer interaction) to become familiar with different techniques used in hand-gesture recognition. Hand gestures are nonverbal forms of communication in which information, emotions, or messages are conveyed by hand movements and positions. They are a universal mode of communication that can be used to supplement or replace spoken language. The study also comprehensively examines all the algorithms and models, like convolutional neural networks (CNNs), Hidden Markov Model (HMM), Latent Dirichlet Allocation (LDA), Mean-shift, etc. We assess their strengths and weaknesses according to their hand gesture detection and recognition performance. The paper also explores past trends of this ever-growing technology. We have studied around 30 papers to evaluate different techniques used for hand gesture recognition to date. Hand-gesture recognition is so important for review as it is extensively used in many domains like the gaming industry, healthcare and has many more limitless opportunities.

Paper Presenter

Adey Purohit

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Exploring Trust Factors in Virtual Finance: The Role of Human-Computer Interaction in Shaping User Intentions in Metaverse Banking

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Rashmy Moray
Abstract - The objective of the study is to examine the trust elements influencing the intention to use banking on metaverse. Survey method was used to collect the primary data using simple random sampling technique. Human computer trust model measurement scale was used to quantify the trust factors and evaluate its impact on users’ intention to use banking on metaverse. The data was analyzed using Smart PLS and proposed a model framework by applying structure equation method. The analysis highlights that benevolence and competence has a statistically significant impact on trust. Whereas intention to use is influenced by the antecedent trust positively. The study makes significant contribution in the field of immersive technology where the future researchers, academicians and banking system can refer to evaluate the users trust and usage intention of banking on metaverse.

Paper Presenter

Rashmy Moray

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Role of Mobile Commerce in Rural Entrepreneurship

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - T.A. Alka, Aswathy Sreenivasan, M. Suresh
Abstract - “Role of m-commerce in rural entrepreneurship” highlights how rural entrepreneurs use m-commerce opportunities to aid the expansion of rural entrepreneurship, factors that influence m-commerce adoption, the role of government and other support institutions, obstacles that prevent it from achieving its full potential and what are the future trends of m-commerce. A systematic review of the literature was used in this investigation. After a thorough investigation, the important findings are as follows: rural entrepreneurs have access to global markets beyond their immediate surroundings. M-commerce significantly reduces traditional entry barriers. Online business startups typically have lower launch costs than traditional startups, which promotes entrepreneurship and job creation in rural areas. Systems for mobile payments and digital banking make transactions simple, secure, and better for managing finances. Entrepreneurs get more familiar with technology resources and skills as they interact with digital platforms, which can enhance their business operations and overall competitiveness. Despite the obvious benefits, rural areas struggle with issues like inadequate internet connectivity, lack of digital awareness, cultural resistance infrastructure gaps, etc. To solve these issues specifically, governments, organizations, institutions, and stakeholders must collaborate for potential solutions including improving connectivity and offering online training programs. The study will aid in the effective formulation of policies, plans, and programs for decision-makers. The study's originality resides in its presentation of an organized, methodical, thorough, and in-depth literature review that defines comprehensive evaluation and provides the data needed to ascertain sustainability.

Paper Presenter

T.A. Alka

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

RoomX: Integrating Data-Driven Analytics and User-Friendly Interfaces for Optimized Meeting Room Booking

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Aayush Dighe, Srushti Kokate, Imran Khan, Edmond Jonathan, Rahul Jadhav
Abstract - This abstract highlights a robust meeting room booking system that incorporates both user and admin modules, prioritizing seamless booking experiences while leveraging the power of insightful data analytics. The system provides users with comprehensive analytics on a monthly basis, offering insights into meeting statistics, slot availability trends, and optimal booking times. One of the key features of this solution is its emphasis on analytics dashboards, which provide users with valuable insights to inform their booking decisions. Additionally, the absence of pricing ensures accessibility for all users, democratizing access to meeting room resources. The booking procedure is intuitively designed for ease of use, prioritizing a straightforward process for both users and administrators. The admin module offers administrators control over essential features, including confirming bookings and managing resources effectively. Through these functionalities, the meeting room booking system aims to streamline scheduling processes, enhance user decision-making, and provide a user-friendly platform for efficient room reservation.

Paper Presenter

Aayush Dighe

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Software Driven Revolution Redefining Automotive Industry

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Rushikesh Bhandari, Gaurav Gupta, Harsha Vardhan Sanne, Arun Pandiyan Perumal, Anandaganesh Balakrishnan, Saikat Gochhait
Abstract - Modern automotive technologies such as ADAS, Electrification and connectivity—two concepts defined by separate hardware and software development—highlight the importance of software in the automotive sector. Automotive Software-Defined is revolutionizing the automobile sector by enabling increased personalization, adaptability, and remote upgradeability. Here are several new business models that will provide customers new services: wireless software updates, car ownership based on a subscription, and enabling OEMS. Nevertheless, challenges like changes The intrinsic advantages of software-defined cars are under- mined by challenges with cybersecurity, a lack of autonomous distributed software development E/E architectures, and a lack of solutions for seam- less communication. OEMs have dealt with these issues. by concentrating on creating specialized software platforms that operate independently of hardware, unify the E/E architecture, and make use of the fast 5G

Paper Presenter

Rushikesh Bhandari

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Strengthening Crisis Response with Organizational Resilience Strategies to Achieve Sustainability

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Priyanka Tomar, Supriya Srivastava
Abstract - Crisis management is a crucial strategy for businesses and organizations to effectively respond to, recover from, and mitigate the effects of unexpected disruptions. Sustainability, crisis management, and organizational resilience are interconnected in today's volatile environment. The Power of Preparedness aligns strategies with Sustainable Development Goals (SDGs)for long-term sustainability. This study looks into the factors that affect the growth of organizational resilience in Himachal Pradesh's pharmaceutical sector, with a particular emphasis on crisis management techniques. The main goal is to find the essential components that support organizational resilience in this industry. Using both online and offline structured questioners, a sample size of 500 responses was gathered from six pharmaceutical industries, yielding 483 valid responses. Three crucial components - "Innovations and Employee Engagement," "Organizational Resources," and "Organizational Culture and Values" came to light as important contributors to organizational resilience through the use of factor analysis with SPSS software. The results highlight how crucial these elements are to improving pharmaceutical companies' capacity to endure crises and act decisively in their aftermath. "Innovations and Employee Engagement" emphasize how important it is to develop an environment where employees feel encouraged to be creative and take initiative in order to deal with difficult situations. In efforts to establish resilience, "Organizational Resources" highlight the critical role that sufficient infrastructure, financial resources, and technological breakthroughs play. Lastly, "Organizational Culture and Values" emphasizes how common standards, values, and beliefs can foster cohesiveness and togetherness in the face of adversity. The pharmaceutical companies in Himachal Pradesh can enhance their crisis response capabilities and foster an organizational culture that is resilient by acknowledging and giving priority to these elements. Organizations may assure long-term viability in a more unstable environment and improve their readiness for future crises by putting these insights into practice through focused tactics.

Paper Presenter

Supriya Srivastava

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Swarm Robotics

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Vanishree Pabalkar, Ruby Chanda
Abstract - Swarm robotics is the method used in order to have coordination amongst robots as a system. It is used to implement tendency that involves the action that is in a group or swarm through coordination amongst multiple flocks along with the communication with the surroundings. Artificial Intelligence and AI techniques that are relevant in robotics, like machine learning, deep learning, and evolutionary algorithms, are created to put these robots to tasks, that are crucial for enabling robots to learn and adapt in dynamic environments. Robots are used in autonomous construction of huge structures through multiple swarms. This task includes designing algorithms for collaborative planning, coordination, and execution of construction tasks by multiple robots. The process is adopted through collective intelligence by multiple robots, termed as Swarm intelligence. Swarm intelligence is a process that involves problem-solving behavior by way of collective intelligence. The intelligence is exhibited by a group for attaining better results, like bees, fish, ants, birds etc. The concept pf swarm intelligence, can be applied in the field of Agriculture, in order to attain better results. Swarm intelligence aids in enhancing the quality of crop production, thereby enhancing the efficiency, and increasing productivity. The swarm, which is the group intelligence acts as a catalyst and a responsive system that holds the capacity of resolving the issues and challenges faced in the field of agriculture. A swarm is made up of numerous homogeneous flocks that communicate with the surroundings on a local level without any central command, allowing for the emergence of novel behavior on a larger scale. In the current study, the attempt has been made to understand the correlation between Swarm Intelligence and Agriculture. The attempt here to understand the role of Swarm Intelligence in having a better crop yield in the field of Agriculture. In this paper, the key aspects of Swarm Intelligence are discussed. Ant Colony Optimization and Particle Swarm Optimization are significant topics in Swarm Intelligence, which have been discussed in depth. The aim is to address the key aspects of swarm robotics and autonomous construction. In the concluding remarks, it has been mentioned that though Swarm Intelligence has been used and applied in several fields, the current study discusses the role of Swarm Intelligence through swarm robotics.

Paper Presenter

Vanishree Pabalkar

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Working of convolutional neural network (CNN) in network intrusion detection system

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Zakiyabanu Malek, Himali Gajjar
Abstract - Internet apps have grown in popularity now a days. As the use of internet technology is increasing day by day security concern over internet is also increasing. For that we need network to be more secure to overcome the security concern it is mainly depending on intrusion detection systems (IDSs).Many technologies have already develop to fight against network security concern, this technology is mainly work with the help of deep learning as well as artificial intelligence techniques Deep leaning is heavily effective in IDSs as a metafield of AI. Convolutional neural networks (CNNs) use a common deep learning neural network topology to process complicated input. CNN is commonly used in intrusion detection systems (IDSs) and overcomes the limitations of classic machine learning approaches. IDSs manage security and privacy concerns using a variety of CNN-based approaches. However, to the best of our knowledge, no comprehensive assessments of IDS projects have used CNN. The primary goal of this research is to gain a better understanding of the many way and working of CNN, irregularities, and types of assaults. In a study artistically organises the major characteristics and contributions of the examined CNN-IDS approaches into several categories. These approaches are compared based on their essential components, which include the classifier method, architecture, input shape, performance, evaluated metrics, and dataset. The experimental findings of CNN-IDS research are not comparable since different datasets are used. As a consequence, an empirical experiment was conducted in this study to evaluate alternative approaches using combined datasets. In this paper we have explained some results in deep.

Paper Presenter

Himali Gajjar

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Automated Billing Cart System Using Computer Vision and Web Integration

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Sheetal Phatangare, Rudra Mondal, Sahil Makadi, Amey Mahulkar, Ayush Patle
Abstract - The retail landscape is undergoing a transformation, with our research focusing on the integration of advanced technology into traditional shopping carts. In response to the surge in online shopping, our project aims to elevate the in-store shopping experience by introducing the Automatic Billing Cart System. This innovative solution seamlessly combines automated mobility, instant bill generation, and a user-friendly interface. Utilizing a camera module and Open CV-based Object Detection, the system simplifies the shopping process, enabling customers to effortlessly navigate the store, add items to their cart, and eliminate the need for conventional checkout procedures.

Paper Presenter

Rudra Mondal

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Bridging the Gap : Improving Students’ Academic Performance through Attentive Listening and Effective Time Management

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Vinayak Hegde, Vishrutha M, Rekha Bhat, Pallavi M S
Abstract - The paper examines students’ academic achievement and considers to what extent time management, extra work, and active listening in the classroom affect students’ academic success. In terms of methodology, the project starts with the data collection through an online survey of 350 participants. This is followed by data preprocessing chores and feature selection, then Spearman correlation analysis, ANOVA tests, Pearson correlation analysis and Random forest classifier. The first hypothesis is about a positive correlation between academic achievement and students’ time management abilities. The analysis of Spearman’s correlation coefficient showed that such factors as hours of study (0.6242), exam preparation (0.6790), note-taking (0.5440), and others are closely connected and cause high levels of students’ academic performance. The second hypothesis was confirmed by the results of analysis of variance and suggests a positive correlation between academic success and listening to lectures (F-statistic: 65.73, p-value: 2.70e-24), discussion (F-statistic: 63.48, p-value: 1.28e-23) and classroom attendance (F-statistic: 90.53, p-value: 2.55e-31). The third assessed assumption was the effect of more work on academic performance. The hypothesis claimed that there is a negative association between the one produced by the analysis using the Pearson correlation coefficient and the other the Random Forest Classifier finding an accuracy of 66.67% and an F1 score of 0.6145. It solidifies the understanding that for students to succeed in academic objectives, there is a need to properly handle time and engage actively in lessons and cautiously approach extra work.

Paper Presenter

Vishrutha M

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Empowering Crisis Resilience: An Immersive Journey to Survival Mastery

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Amrutha Anup, Tarun Kumar
Abstract - This study significantly contributes to the discussion on disaster preparedness by analysing the essential elements of both mental and physical readiness. It combines scholarly principles with real-world applications, highlighting the connection between education and the ability to make critical decisions in high-stakes situations. The study explores different facets of preparedness, conducting a comprehensive analysis of the relationship between psychological and physical factors. Through the integration of theoretical frameworks and empirical data gathered from face-to-face interviews, this study provides a comprehensive exploration of successful emergency response strategies. This all-encompassing approach strives to empower individuals with a wide range of skills and perspectives, promoting adaptable thinking in the face of unexpected obstacles.

Paper Presenter

Amrutha Anup

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Enhancing Named Entity Recognition (NER) in Biomedical Texts: BIOBERT on CORD19 Dataset

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Saripudi Suneetha, Jarubula Ramu, Neerukonda Kanthi Priyadarsini, Thulasi Bikku
Abstract - The CORD-19 data and Bio BERT-NER (Bidirectional Encoder Representations from Transformers for Named Entity Recognition) are strong natural language processing and biological research approaches. Bio BERT-NER provides scientific articles on COVID-19 and associated historical coronavirus re-search. CORD-19 allows for text mining and data retrieval system development using its extensive metadata and structured full-text publications. Applying the BioBERT model to the CORD-19 data to recognise named entities (NER). An adaptation of the BERT concept is tailored to deal with biomedical works. Named entities (people, places, things, etc.), biomedical entities (genes, proteins, illnesses, etc.), and other types of textual entities are recognised and placed into predetermined categories in NER. Since its release, The CORD-19 dataset has been used as the foundation for several text analysis and discovery algorithms focused on COVID-19. In this study, we present a comprehensive approach utilizing the BioBERT model for NER on the CORD-19 dataset, which contains a vast collection of scholarly articles related to COVID-19. The workflow begins with data preprocessing, including handling missing values, dropping low-frequency tags, and tokenizing the text using the BioBERT tokenizer. The tokenized sequences are then encoded into numerical representations using BioBERT's vocabulary. A custom NER model is constructed using PyTorch, with the pre-trained BioBERT weights loaded for transfer learning. This article provides an in-depth account of creating a dataset, focusing on the difficulties and significant choices made during its creation. This research will facilitate the collaboration between the scientific computing community, biomedical professionals, and policymakers in pursuing efficient therapies and management strategies for COVID-19.

Paper Presenter

Thulasi Bikku

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Imaginate: A Generative AI Approach Using Segmentation For Image Modification

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Andre Isaac Nazareth, Trisha Nitin Nagarkatte, Grace Prashant Pereira, Garima Tripathi
Abstract - Generative AI represents the intersection of technology and creativity, it is the process of creating original content such as images, videos, music, texts, and much more using generative models and thereby expanding the horizons of digital creative expression. GenAI finds its application in the interior design field. Interior design is the art of creating aesthetically pleasing living spaces to meet user needs. To cater to this design field with GenAI we have built an application that makes use of image segmentation and prompt application to generate images or make changes to an image that is uploaded by the user. The proposed system eliminates manual drawings and generates creative designs as per user needs. Image segmentation is accomplished using the Segment Anything Model (SAM). The segmented part of the image along with the prompt that the user has inputted is given to the Stable Diffusion Model. This model will then give the output which is superimposed on the original image to give the final output image using various image overlay methods. This approach epitomizes the fusion of cutting-edge AI methodologies and enhances the potential for creative and transformative image manipulation with efficient decision-making capabilities.

Paper Presenter

Andre Isaac Nazareth

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Implementation of a Web Application for Secure File Up-load and Virus Scanning

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Abraham Shukla, Abhishek Ranjan, Shivakarthik S, Swati Mehta, Akash Udaysinh Suryawanshi, Snehal Chaudhary
Abstract - This research presents the development and implementation of a web application that enables users to securely upload files and perform virus scanning using ClamAV with a single click. The application utilizes Firebase for file storage and retrieval, providing a seamless and secure experience for users. This paper discusses the architecture, functionality, and security features of the web application, along with the results of performance and security testing.

Paper Presenter

Abraham Shukla

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Influence of Deep reinforcement learning techniques in vehicular networks

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Anushree Raj, Pallavi M O, Sadhana Kumble, Ragesh Raju
Abstract - Vehicle networks have become a prominent research topic because of their distinctive characteristics and uses, such as consistency, effective traffic control, road security, and infotainment. The network entities must make judgments on how to exploit network operation under ambiguous conditions. A challenging environment is produced by the expanding usage of wireless technology in a highly mobile environment. To improve communication dependability in this environment, intelligent technologies must be used to solve the routing issue and construct a more durable communication system. An excellent solution to this problem is reinforcement learning (RL). You can achieve your goal by using Re-Enforcement Learning (RL), which can effectively handle challenges with decision-making. Yet, the state and action spaces in large-scale wireless networks are huge and complex. As a result, it's possible that RL won't be able to decide on the best course of action in time. Deep Reinforcement Learning (DRL), a hybrid of RL and DL, was created as a solution to this issue. We begin by introducing vehicular networks and giving a brief overview of the concepts of RL and DRL in this analysis. Then, to address fresh issues in 6G vehicle networks, we discuss RL and, in particular, DRL approaches. Finally, we list a few concerns that still need to be studied further.

Paper Presenter

Anushree Raj

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

IOT BASED SAFE AND SMART AUTOMATIONS OF AGRICULTURE LANDS

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Dhanush C, Karun L J, Arun Kumar, Vijay Kumar S, Geetha B
Abstract - In the realm of agriculture, particularly in developing nations such as India, where farming serves as the predominant occupation, despite advancements in science and technology, the prevalence of erratic power supply disrupts agricultural activities. Enhancing agricultural productivity becomes paramount. Solar power emerges as a viable renewable energy option glob-ally. Automation, particularly in tasks like water management, becomes crucial to optimize productivity. Utilizing GSM technology, farmers can remotely monitor and control irrigation systems, leading to efficient water usage and reduced reliance on government electricity subsidies. In our paper, we propose a method to overcome the drawback of erratic power usage for farm irrigation. We suggest utilizing solar power as an alternative to electricity and switching between these two modes based on the irrigation requirements. Our approach leverages IoT (Internet of Things) and sensors, enabling not only irrigation but also notifying the farmer in case of any intrusion into the farm. By integrating these technologies, our work aims to optimize agricultural practices, enhance productivity, and mitigate challenges associated with power supply and security in farming operations.

Paper Presenter

Dhanush C

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Novel Hybrid Machine Learning Algorithms for Resource Optimization in Cloud

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Prathamesh Vijay Lahande, Parag Ravikant Kaveri, Jatinderkumar R. Saini
Abstract - The resource optimization process in the cloud is crucial and can be achieved through the ideal Load Balancing (LB) mechanism. The cloud under-goes several challenges with resource optimization due to poor LB mechanism, where its Virtual Machines (VMs) are either overloaded or idle. The main aim of this experimental-based research is to enhance the LB mechanism of the cloud by implementing and comparing the performance of novel hybrid LB algorithms RLFCFS and RLSJF to optimize the resources. The RLFCFS and RLSJF novel LB algorithms are designed by combining the Reinforcement Learning (RL) technique with the heuristic FCFS and SJF algorithms. The proposed algorithms improve resource optimization in terms of cost and time by facilitating enhanced LB mechanism through RL intelligence mechanism. The performance of RLFCFS and RLSJF LB algorithms is compared with respect to the average (avg.) load managed by the VMs and the avg. percentage (perc.) of deviation observed against the expected load in each experimental stage. The experimental throughput conveys that the RLFCFS LB algorithm managed an aggregate avg. load of 968.77 tasks against the RLSJF LB algorithm, which managed 999.08 tasks aggregately across all experimental stages. Concerning the avg. perc. of deviation, the RLFCFS LB algorithm deviated by 63.44 % against the ideal expected load to manage against the RLSJF LB algorithm, which deviated by 64.60 %. This shows that the RLFCFS LB algorithm gave better resource optimization results than the RLSJF LB algorithm. Lastly, these results are mathematically validated using the Simple Linear Regression model.

Paper Presenter

Prathamesh Vijay Lahande

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

PlantMaps: Environmental Conservation Using Gamification

Thursday August 8, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Riddhi Kasar, Tarun Kumar
Abstract - In the past three decades, the world has lost 10.3% of its forested area. Deforestation, being a leading cause of global warming and climate change, has been posing a risk of pandemics, food insecurity, and reduced biodiversity. This paper identifies the need to promote environmental conservation to ensure sustainability. The use of design thinking is leveraged to propose a product service system that uses gamification and geolocation – incorporated in a smartphone application and onsite dispensers – for improving tree planting in users. Behaviour patterns are investigated, and rewards and incentives are applied to bring about the desired change in users and encourage them to act for environmental conservation. Ergonomics is maintained to ensure a user-centric experience and instils willingness. Testing of the system and smartphone application revealed a significant change in user behaviour in terms of tree planting. Gamification has proven to not only instil willingness but has also helped reach the desired goal of sustainability. Efficient and showcasing significant potential, this system directly involves all the stakeholders related to environmental conservation, thus proving to be the much needed, possibly impactful solution.

Paper Presenter

Riddhi Kasar

India

Thursday August 8, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Thursday August 8, 2024 11:15am - 11:20am IST

Virtual Room A

Thursday August 8, 2024 11:15am - 11:20am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Thursday August 8, 2024 11:15am - 11:20am IST

Virtual Room B

Thursday August 8, 2024 11:15am - 11:20am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Thursday August 8, 2024 11:15am - 11:20am IST

Virtual Room C

Thursday August 8, 2024 11:15am - 11:20am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Thursday August 8, 2024 11:15am - 11:20am IST

Virtual Room D

Thursday August 8, 2024 11:15am - 11:20am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Thursday August 8, 2024 11:20am - 11:30am IST

Virtual Room A

Thursday August 8, 2024 11:20am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 4A, Virtual Room A

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Thursday August 8, 2024 11:20am - 11:30am IST

Virtual Room B

Thursday August 8, 2024 11:20am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 4B, Virtual Room B

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Thursday August 8, 2024 11:20am - 11:30am IST

Virtual Room C

Thursday August 8, 2024 11:20am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 4C, Virtual Room C

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Thursday August 8, 2024 11:20am - 11:30am IST

Virtual Room D

Thursday August 8, 2024 11:20am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 4D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:00pm IST

Opening Remarks

Thursday August 8, 2024 12:00pm - 12:03pm IST

Tango 1

Thursday August 8, 2024 12:00pm - 12:03pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

12:00pm IST

Opening Remarks

Thursday August 8, 2024 12:00pm - 12:03pm IST

Tango 2

Thursday August 8, 2024 12:00pm - 12:03pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

12:00pm IST

Opening Remarks

Thursday August 8, 2024 12:00pm - 12:03pm IST

Strategy/Analysis

Thursday August 8, 2024 12:00pm - 12:03pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

12:00pm IST

Opening Remarks

Thursday August 8, 2024 12:00pm - 12:03pm IST

Debate

Thursday August 8, 2024 12:00pm - 12:03pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

12:03pm IST

ICT adoption and personality trait: Review from an Indian higher education perspective

Thursday August 8, 2024 12:03pm - 12:14pm IST

Tango 1

Authors - Mohar Banerjee Biswas, Srikant Das, Joydeep Biswas
Abstract - The Covid 19 pandemic has made the usage of technology in imparting knowledge more crucial in the last two years. There has been continuous investment in ICT in the higher education, however the adoption rates have not been very promising. On further investigation into poor technology adoption rates, it was revealed that even though teachers play a very crucial role in the ICT adoption in education, but there is a considerable gap between the expectations and how ICT is used in their daily teaching and learning processes. It has become the need of the hour to study and analyze why few teachers are more prone to adopting technology in their work area. The integration of technology into education is found to be significantly dependent on the attitude and personality traits of the teachers. The objective of the article is to understand why certain people in academics adopt technology more than others and the investigate on the possibility of a relationship between the individual personality trait and the adoption behavior of teachers in higher education. The paper concludes with hypothesis around the relationship between personality traits and ICT adoption in academics along with studying the impact of moderating elements that would influence the relationship.

Paper Presenter

Mohar Banerjee Biswas

India

Thursday August 8, 2024 12:03pm - 12:14pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

12:03pm IST

Smart Building Optimization using LiFi-BMS Integration for Efficient Lighting

Thursday August 8, 2024 12:03pm - 12:14pm IST

Tango 2

Authors - Devanth Mallikarjunaiah, Neha S, Nidhi Sridhar, Niranjan M Nadiger, Venugopal N
Abstract - This article explores the integration of Building Management Systems (BMS) and Light Fidelity (Li-Fi) technologies within a Direct Current (DC) network design to optimize connectivity, data transfer, and energy efficiency in smart buildings. A unique method for enhancing the general dependability and efficiency of smart building systems is to take advantage of Li-Fi's potential in a DC setting. In addition to outlining quantifiable goals to assess the integration's efficacy, the article offers a thorough investigation of the possible advantages of it. Intelligent buildings can achieve continuous connectivity throughout their premises by utilising Li-Fi's inherent advantages, which include enhanced security, improved coverage, and resistance to electromagnetic interference. Moreover, the integration with BMS enables real-time data sharing and centralised control over a range of building functions while optimising energy consumption and enhancing occupant comfort.

Paper Presenter

Devanth Mallikarjunaiah

India

Thursday August 8, 2024 12:03pm - 12:14pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

12:03pm IST

A Comparative Analysis of Symmetric and Asymmetric Cryptographic Algorithms: Performance, Security, and Versatility

Thursday August 8, 2024 12:03pm - 12:14pm IST

Strategy/Analysis

Authors - Harsh Dudhat, Krunal Jodhani, Jyot Delvadiya, Utsav Gundaraniya, Sneha Padhiar, Raj Fachara
Abstract - Cryptography is the basis of modern information security, combining symmetric and asymmetric algorithms to protect digital information. This article presents a comparison of the main algorithms in the two fields. Explore symmetry algorithms such as RC4, AES and DES for their performance, security, and versatility. In contrast, asymmetric algorithms such as RSA, ECC and ElGamal are analyzed for their management complexity, computational overhead, and vulnerability to cryptographic attacks. Understanding the unique characteristics of each algorithm allows practitioners to make informed decisions about choosing the encryption method that best suits their specific security needs. This misunderstanding is necessary to create resilient cryptographic systems and reduce vulnerabilities in digital systems. In addition, this research contributes to cryptographic knowledge by addressing new trends and current issues in the field. The insights gained from this research not only help support the use of strong encryption techniques but also lay the foundation for future innovations in digital security techniques. Finally, this article aims to deepen the understanding of the encryption process so that participants can investigate complex problems and create secure system knowledge. It aims to increase the effectiveness of digital systems against changing threats in the connected world through comprehensive analysis and to ensure the integrity and confidentiality of sensitive data.

Paper Presenter

Krunal Jodhani

India

Thursday August 8, 2024 12:03pm - 12:14pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

12:03pm IST

Design and Implementation of a Framework for Detection and Prevention of Drowsiness and Yawning during Driving

Thursday August 8, 2024 12:03pm - 12:14pm IST

Debate

Authors - Parth Thakkar, Mohammed Kaif Shaikh, Harsh Sanghavi, Dhruv Shah, Vinodray Thumar, Jaimin Shroff
Abstract - The persistent concern of road safety is to be addressed by introducing a cost-effective and robust model for detection of drowsiness and yawning while driving on road. Utilizing theArduCam camera modules, the system constantly records facial benchmarks to analyze the Eye Aspect Ratio (EAR). In the event of calculated EAR values falling below or exceeding the defined threshold range, indicating driver drowsiness or wakefulness, the system issues timely alerts through a speaker. The scope of this work extends to capturing driver’s images in challenging conditions, optimizing emergency response by sending messages to authorities, and implementing a personalized alert system. The ultimate goal is to significantly reduce road accidents and contribute to enhance road safety.

Paper Presenter

Dhruv Shah

India

Thursday August 8, 2024 12:03pm - 12:14pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Thursday August 8, 2024 12:15pm - 12:20pm IST

Virtual Room A

Thursday August 8, 2024 12:15pm - 12:20pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Thursday August 8, 2024 12:15pm - 12:20pm IST

Virtual Room B

Thursday August 8, 2024 12:15pm - 12:20pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Thursday August 8, 2024 12:15pm - 12:20pm IST

Virtual Room C

Thursday August 8, 2024 12:15pm - 12:20pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Thursday August 8, 2024 12:15pm - 12:20pm IST

Virtual Room D

Thursday August 8, 2024 12:15pm - 12:20pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Thursday August 8, 2024 12:15pm - 12:20pm IST

Virtual Room E

Thursday August 8, 2024 12:15pm - 12:20pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Impact of BERT on Evaluating the Quality of Question Papers using Bloom's Taxonomy

Thursday August 8, 2024 12:15pm - 12:26pm IST

Tango 1

Authors - Dhaval Patel, Krish Bhikadiya, Nikita Bhatt, Ronakkumar Patel, Trusha Patel
Abstract - In education, the quality of question papers is crucial as assessment depend on the performance of students. Manual assessment can be time-consuming, especially with numerous questions. The quality of a question paper can be measured with various factors including difficulty level of questions, relevance to questions and time requirement to attempt the question. This paper focuses on the analysing the quality of question paper based on the bloom’s taxonomy, which is a framework used to assess the quality of a question paper by evaluating the cognitive processes involved, such as remember, understand, apply, analyze, evaluate and create. The work presented here explored various tokenization methods like BERT and deep learning models like LSTM, Bi-LSTM and BERT. The experiments were conducted using a dataset generated by importing questions from university papers across different courses. The generated results conclude that transformer-based BERT model gives the Higher Accuracy than Other Deep Learning models.

Paper Presenter

Nikita Bhatt

India

Thursday August 8, 2024 12:15pm - 12:26pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

12:15pm IST

Blockchain Based Healthcare Management Systems: A Survey

Thursday August 8, 2024 12:15pm - 12:26pm IST

Tango 2

Authors - Sharwari S. Solapure, Anant J. Umbarkar, Nirmit Chattoo, Ashish Kyasari
Abstract - The integration of blockchain technology into healthcare management systems has shown promise in revolutionizing the healthcare industry. This paper aims to provide a comprehensive comparison of various works on blockchain based healthcare management systems. Key parameters such as blockchain type, consensus algorithm used, platform used, type of data storage, data encryption, confidentiality, integrity, privacy, access control, implementation, scalability, interoperability, regulatory compliance, energy efficiency, and governance model evaluated and compared. Evaluating these parameters, this paper will provide a survey of the different blockchain based healthcare management systems. This survey article is a valuable resource for researchers who are using blockchain in healthcare.

Paper Presenter

Anant J. Umbarkar

India

Thursday August 8, 2024 12:15pm - 12:26pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

12:15pm IST

A Review: Implementation of Partially Homomorphic Encryption and Fully Homomorphic Encryption on Cloud Computing

Thursday August 8, 2024 12:15pm - 12:26pm IST

Strategy/Analysis

Authors - Aashka Raval, Jaivik Jariwala, Vrundan Sojitra, Nishant Doshi
Abstract - Encryption and decryption are used even before the word democracy came into existence. Asset encryption systems rely on key sharing (public or private) between peers involved in exchanging encrypted messages, but with the passage of time, we have observed concerns towards privacy. Users or key service providers have exclusive rights to data and when we talk about the cloud is known how vulnerable our data is to cloud providers as well as third-party service providers. Even if the keys are not shared, encrypted equipment is shared with someone who does not need access to the content, and all this access is provided through untrusted sources like computers, servers to all the accessible places and people they do not even need permission which makes it freer to violate privacy. Indeed, Homomorphic Encryption (HE), a special type of encryption system, can address this concern as it allows any outside organization to process encrypted data without having to extract it prematurely. Although this extremely useful feature of the HE system has been known for more than 30 years, the first sound and accessible Fully Homomorphic Encryption (FHE) system, which allows any tangible work to be done on encrypted data, was introduced by Craig Gentry in 2009. While this has been a remarkable success, the different uses have so far shown that FHE still needs significant improvements to work across all platforms. This paper focuses on the comparison of Partially Homomorphic Encryption (PHE) and Fully Homomorphic Encryption in cloud computing. Both have some pros and cons and the computation is a crucial part of the implementation to see how they work.

Paper Presenter

Aashka Raval

India

Thursday August 8, 2024 12:15pm - 12:26pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

12:15pm IST

Real-Time Object Detection and Recognition on Jetson Nano

Thursday August 8, 2024 12:15pm - 12:26pm IST

Debate

Authors - Dhruvi J. Patel, Priyanshi S. Patel, Trupal J. Patel, Mahek D. Viradiya, Jaykumar B. Patel, Dweepna Garg
Abstract - An object's site and labelling within a mathematical picture or television frame is the task of object detection in a computer vision. It offers particularized news about the location and somewhat articles present knowledgeable, going beyond fundamental figure categorization, which gives a name to the whole figure. The purpose of this research is to search the use of the NVIDIA Jetson Nano terrace real-time object labelling on edge ploys. Accompanying applications varying from driverless cabs to following, object detection is an essential task in calculating apparition. The Jetson Nano is an excellent option for efficiently killing complex deep knowledge models in settings accompanying restricted money because of the allure of GPU-increased computational volume. In this paper, we try the exercise of contemporary object detection models on the Jetson Nano, containing YOLO (You Only Look Once) and SSD (Single Shot MultiBox Detector). Allowing for the possibility of the work-offs middle from two points model complicatedness and palpable-time conclusion, we evaluate these models' veracity and speed of operation. We likewise scrutinize growth methods to further correct conduct accompanying minimal abeyance, like model quantization and ornamentation. By trying that object detection on edge ploys like the Jetson Nano is two together possible and effective, the research judgments cause the progress of embedded calculating concept.

Paper Presenter

Priyanshi S. Patel

India

Thursday August 8, 2024 12:15pm - 12:26pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

12:15pm IST

AI-driven skin disease detection, diagnosis, and tailored medication recommendations Model

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Sneha Rajendra Jadhav, Shabana Pirjade, Vinodkumar Bhutnal, Lakhan Rathod, Sonali Jagdale, Janvi Naik
Abstract - Skin diseases may have a detrimental effect on an individual's quality of life and can be difficult to diagnose and treat because of the lack of adequate medical resources. The skin is an essential organ that protects the body from environmental hazards. With a focus on early detection and efficient treatment, this research combines deep learning with image processing to provide a framework for accurate skin disease diagnosis. Skin condition classification is made easier by the use of cutting-edge methods such as the CNN model's DenseNet layers and VGG-19 for analyzing real-time picture data. Using sophisticated picture processing, the method makes illness symptoms visible and allows for early detection. As it guides healthcare activities proactively, the system creates customized recommendations for diagnosis-based treatments and preventative measures. This work greatly enhances healthcare outcomes by using technology to intervene promptly and to diagnose skin diseases more accurately and easily. Reducing negative effects on people's lives and promoting improvements in dermatological procedures and medical results are among the revolutionary possibilities. The ability to handle skin diseases holistically is demonstrated by this innovative approach.

Paper Presenter

Lakhan Rathod

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Analyzing Modifications in Architecture of Classification to Regression Neural Network for Super Resolution Application

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Mrunmayee V. Daithankar, Sangeeta R. Chougule
Abstract - The era of artificial intelligence is leading the world and has become a foremost decision maker of human life by proving its rapid growth in every field. One of the recognized areas is super-resolution of videos or images. The world comes closer by communication means and the visual information source is turned out promising due to its ease of content understanding. So, the quality expectations during processing and after transmission for accurate decision making, grabs attention of researchers. Researchers presented variety of techniques to improve the quality of various types of input visual data. The approaches with neural network tool are frontrunners. These solutions give rise to distinct problems concerning precision, trade-off between accuracy and complexity, energy usage, and memory needs. The author has addressed the benefits of modification of basic classification neural network into regression one through experimentation particularly for super resolution application as the neural networks basically designed for classification and not for regression purpose. The satisfactory results of performance measurement parameters; training accuracy and root mean square error of experimentation, motivate author for future embedding of explored concept with variety of data for more generalization of algorithm.

Paper Presenter

Mrunmayee V. Daithankar

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Bibliometric Survey on DevOps

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Pradnya Purandare, Samaya Pillai Iyengar, Venkatesh Iyengar, Pankaj Pathak, Rishabh Vantagudi
Abstract - Asian IT market and economy is impacted by DevOps progression significantly, hence research of DevOps is necessary to bring innovation and improvements in DevOps methods and IT projects. Hence as the commencement to IT industry applicable research of DevOps in future, we started with research of this bibliometric study. It is supported with thorough literature review and in-depth bibliometric analysis of DevOps research studies, to understand trends in DevOps. In long run DevOps is impacting IT market which is an important economic aspect in Asia and globally. The Asia Pacific DevOps Market is predicted to grow at a CAGR of 20.2 Bibliometric measures conducted includes author search, citation counts, etc. This research study is spanned across research year 1999 to 2020. Bibliometric scrutiny is conducted with Scopus, Google Scholar, and the tools like Gephi, etc.

Paper Presenter

Pradnya Purandare

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Comparative Analysis of Machine Learning Models in Autism Spectrum Disorder Identification

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Cheritha Kondru, Abhinav Jayakuma, Sarath S
Abstract - This paper provides methods to recognize patients with potential Autism Spectrum Disorder(ASD). It is a tedious work to find it manually by going through every patient as it is troublesome. In this case, machine learning techniques are beneficial, helping people to diagnose ASD more quickly so that they don’t go through difficult procedures. Two datasets were chosen, one including adult-related information and the other toddler-related information. A number of models were trained on both datasets. The outcomes showed that the adult screening dataset performed better with the Support Vector Machine(SVM) (92.4%) and k-Nearest Neighbors(KNN) (97.1%) models when the accuracy was considered, and the toddler dataset performed well with the KNN (73.9%) and Gaussian Naive Bayes(GNB)(91.4%). With Receiver Operating Curve(ROC), KNN worked well with better results on the adult dataset and GNB for the toddler dataset.

Paper Presenter

Cheritha Kondru

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Comparative Analysis of Real-Time Scheduling Algorithms on Multi-Core Architectures

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Jyotsna Gaikwad
Abstract - Real-time processing is becoming more important in modern computer systems, necessitating the use of efficient real-time scheduling techniques, particularly in the context of multi-core architectures. This work provides a comprehensive analysis and comparison of various real-time scheduling techniques specifically tailored for multi-core CPUs. The major aims are to assess their functionality, scalability, and adaptability for handling real-time workloads in a multi-core environment. We will provide performance measures and trial outcomes in tables to clearly outline the advantages and downsides of each algorithm.

Paper Presenter

Jyotsna Gaikwad

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Corporate Social Responsibility and Human Resource Management: A Qualitative Examination of how one impacts the other

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Nandana P Nair, Aswathy R, T P Anju, Vandana Madhavan
Abstract - In the present corporate environment, business organizations prioritize corporate social responsibility (CSR) initiatives. To find the extent to which these activities impact the workforce of the organizations thereby leading to employee engagement, commitment, and employer branding we have undertaken this study. It is very beneficial for organizations if they approach CSR with an employee engagement perspective, so our study aims to find a relationship between CSR as well as Human Resource practices of prominent companies in India. For our study, we have taken various Indian companies based on CSR spending, HR linked CSR initiatives and found how these activities positively affect the employees of the organization. Using qualitative methodology, we analyzed the selected companies' corporate social responsibility reports, environment sustainability reports, and annual reports. We collected the relevant excerpts and did a thematic analysis of the extracted content. We then compared them against the reviews of the employees about their organizations. We were able to understand that these initiatives have a great impact on multiple areas of human resource management. Our work was created to find the relationship between CSR and HRM.

Paper Presenter

Nandana P Nair

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Enhanced Machine Learning Algorithm For Pharming Detection

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - V.Vijayalakshmi, K.Suguna
Abstract - Pharming is a two-pronged cyber threat that involves installing harmful malware on a victim's device and then redirecting them to false websites. It is a serious threat to internet security. This work investigates how to improve the detection of pharming assaults by applying machine learning (ML) techniques, specifically focusing on Naive Bayes classification algorithms. By using principal component analysis (PCA) to classify URLs according to their features, the suggested model offers a thorough summary of the dataset that was acquired from UCI and consists of typical pharming attack cases. Using machine learning (ML) to analyze large datasets and find traits, trends, and anomalies that point to malicious activity is the methodology. The suggested method is made more effective by exploring the dataset's attributes through the use of feature

Paper Presenter

V.Vijayalakshmi

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Intelligent headgear system based on Peer-to-Peer Communication

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Aaryan Chipkar, Aaryan Chaudhari, Shreya Panicker, Sakshi Khatke, Vinodkumar Bhutnal
Abstract - The mining industry also known as the ‘killing industry’ is a highly dangerous industry due to the high probability of accidents due to various environmental factors like toxic gases, collapse/flooding of mines, and various challenges due to confined spaces and limited visibility. One of the key challenges that occur in this industry is the rapid and timely response during an emergency. The primary objective of this research paper is to address this problem by exploring various communication technologies suitable for the underground environment by delving into the aspect of peer-to-peer communication, exploring various efficient routing algorithms as well as methods for determining the direction of signals. One of the integral concepts to this framework is the methodology to determine the most effective way for transmitting the emergency messages to central network and the other helmets in the vicinity for rapid response and coordination in emergency situations. One of the other objectives of this paper is to determine various ways of direction discovery of the incoming emergency signals to pinpoint the location of the accident or hazards. Our research also includes a simple mathematical model for node selection in the routing algorithms. The findings and contributions of this paper lie in the improved safety and communication capabilities of the helmet which are crucial for the safety of the underground workers.

Paper Presenter

Aaryan Chaudhari

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Recommender Systems for Job Seekers: Investigating Trust, Personal Innovativeness, and Adequacy of Alternatives in their Adoption

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Sanjay V. Hanji, Sanjeev Ingalagi, Nagaraj Navalgund, Sumanth Desai, Savita Hanji, Rajeshwari B. Tapashetti
Abstract - This study uses an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) paradigm to examine how job seekers use job recommender systems. Alongside standard UTAUT-2 variables, trust, personal innovativeness, and adequacy of alternatives were also examined. A survey involving 476 job seekers was conducted, with structural equation modelling employed for analysis. Results indicate positive influences on intention to use job recommender systems from factors such as performance expectancy, habit, personal innovativeness, and adequacy of alternatives. The study holds significant implications for both theoretical understanding and managerial practice.

Paper Presenter

Sanjay V. Hanji

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Traffic Congestion Management

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Mohanraj K Y, Santhameena S, Mahendra Deshi, Prashant Naik, Prabhanjan Kalburgi
Abstract - One of the main issues facing today's urban environments is traffic congestion, which is exacerbated by exponential population growth and the ensuing rise in vehicle traffic. This problem not only prolongs commutes but also has substantial impacts on environmental sustainability, public health, and total urban responsibility. To solve this problem, our idea proposes developing and putting into place an efficient traffic management system, the integration of PTV Vissim for dataset generation and the utilization of machine learning algorithms, combined with Dijkstra's algorithm for route optimization, constitute comprehensive solution within our traffic congestion management System. By leveraging these advanced technologies, our system aims not only to alleviate current traffic congestion challenges but also to contribute to the creation of more sustainable and efficient urban transportation systems.

Paper Presenter

Mahendra Deshi

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Abnormal Event Detection in Surveillance Videos using an Enhanced Fusion Method

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Vishalsinh P Gohil, Chetankumar Chudasama
Abstract - In the field of surveillance video analysis, the identification of anomalous occurrences is of utmost importance in order to guarantee security and safety. Nevertheless, current techniques frequently encounter difficulties in precisely detecting abnormalities within intricate contexts and fluctuating environmental circumstances. In order to tackle these problems, this research suggests a novel strategy that combines two complementing techniques: Multiple Segment Learning (MSL) ranking loss and a fusion of object identification and posture estimation. The suggested fusion technique synergistically integrates the advantages of both methodologies to optimise the precision and effectiveness of abnormal event detection. The MSL ranking loss model is trained for robust anomaly detection by dividing surveillance films into defined segments during training and employing both positive and negative containers. Simultaneously, YOLO is utilised for object recognition while pose estimation methods are employed to extract information about object classes and human-related poses. The integration of these streams not only boosts the accuracy of anomaly detection but also improves the identification of events that are not connected to humans. This makes the suggested technique adaptable and efficient in many surveillance settings.

Paper Presenter

Vishalsinh P Gohil

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Cognitive Methods for Solution to Multicollinearity and Feature Selection in Regression Analysis for Thyroid Disease

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - R. Usharani, P. Saranya, T.Johnpeter, D.Anandhababu
Abstract - Multicollinearity (MC) occurs when various variables in a multiple linear regression analysis are substantially correlated not only with the response variable, but also with each other. Due to MC, several of the relevant variables under investigation become statistically insignificant. Conversely, overfitting occurs when the model fits the training set too closely, resulting in unwanted data being captured instead of the patterns that lie beneath. This research addresses three basic strategies for finding MC in Thyroid Disease dataset. The RE estimator (RE) compared with Principal Component Analysis (PCA) and also compared with least absolute shrinkage and selection operator (Lasso) and the results summarized. Principal components are used by PCA to represent the data instead of performing explicit Feature Selection (FS). Since these elements are only linear combinations of the original traits, it could be difficult to see how they contribute. A small number of factors are chosen by the PCA with the help of information gain at an acceptable level of P values of 0.4 and below. With P values of 0.5 and lower, the RE automatically chooses factors. With more acceptable P values, like 0.03, 0.02 and 0.007, and so forth, the Lasso automatically chooses factors. RE and Lasso have chosen a log lamda of 0.4 and 0.3, respectively, to resolve MC. The resolution of MC for the RE and PCA is 0.49 and 0.51, respectively. The RE incorporates all of the model's properties while penalizing the coefficients to keep them from growing excessively. The Lasso model drives some coefficients absolutely to zero in order to carry out automatic FS. It offers a limited collection of chosen features with nonzero coefficients, making it possible to create a more understandable model that concentrates on the most significant predictors. But we can use RR to choose the model's more salient features. On the other hand, a preferable alternative is to utilize Lasso to choose the model's minimum number of salient features. In contrast, MC resolution and FS can be handled concurrently by RE and Lasso. But the PCA wasn't the best choice for FS in parallel; it was only better at resolving MC.

Paper Presenter

R. Usha Rani

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Cryptocurrency pre-and post-Covid19: A Time Series analysis

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Abhijith M, Devika S, Dhanya M
Abstract - The emergence of cryptocurrencies, led by Bitcoin, has transformed financial paradigms, ushering in decentralized and encrypted transactions via blockchain technology. Ethereum, a notable cryptocurrency, employs Smart Contracts for enhanced transaction capabilities, surpassing Bitcoin in flexibility and complexity. In this study, we implement an in-depth analysis of cryptocurrency performance before and after COVID. Using rigorous time series analysis techniques including ARIMA, the Holt method, ACF, and ADF, we explore the volatility, trends, and stability of cryptocurrencies during and after the epidemic, providing useful insights into their market dynamics.

Paper Presenter

Abhijith M

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Driving Towards Tomorrow: A Comparative Study of Electronic Toll Collection and Satellite-Based Tolling in India's Vision on Vikasit Bharat 2047

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Deepak Sharma, Pankajkumar Anawade, Shailesh Gahane
Abstract - This study conducts a comprehensive comparative analysis of Electronic Toll Collection (ETC) and Satellite-Based Tolling systems, aiming to evaluate their respective effectiveness, efficiency, and suitability for modern transportation infrastructure. The research examines key factors such as technology, infrastructure requirements, coverage, accuracy, privacy concerns, interoperability, cost, maintenance, reliability, and environmental impact. Satellite-based tolling in India offers multifaceted benefits. It enhances efficiency by reducing traffic congestion and travel time, while promoting transparency in toll collection, curbing corruption, and ensuring accurate revenue collection. The system improves convenience through cashless transactions and boosts safety by minimizing the risk of accidents at toll plazas. Overall, Satellite-Based Tolling streamlines transportation fosters economic growth, and enhances the commuting experience for millions of Indians, marking a significant step towards modernizing the country's infrastructure as a vision on Vikasit Bharat 2047. By comparing and contrasting these two toll collection methods, the study seeks to provide valuable insights for policymakers, transportation regulatory authorities, and stakeholders in the field of transportation management.

Paper Presenter

Deepak Sharma

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Enhancing Railway Platform Safety through Rotating and Sliding Gates with RFID Sensor Technology

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Shreya Patil, Shruti Khochage, Sachin Patil, Pravin Desai
Abstract - Various modes of transportation, including air, water, and land, serve as crucial elements of global connectivity. Among land transportation options, railway transport stands out for its cost-efficiency and widespread infrastructure. India, in particular, boasts the world's fourth-largest railway network, yet grapples with significant safety challenges, notably railway accidents. These accidents often stem from hazards such as the gap between the railway and the platform, as well as unauthorized track crossings. To address these safety concerns effectively, a proposed solution involves the implementation of two distinct gate mechanisms. Firstly, a rotating gate system is devised to bridge the gap between the railway and the platform, mitigating the risk of accidents caused by the gap. Secondly, a sliding gate mechanism is intended to deter individuals from unauthorized access to the railway track, thus reducing the incidence of accidents related to track crossings. The implementation of the proposed system relies on the integration of various sensor technologies, including Radio-Frequency Identification (RFID) sensors, servo motors, buzzers, Arduino microcontrollers, and DC motors. These components work in tandem to detect train arrivals, trigger gate movements, and alert pedestrians of potential hazards through auditory cues. Furthermore, the incorporation of a solar power system enhances sustainability by reducing reliance on traditional electricity sources. By leveraging advanced technologies and innovative design principles, the proposed system aims to significantly diminish the frequency of railway accidents, thereby safeguarding human lives and promoting safer transportation infrastructure. Through proactive measures and interdisciplinary collaboration, the proposed system holds the potential to make substantial strides in enhancing railway safety and fostering societal well-being.

Paper Presenter

Shreya Patil

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Guarding Inboxes: An NLP-based Approach for Email Spam Detection

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Linda Varghese, Rajesh R Pai, Nandini Kumari, Savitha G, Girisha S
Abstract - The unsolicited and misleading email material is sent in bulk to many recipients, sometimes known as spam or junk email. In the recent time, the increasing volume of such emails poses challenges to the electronic communication. This study therefore tries to build a reliable and accurate method for identifying and preventing spam emails, for improving user experience and information security. The dataset "Spam email classification" extracted from the Kaggle website is used in this study to detect and categorise email spam. It analyses the text of the email using natural language processing and applies machine learning techniques to original unbalanced and resampled balanced datasets. The results indicate that the Random Forest model performs most effectively with an F1-Score of 98% and an accuracy of 93%, respectively.

Paper Presenter

Linda Varghese

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Pot-Hole Detection Using YOLO-V8

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Nishi, Rohit Pujar, Abdul Kareem, Amogh G Goni, V.V.Hosallimath
Abstract - In the pursuit of a cutting-edge solution for real-time object identification, YOLOv8 emerges as an innovative choice. Distinguished from other approaches, this state-of-the-art solution excels in achieving an optimal equilibrium between speed and accuracy. YOLOv8 accomplishes this through the implementation of an advanced network architecture, a groundbreaking anchor-free detection methodology, carefully crafted training approaches, and a streamlined decoupled head strategy. The utilization of YOLOv8 promises accurate and rapid outcomes, particularly in demanding scenarios.

Paper Presenter

Nishi

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Predictive analytics for seismic-prone regions of the Indian subcontinent using machine learning techniques

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Ruchi Sharma, Aniket Bhardwaj, V.K. Chandana, Manju Vyas, Nidhi Tiwari
Abstract - Earthquakes, as perilous natural calamities, have been a significant reason for casualties caused around the world. If predicted accurately, it can offer a valuable window of time to make substantial preparations, safeguarding several lives around seismic-prone regions. India has been observing an increase in the frequency of earthquakes of varying magnitudes, particularly around the northern plains. Although, there have been multiple studies performed on predictions of epicenters and magnitude yet only a few are based on the Indian Subcontinent Dataset. This study aims to give predictions of magnitudes and possible epicenters with higher accuracy and precision. In this paper, we use applications of various advanced technologies including metaheuristics mathematical analysis, machine learning models and deep learning models to analyze the dataset to predict course of earthquakes occurring within or in the vicinity of India.

Paper Presenter

Aniket Bhardwaj

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Risks in Instant Loan Apps: Analysing User Perceptions Using Machine Learning Approach

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Lekshmi A, Atul J, Adith J Pillai, Dhanya M, Sanju Kaladharan
Abstract - Instant loan apps have become increasingly popular, providing users with quick and easy access to loans. However, their rapid growth has raised concerns about potential risks, such as predatory lending practices, high-interest rates, and privacy issues. This study investigates user perceptions of these risks using machine learning techniques. It analyzes customer reviews of three popular Indian loan apps to identify user concerns. The findings show that while users value the convenience of these apps, they also express worries about high-interest rates, privacy risks, and predatory lending practices. The study highlights the importance of user financial literacy, transparency and ethical behavior from app developers, and appropriate regulations to ensure consumer protection and fair lending practices. It suggests further research avenues such as user experience studies, regulatory frameworks, and algorithmic accountability. Overall, this study contributes to the ongoing discussion about responsible lending practices and consumer protection in the digital lending space.

Paper Presenter

Lekshmi A

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Unravel the DFL Level among Nationalized Bank Women Employees in Kerala

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - M. D. Parvathy, Dayana Das, N. Ajithkumar
Abstract - The global surge in the adoption of digital financial services, accelerated by the recent crisis, underscores the critical importance of Digital Financial Literacy (DFL). In the dynamic landscape shaped by digitization, proficiency in DFL is not just advantageous but indispensable. It forms the foundation for individuals to adeptly navigate and leverage digital financial services, make informed decisions, optimize savings, and engage in judicious investments. This study, conducted on a sample size of 384 women employees from a population of 15,158 within nationalized banks in Kerala, investigates the level of DFL among working women. Findings indicate a generally high level of DFL, highlighting the adaptability of women employees in utilizing digital financial tools. However, specific areas such as 'Knowledge of Digital Financial Services,’ 'Self-Determination to Use Knowledge and Skill,’ 'Financial Behaviour,’ 'Financial Attitude,’ and 'Financial Knowledge' demonstrate room for improvement. The mean percentage score is employed as an analytical tool, shedding light on nuances within the DFL spectrum. This research provides valuable insights into the DFL landscape among women employees in nationalized banks in Kerala, offering a foundation for targeted interventions to enhance digital financial literacy. As the financial landscape evolves, cultivating a robust DFL becomes not only advantageous but imperative for ensuring the financial well-being of individuals in today's rapidly changing economic environment.

Paper Presenter

M. D. Parvathy

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

A study on the perceptions and factors influencing the current utilisation of Technology-Based Audit Techniques (TBAT)

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Anand V, Vishnu R S, Gayathri V Nair, Priyanka K
Abstract - This study investigates the perceptions and factors influencing the current utilisation of Technology-Based Audit Techniques (TBAT) in India. In-depth interviews with Chartered Accountants (CAs) explored their perceptions and revealed the importance of prioritising high-risk areas and considering materiality when deploying TBAT. The findings highlight potential shortcomings in cost-benefit analysis, risk assessment, and auditor attitudes, which can negatively impact audit quality when using TBAT. In conclusion, successful TBAT implementation requires overcoming auditor resistance, prioritising high-risk areas with materiality considerations, maintaining healthy skepticism alongside software use, and employing a structured Cost-Benefit Analysis (CBA) that encompasses long-term benefits and stakeholder impact. Ultimately, these measures safeguard audit quality and the organisation's reputation

Paper Presenter

Anand V

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Access control scheme for Medical Cyber-Physical Systems using Quantum Cryptography

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Parikshit N. Mahalle, Siddhesh S. Raskar, Abhishek PravinPatil, SwaranIthape
Abstract - In recent years there has been a boom in the internet that we know today and it forms a vital part of transferring data, data analysis, and sharing of resources. The sharing of resources becomes a serious concern when the data is highly valuable, especially in the case of Medical Cyber-Physical Systems. Since sensitive data is sent using some protocols that could be easily intruded into, with the help of emerging quantum systems in a matter of seconds, the security of the data becomes a major concern. This paper presents a model of ECC-based encryption/decryption using quantum cryptography. This model ensures the integrity of the data and alerts the system if the data has been intercepted or eavesdropped by an external entity by using the quantum properties of the quantum key and also the algorithm needed to implement the system.

Paper Presenter

Siddhesh S. Raskar

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Automated Breast Cancer Detection Using Convolutional Neural Networks

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Sachi Joshi, Upesh Patel
Abstract - The development of particular and effective diagnostic tool is imperative as breast cancers continues to be a major worldwide health problem. Convolutional Neural Networks one form of deep learning approach, have proven wonderful overall performance in medical image evaluation responsibilities in present day years. The method provided in this paper demonstrates CNNs' advantages inside the detection of breast cancers. This paper used the CNN for diagnosing breast cancer using CBIS-DDSM (Curated Breast Imaging Subset of DDSM). The suggested technique first makes use of a CNN architecture to identify patterns that are suggestive of breast abnormalities via extracting excessive level features from mammography images and histopathology images. These features are then extracted and fed into in default MLP classifier, which completes the very last category task and further refines the illustration. By the usage of CNNs' hierarchical feature learning capabilities, this method increases detection accuracy via a synergistic effect. Extensive experiments are achieved using publicly to be had datasets of images so as to assess the efficacy of the technique. The findings show that almost about breast cancers detection task, the CNN version outperforms more conventional machine learning algorithms in phrases of accuracy, sensitivity, and specificity.

Paper Presenter

Sachi Joshi

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Convolutional Speech verification: Detecting synthetic speech using deep learning

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Vijeta V Shettar, Damini A Sunkad, Rakshankhan A Kulkarni, Satish Chikkamath, SR Nirmala, Suneeta V Budihal
Abstract - Today, with the unlawful activities and manipulations carried out by deep fakes, fake speech detection has become highly significant. Sound synthesis produced by specific deep learning algorithms is known as a ”deep fake.” While approaches based on deep learning have demonstrated improved performance and encouraging outcomes, they have significant dependence on training data and require careful selection of hyperparameters, which poses a barrier to generalization. Literature proves that Recurrent neural networks (RNN) provide good results on such tasks. Recently, a Convolutional Neural Network (CNN) has been explored for detecting fake speech; in this direction, we propose a Convolutional Neural Network(CNN) model that inputs raw waveform after preprocessing and predicts whether the output is real or fake. The tested Convolutional Neural Network (CNN) model has given significant results comparable with Recurrent Neural Network (RNN) models.

Paper Presenter

Vijeta V Shettar

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Enhancing Emotion Classification through CNN Models for Speech Analysis

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Sri Samyu Tankasala, Sai Harshitha Peddi, Sushma Bodpati, Jahnavi Kuddigana, Prathibhamol C.P
Abstract - Applications for emotion recognition in speech span from mental health evaluation to human-computer interaction. In order to analyze emotional expressions in speech signals, this research introduces a novel method that combines convolutional neural networks (CNNs)[1] with attention processes. Speech emotion identification systems have advanced in a number of ways, including the application of deep learning models and novel temporal and auditory variables. This research presents a two-dimensional Convolutional Neural Network (CNN) and long short-term memory (LSTM)[2] network combination to develop a self-attention based deep learning model. This work expands on previous research by conducting extensive experiments on various combinations of spectral and rhythmic information in order to determine the features that perform the best for this task. By modelling speech as Mel-Spectrograms, we allow CNNs to capture spatial information while also accounting for temporal dynamics of emotions. Our Parallel CNN-Transformer network has an accuracy of 74 percent, followed by Parallel CNN-BLSTM-Attention at 60 percent, outperforming standalone models. Notably, our solution requires fewer parameters, increasing efficiency while maintaining performance..

Paper Presenter

Sri Samyu Tankasala

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Green Entrepreneurship and Sustainable Development in South India Linking to SDG 9

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Ganga S Nair, Dayana Das
Abstract - Green entrepreneurship serves a crucial influence on overcoming social challenges and damage to the environment. The objective of green entrepreneurship aims to promote the economy's steady expansion over the long term. Businesses posses s an enormous chance to formulate, transmit, and report their overall plan, goals, and activities to the SDGs, and will allow them to take benefit of multiple perks. A worldwide path for honour, harmony, and development for people and the planet both now and in the future is supplied by the 2030 Agenda for Sustainable Development. This study investigates the way green entrepreneurship assists South India meet it s 9th sustainable development goal and mainly focuses on youth and how they supports in achieving the 9th goal of sustainable development The research design is descriptive and hypothetic statements were evaluated. Analysis of the research provides light on the impact of green entrepreneurship associated with SDG 9 in South India, which projects that Indian economy is progressing towards the direction of sustainable entrepreneurship.

Paper Presenter

Ganga S Nair

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Innovative Approaches to Mental Health: Chatbot Engagement and NLP for Detection and Support

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Preetam Vitthalkar, Prateek Deshpande, Vijeta Aarsanal, Satish chikkamath, Nirmala S R, Suneeta Budihal
Abstract - Sentiment analysis is the technique of analyzing people’s emotions, attitudes, and thoughts expressed in the form of written text. Detection and addressing of mental health issues early is vital for better outcomes and reducing overall societal costs. The majority of the research is based on opinion mining to comprehend the public’s opinion towards product perception. This work introduces a novel chatbot system to interact with users. The gathered user data is classified using a hybrid model combining Bi-LSTM and Na¨ıve Bayes classifier. The classifiers are trained on a concatenated dataset comprising reviews, tweets, comments, and texts, with additional comparison against various machine learning classifiers for accuracy assessment. Results indicate the effectiveness of the trained and tested model, achieving a high accuracy rate in predicting mental health conditions.

Paper Presenter

Preetam Vitthalkar

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Role of Chatbots and Virtual Assistants in Customer Service for Life Insurance Companies in India

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Vanishree Pabalkar, Ruby Chanda, Pooja Nair
Abstract - The emerging trend in user interaction with web and mobile applications is chatbots. In the past, call centres or helpline numbers had to be called in order to resolve questions about a product or program. Natural language processing ("NLP") is the technology that is being used for chatbot development. The accuracy and efficiency of natural language processing have significantly improved thanks to machine learning technology, making chatbots an attractive alternative for many businesses. The efficiency of chatbots should continue to increase in the years to come thanks to technological developments in NLP. By giving the bot some fundamental commonly asked questions by clients or users and the answers to those questions, a simple chatbot may be developed. By integrating chatbots with business software, an organization's functionality can be enhanced. Questions like "What is policy count for today?" or "What is the status of policy?" or "What number of policies issued?" can now be addressed. Commercial chatbots of today rely on IT giants' platforms for their natural language processing. These include Amazon Lex, Facebook Deep Text, Google Cloud Natural Language API, and Microsoft Cognitive Services. Chatbots are used on a variety of business platforms, including e-commerce sites, insurance providers, banks, and other customer service providers. The current study revolves around understanding the role of chatbots and virtual assistants in customer service for life insurance companies in India.

Paper Presenter

Vanishree Pabalkar

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

The Random Forest that Found the Fibroids: Machine Learning Algorithms for Uterine Fibroid Detection

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Rudrani Chavarkar, Shreya Kamath, Kumkum Saxena
Abstract - Uterine fibroids, common among women of childbearing age, cause major health challenges, including infertility and miscarriage. This study evaluates five machine learning algorithms, including Support Vector Machine, VGG16, Gaussian Mixture Model, Gaussian Mixture Model with Stacking (using Random Forest and Logistic Regression), and Random Forest for fibroid detection. Random Forest came forth as the best-performing model, achieving 99.0% accuracy with low inference time. The accuracy of SVM and VGG16 turns out to be 93.5% and 93.7% respectively but with certain limitations in precision and recall rates. Using the stacking ensembling technique in GMM-S we improved the performance resulting in an accuracy of 97.2%, which is closer to that of Random Forest while improving recall and precision rates. The findings of these machine learning approaches mark their capacity to improve the diagnostic accuracy of uterine fibroids.

Paper Presenter

Shreya Kamath

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Towards Precision Agriculture: Machine Learning-Based Crop Yield Prediction in Maharashtra

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Sandip Shinde, Vaishnavi Gosavi, Revati Nimbalkar, Vaishnavi Patade, Kaustubh Lanke, Pranav Palekar
Abstract - For Maharashtra, India, to optimize agricultural practices and ensure food security, accurate crop yield forecasts are essential. In light of easily accessible metrics including area sown, temperature, rainfall data, and district, this study examines the effectiveness of machine learning algorithms in predicting crop output. Comparison of three well-known algorithms—linear regression, random forest, and decision tree—is the subject of this study. Random Forest proved to be the most effective, achieving the highest accuracy of 98.15%. The study tries to determine the optimal approach for yield prediction by assessing these algorithms' performance on historical agriculture data of Maharashtra such as crop yield, area, production, rain, temperature, etc. In the end, this will boost agricultural output and resistance to climate unpredictability by providing farmers with insightful information for managing resources and choosing crops.

Paper Presenter

Vaishnavi Gosavi

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Advanced Deep Learning Solutions for Enhancing Pearl Millet Crop Health and Productivity

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Manoranjitham R, Yogesh K M, Alvino Rock, Vaishali R Kulkarni, Punitha S, Thompson Stephan
Abstract - This study addresses the significant impact of leaf diseases, such as rust and blast, on the agricultural productivity of pearl millet, a crop known for its high nutritional value and micronutrient content. In tackling these challenges, the research introduces a deep learning-based approach for the accurate and minimally supervised identification and diagnosis of these diseases. The methodology employs advanced deep learning algorithms, including VGG-16, Mobile Net V1, and Mobile Net V2, renowned for their pattern recognition capabilities and adaptability in applying knowledge from previous tasks to new scenarios. These mod-els are specifically utilized to detect rust and blast diseases in pearl millet. Performance metrics such as accuracy, precision, recall, and F1-score are used to evaluate the effectiveness of these models. Results indicate a high level of accuracy, with the VGG-16 model achieving 99.45%, and both Mobile Net V1 and Mobile Net V2 models showing an accuracy of 99.32% in detecting diseased leaves. This research not only contributes to advancements in agricultural technology but also provides valuable tools for farmers and the agricultural industry to manage crop diseases more efficiently.

Paper Presenter

Manoranjitham R

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Blockchain Driven Auction App

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Tanishq Shinde, Anurag Nalkar, Aryan Nikale, Rohan Mathew, Priyamvada Singh Chauhan
Abstract - This paper unveils "BidChainX," a cutting-edge blockchain-based auction platform designed to revolutionize conventional auction models. Departing from centralized approaches, this system prioritizes decentralization, transparency, and security, empowering both buyers and sellers alike. Through the fusion of smart contracts with cryptocurrency, BidChainX orchestrates real-time updates, seamless bidding experiences, and rapid payment settlements. Furthermore, it integrates a robust reputation management system to foster trust within the marketplace. Notably, BidChainX places paramount importance on security and privacy, exemplified by the incorporation of mutual anonymity and comprehensive user protection measures. As it disrupts traditional retail dynamics, this project aims to expand its global reach and stimulate international trade and commerce, all while maintaining a user-friendly approach.

Paper Presenter

Tanishq Shinde

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Building an Arduino-Based Dual Axis Solar Tracking System for Enhanced Energy Efficiency

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Thangam S, M Gurupriya, Anees Sajid Injeti, G. Neha Rupsica, Gopireddy Praneetha Reddy
Abstract - The construction of an Arduino-based solar tracking system to increase solar panel efficiency is described in this project. Through the use of servo motors and light sensors (LDRs), the system continuously modifies the orientation of the solar panel to face the sun. Installing the sensors and putting the solar panels on a moveable frame comprise the hardware setup. For the best possible alignment with the sun, the servo motor is controlled by the Arduino board, which also analyses data from the sensors. Coding is used in the software component to interpret sensor data and control the movement of the servo motors. Accurate tracking requires calibration. To provide optimal energy capture under varying illumination conditions, precise solar tracking requires extensive testing and fine-tuning. For the system to perform over the long run, consideration is also given to the power supply and maintenance issues. This study provides a methodical and easily understandable way to improve solar energy harvesting, which might lead to sustainable use of solar energy.

Paper Presenter

M Gurupriya

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Challenges in Determining the Authenticity, Honesty, and Intentions of Opinions Expressed on Twitter and Sentiment Analysis

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Ahongsangbam Dorendro, H. Mamata Devi
Abstract - Social media platforms, notably Twitter, have emerged as pivotal arenas for the dissemination of opinions spanning diverse domains, with politics standing prominently among them. However, discerning the authenticity, honesty, and underlying intentions behind these expressed opinions poses a formidable challenge. This study delves into the multifaceted obstacles associated with gauging the credibility of opinions proliferating on Twitter, with a particular focus on the pervasive influence of social dynamics, the manipulation of narratives through the creation of new accounts, and the heightened complexities surrounding political discourse. Social dynamics wield considerable influence over the credibility of opinions expressed on Twitter. Users often engage in echo chambers, where confirmation bias amplifies certain viewpoints while stifling dissenting voices. Additionally, the phenomenon of social influence leads individuals to conform to prevailing opinions, further complicating the task of discerning genuine sentiment. Moreover, the proliferation of fake accounts designed to manipulate narratives poses a significant challenge to opinion credibility assessment. To address these challenges, novel approaches must be incorporated into Twitter data Sentiment Analysis frameworks.

Paper Presenter

Ahongsangbam Dorendro

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Deep Learning Based Group Activity Recognition: In Depth Analysis Based on Videos

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Yogita K. Desai, Amol D. Potgantwar
Abstract - Group activity recognition(GAR) has several practical applications such as Analysis of sports videos, surveillance and security, crowd management, public safety etc. Researchers are focusing more on group activity recognition using videos. A state of the art review is given in this paper for Group activity recognition in videos. First the importance of Group activity recognition is explored, then a survey on group activity recognition methods is given which includes several categories of group activity recognition like actor relation based, attention based, Recurrent Neural Network (RNN) based, skeleton based and graph based. Several datasets which are commonly used in group activity recognition are discussed in detail. As group activity recognition performs classification of different activities, performance metrics of classification are elaborated. Finally, through several challenges conceivable directions for upcoming researchers are summarized.

Paper Presenter

Yogita K. Desai

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

E-Parking Assistant

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Ashutosh Marathe, Atharva Borade, Aryan Chalpe, Rachit Chandawar, Pratik Davare, Eshan Dasarwar
Abstract - The abstract presents an overview of our research on the "Intelligent E-Parking Assistant." In response to the burgeoning challenges of urban parking, our comprehensive system leverages image processing, database management, mobile application development, and predictive analytics. The architecture integrates Python, Firebase, and Java, with team members contributing to coding, UI design, integration, and documentation. Experimental results showcase high spot detection accuracy, efficient navigation, and optimized predictive analytics. The e-parking assistant stands as a promising solution, mitigating urban congestion and enhancing the overall parking experience, marking a significant advancement in intelligent urban transportation systems.

Paper Presenter

Eshan Dasarwar

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Multi-modal image-text fusion for Respiratory Disease Classification

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Thi-Diem Truong, Phuoc-Hai Huynh, Van Hoa Nguyen, Thanh-Nghi Do
Abstract - In disease classification, multi-modal fusion model has emerged as a promising approach to enhance both diagnostic accuracy and efficiency. In this paper, we propose to train the multi-modal model for classifying respiratory illnesses from chest X-ray images and symptom texts. The proposed model uses Support Vector Machine (SVM) on top of Vision Transformer (ViT) and Random Forest (RF) with Term Frequency- Inverse Document Frequency (TF-IDF) for the disease classification. We collect a new real dataset from An Giang province regional general hospital. The experimental results show that using only the ViT model for classifying diseases from chest X-ray images achieves an accuracy of 62.43%. Furthermore, disease classification based on clinical symptom text achieves accuracies of 77.52% and 70.10% respectively when using RF and SVM models with TF-IDF technique. Our multi-modal model achieves an accuracy with 80.10%, surpassing uni-modal models using only images or text.

Paper Presenter

Thi-Diem Truong

Vietnam

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Navigating Technology-Enhanced Language Teaching: Assessing Teachers’ Preparedness and Obstacles Amidst the COVID-19 Crisis

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Khushboo Kuddus, Barsarani Panigrahi, Lopamudra Mohapatra
Abstract - The whole world went through a tough time during the catastropic COVID-19 pandemic, resulting in unanticipated drastic changes in almost every aspect of our lives. It brought about a remarkable change in the education system worldwide. In order to keep teaching and learning continuing amidst the complete closure and lockdown, the entire education system went through a paradigm shift, from traditional face-to-face classroom teaching to online education. This technology-enabled teaching mode of education incorporated cutting-edge technologies and software to conduct classes. As it was the only alternative to conduct classes during the pandemic, teachers, the most important stakeholders in the educational system, had no choice but to continue teaching without having any time to get ready for the change or to get trained in integrating technology into the teaching process. As a result, they experienced a lot of challenges and, at the same time, gained experience in online teaching. Considering the condition, it is pertinent to investigate the online teaching experience of ESL (English as a Second Language) teachers in order to understand their perceptions towards the efficacy of technology-enhanced language teaching (TELT) and the challenges they faced while adapting the new pedagogy of English language teaching (ELT). The study is based on a quantitative study conducted with ESL teachers of several schools in Khurda, Balasore, and Mayurbhanj districts of Odisha, India. It has been found that the paradigm shift in teaching pedagogy due to the pandemic has made ESL teachers adopt technology-enhanced language teaching. Although certain inhibiting factors impact the integration of technology in their teaching, they are motivated to incorporate TELT and are willing to get trained in technology-integrated language learning. These challenges can further be analysed and mitigated to enhance the preparedness of the teachers for the future and help them embrace the latest developments in TELT.

Paper Presenter

Barsarani Panigrahi

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Neural Network-Powered Image Captioning: Generating Descriptive Text for Visual Content

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Sneha Jakati, Sukhadevi Kannal, Charvi Kolloori, Satish chikkamath, Nirmala S R, Suneeta V Budihal
Abstract - Image captioning is the process of identifying an image’s content and adding a pertinent caption to it. Each image has a wealth of information that humans can quickly pick up. It is challenging for a machine to mimic the human ability to comprehend visual information and generate descriptive language. This work aims to bring Aqueduct between computer vision and natural language processing, which should be able to provide an accurate and relevant caption for a given image. The present work utilizes a technical approach using the ViT (Vision Transformer)-GPT-2 (Generative Pre-trained Transformer 2) model and the encoder-decoder design employing CNN (Convolutional Neural Network) LSTM (Long Short-Term Memory). The dataset used is Flicker8k, consisting of 8000 images. There are five distinct captions for each image, offering a variety of explanations for a single picture, wherein it selects the most relevant single caption for a given image.

Paper Presenter

Sneha Jakati

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Priority-Based Resource Allocation in Narrowband IoT Networks

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Anirudh Girish, Suneeta V Budihal
Abstract - Narrowband Internet of Things (NB-IoT) networks serve as the backbone for a multitude of low-power, low-bandwidth IoT applications. However, prevailing resource allocation strategies often struggle to efficiently utilize network resources and meet diverse Quality of Service (QoS) requirements. This paper introduces a novel priority-based resource allocation approach for NB-IoT networks, dynamically prioritizing resources based on application criticality and network dynamics. Through simulations, our method shows significant improvements in key performance metrics, ensuring efficient network utilization and meeting diverse QoS requirements. Rigorous evaluations validate its superiority, promising improved IoT connectivity and resource management.

Paper Presenter

Anirudh Girish

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

A Review on the Applications of Machine Learning, Predictive Modelling and Virtual Screening for Drug Discovery

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Ayush P. Gadkari, Mansvi Daigavhane, Anushka Arghode, Prateek Verma, Swapnil Gundewar
Abstract - In the realm of drug discovery process, Machine Learning (ML) is essential for enhancing decision-making in biological or pharmaceutical databases. ML has applications in several phases of the drug development process, such as target validation, predictive biomarker identification, and digital pathology data interpretation in clinical trials. Utilizing ML in drug discovery can increase success rates and expedite the identification of promising new therapeutic targets. The goal of drug discovery is to find new drug candidates by analyzing enormous amounts of biological or medicinal data using computational algorithms. A drug development process faces a number of difficulties, including insufficient data, model transferability, sparse and heterogeneous data, repeatability and validation, and feature representation and selection. In the area of drug discovery, virtual screening and predictive modelling are the two main uses of ML. By effectively screening huge chemical libraries, supporting target identification and optimizing, and easing drug repurposing initiatives, virtual screening significantly speeds up the drug development process and eventually results in the identification of novel therapeutic agents. In the realm of drug development, the current study reviews the role of virtual screening and predictive modelling to analyze large amounts of data and forecast treatment outcomes for cancer and other diseases.

Paper Presenter

Ayush P. Gadkari

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

A Survey on Deep Learning and Image Processing Techniques on Leaf Disease Detection

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Yudhveer Singh Moudgil, Ritika Mehra
Abstract - We examine the integration of deep learning and image processing techniques for the detection of plant leaf diseases, with a focus on the incorporation of saliency maps to enhance model interpretability. Through an analysis of various methodologies and classification techniques, we highlight the significance of considering crop-specific characteristics in disease segmentation. Despite notable advancements, a crucial research gap persists in the interpretability of models, necessitating further refinement of saliency map techniques. By addressing this challenge, we envision a transformative impact on agricultural disease detection, fostering global food security and sustainable farming practices through informed interventions and minimized crop losses.

Paper Presenter

Yudhveer Singh Moudgil

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Challenges and Solutions in Managing Scattered Applications in Micro, Small and Medium Scale Enterprises

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Zabiullah Khan, Arun, Raju Kumar. A, Juveria Talha, Ranjith.P
Abstract - As technology advances, businesses increasingly rely on a multitude of software programs. The diverse range of software programs utilized within businesses can pose several challenges. These include hindering effective information sharing, compromising security measures, and potentially slowing down operational processes. We have observed that the fragmented utilization of software significantly impacts business operations. It leads to decreased productivity among workers, disrupts data organization, and adversely affects overall company performance. However, there are effective strategies to address these challenges. By leveraging specialized software tools, adhering to established protocols, and transitioning certain programs to web-based platforms, businesses can optimize their operations for improved efficiency and performance. Moreover, proper employee training is essential to ensure smooth adaptation to these changes. Although managing multiple software systems can be challenging, with the right approach, businesses can streamline operations, enhance security measures, and sustain growth in the dynamic landscape of business.

Paper Presenter

Arun

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Enhancing the Average Capacity of 6G Networks by Utilizing NOMA and mMIMO with Spectrum Sharing Modes

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Mohamed Hassan, Manwinder Singh, Khalid Hamid, Ghada A.M. Abdu, Imadeldin Elsayed
Abstract - Sixth-generation (6G) and other next-gen networks may greatly profit from non-orthogonal multiple access (NOMA). Promising new technologies that could be used to increase capacity are cognitive radio (CR) and multiple access. With the combination of Cognitive Radio Networks (CRNs) and network-oriented multi-access NOMA capabilities, a communications revolution is expected. The study shows a new way to improve the NOMA power domain's average capacity in the downlink (DL) when dealing with an uncooperative interweave CRN (UICRN(. This occurs when a primary user (PU) is unable to receive data over the dedicated channel due to the presence of noise or interference. The four network topologies use quadrature phase shift keying (QPSK) modulation over 70 MHz bandwidths (BWs). The transmit powers, user distances, and power location coefficients vary. The network architectures include massive multiple-input multiple-output (mMIMO) (128x128, 256x256, and 512x512), among others. In the performance study, channel instability, successive interference cancellation (SIC), and frequency-dependent Rayleigh fading are all looked at. The average output of the given model is found using MATLAB. Adding 128x128, 256x256, and 512x512 mMIMO to DL NOMA boosts average capacity by 60%, 65.5%, and 66.7% and improves by 70.1.1%, 76.4%, and 77.6% using the UICR NOMA model for the best user. mMIMO and CRN significantly improve average capacity performance. The produced expressions match the Monte Carlo simulations, validating our findings.

Paper Presenter

Mohamed Hassan

Stu6, India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Green HRM: The resilience strategy for The VUCA World

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Reena Lenka, Ankita Bhatia
Abstract - The dawn of the 21st century was enthusiastically anticipated by people all around the world. Nobody anticipated that the beginning of the century would be so terrifying and horrible that the entire world would experience such a high degree of death and destruction. The VUCA World has played a significant role in eradicating humankind. Every aspect of a person's support system has been impacted. The global economy and health have suffered significantly since Jobs. Every nation in the world is putting various recovery, resilience, and adaptation methods into practice in a variety of work sectors, including HR, Finance, Marketing, IT, and others, to turn the lockdown world into an active one. This essay discusses recuperation, resiliency, and adaptation tactics. The human workforce is the most crucial foundation of any firm in The VUCA World, directly influencing the economy of the nation as a whole. This document offers recovery, resilience, and adaptation techniques for The VUCA World in the form of Green HR. Considering the current environment, global sustainability solutions are required.

Paper Presenter

Reena Lenka

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

KisanSaarthi: A Comprehensive Agricultural Ecosystem for Smart Farming and Sustainable Crop Management

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Ayush Jha, Harsh Mishra, Ruchir Gaur, Sagar D
Abstract - This article introduces "KisanSaarthi," a system, for analyzing crops and providing recommendations aimed at transforming investments. Created as a cross platform mobile application, KisanSaarthi allows landowners to list their farmland for rent or lease while helping investors make well informed decisions with crop suggestions based on advanced data analysis. The system uses datasets such as weather information, land characteristics, crop details and market price trends to train a Random Forest Classifier for crop forecasts. Notably this machine learning model is regularly retrained to adapt to changing conditions ensuring enhancement in prediction precision. KisanSaarthi provides premium services for crop cultivation. Facilitates bidding processes for selling harvested crops to distributors. It features a user interface with functionality. This paper discusses the aspects, database integration and benefits of the retraining mechanism, in the machine learning model used in KisanSaarthi compared to existing systems emphasizing its potential to modernize and optimize agricultural investment strategies.

Paper Presenter

Ayush Jha

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Sneaker Resale Price Prediction using Ensemble Learning Techniques

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Laksh Doshi, Jay Samberkar, Chaitanya Deshpande, Kumkum Saxena
Abstract - The valuation of the sneaker resale industry has reached a mark of about $13.37 billion in 2024 and it is assured to reach a mark of $30 billion by 2030. This has a simple indication that the growth in the sale of the sneakers has become a powerful business opportunity. E-commerce giants have emerged in the sneaker resale market like StockX and GOAT. Sneaker resale price prediction can help small scale resellers and buyers. The aim of this research is to compare the performance of different machine learning algorithms and find out the best model for the prediction of the resale price of the sneakers. The machine learning models used in this study are Linear Regression, Random Forest Regressor, Lasso Regression, followed by the ensemble learning methods – bagging and stacking. All the three base models give similar performance with lasso having slight edge. Further research shows that stacking using lasso regression with base model lasso regression gives the best result.

Paper Presenter

Laksh Doshi

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

The Role of Artificial Intelligence in Simulating, Automating and Analysing Business Operations

Thursday August 8, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Kranti Shingate, Veena Grover, Shivi Khanna, Gaurav Gupta, Pradeep Chintale, HarshaVardhan Nerella, CH Vanipriya, Saikat Gochhait
Abstract - Business processes have been transformed with the advent of Artificial intelligence. However, to efficiently utilize the technology and to close the gap, we reviewed the literature to find these solutions in this work. We ensured that styles worked because they allowed for extensions and replication. In these studies, we correlated patterns that assisted with task automation and helped analysts create, expand, or re- engineer business processes with the confidence to make judgments. The authors used various AI methods, including swarm intelligence, Bayesian networks, and K-means. Our analysis gives data on the approaches and issues being dealt with and indicates potential future directions. Processes for Predictive Business Future planning and activity prediction are examples of monitoring jobs that are becoming less significant as new technologies allow for the intelligent automation of company processes. Deep learning models are used in recent work on this subject to encapsulate historical event information without further processing. The data context, which includes the dependence of conditions and particular traits, might also have an impact on the anticipated data, even though it was not taken into account in earlier research. We present a novel encoding strategy for state data, encompassing non-existent, multi-character private, and regular event states. We present the Transformer and LSTM deep learning models, two new deep learning models, two popular deep learning models.

Paper Presenter

Kranti Shingate

India

Thursday August 8, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:27pm IST

Web-based Sustainable Waste Minimization System

Thursday August 8, 2024 12:27pm - 12:38pm IST

Tango 1

Authors - Seema Jogad, Milind Late, Rishika Sonker
Abstract - The climate change and global warming are biggest threats to our planet. Increase in number of people and urbanization affects our amount of waste generation per day. Every year India generates 64M tonnes of waste and it is estimated that by 2030 it will reach to 456M tonnes annually. Because of poor source segregation, littering and bad waste disposal habits, most of our waste ended up in drainage system, water bodies, lakes, roadside dump yards and at last in landfill. In this work we have proposed a web-based solution to minimize our per day waste. This system provides solution to minimize the waste generation per day by every individual. By adopting such solutions and conscious consumption a lot of waste is minimized from going into the landfill. This system is developed using Extensive hypertext markup language and cascading style scheme (CSS). Further, PHP and JavaScript are used. Hence this contributes lesser pollution and a step towards greener future.

Paper Presenter

Seema Jogad

India

Thursday August 8, 2024 12:27pm - 12:38pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

12:27pm IST

Leveraging RNNs and Transformers for Personalized Mental Health Chatbots: A Review

Thursday August 8, 2024 12:27pm - 12:38pm IST

Tango 2

Authors - Bhawani Singh Rathore, Sandeep Chaurasia
Abstract - The rising incidence of mental health issues makes it more important than ever to include technology-driven solutions into the field of mental health assistance. This study looks at how important it is to use Transformer-based language models and Recurrent Neural Networks (RNNs) to create healthcare chatbots that offer individualized mental health care. To help chatbots comprehend and interact with users in a more sympathetic and contextually relevant way, this paper investigates the synergistic use of these two AI approaches. This research highlights the value of individualized mental health care through a thorough literature analysis, underscoring the necessity for chatbots to adjust and develop in response to the unique requirements of each user. With the help of Transformer models and RNNs, these chatbots can provide responses that are human-like while also maintaining and managing the context of ongoing conversations. These effects include improving emotional intelligence, providing tailored solutions, and continually learning from user interactions. It highlights how important a role these chatbots might play in providing mental health help to a larger community. This survey paper offers a pilot study in which we cover both RNN and Transformer role in deployment of healthcare solution. The findings show that using RNNs and Transformers to provide individualized mental health care can have positive effects, since users report feeling more satisfied and that their treatment is effective.

Paper Presenter

Bhawani Singh Rathore

India

Thursday August 8, 2024 12:27pm - 12:38pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

12:27pm IST

UNIXCOLL (A Attendance management system)

Thursday August 8, 2024 12:27pm - 12:38pm IST

Strategy/Analysis

Authors - Samarth Ashok Pujari, Shubham Anil Taru, Nikita Arjun Bhutnale, Manav Ashok Thakur, Sthavir Mahendra Rokade
Abstract - The Attendance Portal is software designed to effectively manage student attendance on a daily basis within a school environment. This system is responsible for maintaining detailed records of student attendance, generating reports based on their presence in class, and providing access to both staff and students through individualized usernames and passwords. Staff members are granted separate credentials to mark students' attendance, ensuring accountability and accuracy in attendance tracking. Each staff member is assigned a unique username and password for attendance management purposes. This system generates precise reports reflecting student attendance on a weekly and monthly basis, facilitating comprehensive oversight of attendance patterns. Furthermore, students are provided with their own login credentials, allowing them to access and review their attendance status independently. This enhances transparency and encourages students to actively monitor their attendance records. The UNIXCOLL Attendance Management System prioritizes data accuracy, security, and accessibility, ensuring a streamlined and efficient process for monitoring and managing student attendance within the educational setting.

Paper Presenter

Manav Ashok Thakur

India

Thursday August 8, 2024 12:27pm - 12:38pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

12:27pm IST

Unveiling the Potential of 6G Technology: A Comprehensive Analysis and Future Prospects

Thursday August 8, 2024 12:27pm - 12:38pm IST

Debate

Authors - Prachi Gaurang Desai, Kanubhai K. Patel, Sagar Kavaiya, Krishna Kant, Nilay Vaidya
Abstract - The world is expecting another dramatic breakthrough in wireless communication with the impending arrival of 6G technology. Providing a comprehensive analysis of 6G technology, this study seeks to clarify its basic ideas, its uses, obstacles, and possibilities. In this article, a roadmap for the development of 6G technology is presented, along with an analysis of its revolutionary influence on multiple sectors, based on an extensive assessment of the literature and expert observations. It also looks into the technological developments that are going to reshape wireless communication, like terahertz frequencies, artificial intelligence (AI)-powered networks, and ubiquitous broadband. This research study provides important insights into the next frontier of telecommunications by assessing the potential and challenges related to 6G implementation.

Paper Presenter

Prachi Gaurang Desai

India

Thursday August 8, 2024 12:27pm - 12:38pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

12:39pm IST

Winning Formula: Data-Driven Cricket Team Selection and Match Prediction

Thursday August 8, 2024 12:39pm - 12:50pm IST

Tango 1

Authors - Muhammad Ashar Reza, Papineni Sai Charan, Pranit Prasant Pai, Pratham R Shetty, R Bharathi, Sandesh B J
Abstract - Cricket is a sport adored by people all over the world. It transcends mere competition between two teams of eleven players. It comprises an extensive ecosystem including fans, media, coaches and technology. As the popularity of the sport soars to new levels and investments in players increase, a data-driven approach towards decision-making is the need of the hour for cricket teams all around the globe. A model-based recommender system for cricket team selection is introduced which takes into consideration various key aspects of the game such as player statistics, match-ups and pitch conditions. Further, the results and validations for matches in the 2023 One-Day International World Cup held in India are presented. The research leverages data science, machine learning and graph analysis concepts in order to enhance cricket team selection and also offers a comprehensive framework for cricket enthusiasts, analysts and team management looking to offer deserving players a contract.

Paper Presenter

Muhammad Ashar Reza

India

Thursday August 8, 2024 12:39pm - 12:50pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

12:39pm IST

Cross-Lingual Dictionary Generation Tool Using Phonetic Similarity for Natural Language Translation of Gujarati to Hindi

Thursday August 8, 2024 12:39pm - 12:50pm IST

Tango 2

Authors - Ashwin Makwana, Hemit Rana, Adnan Vahora, Heer Patel, Shruti Rana, Nisarg Shah, Yagnik Poshiya
Abstract - Although most of us are unaware of it, we all use Natural Language Processing -based software and applications in our daily lives to assist us in performing our responsibilities in the twenty-first century. The task of automatically transforming one natural language into another while keeping the same meaning of the input text and generating fluent text in the output language is known as machine translation (MT). While machine translation is one of the artificial intelligence's oldest subfields, the current shift toward large-scale empirical methodologies has resulted in considerable translation quality improvements. There are numerous features of MT that are difficult to master: the enormous number of languages, alphabets, and grammars; transforming a sequence (for example, a sentence) to a sequence is more difficult for a computer than working with numbers alone; there is no single correct answer in most of the cases. (e.g.: translating from a language without gender-dependent pronouns, he and she can be the same). Linguistic resources such as corpora, multilingual dictionaries, and morphological rules are needed for optimal Machine Translation. The attempt has been made to make semi-automatic dictionary generation tool using historical corpora. in this research, as dictionaries are a critical resource for machine translation. The task becomes easier when related scripts and languages are considered, and the developed project is aimed for scenarios in which there is a requirement bilingual semi-automatic dictionary generation tool.

Paper Presenter

Ashwin Makwana

India

Thursday August 8, 2024 12:39pm - 12:50pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

12:39pm IST

Campus Placement Prediction and Analysis

Thursday August 8, 2024 12:39pm - 12:50pm IST

Strategy/Analysis

Authors - Rushikesh Joshi, Vijay Shilwant, Roshan Dandge, Shreyash Rajput, Manav Ashok Thakur
Abstract - We have designed a campus placement prediction system aimed at assessing a student's likelihood of securing employment through campus recruitment. This predictive model incorporates multiple parameters to gauge a student's skill level. Some of these parameters are drawn from the college's records, including academic performance, CGPA, attendance, and more, while others are derived from assessments conducted within the placement management system. By amalgamating these data points, our model can provide accurate predictions regarding a student's potential placement in a company. Furthermore, we leverage data from previous group of students to train our model, employing educational data mining techniques to access authentic historical data from our college's alumni. This approach enhances the efficacy of our machine learning model when making predictions specific to our institution.

Paper Presenter

Manav Ashok Thakur

India

Thursday August 8, 2024 12:39pm - 12:50pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

12:39pm IST

Post Quantum Cryptography: A Gentle Introduction of Lattice-Based Cryptography (Kyber, NTRUCrypto)

Thursday August 8, 2024 12:39pm - 12:50pm IST

Debate

Authors - Parth Shah, Priteshkumar Prajapati, Ravi Patel, Dhaval Patel
Abstract - RSA, Diffie-Hellman (DH), and Elliptic Curve Cryptography (ECC) like public key cryptography algorithms have proved their significance before the era of quantum cryptography. The security of RSA is based on the factorization problem while the security of DH and ECC is based on the problem of secret logarithm problem. These problems are considered hard to solve with the current computation facilities. However, these problems would be easy to solve with the quantum computer. This leads to the search for another cryptographic algorithm that can be sustained in the era of quantum computers. The algorithm must be computationally secure and efficient such that it should not be solved by even a quantum computer. Few of the candidate algorithms are based on lattice. Many researchers have provided literature to explain the workings of lattice-based cryptography. In this paper, a very simple but concrete explanation is given. Also, the possible attacks and countermeasures are discussed.

Paper Presenter

Parth Shah

India

Thursday August 8, 2024 12:39pm - 12:50pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

12:51pm IST

Behavioral Analysis of Single-Unit Systems with Weibull Densities under Classical and Bayesian Framework

Thursday August 8, 2024 12:51pm - 1:02pm IST

Tango 1

Authors - Ravi Chaudhary, Ashish Kumar, Monika Saini, Kapil Kumar
Abstract - The prominent objective of present study is to conduct the behavioral analysis of single unit systems in classical and Bayesian setups. For this purpose, a stochastic model of single unit system is developed with the concepts of preventive maintenance, degradation, waiting time for repairman, single server, perfect switch devices, and Weibull densities. The degraded unit after failure replaced by new one. A simulation study in classical and Bayesian setup is carried out for behavior analysis of the system. Various measures of system effectiveness are derived in both frameworks using semi-Markovian approach and regenerative point technique. The numerical values of various measures of system derived to high light the importance of the study. The results may be beneficial for system designers and maintenance personnel.

Paper Presenter

Monika Saini

India

Thursday August 8, 2024 12:51pm - 1:02pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

12:51pm IST

Leaf Doctor: Automated Detection and Diagnosis of Mango Leaf Diseases Using Machine Learning

Thursday August 8, 2024 12:51pm - 1:02pm IST

Tango 2

Authors - Priyanka Patel, Anshuman Prajapati, Viraj Koradia
Abstract - One of the most significant fruit crops in the world is the mango, however mango illnesses can significantly reduce crop productivity and quality, which has an effect on the industry's profitability. It is difficult to identify mango illnesses at an early stage because conventional ways for doing so require a lot of time and labor. In this study, we developed a unique method for applying deep learning to identify mango disease leaf. model approach consists of four steps: collection, data preprocessing, model training, and model evaluation. A collection of 1000-1200 photos of mango leaves, both healthy and sick, was gathered. The photographs were pre-processed using methods like pixel normalization, color correction, and image scaling. Metrics including accuracy, precision, recall, and F1-score were then used to evaluate the convolutional neural network (CNN) model's performance. This method's accuracy on the testing set was 90-95%, demonstrating its potency in identifying mango illnesses. By reducing the losses caused by mango diseases, the recommended method would improve the efficacy and precision of mango disease diagnostics, which would be beneficial to the fruit industry.

Paper Presenter

Priyanka Patel

India

Thursday August 8, 2024 12:51pm - 1:02pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

12:51pm IST

College Website For VPSCET

Thursday August 8, 2024 12:51pm - 1:02pm IST

Strategy/Analysis

Authors - Pranav Palkar, Sumit Nevase, Makarand Goralkar, Aditya Patil, Rashmi S. Bhumbare
Abstract - Site makes it straightforward to connected with client with simple get to to all substance. The current site of our college is overseen by a company, so there are few disadvantages. As the college need to pay huge sum and there was too chance of information misfortune so to overcome this issue we have created “VPSCET” college site. In our site we have utilized MySQL and PHP as backend plan and HTML, CSS and JavaScript are utilized as front conclusion apparatuses. The most point of our extend is to alter substance powerfully and to supply utilize interface applications. This location will give virtual visit of campus, here we are going get most recent subtle elements approximately the institution VPS/edu.Com was a web plan extend attempted on sake of five offices and an regulatory office of the College of Vidhya Prasarini Sabha's college Of Building and Innovation. The part of the VPS/edu.Com center group was to supply plan and specialized direction for the our group working straightforwardly with these units. The center group made a model from which the unit groups planned their person destinations. Afterward the center group made a difference actualize the unit destinations. As portion of the plan exertion, the center group inspected various college Web destinations and thought through a assortment of plan issues. Three are talked about in this paper: (1) showing the personality of person units inside the various leveled structure of the institution. (2) keeping up visual consistency all through the location (3) harmonizing the messages passed on by the university's domestic page and the domestic pages of the university's colleges and division.

Paper Presenter

Rashmi S. Bhumbare

India

Thursday August 8, 2024 12:51pm - 1:02pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

12:51pm IST

Impact of Low Code/No Code on Traditional Software Development

Thursday August 8, 2024 12:51pm - 1:02pm IST

Debate

Authors - Pranav Mathur, Deepa Gupta
Abstract - This study examines the profound influence of Low Code/No Code (LC/NC) development platforms on conventional software development processes. LC/NC systems, characterised by their intuitive interfaces and interchangeable components, democratise the process of app creation. They empower anyone without extensive technical knowledge to quickly design and deploy applications. This move not only speeds up digital innovation within organisations but also represents a wider transition towards more inclusive, agile, and cost-efficient software development methods. Although LC/NC platforms do not replace conventional approaches, they do complement them. However, their increasing popularity requires a considerable change in skills and workforce, emphasising the need for a combination of technical, analytical, and problem-solving talents in the digital era.

Paper Presenter

Pranav Mathur

India

Thursday August 8, 2024 12:51pm - 1:02pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

1:03pm IST

Improvement in image segmentation for Flood Images using UNet and U2Net

Thursday August 8, 2024 1:03pm - 1:14pm IST

Tango 1

Authors - Aniruddh Mukherjee, Dev Nandurbarkar, Hemant N Yadav, Jalpesh Vasa
Abstract - Image segmentation is crucial for flood analysis because it helps identify flood-prone regions that require attention from NGOs and government aid. It becomes challenging to scout small and narrow flood-affected areas, particularly in countries like India with lush forests and limited visibility, especially in lowlight settings, surrounded by borders on three sides. In this comparative study, we evaluate the performance of two prominent deep learning architectures, UNet and U2Net, in the context of flood image segmentation. Leveraging a diverse of flood images, our analysis assesses their effectiveness in accurately identifying and delineating flooded areas in aerial imagery. While UNet demonstrates robustness in scenarios with well-defined flood boundaries, U2Net excels in capturing subtle flood patterns amidst complex backgrounds. The study's findings provide valuable insights for selecting the most suitable model based on specific flood monitoring needs, ultimately enhancing flood management and disaster response efforts for flood-prone regions.

Paper Presenter

Aniruddh Mukherjee

India

Thursday August 8, 2024 1:03pm - 1:14pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

1:03pm IST

Signature Analysis of Physical Processing Unit of a Sewage Treatment Plant

Thursday August 8, 2024 1:03pm - 1:14pm IST

Tango 2

Authors - Vijay Singh Maan, Monika Saini, Ashish Kumar
Abstract - The signature reliability plays as a fundamental and vital role in assessing the reliability measures for binary and complex system. This study focuses on calculating the signature reliability of the Physical Processing Unit (PPU) within a sewage treatment plant, utilizing Universal Generating Function (UGF) techniques. A reliability block diagram is proposed to facilitate this calculation. UGF technique is applied to access the reliability measures like mean time to failure (MTTF), expected time and cost of the system, reliability function, signature and tail signature of the system. Additionally, Barlow-Proschan (B-P) index is computed to assess the sensitivity of the system relative to its subsystems, employing Owen's formula. The results shows that the expected cost of the system is determined to be 8.37747, while the B-P index highlights that subsystems A and B are the most sensitive subsystem among all.

Paper Presenter

Vijay Singh Maan

India

Thursday August 8, 2024 1:03pm - 1:14pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

1:03pm IST

Alert Generation On Detection Of Suspicious Activity Using Deep Learning

Thursday August 8, 2024 1:03pm - 1:14pm IST

Strategy/Analysis

Authors - Rashmi S Bhumbare, Aarti Machhindra Chavan, Mayuri Sanjay Chavan, Pratiksha Vijay Chavan, Shejal Sanjay Pawar
Abstract - In contemporary times, video surveillance assumes a crucial role, especially given the widespread adoption of cutting-edge technologies such as artificial intelligence, machine learning, and deep learning. These advancements have fostered the creation of intricate systems capable of discerning various forms of questionable conduct from live video streams. Identifying suspicious behavior, often subtle and challenging to discern from typical actions, proves to be one of the most demanding tasks. To tackle this hurdle, a blend of methodologies, including deep learning, is utilized. Deep learning algorithms are trained to identify anomalous patterns of behavior across diverse settings, notably within educational institutions. The surveillance process typically encompasses the examination of frames extracted from video recordings. These frames undergo a dual-stage processing: initial feature extraction followed by classification using these features to ascertain the presence of suspicious behavior. In essence, these dynamic systems harness state-of-the-art technology to bolster surveillance capabilities, facilitating prompt identification and response to potential security risks. Upon detecting suspicious activities, timely alert notifications are dispatched to relevant authorities, ensuring a proactive stance towards upholding safety and security.

Paper Presenter

Rashmi S. Bhumbare

India

Thursday August 8, 2024 1:03pm - 1:14pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

1:03pm IST

Real-Time Tow Truck Detection: Filling the E-Challan Knowledge Gap using YOLOv8 & YOLOv

Thursday August 8, 2024 1:03pm - 1:14pm IST

Debate

Authors - Jaitej Singh, Dharmendrasinh Rathod, Parth Shah, Priteshkumar Prajapati
Abstract - This research addresses a critical knowledge gap in intelligent traffic management, here, E-Challan systems, by pioneering the exploration of real-time tow truck detection using comparative analysis of YOLOv8 and YOLOv9 models. Tow truck detection, an underexplored aspect, holds significant importance in scenarios such as accidents, breakdowns, and emergencies. Leveraging the advanced features of YOLOv8 and YOLOv9, including anchor-free detection and task-aligned assignment, our study presents a comprehensive framework for accurate and adaptable tow truck detection. Through benchmarking YOLOv8n, YOLOv8s, YOLOv8l, and YOLOv9c models, we perform a comparative analysis of their contributions and trade-offs, revealing the strengths of each version. Visualization graphs and evaluation metrics, including mAP-50 and mAP50-95, provide detailed insights into the performance comparison between YOLOv8 and YOLOv9, showcasing the superiority and improvement of the latest YOLOv9 model. This research fills a crucial gap in E-Challan systems and introduces an innovative approach to enhance traffic management and rule enforcement standards.

Paper Presenter

Jaitej Singh

India

Thursday August 8, 2024 1:03pm - 1:14pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

1:15pm IST

Fine-tuning Deep learning model using Transfer learning for Pneumonia Diagnosis

Thursday August 8, 2024 1:15pm - 1:26pm IST

Tango 1

Authors - Khushi Shah, Akshar Patel, Hemant N Yadav
Abstract - The prognosis of a patient depends critically on an accurate diagnosis, but traditional methods are frequently unreliable and yield insufficient data. To improve pneumonia detection, we investigate in this work the automated use of transfer learning models. We carefully trained and validated five well-known convolutional neural network (CNN) models: ResNet152V2, VGG18, ResNet50, InceptionV3, and MobileNetV2. We did this by using a carefully calibrated Chest X-ray dataset. We obtained an impressive accuracy of 97% using an extensive evaluation that included confusion matrices, accuracy and loss graphs, and intermodel comparisons. This breakthrough outperforms conventional methods, highlighting the effectiveness of transfer learning for accurate pneumonia diagnosis. The enhanced diagnostic procedure, which has a specificity of 0.98, promises better patient outcomes by enabling more precise diagnoses, cutting down on pointless sampling, and boosting medical confidence. This study highlights the critical role that transfer learning plays in improving diagnostic accuracy as well as the transformative potential of deep learning methodologies in medical imaging analysis.

Paper Presenter

Khushi Shah

India

Thursday August 8, 2024 1:15pm - 1:26pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

1:15pm IST

Personal Protective Equipment Detection

Thursday August 8, 2024 1:15pm - 1:26pm IST

Strategy/Analysis

Authors - Pratik Haribhakta, Shubham Raut, Bramhadev Garud, Priti Chorade
Abstract - This study focuses on the example of segregation of personal items in high-risk sectors such as clothing and personal protective equipment. We propose using biometric objects from Open Images V5 and DeepFashion2 datasets for pre-training mask segmentation networks for recognition and segmentation of personal protective equipment in the workplace. The preliminary results of our proposed model achieve a mean average precision with modest optimization, which results in extremely effective segmentation of welding masks, high visibility vests, construction helmets, and ear protection in the workplace. The results of this research can be applied to improve workplace safety in high-risk industries by providing a way to ensure that personal protective equipment (PPE) is used appropriately while protecting employee privacy.

Paper Presenter

Priti Chorade

India

Thursday August 8, 2024 1:15pm - 1:26pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

1:15pm IST

Insights on Performance Improvement for Cloud Com-puting Applications

Thursday August 8, 2024 1:15pm - 1:26pm IST

Debate

Authors - Nirav Bhatt, Priyanka Patel, Uttam Bhavani, Hiren Kakadiya
Abstract - Cloud computing has become a popular choice for businesses and organizations looking to improve the performance of their applications, including the ability to scale resources on demand, the use of distributed computing architectures, and the ability to leverage the latest hardware and software technologies. This research paper explores various ways in which cloud computing can be used to enhance application performance, including the use of virtualization, containerization, and serverless computing. The paper also discusses the benefits and limitations of each approach, as well as the importance of proper planning and management to achieve optimal results. Overall, the findings of this research imply that cloud computing can be a useful tool for enhancing application performance, but businesses must carefully analyses their individual needs and select the solution that best meets their objectives.

Paper Presenter

Nirav Bhatt

India

Thursday August 8, 2024 1:15pm - 1:26pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

1:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 1:27pm - 1:30pm IST

Tango 1

Invited Guests/ Session Chairs

Prof. Sangeeta Chakrabarty

HoD & Associate Professor, S. S. Dempo College of Commerce and Economics, Goa, India

Thursday August 8, 2024 1:27pm - 1:30pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 1A, Tango 1

Host Organization Global Knowledge Research Foundation

1:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 1:27pm - 1:30pm IST

Tango 2

Invited Guests/ Session Chairs

Prof. Solley Joseph

Associate Professor, Carmel College of Arts Science & Commerce for Women, Goa, India

Thursday August 8, 2024 1:27pm - 1:30pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 1B, Tango 2

Host Organization Global Knowledge Research Foundation

1:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 1:27pm - 1:30pm IST

Strategy/Analysis

Invited Guests/ Session Chairs

Dr. Nilanjan Dey

TPC Chair – ICT4SD 2024, Professor, Techno International New Town, Kolkata, India

Thursday August 8, 2024 1:27pm - 1:30pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 1C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

1:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 1:27pm - 1:30pm IST

Debate

Invited Guests/ Session Chairs

Dr. Shyam Akashe

TPC Chair – ICT4SD 2024, Professor, ITM University, Gwalior, India

Thursday August 8, 2024 1:27pm - 1:30pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 1D, Debate

Host Organization Global Knowledge Research Foundation

1:30pm IST

Opening Remarks

Thursday August 8, 2024 1:30pm - 1:35pm IST

Tango 1

Thursday August 8, 2024 1:30pm - 1:35pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

1:30pm IST

Opening Remarks

Thursday August 8, 2024 1:30pm - 1:35pm IST

Tango 2

Thursday August 8, 2024 1:30pm - 1:35pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

1:30pm IST

Opening Remarks

Thursday August 8, 2024 1:30pm - 1:35pm IST

Strategy/Analysis

Thursday August 8, 2024 1:30pm - 1:35pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

1:30pm IST

Opening Remarks

Thursday August 8, 2024 1:30pm - 1:35pm IST

Debate

Thursday August 8, 2024 1:30pm - 1:35pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

1:35pm IST

Comparative Analysis of Data Security Algorithms for IoMT Applications

Thursday August 8, 2024 1:35pm - 1:46pm IST

Tango 1

Authors - Manita Rajput, Pranali Choudhari
Abstract - Internet of Things (IoT) technology is witnessing widespread integration across diverse sectors including manufacturing, automotive and healthcare. It has a vast application area and exponential growth rate. Lately, IoT has seen remarkable utility in the health care sector. The technology of IoT used in the medical field is called Internet of medical Things (IoMT). The sensitive biomedical data of patients need a secure transit and cloud storage. Securing the data at the sensor level or transit level is a challenging task. The huge amount of data exchanged between IoT nodes to cloud brings new risks and more challenges. People illicitly obtain the personal Identifiable information (PII) and misuse it for various unlawful purposes. Few encryption algorithms are specifically designed for low power IoT nodes but are vulnerable to attacks. There is a need of extensive analysis of the existing algorithms specifically for IoMT applications. This paper focusses on the 5 encryption algorithms that consume less power and memory and can be used at the end nodes of an IoMT network. These algorithms are implemented in C and analyzed with respect to important performance metrics such as memory size and execution time. The performance of algorithms have been tested with values of biomedical parameters.

Paper Presenter

Manita Rajput

India

Thursday August 8, 2024 1:35pm - 1:46pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

1:35pm IST

E-Governance Through Enhanced ICT Strategies Insights from Sentiment Analysis

Thursday August 8, 2024 1:35pm - 1:46pm IST

Tango 2

Authors - Praveen M Kulkarni, Prayag Gokhale, Basavaraj S. Tigadi, Lakshminarayana.K, Ameet V Kulkarni
Abstract - This research paper presents a meticulous and thorough exploration of user sentiment and feedback concerning the e-governance mobile applications, employing cutting-edge natural language processing (NLP) techniques alongside illustrative coding examples. By scrutinizing an extensive dataset comprising approximately 2400 user reviews sourced from diverse online platforms, we unravel nuanced insights into user experiences, satisfaction levels, and areas ripe for improvement. Our analysis not only uncovers commendations for the app's convenience and functionality but also sheds light on recurring concerns such as technical glitches and data quality issues voiced by users. Furthermore, we offer actionable recommendations tailored for policymakers, underpinned by empirical evidence and augmented by code snippets showcasing sentiment analysis methodologies. This paper endeavors to equip stakeholders with a comprehensive understanding of user perspectives, thereby fostering informed decision-making to bolster the e-governance mobile application usability and efficacy in driving forward government service delivery in Karnataka, India.

Paper Presenter

Basavaraj S. Tigadi

India

Thursday August 8, 2024 1:35pm - 1:46pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

1:35pm IST

Empirical Investigation of Neural Network-Based Beam Selection Mechanism in 5G Networks

Thursday August 8, 2024 1:35pm - 1:46pm IST

Strategy/Analysis

Authors - Rajesh Kumar, Deepak Sinwar, Vijander Singh
Abstract - Fifth-generation mobile technology provides ultra-reliable low latency communication and broadband service to transfer data at high speed. To achieve this target beamforming plays a very important role in radio resource allocation that points the focused beam toward the user. Some of the beamforming mechanisms calculate the optimal beam pair index based on the channel state information (CSI) and signal to interference and noise ratio (SINR). To identify the optimal beam pair index in the beam selection procedure, it is essential to employ a unique technique that minimizes overhead during beam sweeping and selection while maintaining low complexity. In this paper, we used neural networks for beam selection based on the global positioning system (GPS) coordinates of the receiver. Neural networks take GPS coordinate of the receiver and optimal beam pair index as input to train the model. In the output of the neural network, the K optimal beam pair indices are chosen based on the average reference signal received power (RSRP). Neural networks contribute to the high accuracy and average RSRP beam selection as compared to the benchmarked algorithm.

Paper Presenter

Rajesh Kumar

India

Thursday August 8, 2024 1:35pm - 1:46pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

1:35pm IST

Estimation of Risk Index for Parking of Commercial Building

Thursday August 8, 2024 1:35pm - 1:46pm IST

Debate

Authors - Sayali Dharne, Shruti Sukhdhan, Pranesh Chawhan, Kiran Sharikar
Abstract - Now a days with the increase in rate of population rate of vehicle is also increase. Which may cause lack of parking spaces in public as well as commercial buildings? For this study we have used parking of commercial building. in which we have to calculated the risk indices of parking of commercial building. For that a trench is selected for study near Chinchwad railway Station of various commercial building for parking study. This risk index is helpful for determining the risk index of that building regarding to various factors such as safety ,parking time , type of vehicle, no of owners and customers arrived in the complexes. Where the building at a high and medium is been considered and recommended to PCMC to take attributes towards it. Hear one building is taken into consideration to calculate the risk index of the commercial building parking , 5-8 building will be taken into consideration for further study.

Paper Presenter

Sayali Dharne

India

Thursday August 8, 2024 1:35pm - 1:46pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

1:47pm IST

A Deep Learning Approach for Early Detection and Classification of Mango Leaf Diseases for Sustainable Agriculture

Thursday August 8, 2024 1:47pm - 1:58pm IST

Tango 1

Authors - Sneh Soni, Mahek Siroya, Rutva Shingala, Purvi Prajapati, Madhav Ajwalia, Hemant Yadav
Abstract - A growing challenge in agriculture is identifying new cases of new cases of fungal-caused plant diseases, which is made even worse by the consistently changing climate and its unpredictable impacts These diseases are among the biggest threats to agriculture as they lower the quality of crops, undermine the sustainability of farming, cause financial losses, and lead to nutritional deficiency. In fact, the agricultural sector suffers substantial annual losses, with pests affecting up to 20–40% of global productivity. In this research, we aim to tackle this very problem using state-of-the-art technologies. We are particularly using Convolutional Neural Networks (CNNs) and Deep Learning, a subset of artificial intelligence, to automate the detection and classification of mango leaf diseases. Through these innovative technologies, we seek to not only enhance the techniques of disease management but also drastically cut crop losses, which will lead to the sustainability and resilience of agricultural systems across the globe.

Paper Presenter

Sneh Soni

India

Thursday August 8, 2024 1:47pm - 1:58pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

1:47pm IST

Classification of Scanning Electron Microscopy (SEM) Images using Deep Learning Algorithms

Thursday August 8, 2024 1:47pm - 1:58pm IST

Tango 2

Authors - Ranispoorti Ravindra Patil, Jayalaxmi G N, V. H. Choudapur, Vishwanth P. Baligar
Abstract - Scanning Electron Microscopy (SEM) captures nanoscale images, whereas Deep Learning (DL) analyzes data with neural network models. The authors of this study investigate three types of SEM pictures at varying magnifications, and 93 pictures in all are created for processing and analyzing. SEM images are classed according to the doping component present in the main sample: Pure Cobalt Chromium Oxide, Lanthanum doped Cobalt Chromium Oxide, and Neodymium doped Cobalt Chromium Oxide. Augmentation methods increase the quality and look of images. The similarity and complexity of photos in all three groups, as well as the presence of images of varying magnification, offered a challenge to categorization, reducing the accuracy rate of the procedure. The authors suggest a low-complexity technique for extracting features and increasing model performance. In comparison with pre-trained models, this method reduces time and computing resources, increasing efficiency. Training accuracy is 100% while testing accuracy obtained is 78.26%. Additionally, CNN and classical deep learning models VGG16 and Inception v3 are used to classify SEM pictures. SEM images are segmented utilizing a holistic approach that incorporates the watershed algorithm along with contours. A SEM segmented image is used to determine the area of surface of a Cobalt Chromium Oxide sample. It was calculated that the material’s surface area was 41,02,628 nm2. . . .

Paper Presenter

Ranispoorti Ravindra Patil

India

Thursday August 8, 2024 1:47pm - 1:58pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

1:47pm IST

Deep Learning based Sign Language Detection and Prediction for Enhanced Communication

Thursday August 8, 2024 1:47pm - 1:58pm IST

Strategy/Analysis

Authors - Krisha Zalaria, Nishit Dadhaniya, Priyanka Patel
Abstract - The project aims to recognize sign language using hand gestures in real accurately. Hand gesture recognition helps to reduce the gap between people who are hard of hearing or are not able to speak and who can hear and speak well. The system receives sequential data representing gestures taken using a camera. In order to extract useful information from hand gestures, pre-processing techniques are utilized to increase the quality of the input data, followed by feature extraction. The recognition outcome depends on the quality of the input data, the efficacy of feature extraction, the structure of the recognition model, the richness of the training dataset, and the accuracy of the training model during real-time scenarios. Using LSTM and MediaPipe Holistics, the model archives an accuracy of around 97.4% across different dynamic signs(600 clips, 15 classes) along with static signs (1444 images, 39 classes). This study demonstrates the efficacy of the proposed system in accurately reconizing sign language gestures, therby facilitating improved communication for indivuals with hearing or speech impairments.

Paper Presenter

Krisha Zalaria

India

Thursday August 8, 2024 1:47pm - 1:58pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

1:47pm IST

Machine Learning Model for Genetic Disorder Prediction

Thursday August 8, 2024 1:47pm - 1:58pm IST

Debate

Authors - Vanashree Agnihotri, Prathamesh Hire, Vedant Ingle, Aneesha Kavathekar, Chhaya Pawar
Abstract - Genetic disorders, intrinsic to DNA, can manifest unpredictably, often causing severe health implications. A lack of awareness about genetic disorders among people results in low genetic testing during the early stages which leads to an increase in the potential risk of disease severely affecting life of individuals. The severity and distribution of genetic disorders across the globe vary significantly. Current machinelearning diagnostic methods are limited to specific diseases leading to a constricted scope of prediction systems. There is a necessity for an efficient, non-invasive, and economical genetic disorder prediction system. The project aims to develop a predictive model leveraging Machine Learning algorithms and model development techniques. The core objective is formulating a model proficient in pinpointing genetic disorders and disorder subclass, offering swift, accurate diagnostics leading to timely medical interventions. Uniquely, our approach merges a Genetic Algorithm to extract important features, which are used to perform model training incorporating the Random Forest algorithm. The development of a machine learning predictive model enables predict susceptibilities to genetic disorders and the disorder subclass distinguishing it from traditional genetic sequencing, and gene testing diagnosis procedures.

Paper Presenter

Aneesha Kavathekar

India

Thursday August 8, 2024 1:47pm - 1:58pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

1:59pm IST

Unveiling Consistency and Disparities: Exploring the Dynamics Between Customer Reviews and Ratings

Thursday August 8, 2024 1:59pm - 2:10pm IST

Tango 1

Authors - Dhruvi Patel, Mansi Deshpande, Anil Jadhav
Abstract - Online consumer reviews consist of product ratings and product reviews, which are becoming increasingly powerful in supporting potential customers in making well-informed purchasing decisions. Online reviews are very important to for potential customers because they help them make better informed and rational purchase decisions. Objective of this study is to examine the consistency between customer reviews and ratings. Our research methodically examined the consistency between product ratings and consumer reviews for headset purchases by employing a TextClassifier model. Confusion matrix, chi-square tests and Cohen’s Kappa test were used in conducting the statistical analysis that was aimed at determining the association between these two aspects. The results conclusively indicate a notable consistency between reviews and ratings.

Paper Presenter

Dhruvi Patel

India

Thursday August 8, 2024 1:59pm - 2:10pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

1:59pm IST

Multi Noise Classification in Images Using Fast-Fourier Transform and Power Spectrum Density

Thursday August 8, 2024 1:59pm - 2:10pm IST

Tango 2

Authors - Aakanksha Jain, Harshal Arolkar
Abstract - Noise in data is an enormous barrier to the performance of classification algorithms in a number of real-world circumstances. When multiple sources of noise concurrently impact data, traditional classification techniques such as linear classifiers or simple decision trees often struggle to accurately identify the noise. We present a novel method for multi-noise classification in this work. By using well-known signal processing methods— Fast Fourier Transform (FFT), and Power Spectral Density (PSD) analysis we offer a thorough method for multi-noise classification. The suggested methodology first preprocesses noisy signals to extract significant frequency-domain information. Multiple evaluations are carried out utilizing different benchmark datasets comprising a variety of noise types, such as Gaussian noise, impulse noise, motion noise, and mixtures of these noises, in order to assess the performance of the suggested approach.

Paper Presenter

Aakanksha Jain

India

Thursday August 8, 2024 1:59pm - 2:10pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

1:59pm IST

Electron Energy Prediction in High Granularity Calorimeter of the CMS detector Using Graph Neural Network

Thursday August 8, 2024 1:59pm - 2:10pm IST

Strategy/Analysis

Paper Presenter

Sharmila Sengupta

India

Thursday August 8, 2024 1:59pm - 2:10pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

1:59pm IST

Mitigating Cold Start Challenges in Serverless Computing: A Survey

Thursday August 8, 2024 1:59pm - 2:10pm IST

Debate

Authors - Anushka Mukherjee, Rahi Patel, Himja Patel, Ravi Patel
Abstract - This paper addresses the cold start problem in several sectors of serverless computing. It investigates how serverless architectures might become more scalable and efficient by using microservices. Recent research is used to describe strategies for eliminating cold start issues and enhancing performance. In real-time applications like e-commerce and IoT, cold start latency is still a major obstacle, even with advances like parallelism and container reuse. Performance of serverless computing can be optimised in a variety of scenarios by leveraging microservices, which offer potential to improve scalability and agility.

Paper Presenter

Anushka Mukherjee

India

Thursday August 8, 2024 1:59pm - 2:10pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Thursday August 8, 2024 2:00pm - 2:05pm IST

Virtual Room A

Thursday August 8, 2024 2:00pm - 2:05pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Thursday August 8, 2024 2:00pm - 2:05pm IST

Virtual Room B

Thursday August 8, 2024 2:00pm - 2:05pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Thursday August 8, 2024 2:00pm - 2:05pm IST

Virtual Room C

Thursday August 8, 2024 2:00pm - 2:05pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Thursday August 8, 2024 2:00pm - 2:05pm IST

Virtual Room D

Thursday August 8, 2024 2:00pm - 2:05pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Thursday August 8, 2024 2:00pm - 2:05pm IST

Virtual Room E

Thursday August 8, 2024 2:00pm - 2:05pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Thursday August 8, 2024 2:05pm - 2:15pm IST

Virtual Room A

Thursday August 8, 2024 2:05pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 5A, Virtual Room A

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Thursday August 8, 2024 2:05pm - 2:15pm IST

Virtual Room B

Thursday August 8, 2024 2:05pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 5B, Virtual Room B

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Thursday August 8, 2024 2:05pm - 2:15pm IST

Virtual Room C

Thursday August 8, 2024 2:05pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 5C, Virtual Room C

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Thursday August 8, 2024 2:05pm - 2:15pm IST

Virtual Room D

Thursday August 8, 2024 2:05pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 5D, Virtual Room D

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Thursday August 8, 2024 2:05pm - 2:15pm IST

Virtual Room E

Thursday August 8, 2024 2:05pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 5E, Virtual Room E

Host Organization Global Knowledge Research Foundation

2:11pm IST

Clinical Decision Support system for Multiple Diseases

Thursday August 8, 2024 2:11pm - 2:22pm IST

Tango 1

Authors - Shradha Sahu, Sreerag Rajesh, Sahil Wake, Abhishek Tiwari, Namrata Patel
Abstract - In today's fast-paced world, the demand for an efficient and reliable healthcare decision support system has never been greater. With the increasing prevalence of diseases such as cancer, stroke, and heart disease, there is a critical need for a system that can accurately predict these conditions and provide users with comprehensive healthcare information. Enter the Clinical Decision Support System, a state-of-the-art web application designed to meet this need head-on. Utilizing advanced algorithms, this system offers personalized disease predictions, enhancing the accuracy of healthcare outcomes. An integral component of this system is its AI chatbot, which provides users with immediate access to essential information, including symptoms, causes, treatments, and the nearest healthcare facilities. This innovative tool streamlines the process of acquiring healthcare knowledge, thereby improving the decision-making process for both patients and healthcare providers. The Clinical Decision Support System is more than just a prediction tool; it is a gateway to a wealth of healthcare information and a step towards revolutionizing the healthcare industry. With the potential for future integration with blockchain technology, the system promises enhanced data security and management, further solidifying its position as a critical tool in modern healthcare. This project represents a significant advancement in healthcare technology, offering promising solutions to improve patient care and outcomes.

Paper Presenter

Sahil Wake

India

Thursday August 8, 2024 2:11pm - 2:22pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

2:11pm IST

Enhancing Rural Connectivity: A Developmental Leap for Achhepur through Strategic Transportation Planning

Thursday August 8, 2024 2:11pm - 2:22pm IST

Tango 2

Authors - Pechetti Karteeka Sai Jashnavi, Harsh Kumar Singh, Divya Sharma SG, Sagar Basavaraju
Abstract - Addressing the core issue of connectivity, this paper presents a strategic roadmap to transform Achhepur’s access to essential services and ignite socio-economic development. The current system hinders primary facilities like secondary and higher education, employment, healthcare system, commercial services, and infrastructure development due to poor connectivity. In this paper a three-phase strategy has been proposed to address the development of the village Achhepur, scheduling timely operated public and private transport is pivotal, promising to connect Achhepur to vital amenities and neighboring towns. This paper highlights the importance improved transportation in rural India which is not just a convenience but a catalyst for resolving broader socio-economic issues. By facilitating better access to education and healthcare, the plan aims to disrupt cycles of poverty and social stagnation, empowering the community towards a more prosperous future. The aim of the research is to understand the various opportunities available to the village Achhepur and estimate the probable methods to connect the village for various development-oriented activities and identify and propose considerable solutions for resolving multiple issues of the village.

Paper Presenter

Pechetti Karteeka Sai Jashnavi

India

Thursday August 8, 2024 2:11pm - 2:22pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

2:11pm IST

FoodMO: A Food Nutrient Analysis Application Using Optical Character Recognition and Machine Learning

Thursday August 8, 2024 2:11pm - 2:22pm IST

Strategy/Analysis

Authors - Shruti Jha, Ishmeen Kaur Garewal, Lancy Aathisaya, Leona Alphonso, Bhakti Aher
Abstract - This project proposes a novel approach to streamline the extraction and organization of nutritional details from food packaging using OCR. The proposed system efficiently retrieves vital nutritional data from images or text of food products, providing users with accurate and easily accessible information. Additionally, it tracks users' dietary restrictions and fitness goals, enabling customized diet plans. Nutritional information is an essential consideration for making informed food choices. However, extracting this information from food packaging can be time-consuming and challenging, especially for individuals with dietary restrictions or fitness goals. Traditional methods of manual data entry are prone to errors, while existing automated solutions often lack the accuracy and flexibility required. The proposed system addresses these limitations by leveraging OCR technology to extract nutritional information from food packaging with high accuracy. The system first pre-processes the input image to improve readability and reduce noise. Next, it applies OCR algorithm to extract the text from the image. The extracted text from the food label is parsed to identify key nutritional information which includes calorie count, macronutrients, and vitamins. This is done using a data analysis and random forest classifier. Finally, the results include nutritional information in easy language, data visualization to give a visual appeal and information regarding allergies from the ingredients used in the product.

Paper Presenter

Ishmeen Kaur Garewal

India

Thursday August 8, 2024 2:11pm - 2:22pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

2:11pm IST

Monitoring and Alerting Model for coal mines using IOT

Thursday August 8, 2024 2:11pm - 2:22pm IST

Debate

Authors - Harshit, Arman Aryan, Ankit Kumar, Himanshu Sekhar Das, Sasmita Mohapatra
Abstract - The importance of safety inside coal mines cannot be overlooked, which is why monitoring systems are needed to reduce risks and ensure the welfare of miners. This paper contains, a detailed study of an Internet of Things-based Coal Mine Safety observing and Alerting model that integrates vibration sensor, gas sensor, temperature sensor and smoke sensor interfaced with a microcontroller i.e, ESP32 which is finally interfaced with an application to view the above parameters has been proposed. The goal of the proposed system is to provide real time monitoring of essential safety parameters in underground settings. The system’s architecture includes a network of sensor strategically placed throughout the mine which continuously collects data on vibration level, gas concentration, temperature variation, and smoke presence using wireless communication protocols. Sensor data is then transferred to a centralized monitoring station where it gets analyzed and processed. When the conditions are not normal, the system triggers an alert to miners and supervisors so an immediate response is initiated to evacuate the mine. Evaluating the system’s performance through field testing shows that it is effective in improving safety measures and reducing accidents and thus ensuring a safe and secure work environment for the mine workers.

Paper Presenter

Sasmita Mohapatra

India

Thursday August 8, 2024 2:11pm - 2:22pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

2:23pm IST

Identifying Interictal activity amidst artifacts using Convolution Neural Network

Thursday August 8, 2024 2:23pm - 2:34pm IST

Tango 1

Authors - Arshpreet Kaur, Kumar Shashvat
Abstract - Identifying inter-ictal activity in EEG amidst of artefacts is a primary challenge for diagnosis of epilepsy. Artifacts corrupt the EEG; such that identifying inter-ictal activity becomes difficult. There are different artefacts that present the EEG some of the prominent ones are movement artifact, eye movement, electrode and emg artifact. The evaluation of EEG is a subjective procedure and detecting inter-ictal activity among the artifacts is a challenge. We have designed convolution neural network to identify between different artifacts and inter-ictal activity. For this work five sets have been considered, the first four sets compare each artefact with inter-ictal activity and set E, compares all artefacts with inter-ictal activity. The proposed method has achieved 100% accuracy in identifying electrode and emg artifacts from each other while for other artefacts the method also performed efficiently.

Paper Presenter

Arshpreet Kaur

India

Thursday August 8, 2024 2:23pm - 2:34pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

2:23pm IST

A Multi-layered Approach: Examining the Interplay Between GDPR, EU AI Act, and DPDP Act for ICT

Thursday August 8, 2024 2:23pm - 2:34pm IST

Tango 2

Authors - Meenakshi Punia, Arjun Choudhary, Kumari Sudha, Thammadi Shashank, Sonu Agarwal, Vikash Kumar Kharbas
Abstract - Internet Communication Technologies (ICTs) are shaping our lives in diverse and dynamic ways. The information exchanged through these technologies is of multiple proportions. Data is processed, retained, managed through ICTs. Hence ICTs are the medium that have created a data driven virtual world which affects lives from microscopic to macroscopic level. Also, Internet of things (IoTs) relies on ICTs for functioning effectively, synergizing these with adoption of Artificial Intelligence can lead to surprising productive results. This potent trio (IoTs, ICTs and A.I.) of the Virtual world flourish on information in the form of Data. Fundamentally these technologies are data-driven technologies therefore it becomes essential to regulate the data and its retention, processing, and management. Globally efforts are being done to strengthen the data regulation regime and mechanism to answer various challenges posed by these very Trio of Virtual worlds. The Paper will comprehensively examine the data regulations mechanism of Europe and India. Since GDPR and EU AI Act 2023 are the path breaking legal manifestoes for the globe to regulate data generated and used by ICTs and AI.

Paper Presenter

Arjun Choudhary

India

Thursday August 8, 2024 2:23pm - 2:34pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

2:23pm IST

Designing and Analyzing a Wrist Splint for Rheumatoid Arthritis Rehabilitation

Thursday August 8, 2024 2:23pm - 2:34pm IST

Strategy/Analysis

Authors - Harish Harsurkar, Husain Shaikh, Tanuja Hulavale, Sunil Parge
Abstract - A wrist splint serves as a device that is design to immobilize the arm, aiding in the recovery from arm injuries. However, traditional ways of creating splints often overlook the biomechanical sides of arm joint interaction, leading to mechanical fails in splints or potential harm to patients. There an clinical requirement for an inventive approach to design and optimize custom functional arm splints. This study it showcase a technique for splint design that combines topology optimization and additive manufacturing, using biomechanical analysis to achieve advanced customization in terms of comfort, function and ventilation. Prototypes were made using Fused Filament Fabrication (FFF) in vertical and horizontal orientations, along with Powder Bed Fusion (PBF). Finite element analyses were used to mimic splint movements under maximum patient loads, with validation through physical testing. The function and stiffness of splints made through different ways were assessed and compared. Results show that the created splint meets patients' biomechanical and functional needs, limiting sagittal movements by 95.7%, coronal movements by 89.8%, and decreasing maximum grip strength by 18.7%. Among the production methods looked at, FFF vertical printing is suggested for general clinical use because of its surface quality, safety, function and cost-effectiveness.

Paper Presenter

Harish Harsurkar

India

Thursday August 8, 2024 2:23pm - 2:34pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

2:23pm IST

Performance Evaluation Of CGLS For HMC At JSW Steel (Steel Melting Shop) Dolvi

Thursday August 8, 2024 2:23pm - 2:34pm IST

Debate

Authors - Harish Harsurkar, Husain Shaikh, Abhishek Ganpat Satpute, Bhosale Shyam Santosh, Garad Rohan Ramling, Garud Abhijeet Arvind
Abstract - Centralized Grease Lubrication System (CGLS) for Hot Metal Cars: Enhancing Efficiency and Ensuring Worker Safety This overview provides insight into the engineering project titled "Centralized Grease Lubrication System (CGLS) for Hot Metal Cars." The fundamental objective of this project is to design a specialized lubrication system that not only optimizes the performance of hot metal transportation in the metallurgical industry but also prioritizes the safety of workers The project aims to create, construct, and integrate a Centralized Grease Lubrication System (CGLS) tailored explicitly for hot metal cars. The CGLS focuses on simplifying and automating the lubrication process, ensuring consistent and appropriate grease application to crucial moving parts. This not only enhances the longevity of the hot metal cars but also minimizes potential risks to the workers. The CGLS addresses prevalent challenges linked to manual lubrication, such as inconsistent grease application, which can lead to equipment damage and shortened operational life. By automating this process, the CGLS intends to maintain adequate lubrication levels, reducing the likelihood of equipment malfunction and promoting the safety of the workers. Furthermore, the project pays meticulous attention to the CGLS design, emphasizing precise grease measurement, efficient distribution mechanisms, and reliable valves in line with safety regulations and industry standards. The system is designed to endure external environmental factors, vibrations, and possible malfunctions, thereby ensuring the safety and well-being of workers In summary, this engineering project pioneers an innovative solution, the Centralized Grease Lubrication System (CGLS), tailored for hot metal cars. The project showcases the advantages of automated lubrication, highlighting improved equipment efficiency, extended operational life, and a safer work environment for workers in the metallurgical industry.

Paper Presenter

Husain Shaikh

India

Thursday August 8, 2024 2:23pm - 2:34pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

2:35pm IST

Future of Internet of Nano Things (IoNT) in India

Thursday August 8, 2024 2:35pm - 2:46pm IST

Tango 2

Authors - Sarfraz Hussain, Anil Kumar Shaw
Abstract - The impact of the Internet of Things (IoT) worldwide shows the present scenario of India in this domain. As IoT is a vast domain, a lot of innovations for sustainable development can be seen in the fields of agriculture, healthcare, defense, space, etc. As the world is integrating AI and IoT, India also perceives to gain intensive knowledge in this field. India has invested a huge fortune in smart meters for better growth. The Internet of Nano Things (IoNT) has emerged from IoT which includes the use of nano sensors. As technology is advancing, industries and academia such as IISC, IIT Bombay, NIT Allahabad, etc. are taking part in developing nano sensors and integrating them into IoT. The IoNT is mostly used in agricultural and healthcare applications. The study shows the present status of India in IoT and how India can create an impact in developing IoNT based applications.

Paper Presenter

Sarfraz Hussain

India

Thursday August 8, 2024 2:35pm - 2:46pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

2:35pm IST

Next-Generation Digital Forensics: Leveraging AI for Effective Cyber-security Solutions

Thursday August 8, 2024 2:35pm - 2:46pm IST

Strategy/Analysis

Authors - Soni R Ragho, Manav A Thakur, Priti Chorade, Rashmi Bhumbare
Abstract - Artificial Intelligence (AI) is rapidly advancing technology that is revolutionizing various domains and applications, including cybersecurity. Its widespread adoption is evident in its significant role throughout the development and operational phases of modern technologies. This paper aims to provide a comprehensive overview of AI's role in cybersecurity, highlighting its advantages while acknowledging potential challenges and negative impacts. Additionally, it will delve into AI-based models that enhance security across infrastructures and networks, contributing to the overall improvement of cybersecurity. The paper will explore different strategies for leveraging AI in cybersecurity applications to address emerging threats and vulnerabilities, considering the socio-economic implications of AI integration in cybersecurity.

Paper Presenter

Manav Ashok Thakur

India

Thursday August 8, 2024 2:35pm - 2:46pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

2:35pm IST

SCAR – Speech Conversion & Assist Responses

Thursday August 8, 2024 2:35pm - 2:46pm IST

Debate

Authors - Rahul Adkar, Siddhesh Balghare, Chaitanya Waghmare, Abhishek Jadhav, Soni Ragho
Abstract - Voice assistants are intermediator between agents that can interpret human speech and respond via synthesized voices. It's like a magical friend in your device. For people who can't see, it's like having superpowers. This amazing assistant can do lots of things! It can change different types of files, making them easy to understand. If you want a file in a special way, it can do that too, just like magic! But there's more! It can read words on the screen out loud, so you can listen instead of read. And if you talk to it, it can write down what you say. It makes technology easy and fun for everyone. Imagine it as a bridge, connecting people to the digital world. It doesn't matter if you can see or not – the voice assistant makes sure everyone can use technology without any trouble. It's all about making friends with technology and making the world a friendlier place for everyone!

Paper Presenter

Soni Ragho

India

Thursday August 8, 2024 2:35pm - 2:46pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

2:47pm IST

Big Spatial Data Management - Tools and Technologies Landscape

Thursday August 8, 2024 2:47pm - 2:58pm IST

Tango 1

Authors - Purnima Gandhi
Abstract - Modern users demand fast, scalable, simple, user-friendly, and cost-effective solutions to perform complex analytics on complex and disparate data including spatial data. The complex characteristics of spatial data have made analytics and management more challenging. The paper highlights the overall research and development done in the area of big data management including geometry attributes. The state-of-the-art databases, frameworks, and architectures are reviewed and compared with significant parameters. It also presents issues and challenges to meet the current demand of modern users to perform spatial analytics and management.

Paper Presenter

Purnima Gandhi

India

Thursday August 8, 2024 2:47pm - 2:58pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

2:47pm IST

Security and Challenges of Blockchain-based IoT Use Cases

Thursday August 8, 2024 2:47pm - 2:58pm IST

Tango 2

Authors - Madhav Ajwalia, Kamal Mer, Raj Bhatia, Parth Shah, Priteshkumar Prajapati
Abstract - This study explores the intersection of Blockchain and the Internet of Things (IoTs), focusing on security challenges and potential use cases. With the exponential growth of connected IoT devices, reaching 16.7 billion in 2023 and projected to rise to 29 billion by 2027, ensuring the security of these devices becomes paramount. This study discusses the real-world applications of IoT in industries such as healthcare, agriculture, smart homes, smart cities, and Industry 4.0. That highlights the critical role IoT plays in advancing automation and efficiency. Identifying security threats posed by the explosive growth of IoT, the paper proposes Blockchain as a solution to enhance the security of IoT devices. The integration of Blockchain with IoT is examined to address security concerns, such as data integrity, decentralization, identity management, and resource sharing. Despite the promises of Blockchain in enhancing IoT security, the paper discusses various challenges, including scalability, latency, energy consumption, and regulatory complexities.

Paper Presenter

Madhav Ajwalia

India

Thursday August 8, 2024 2:47pm - 2:58pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

2:47pm IST

LEAVE MAMAGEMENT SYSTEM

Thursday August 8, 2024 2:47pm - 2:58pm IST

Strategy/Analysis

Authors - Manav Ashok Thakur, Ajinkya Santosh Pawar, Prajyot Ashok Bhise, Sanket Pradip Deokate
Abstract - The "Educator Leave Administration Platform" is a robust system crafted to simplify and automate leave management for teachers. It facilitates leave request submissions, approval workflows, and live tracking of teacher absences. Equipped with intuitive interfaces and effective notification mechanisms, it facilitates seamless communication between educators and administrative staff. The platform guarantees transparency and responsibility, alleviating administrative workload. Its analytical tools empower evidence-based decision-making, facilitating enhanced resource management. In essence, it streamlines teacher scheduling, bolsters efficiency, and enriches the educational landscape.

Paper Presenter

Manav Ashok Thakur

India

Thursday August 8, 2024 2:47pm - 2:58pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

2:47pm IST

Virtual Assistance for Visually Impaired People

Thursday August 8, 2024 2:47pm - 2:58pm IST

Debate

Authors - Raghu Soni, Pranav R Nair, Anushka A Pawar, Apeksha Jadhav, Gaurav Gore
Abstract - Addressing the needs of the 250 million individuals globally who experience vision impairment, with 40 million among them being blind, presents a significant challenge. Many technologies have emerged to assist them, aiming to promote independence. For instance, there's a desire to create an integrated machine learning system. This system would empower individuals with visual impairments to recognize and categorize objects in real-time. Additionally, it would offer voice feedback and distance information, issuing warnings as necessary for proximity to objects.

Paper Presenter

Soni Ragho

India

Thursday August 8, 2024 2:47pm - 2:58pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

2:58pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 2:58pm - 3:00pm IST

Tango 1

Invited Guests/ Session Chairs

Prof. Nirav H. Bhatt

Head, Department of AI-ML AM IST, Charotar University of Science and Technology, India

Thursday August 8, 2024 2:58pm - 3:00pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 2A, Tango 1

Host Organization Global Knowledge Research Foundation

2:58pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 2:58pm - 3:00pm IST

Tango 2

Invited Guests/ Session Chairs

Prof. Sharmila Kunde

Technology Advisor, Vidya Vikas Mandal, Goa, India

Thursday August 8, 2024 2:58pm - 3:00pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 2B, Tango 2

Host Organization Global Knowledge Research Foundation

2:58pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 2:58pm - 3:00pm IST

Strategy/Analysis

Invited Guests/ Session Chairs

Prof. Vinaya R. Gad

Associate Professor, G.V.M.'s Gopal Govind Poy Raiturcar College of Commerce and Economics Farmagudi, Ponda-Goa, India

Thursday August 8, 2024 2:58pm - 3:00pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 2C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

2:58pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 2:58pm - 3:00pm IST

Debate

Invited Guests/ Session Chairs

Mr. Abhay Avinash Bhamaikar

Director and Co-founder, Innovease India Private Limited, India

Thursday August 8, 2024 2:58pm - 3:00pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 2D, Debate

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:03pm IST

Tango 1

Thursday August 8, 2024 3:00pm - 3:03pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:03pm IST

Tango 2

Thursday August 8, 2024 3:00pm - 3:03pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:03pm IST

Strategy/Analysis

Thursday August 8, 2024 3:00pm - 3:03pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:03pm IST

Debate

Thursday August 8, 2024 3:00pm - 3:03pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:05pm IST

Virtual Room A

Thursday August 8, 2024 3:00pm - 3:05pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:05pm IST

Virtual Room B

Thursday August 8, 2024 3:00pm - 3:05pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:05pm IST

Virtual Room C

Thursday August 8, 2024 3:00pm - 3:05pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Thursday August 8, 2024 3:00pm - 3:05pm IST

Virtual Room D

Thursday August 8, 2024 3:00pm - 3:05pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

AMAZE-A Mobile Application for Comparing a Particular Electronic Gadget in Different E-Commerce Websites

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - K. Rama Krishna, P. Sandeep, K. Santhosh Kumar, P. Bhanu Tej, B. Koteswararao
Abstract - Amaze is an e-commerce app that provides access to a large worldwide product selection in an online marketplace. By giving a unified search and browse feature across a variety of e-commerce websites, such as but not limited to Amazon, eBay, Walmart, and more, this software seeks to give customers a smooth purchasing experience. "AMAZE" extracts real-time product details, prices, and availability from various websites using state-of-the-art web scraping and data aggregation methods. By giving customers access to many e-commerce sites under a single app, the application transforms online purchasing by providing a varied marketplace experience. This creative approach combines many ecommerce apps so that customers can easily browse a large selection of goods and services. Customers' online shopping experience is streamlined by the ability to explore, compare prices, and make purchases from many platforms through an intuitive interface. By giving people more options and saving time and effort, this integrated approach improves convenience. Furthermore, the application guarantees safe transactions and dependable customer service, which builds consumer confidence and trust. This platform, which embraces the diversity of e-commerce and gives customers an all-in-one, comprehensive buying experience, is reshaping the online retail landscape.

Paper Presenter

P. Sandeep

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

An Implementation of WhatsApp Chat Analytics Platform using NLP

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Rushabh Dabhade, Gaurav Dhokane, Aryan Mahajan, Rishikesh Sutar
Abstract - In this study, a novel machine learning method for real-time sentiment analysis in WhatsApp con- versations is presented. We carefully process the text input, extracting pertinent elements by utilising cutting-edge natural language processing tools. The approach ensures precise sentiment classification by fusing state-of-the-art deep learning models with conventional machine learning techniques in a seam- less manner. Creating a sentiment vocabulary specifically for WhatsApp and adapted to the different language nuances present in these chat discussions is one of the study’s unique features. Moreover, our investigation goes farther to comprehend the subtle impact of temporal dynamics on sentiment patterns, offering important perspectives on the dynamic emotional terrain of this communication medium. Proven adaptability and appropriateness are demonstrated by the suggested framework’s exceptional accuracy across a variety of datasets.Our methodology has potential uses in social media analytics and mental health monitoring, in addition to the immediate context of sentiment analysis. This Research plays a significant role in the continued development of sentiment analysis techniques, especially in the dynamic context of modern communication platforms.

Paper Presenter

Gaurav Dhokane

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

An Investigation into Bitcoin Trading: Are the BANs Sufficient to regulate the Trade ?

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Srinivas Jangirala, Deepika Chandra Verma, Janardan Krishna Yadav, Shashi Kant Srivastava, Anandadeep Mandal
Abstract - Our paper empirically examines whether policy stance on bitcoin trading affect its actual trading or not. Using data from Coindance on trade volumes of Bitcoins and cryptocurrency policy stance of 45 countries, we find that bans on cryptocurrencies lead to a decline in Bitcoin trade more than any other policy stances, legal (countries that consider cryptocurrency transactions in some legal ambit) and neutral (countries that are silent on the policy stance on cryptocurrencies). Further, we find that where some legal recognition has been given to some form of cryptocurrency trade, it has restricted the trade in comparison to those countries where the regulatory bodies are silent on cryptocurrencies.

Paper Presenter

Janardan Krishna Yadav

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Cryptocurrency Policy-Stance of BRICS Countries

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Srinivas Jangirala, Deepika Chandra Verma, Janardan Krishna Yadav, Shashi Kant Srivastava, Anandadeep Mandal
Abstract - Cryptocurrencies have been in the news of late because of evolving regulations to facilitate or contain their trade. Therefore, one observes an extreme range of policy stances- from highly positive to negative. This paper aims to understand and compares the policy-stance of BRICS countries towards cryptocurrency. We find that the policy-stance of BRICS countries is still evolving and except for Brazil, no clear picture of any positive changes in adapting crypto for the other four countries emerges. This may have a domino like effect on the crypto policies of the G-20 nations with India heading it for the next five years. This paper also highlights the implications of positive policies on further adaptation of cryptocurrencies and therefore the Blockchain technology.

Paper Presenter

Janardan Krishna Yadav

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Devnagari Sign Language Recognition for Deaf and Mute Individuals using Convolutional Neural Network

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Deepali R. Naglot, Deepa S. Deshpande
Abstract - Sign language serves as the primary mode of communication for individuals experiencing hearing and speech impairments. This research paper concentrates on vision-based system for recognizing and interpreting the Devnagari Sign Language (DSL). The paper reviews existing literature on various kinds of systems for detecting and interpreting sign language and discusses different approaches, including glove-based systems, vision-based systems, and depth sensors. The proposed system created a dataset of 47 alphabets of Devnagari Sign Language and applied image augmentation techniques, segmentation, and canny edge detection for preprocessing. The system incorporates Convolutional Neural Network architecture with convolutional layers, max-pooling layers, and fully connected neural networks for sign language recognition. This study evaluates the efficiency of a proposed system using precision, recall, F1-score, and support metrics. The proposed model attained an accuracy of 90.43% for 47 Devnagari alphabets.

Paper Presenter

Deepali R. Naglot

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Investigating Awareness Levels of E-commerce Recommendation Systems and Their Influence on Purchase Behaviour/Buying Decisions: with Reference to Udaipur City

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Amrita Todarwal, Narendra Singh Chawda
Abstract - This study delves into the awareness levels of e-commerce recommendation systems and their influence on purchase behaviour and buying decisions with special reference to Udaipur City. As e-commerce continues to expand rapidly in smaller urban areas, comprehending consumer perceptions and behaviours in these emerging markets becomes imperative. The research aims to address this gap by assessing awareness levels, usage patterns, and the impact of recommendation systems on buying decisions and purchase behaviour of customers from these areas. Formulated hypotheses are employed to examine relationships among variables such as awareness, usage, and purchase behaviour. Through a structured approach, the study endeavours to provide valuable insights into consumer behaviour in Udaipur city, offering actionable implications for businesses operating in such markets. By leveraging these insights, businesses can optimize marketing strategies, enhance customer engagement, and make informed decisions regarding investments in recommendation systems. Ultimately, the study aspires to deepen the understanding of e-commerce ecosystems in smaller urban centres like Udaipur, fostering more consumer-centric implementations of recommendation systems. In summary, this research contributes to the literature on e-commerce recommendation systems, illuminating their significance in shaping consumer behaviour in emerging markets like Udaipur.

Paper Presenter

Amrita Todarwal

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Missing Value Imputation in IoT-based Distributed Healthcare Systems: A Review

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Savita S. Hanji, Mahantesh N. Birje
Abstract - The rise in popularity of IoT-aided healthcare systems within distributed environments has facilitated global access to personalized and distributed electronic health services. These systems, known as Internet of Things- based distributed healthcare systems (IoT-DHS), leverage the Internet of Things (IoT) to connect diverse medical resources. Consequently, they offer intelligent, reliable, and effective healthcare services, particularly to patients with chronic illnesses and the elderly. An essential aspect of these systems is the analysis of healthcare data, which plays a pivotal role in informed decision-making regarding disease prediction, medication prescriptions, and overall patient health maintenance. However, healthcare data collected from different systems often contains numerous missing values. These missing values can introduce bias, compromise decision accuracy, and diminish the ability to detect critical associations, posing significant challenges across various fields. To address this issue, state-of-the-art methods for handling missing data in IoT-DHSs have been surveyed. From this survey, a taxonomy has been derived, categorizing these methods based on different aspects of IoT-DHSs.

Paper Presenter

Savita S. Hanji

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Predictive Modeling for Job Recommendations: Harnessing the Power of KNN, SVM, and LR Algorithms

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - P. J. R. Shalem Raju, M. Prasad, Raja Rao PBV, P. Kiran Sree, Sharani Bhuvana Sree Biruda, Likhitha Sri Akula, Cherukula Archana, Navya Sri Gompa
Abstract - A web-based job search site called "Online Job Mapper" enables companies to list job opportunities and evaluate applications while job seekers can register and apply for positions. Conventional hiring procedures are costly and time-consuming. Job searchers have to use a variety of methods to locate employment, including job fairs, college fairs, and adverts. Employers must work very hard in the meantime to locate the best applicant for a position that needs to be filled. The goal of our online application is to solve these drawbacks and offer a user-friendly platform where companies and job searchers can easily find and submit jobs. Candidates can look for employment in any field by using the advanced search tools. Additionally, they can upload their resumes, which are kept on file for later use. Companies can download these resumes, post job openings, or remove them. This portal is administered by the admin, who also selects which jobs and firms can post positions or access the platform. There are no geographical restrictions when using this platform for Employers and Candidates from anywhere in the globe. Today's highly sought-after cutting-edge technology in the IT business were used in the development of this application.

Paper Presenter

M. Prasad

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

SIRS: Stone Inscription Recognition System

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Akula Triyan Subramanyam, H.Summia Parveen, Sindhu C, Kalluri Shanmukha Sai, Cibisundar S, Venkadeshwar A, Vinoth Kumar R
Abstract - Ancient stone inscriptions are invaluable cultural artifacts, often bearing historical texts or inscriptions in languages that have long ceased to be in common use. In this study, we propose a novel approach to the analysis and recognition of characters in the stone inscriptions from ancient times using the Histogram of Oriented Gradients technique. In this context, histogram of oriented gradients offers a promising solution for character recognition by capturing the subtle visual cues that define the shapes and textures of individual characters. We present a comprehensive methodology for applying histogram of oriented gradients to ancient stone inscriptions, including image preprocessing, character segmentation, and the calculation of histogram of oriented gradients descriptors for each segmented character. To enhance the recognition accuracy, we also explore the utilization of machine learning classifiers, such as support vector machines trained on histogram of oriented gradients descriptors from labeled data sets of ancient stone inscription characters. Here, digital images of stone inscriptions from the 11th century are used to create a database. Support Vector Machine is used to classify the features into modern characters after they have been computed. Results show a significant recognition rate for 10 characters out of 300 characters in a database of 300 characters.

Paper Presenter

Akula Triyan Subramanyam

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Smart e-Menu with AI-Based Food Recommendation

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Vedika Patil, Vishal Patil, Rutuja Yadav Patil, Akanksha Mhaske, Atharva Fulari, Chetan Pawar
Abstract - Traditionally, restaurant service has been reactive, requiring direct interaction with waitstaff. However, an ideal service prioritizes the customer, proactively identifying their preferences and history to deliver personalized recommendations. This paper explores the integration of various machine learning algorithms to develop an intelligent e-menu system that achieves this goal. The research delves into the rise of "Smart e-Menu" systems utilizing Artificial Intelligence (AI) for food recommendations. We provide an overview of various AI techniques, their applications, and their impact on customer satisfaction, operational efficiency, and revenue generation within the food service sector. Additionally, we review significant works in the field of menu digitization and food recommendation systems. This study contributes to the understanding of how AI-powered e-menus can personalize the dining experience, ultimately leading to increased customer satisfaction, operational efficiency, and revenue generation for restaurants

Paper Presenter

Vedika Patil

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Tourism Potential of Alleppey District: A Study on Vembanad Backwaters

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Aswathy Prasad, Dayana Das, N. Ajith Kumar
Abstract - Backwater tourism is the leading tourist products in Kerala that attracts a large number of tourists. Traditionally it was used only for the purpose of transportation. But now a days it is one of the leading tourist destinations. Kerala, the most popular backwater tourism is Vembanad backwater tourism in Alappuzha district. The major attraction of backwaters is houseboat tourism. Here the study is conducted to know the tourism potential of Vembanad backwaters with special reference to Alappuzha district. This paper focuses to study the psychographic and demographic profile of respondents, the level of satisfaction with services offered in houseboat and also discuss the environmental issues related. Primary data has been collected from tourist and employees through interview method with structured questionnaire. Convenient sampling technique was used for the data collection process. Statistical Package for Social Science (SPSS) was used for analysis. Test such as the Co efficient of variation (CV), Mean percentage, chi-square and one-way annova were used.

Paper Presenter

Aswathy Prasad

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Analyzing Social Media Analytics for Increasing Brand Equity: Case of Barbie Movie

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Ruby Chanda, Vanishree Pabalkar
Abstract - Social media has become a vital instrument for advertising and boosting the success of films in today's digital age. This research looks at the creative social media methods used in the Barbie movie distribution, aiming to understand how these strategies contributed to the film's popularity. This research provides insights into effective tactics that the entertainment industry may implement to ensure future movie releases' success through a complete review of the film's social media marketing, engagement metrics, and audience responses. The data was collected from online sources to analyze users’ impact and trends toward these marketing strategies. The data was analysed and concluded which clearly reflected that the innovative social media strategies pushed the brand equity and the customer engagement of the movies. This resulted in the success of the movies. The recommendations based on this are presented in this paper, which focus on inclusive campaigns and collaboration with all the stakeholders.

Paper Presenter

Ruby Chanda

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Cloud Adoption and Optimization for Business Growth

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Ruby Chanda, Rahul Dhaigude
Abstract - This research explores the influence of cloud adoption and optimization on business growth. The study was focused on IT employees only, and by commissioning a descriptive research design, primary data was gathered from respondents to ensure consistency, reliability and accuracy in the analysis. By concentrating on the particular Amazon cloud services that are used by various businesses, the study aims to shed light on how cloud computing affects a variety of industries. The goal of the study is to evaluate how well Amazon cloud services are able to support organizational goals by looking at how widely they are adopted and implemented. In summary, this study aims to give significant perspectives on the connection between cloud computing and company development, along with useful recommendations for enterprises navigating the cloud adoption landscape.

Paper Presenter

Ruby Chanda

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Consumer Behaviour towards Digital Tourism Post COVID – A Sentiment Analysis

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Ruby Chanda, Rahul Dhaigude
Abstract - This study investigates the shift in consumer behavior and perception towards tourism on digital platforms post-COVID times. The investigation has been done from social media ‘content creator’ and ‘user’ perspectives. Social media platforms play a crucial role in choosing destinations and consumer travel. Hence, performing social media analytics on influencer and tourist pages can significantly reduce the time of primary market research and reveal real-time, actionable insights into consumer behavior. By implementing sentiment and spatial analysis, the study finds that themes of travelers’ social media activity have changed between the pre-COVID and post-COVID periods. It is thus concluded that post-COVID, travelers have started to focus on other life aspects apart from traveling, and social media usage and content preferences have changed accordingly. Travel companies can use the findings of this report to customize their travel package offerings and social media content to increase customer conversion rates and grow business in the post-COVID world.

Paper Presenter

Ruby Chanda

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Enhanced Symmetric Cryptography with Multi-Factor Authentication

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Garapati Laalitya, Radha.D
Abstract - The popular symmetric-key encryption algorithm, the Triple Data Encryption Standard (3DES) is renowned for its strength and security. On the other hand, due to its perfect confidentiality property, One Time Pad (OTP) is an encryption technique that, when used correctly, is theoretically not breakable. The use of 3DES when combined with OTP to improve data encryption security is examined in this study. One must always be cautious so that someone can eavesdrop on our messages. Cryptography is one of the common and widely used techniques to securely send information from one end to the other. The goal of combining 3DES and OTP is to take advantage of both encryption methods. Strong cryptographic security is provided by 3DES through its multiple encryption rounds, while perfect secrecy is achieved by OTP through the use of a randomly generated key that is the same length as the plaintext message. Comparison of the Triple DES algorithm using a one-time pad with other algorithms like RSA, Blowfish, DES, Triple DES, and AES has been done that basically involves assessing various factors such as security strength, computational efficiency, key length, and practicality in different use cases. Each algorithm has its unique strengths and weaknesses, making it essential to evaluate them based on specific security requirements and performance considerations.

Paper Presenter

Garapati Laalitya

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Evaluating User Intention to Adopt Smart Home Devices in Emerging Markets: A customized TAM Model

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Avinash Shivdas, Arjun B, Akshara K K, Aswin S
Abstract - Smart home is a systemized home technology with multiple appliances having a centralized remote controlling feature that is connected to the Internet. In the evolving world, the connection between humanity and technology has strengthened. Innovation has been constantly reshaping our homes and resulted in our living space undergoing a profound transformation. Though its growth has been rapid, and is being extensively studied in developed nations, there exists a gap in emerging markets like India. We have included factors like Perceived Connectedness and perceived Security to enhance the robustness of the model, which was empirically tested based on inputs from 170 respondents. Results reveal that perceived connectedness and perceived security significantly influence adoption apart from other factors.

Paper Presenter

Arjun B

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Knowledge Graph Creation Using Syntax and Semantic Model

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Aparna Rajendran, Varshitha Rajendran, Veena G
Abstract - The core concept of this project revolves around constructing a knowledge graph from any given text document, employing advanced data science techniques. This paper delves into the significance of structurally arranging data and information. The methodology encompasses several key steps including sentence segmentation, entity extraction, and relation extraction, culminating in the creation of a Knowledge Graph from Text Data. In this project mainly focus on identifying three relations.Song_composedby, Screenplay_Writtenby, and Movie_Releasedin. We created a corpus of 4,300 sentences from 500 articles and recognised movie details in Wikipedia to evaluate the model. These extracted relations are manually checked and created the knowledge graph. This knowledge graph serves as a structured and lucid representation of the underlying text, providing clear access to the desired information. The structured knowledge graph enables precise data retrieval, enhancing overall accessibility and usability.

Paper Presenter

Aparna Rajendran

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

One-Day International Cricket Data Analysis Using Microsoft Power BI

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Ameysingh Bayas, Sudhanshu Gonge, Rahul Joshi
Abstract - Cricket is a popular sport played in many countries around the world, predominantly in South Asia, Australia, and England. Cricket generates an enormous amount of data, and it can be a tedious task to analyze individual performance without having the proper tools. Business Intelligence tools are software applications that are designed to collect, analyze, and present data in a way that helps organizations make informed decisions. By using these tools, teams, and analysts can make data-driven decisions in areas such as team selection, strategy, and performance improvement. This paper discusses the use of Power BI, an open-source business intelligence tool, for analyzing ODI cricket data. Power BI was officially launched by Microsoft in 2015 and is capable of providing interactive visualizations and business intelligence capabilities. It allows users to connect to a wide range of data sources, share insights with others, and create interactive dashboards. The tool is known for its easy-to-use user interface and ability to handle large volumes of data. This paper explains the dashboard design and development phase, including data sources used, visualizations chosen, and user interface. It also explores potential dashboard applications and how they can be used to make data-driven decisions in the cricket industry. A detailed explanation of the process involved in creating a Power BI dashboard for ODI cricket analysis is given. This paper aims to explain how data can be cleaned and transformed using the Power Query Editor. Vibrant visualizations have been chosen for this dashboard, including bar charts, scatter plots, heat maps, and tables, and the use of these visualizations to help identify patterns in the data that can be used to make informed decisions is explored. Finally, potential applications of this dashboard in the cricket industry have been explored. They suggest that it could be used by coaches to analyze player performance or by team managers to identify areas for improvement. They also discuss how it could be used by broadcasters to enhance their coverage of ODI matches. Overall, this paper provides a comprehensive guide to using Power BI for ODI cricket analysis and it demonstrates how this powerful tool can be used to transform raw data into actionable insights that can drive decision-making in the cricket industry.

Paper Presenter

Sudhanshu Gonge

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Voting Regressor Model for timely Prediction of Sleep Disturbances using NHANES Data

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Revathy P, Manju Bhargavi N, Gunasekar S, Lohit A
Abstract - Sleep disturbances represent a significant health concern, with widespread implications for overall well-being. The study involves exploratory analysis to understand the relationships and associations between sleep disturbances and various chronic disorders, mental disorders, and demographics of individuals. Leveraging a rich dataset encompassing respondent sequence numbers and diverse sleep-related and health-related variables, this study employs to extract essential variables for further analysis. The predictive analysis involved the use of robust visualization and statistical tools to better understand the major distributing agents of sleep disturbances in the participants of the NHANES questionnaire. The second phase of this project focuses on fine-tuning the predictive model developed in the initial phase to enhance its accuracy and reliability. Building upon the insights gleaned from exploratory analysis and initial modelling, this phase employs advanced techniques to refine the predictive capabilities of the model. Specifically, the methodology involves the implementation of a voting regressor approach, wherein a diverse set of regression models are built and combined to make the final prediction. By leveraging the collective wisdom of multiple models, the voting regressor technique aims to mitigate individual model biases and uncertainties, ultimately yielding a more robust prediction of sleep disturbance likelihood. Through rigorous evaluation and validation, this phase seeks to optimize the performance of the predictive model, ensuring its effectiveness in real-world scenarios. The outcomes of this phase contribute to the overarching goal of harnessing machine learning to better understand and predict sleep disturbances, thereby facilitating proactive interventions and improving overall health outcomes.

Paper Presenter

Manju Bhargavi N

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Wearable Devices in Education: Enhancing Learning and Teaching

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Ruby S Chanda, Vanishree Pabalkar
Abstract - With more people buying wearable technology, the field of wearable technology is having a fast-expanding influence on society. Both educators and academics in this sector are becoming increasingly interested in using wearable technology in education. The efficient use of this new technology by academic institutions has been shown to make it simple to increase students' involvement and engagement with their learning. The article focuses on examining current implementations of this developing technology in the sphere of higher education and emphasizing the drawbacks and challenges these applications provide. The article came to the conclusion that before suggesting wider integration of wearable devices in learning and teaching, educators and makers of this technology should evaluate a number of limitations.

Paper Presenter

Ruby Chanda

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Advancement of Crypto-economics in India

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Anusuya Choudhary, Ritu Srivastava, Archana Gulati
Abstract - The purpose of this study is to increase readers' understanding of the blockchain technology-based cryptocurrency. As a developing country, India is attempting to learn from other countries like China and United States about its future steps toward such alternatives. The goal of this research is to close the gap between investor response and long-term implications. The study makes use of the Arima model to analyze price and volume data for Bitcoin to comprehend investor reaction for a period of five years. Second, a candle stick analysis of two years data of Binance coin was performed to comprehend the trading pattern. It was found that following the COVID-19 pandemic, investors attempted to turn this technology into a major industry, and investment increased significantly. This indicates that individuals can gain confidence if they are given the correct information. India's economy can greatly benefit from blockchain based cryptocurrencies as it provides more transparency in several industries, including finance, supply chains, and government.

Paper Presenter

Anusuya Choudhary

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Campus Connect- A Centralized Hub for Club Announcement’s and Community Engagement with Analytics

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Archit Sunil Navale, Rajdeep Sharma, Rahul Jadhav, Allan David, Avneet Singh
Abstract - All important announcements of various clubs and organizations of college are circulated through mobile messaging app. It is difficult to create a creative announcement on messaging app. There’s a chance that a particular message can get ignored by students or they might forget what they have viewed or they may have heard wrong details about club event or also the sender can miss a particular group to send the message. “Campus Connect” is a web-based solution that will serve as a centralized hub where students can easily access college club announcements, ensuring they never miss out on opportunities to participate and contribute to their interests. It also allows club admin or club representative to creatively blog an announcement and post it accordingly. Beyond the announcement feature, Campus Connect also allows real-time interaction through its group chat feature. This feature enables students to clear their doubts about anything related to the club events. To further increase the sense of community, Campus Connect will also provide a dedicated section to explore student community social media. This space will benefit students by fostering a positive and encouraging environment that inspires engagement and collective growth. Additionally, a survey was conducted among students to understand the challenges they faced. Based on these results, analytics were generated, and this system was designed.

Paper Presenter

Archit Sunil Navale

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Comparative Analysis of Object Detection Architectures

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Srivatsa Kulkarni, Sneha Appasaheb Kale, Shweta Ramesh Sankri, Rohan Abbayya, Preeti Pillai, Nalini Iyer
Abstract - In the realm of autonomous vehicles, object detection assumes a pivotal role. Two predominant methods for object detection are prevalent: one-stage and two-stage object detection. In one-stage object detection, classification and bounding box predictions occur in a single step, while in two-stage object detection, these occur in two steps. The current state-of-the-art for one-stage object detection is YOLO v8, while for two-stage object detection, it is Faster R-CNN. Each architecture carries its own set of advantages and disadvantages. One-stage architectures exhibit quicker processing times but often compromise accuracy. Conversely, two-stage architectures demand more processing time but typically deliver superior accuracy. These distinctions stem from the differing approaches employed in object detection. Evaluation of custom datasets reveals that Faster R-CNN yields higher average precision, recall, and mean Average Precision (mAP), rendering it a more promising choice compared to YOLO v8. Consequently, amalgamating the strengths of both architectures could potentially birth a novel model that achieves enhanced accuracy in a shorter timeframe while maintaining robustness. Such advancements hold the promise of facilitating prompt decision-making by vehicles in traffic scenarios, thereby mitigating the occurrence of accidents.

Paper Presenter

Srivatsa Kulkarni

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Developing an Energy-Efficient Reversible Multiplier Architecture Utilizing TSG and Fredkin Gates

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Spoorti Patil, Suhas Shirol, Saroja V S, Vijay H M, Rajeshwari M
Abstract - The study introduces a groundbreaking 4x4 reversible gate named "TSG," capable of functioning as a standalone reversible full adder, which simplifies the implementation process by reducing the need for multiple gates. This TSG gate employs two novel approaches: the parallel generation of partial products through Fredkin gates with a delay ('d'), and the reduction of addition steps to log2N using a reversible parallel adder composed of TSG gates. The 4x4 reversible multiplier utilizing these TSG gates outperforms existing designs by reducing the number of reversible gates required and minimizing the generation of non-functional, or garbage, outputs. This advancement highlights the importance of efficient multiplier architectures in improving processor and computing machine performance, with significant implications for low-power CMOS, quantum computing, nanotechnology, and optical computing, thereby suggesting its potential to revolutionize the efficiency of microcontrollers and digital signal processors.

Paper Presenter

Spoorti Patil

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Enhancing IoT Cybersecurity through Innovative Blockchain Solutions

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Rushali Garg, Anuradha S. Kanade, Prabha Kiran, Saikat Gochhait
Abstract - This revolutionary study presents a complete theoretical framework aimed at improving the cybersecurity of the Internet of Things (IoT) through the use of blockchain technology. The theoretical foundation focuses on essential principles such as decentralisation, consensus processes, and cryptographic procedures, drawing inspiration from various research works across disciplines. The fundamental goal of this paradigm is to address and mitigate security and privacy concerns in the field of IoT by calling for a shift from centralised to decentralised systems. Using blockchain’s inherent capabilities, the framework presents a breakthrough for proactively combating growing security threats. The cryptographic features of blockchain, in particular, are used to develop novel solutions. This framework investigates unique technologies such as encrypted communication routes and decentralised identity management. These cutting-edge technologies seek to strengthen the security infrastructure of IoT ecosystems by providing strong defenses against potential vulnerabilities. Furthermore, the study investigates the theoretical features of several blockchain applications designed expressly to improve Internet of Things security. Exploration of these applications provides useful insights, improving a better understanding of the theoretical foundations supporting the proposed framework. Despite its theoretical nature, the study report emphasises the importance of transforming theoretical capabilities into concrete advances in the rapidly evolving IoT sector. The call to action emphasises the importance of practical implementations that may effectively solve real-world cybersecurity issues. However, the research highlights limits such as scalability and interoperability, which must be considered when implementing the suggested framework in practical contexts.

Paper Presenter

Rushali Garg

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Navigating the Skies: A Journey through Price Prediction Models

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Aneri Shah, Gouri Tibdewal, Samarth Shanbhag, Kumkum Saxena
Abstract - The ever-changing cost of airfare has always proved to be a significant barrier for travellers trying to make the most of their savings by conducting manual searches and scheduling reservations for specific times. However, with the advent of machine learning there came into existence, a practical way of enhancing the aviation sector's capacity for decision-making and outcome prediction. Various regression methods like CatBoost, Random Forest etc. for precisely forecasting flight expenses with the help of machine learning approaches are studied in this paper. We have examined various machine learning models and their ability to represent the complex relationships between a variety of factors that influence airfare, such as airlines, dates of travel, locations of origin and destination, lead times for reservations, and historical price patterns. Analysis of large dataset is performed containing Indian flight data and algorithms which search for patterns and relationships that impact the cost are studied.

Paper Presenter

Aneri Shah

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Smart Library Management System

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - SowmyashreeN, Ravi, Shashank M, Prateek S, Chandana K S
Abstract - Libraries are moving towards automation and digitization in the modern day to improve user experience and streamline operations libraries are empowered by Radio Frequency Identification (RFID) technology. This work aims to develop a Smart Library management system using RFID technology. That includes the development of an RFID-based system prototype, which enables rapid and accurate location and tracking of books within the library, where each book in library will be equipped with RFID tags. The system aims to revolutionize traditional library management methods by integrating RFID tags into library resources, enabling efficient tracking, identification, and management of books. RFID technology offers numerous advantages over conventional barcode systems, including faster data retrieval, automated inventory management, and improved security, by embedding RFID tags in library and strategically deploying RFID readers throughout the library premises.

Paper Presenter

Ravi

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Spectral Analysis of Seashore Minerals by Mineralogical Mapping

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - S. Sudharsan, R. Hemalatha, K.Gowtham, S.Guru Prasadh, J. Johannes Shelson
Abstract - Mineral mapping using spectral reflectance analysis has emerged as a powerful tool in geological exploration, environmental monitoring, and resource management. This abstract provides an overview of recent advancements in the field, highlighting the significance of spectral reflectance techniques in identifying and characterizing mineral compositions remotely. Spectral reflectance analysis utilizes the unique spectral signatures minerals exhibit in response to electromagnetic radiation. We infer valuable information about the mineral composition in a given area by analyzing the reflectance patterns across different wavelengths. This remote sensing approach has revolutionized mineral exploration, enabling cost-effective and efficient surveying over large, inaccessible terrains. Spectral unmixing algorithms and machine learning techniques further improve the discrimination of mineral assemblages, even in complex geological settings. Environmental monitoring and landuse planning benefit from the ability to detect and monitor mineralogical changes associated with natural processes or human activities. For instance, identifying alteration minerals can indicate potential environmental impacts from mining operations. In conclusion, mineral mapping using spectral reflectance analysis offers a versatile and robust approach to understanding earth's surface composition and dynamics. Continued advancements in sensor technology, data analytics, and interdisciplinary collaboration hold promise for further enhancing spectral reflectance techniques accuracy, efficiency, and applicability in diverse fields ranging from geology to planetary science.

Paper Presenter

S. Sudharsan

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Wireless Capsule Endoscopy Images Classification Using MobileNet and Colour Histograms

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Ravi Giri, Shashwati Banerjea, Rajitha B
Abstract - WCE stands for Wireless Capsule Endoscopy. It is a cutting-edge medical image visualisation technique that makes the gastrointestinal (GI) system visible. With WCE, a tiny capsule that is usually fitted with a tiny camera and light source is swallowed and travels through the digestive system, taking high-definition pictures of the GI tract along the way. WCE is primarily used to diagnose a variety of GI tract disorders and anomalies, including ulcers, tumors, and bleeding. The utilization of Wireless Capsule Endoscopy (WCE) for visualising the patient’s digestive tract generates a significant volume of data, which requires a considerable amount of time and specialized expertise for thorough analysis. Even though WCE is a great tool, finding and pinpointing areas with bleeding regions is still a big challenge. The proposed model name Wireless Capsule Endoscopy Images Classifier (WCEIC) is based on a combination of MobileNet features and color histograms for classifying gastrointestinal bleeding images. Its promising performance metrics underscore its potential utility in assisting medical professionals in the diagnosis and analysis of gastrointestinal disorders. Dataset comprising 2618 Wireless Capsule Endoscopy (WCE) images was employed to train & test the model. The evaluation of the model’s performance utilized metrics such as accuracy, precision, recall, F1 score. Results .

Paper Presenter

Ravi Giri

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Your Data, Your Rights: Understanding Consumer Privacy

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Palla Manoj Babu, Ashish Kumar, P Venkata Subbaiah, V Mouneswari, Prabhakiran, Saikat Gochhait
Abstract - Nowadays, more digital data is available, so companies could design and market innovative projects to consumers whereas this creates privacy issues We put the case that small firms are more likely to be harmed severely compared with the larger and established companies when it comes to public relations crises. In spite of the above-mentioned challenges, the firms can apply a number of approaches to ease privacy problems Intriguingly, data privacy issues might spur the innovation and thus generate competitive advantage over competitor for data driven marketing.

Paper Presenter

Ashish Kumar

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Comprehensive Survey of Machine Learning Applications in Agricultural Soil Nutrient Analysis, Fertility Prediction, and Soil Mapping in Wardha District, India

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Aishwarya V. Kadu, KTV Reddy
Abstract - Inadequate soil fertility and the increasing demand for research in data-driven agricultural tools significantly impact crop productivity. To address this challenge, utilizing high-throughput computational algorithms, particularly within machine learning, becomes indispensable for efficiently examining soil and achieving precise predictions of fertility status. This approach facilitates decision-making to optimize soil fertility management. However, challenges arise when selecting essential soil property criteria for accurate fertility forecasting and soil nutrient analysis. Additionally, the inherent limitations within individual ML algorithms and the subjectivity in implementing expert modeling procedures can result in variations in model performance, particularly in predicting lower fertility levels and soil fertility classification. This paper offers an all-encompassing survey of the present landscape of Applications of ML in agricultural soil nutrient analysis, fertility prediction, and soil mapping in Wardha District, Maharashtra. Our study incorporates essential elements, including location maps, district-specific information, climate data, soil maps, soil mapping units, and soil site suitability classifications. Notably, the most frequently examined soil nutrients in Wardha District, Maharashtra, encompass Potassium (K), Organic Carbon (O.C.), Manganese (Mn), Phosphorus (P), Copper (Cu), Zinc (Zn), Potential Hydrogen (pH). Predominant ML algorithms used in this context include Random Forest and Naïve Bayes, with Support Vector Machines, also significantly improving agricultural practices in the area.

Paper Presenter

Aishwarya V. Kadu

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Review on WSN Challenges Focus on quality of service, energy efficiency & security issues

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Yash Prajapati, Miralba Solanki, Nidhi Acharya
Abstract - Wireless Sensor Networks (WSNs) play a crucial part in various intelligent computing systems, but ensuring Quality of Service (QoS), energy efficiency, and security poses significant challenges. This review paper aims to present a comprehensive analysis of the present research landscape in WSNs, with a specific focus on QoS, energy efficiency, and security issues [1]. Being the crucial component of the environment. Monitoring, healthcare, smart cities, and business automation need efficient data transfer with minimal latency, high throughput, and the ability to support decision-making processes; hence the requirement for Quality of Service (QoS). Meanwhile, considering the distance of sensor nodes and battery power, it is important to solve the power consumption problem, thus new solutions for energy-saving communication, data collection and power management are needed. Additionally, it is important to protect WSNs against eavesdropping, data tampering, and denial of service attacks, and the application of effective security techniques such as encryption, authentication, and techniques for detecting intrusions is essential to protect sensitive and confidential information. Solving these issues is essential for the successful deployment and continued rise of Wireless Sensor Networks (WSNs) in various applications.

Paper Presenter

Yash Prajapati

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

An Innovative Approach for Early Dermatological Diagnostics Skin Cancer Detection Using Advanced Deep Learning Techniques

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Hemal Patel, Premal Patel
Abstract - This research study uses a dataset of 1800 benign and 1497 malignant mole photos from the ISIC Archive to demonstrate a Convolutional Neural Network (CNN) approach for the early identification of skin cancer. Acknowledging the vital importance of visual diagnosis in the identification of skin cancer, the study endeavors to enhance automated classification through the utilisation of a deep learning model. Important phases in the 14-step process include loading data, categorical labeling, normalization, and creating models with Keras and TensorFlow backend access. Because the dataset is balanced, accuracy evaluation is possible, and the result is a commendable 97% accuracy and precision score. The research highlights the potential practical utility of the created model, while downplaying the significance of early diagnosis in skin cancer. The incorporation of Ensemble Technique architecture is also investigated, which improves the performance of the model even more. This thorough method shows how CNNs can effectively classify skin lesions visually and high-lights the potential of automated systems to support prompt and accurate skin cancer diagnosis.

Paper Presenter

Hemal Patel

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Deep Convolutional Neural Network with Bicubic Interpolation for Super Resolution in Low Resolution Images

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Pranali Dandekar, Shailendra S. Aote
Abstract - In recent years, the demand for high-resolution images has surged across various domains, including surveillance, medical imaging, and remote sensing. However, capturing high-resolution images can be constrained by factors such as hardware limitations or bandwidth constraints. To address this challenge, super-resolution techniques aim to reconstruct high-resolution images from their low-resolution counterparts. In this paper, we propose a novel approach that combines deep convolutional neural networks (CNNs) with bicubic interpolation to achieve superior super-resolution performance. Our method leverages the powerful feature extraction capabilities of deep CNNs to learn complex mappings between low-resolution and high-resolution image spaces. Additionally, we incorporate bicubic interpolation as a preprocessing step to enhance the input resolution, providing the CNN with more detailed information to facilitate accurate reconstruction. Experimental results demonstrate that our proposed method outperforms existing state-of-the-art approaches in terms of both PSNR and SSIM measure. Overall, our work contributes to advancing the field of super-resolution by offering an effective and efficient solution for enhancing low-resolution images.

Paper Presenter

Pranali Dandekar

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Fast Face Recognition: Siamese Neural Network

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Aditya Gujrathi, Sarvesh Morey, Tushar Mahajan, Ganesh Masute Dhanraj Jadhav, Avinash Golande, Kirti Deshpande
Abstract - This research explores the latest developments in deep learning architectures to achieve higher accuracy in face recognition. We examine the efficacy of well-known models such as VGGFace and Face Net, investigating their capacity to extract unique facial traits that distinguish people under difficult situations. In order to enhance model generalization, the study explores the effects of data augmentation approaches, which create variations of preexisting images in order to artificially extend training datasets. We also go over methods for reducing bias in training data, which is an important part of making sure the model is equitable across a variety of demographics. The study also looks at how the model's performance is affected by various loss functions, which direct the learning process. Lastly, we suggest some directions for additional study to improve the precision and resilience of deep face recognition systems.

Paper Presenter

Aditya Gujrathi

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Multi-Mess Management using Tokens and Blockchain Encryption Technology

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Sunil M. Sangve, Atharva Mohite, Koustubh Soman, Saurav Deshmukh, Neha Bhavar
Abstract - This study presents a novel solution to secure and effective multi-mess management using AES-encrypted QR code tokens. By leveraging the strengths of AES encryption and the convenience of QR codes, this system aims to streamline meal payments, enhance user experience, and address security concerns prevalent in traditional multi-mess environments. While not directly integrating blockchain technology, the system provides a practical and secure solution for institutions with multiple dining facilities.

Paper Presenter

Atharva Mohite

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Self-Sovereign Identity (SSI) for Data Privacy and Security in Ubiquitous Multi-Cloud Computing (UMCC): A literature Survey and Analysis

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Komala R, Arunkumar B R, Shreyas A
Abstract - Multicloud security refers to a solution that helps protect an organization’s assets—such as private customer data and applications—against cyberattacks across multiple cloud environments. In a multicloud environment, an organization uses services from more than one public cloud provider simultaneously. This approach allows flexibility to operate with the best computing environment for each workload, whether private, public, or a combination of both. The adoption of multicloud strategies has become increasingly common due to the benefits of agility, flexibility, and reduced vendor lock-in. However, managing security complexities remains crucial to fully benefit from multicloud economics. It is evident from the literature survey that data in multicloud need privacy and security. In this connection, recent strategies have proposed to extend the users an authority to approve their data for storage, sharing and at the same time ensuring privacy, the paper presents the convergence of multicloud, blockchain and self-sovereign identity technique.

Paper Presenter

Komala R

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Statistical Analysis on Impact of Fake News in Social Media

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Kalpitha S Naik, Asmathunnisa N, Jagadish S Kallimani
Abstract - Fake news more precisely misinformation or false information can be a small piece of information but holds the ultimate power to create a big impact. Such news usually spread like wildfire especially on platforms such as social media which often triggers people’s mind and can lead to changing one’s opinion, belief or even facts and leads to real-world consequences. Not all fake news influence people in a bad way sometimes a little change of thoughts can be good but that doesn’t justify that the intention behind the fake news is a positive one. Fake news are often shared with the intention to manipulate people and this can be further achieved by the advancement of technology and by the introduction of several Artificial Intelligence based tools that creates content that deceive people. People especially on a social media platform often share a piece of information that they come across without first verifying if it’s a legitimate piece of information or not but sometimes people also share such information even after finding out its a false piece of information just to create disbelief among the people. This study aims to provide researches with a statistical and a graphical representation of how and what kind of impacts are caused by such fake news and the consequences and the laws that one has to face in case of occurrence of such events.

Paper Presenter

Kalpitha S Naik

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

The Impact of External Environmental Parameters on Arecanut Growth and Yield Production- A Quantitative review

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Sushitha S, Aparna K
Abstract - The intensive farming system demands accurate estimating or forecast methods, which are extremely difficult because of the reliance of yield efficiency on climatic, ecological, and agronomic factors and their consequences. Many research has been conducted using the booming technologies like Big data, Data analysis frameworks, Neural Networking, Deep learning to forecast the yield and quality of Arecanut crop. The study explores the published studies on Arecanut yield forecasting and also examines the frequently used notable approaches and the impact of various environmental factors on the same. The authors have analyzed the historical published research data and also performed the quantitative research analysis to examine the crop relationship between various environmental factors.

Paper Presenter

Sushitha S

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Transforming HR through technology in global startups

Thursday August 8, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Reena Lenka, Ankita Bhatia
Abstract - The most fundamental procedures in the HR sector have changed as a result of HR technology. Artificial intelligence, robotic process automation, and machine learning are just a few examples of the cutting-edge technologies that are being used in HR technology (Machine Learning). Automation of routine procedures like payroll and onboarding is now possible thanks to human resource technology, which also uses AI to make hiring decisions more intelligent. By enhancing understanding of employee satisfaction and promoting staff growth and retention, HR Technology is also boosting employee engagement. HR technology has several advantages in a variety of HR-related sectors, from making employee scheduling easier to automating tedious processes, cutting expenses, and giving timely information. Companies that successfully integrate HR technology have a much higher chance of retaining personnel and succeeding in an increasingly unpredictable, uncertain, complex, and confusing environment. (VUCA) environment.

Paper Presenter

Reena Lenka

India

Thursday August 8, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:03pm IST

UTILIZATION OF DEMOLITION WASTE

Thursday August 8, 2024 3:03pm - 3:15pm IST

Tango 1

Authors - Pranesh Chawhan, Mohammad Arman Khan, Samudre Pratik Bhagwat, Khot Shanawaz Nadim
Abstract - In recent years, handling and management of demolished concrete waste have emerged as a prominent challenge faced by countries worldwide. Addressing this issue presents a significant challenge that necessitates indigenous solutions. Repurposing demolished concrete waste is increasingly recognized as essential for preserving natural resources and reducing environmental pollution. A research project has been initiated to investigate the viability and recycling prospects of repurposing demolished concrete waste for future construction endeavors. Focus of the current investigation is Exploring the reuse of demolished waste materials to diminish construction impact costs and address housing shortages encountered by underprivileged communities worldwide. The crushed demolished concrete waste undergoes segregation via sieving to obtain the Specified dimensions of aggregate. Subsequently, various test are conducted to know the aggregate properties prior to its upcycling into new concrete. Following procedures were carried out: 1. Concrete mix design was executed, replacing 75% of sand with reclaimed concrete aggregate. 2. Concrete mix design was executed, replacing 100% of sand with reclaimed concrete aggregate. 3. Aggregate crushing, impact, and abrasion tests were performed. 4. Nine cube were cast and tested for 3,7&28 day. This thesis demonstrates the capability of reclaimed aggregates obtained on-site in producing high-quality concrete

Paper Presenter

Pranesh Chawhan

India

Thursday August 8, 2024 3:03pm - 3:15pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

3:03pm IST

2D-CRYPT: An Efficient Approach using Pixel Transposition and 2D-Logistic Map based Substitution

Thursday August 8, 2024 3:03pm - 3:15pm IST

Tango 2

Authors - Sachin Pujappa Baluragi, Prajwalasimha S N, Aishwarya R Waghamare, Ashwini Jadhav
Abstract - In this chapter, an efficient image encryption/decryption algorithm using a combined Pseudo Hadamard transformation based pixel transposition and 2D Logistic map based pixel value saturation, is proposed. Due to strong inter-pixel correlation and bulk data capacity, multimedia cryptosystem needs two stages per round for encryption/decryption. Data set is considered from Computer Vision Group (CVG), nearly 96% pixel value difference is observed considering host and cipher images. Various noises are considered along with cipher image in the decryption process and it is observed that about 80% similarity between decrypted images to its host.

Paper Presenter

Sachin Pujappa Baluragi

India

Thursday August 8, 2024 3:03pm - 3:15pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

3:03pm IST

Exploring the Potential of Multiple Cropping for Yield Improvement in Indian Agriculture

Thursday August 8, 2024 3:03pm - 3:15pm IST

Strategy/Analysis

Authors - Dinesh Kumar Arumugam, Tarun Kumar
Abstract - Agriculture has long been the backbone of many societies in India, providing food and income to countless people in India and around the globe. As we face the challenges of climate change and a rapidly developing and growing population, the need for innovation and sustainable agricultural practices has never been greater. However, the present farming practices rely heavily on manual labour, and irrigation techniques could be more efficient, high-cost exploitation of workers. This paper focuses on two crucial aspects of agriculture: irrigation and daily labour in the agricultural fields. Through thoroughly analysing existing literature and field research, we explore the various methods and technologies used in irrigation systems and their impact on farm productivity and sustainability. We delve into the limitations and difficulties of irrigation systems and look forward to identifying new ways to improve their effectiveness and efficiency, more importantly, contributing to the goal of achieving food security for all and solving the rise in demand for daily labour.

Paper Presenter

Dinesh Kumar Arumugam

India

Thursday August 8, 2024 3:03pm - 3:15pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

3:03pm IST

Monochrome: A Sustainably Designed Smartphone Application for a Digital Carbon Footprint Solution

Thursday August 8, 2024 3:03pm - 3:15pm IST

Debate

Authors - Prakruthi Rajendra, R.K. Sneha, Chahak Jain, Tarun Kumar
Abstract - An important cause of carbon emission that goes unnoticed is that which is released from mass digital consumption. Digital carbon footprints amount to the usage of every device, server, and data centre, and produce an alarming rate of carbon emissions each year. An increase in digitalisation has led to the frequent use of smartphones amongst users, leading to an increase in internet usage and social interactions. This study explores the digital carbon footprints and their slow impact on climate change. Climate change is an advancing problem that is caused by the emission of greenhouse gases like carbon dioxide (CO2) into the environment, leading to an increase in atmospheric temperatures. The proposed framework helps address gaps in research and limitations of existing products while building awareness of digital carbon footprints. Therefore, the solution is a smartphone application called “Monochrome,” which helps in tracking and monitoring an individual's digital carbon footprint. The application follows sustainable design principles and ethical guidelines. It aims to help reduce overall digital consumption, having a positive impact on the health of individuals and the environment.

Paper Presenter

Prakruthi Rajendra

India

Thursday August 8, 2024 3:03pm - 3:15pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

3:15pm IST

Sign Language Gesture Recognition using Machine Learning

Thursday August 8, 2024 3:15pm - 3:27pm IST

Tango 1

Authors - Soni R Ragho, Vidya R Ghule, Gayatri S Wasulkar, Sanjivani M Jadhav, Aniket T Ghule
Abstract - People with hearing impairments use sign language to communicate. The goal of project is to use computer vision to take the translate it into text in real time using the four modules. The system comprises four modules: image capturing, preprocessing, classification, and prediction. The spitting image dispensation can be used to segment. Open CV python library is used to process sign gestures. After capturing the gesture, it's transformed into a grayscale image, and noise filtering is applied to enhance prediction accuracy. Prediction and classification are accomplished through the utilization of a neural network.

Paper Presenter

Soni Ragho

India

Thursday August 8, 2024 3:15pm - 3:27pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

3:15pm IST

Metadata Interoperability Considerations for India’s Data Ecosystem: A Study of International Approaches

Thursday August 8, 2024 3:15pm - 3:27pm IST

Tango 2

Authors - Alka Misra, Durga Prasad Misra, Ritu Ghai, Sitansu Sekhar Mahapatra, Sumandro Chattapadhyay
Abstract - Digitalisation-at-scale of service delivery by national and sub-national governments through public digital platforms is transforming people’s lives across the world. These platforms are facilitating effective delivery of welfare and governance services, empowering citizens through enhanced government-citizen engagement, enabling data-driven governance solutions and contributing to inclusive development. In order to harness the full potential of data-driven governance and to create an innovative national ecosystem of Artificial Intelligence, Data Analytics and Machine Learning, a unified sector-agnostic data exchange can be foundational for enabling data sharing, access and usage at-scale among Government entities and between Government and Private entities alike. This paper focuses on one of the core concerns faced by the team leading an initiative to develop such a unified data exchange platform: identifying an appropriate comprehensive, domain- agnostic, extensible and modular metadata standard to enable the various data exchange use cases of the platform, while ensuring technical and semantic interoperability of the shared metadata. It presents a brief overview of the national context of digital transformation of the Indian economy and a review of the global landscape of metadata standards for data exchange. It concludes by discussing the rationale for adoption of W3C’s Data Catalog Vocabulary (DCAT) as the metadata standard for the data exchange platform.

Paper Presenter

Ritu Ghai

India

Thursday August 8, 2024 3:15pm - 3:27pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

3:15pm IST

Antenna with a Circular Microstrip Patch (CMP) For Microwave Communication

Thursday August 8, 2024 3:15pm - 3:27pm IST

Strategy/Analysis

Authors - D Shyam Prasad, Ediga Chandramohan Goud, Samiran Chatterjee, Y Divya
Abstract - In this study, we used the IE3D programme to build and analyse a Circular Microstrip Patch (CMP) antenna intended for microwave communication and its purposes. The principal goal of this project is in the direction of evaluate the proposal of a CMP antenna using a microstrip feed line at various microwave band frequencies in order to make it functional for the intended use. As a result, we employed PTFE substrate material with a 4.4 dielectric constant and a 1.6 mm substrate height. After examining the design, we discovered that this approach is very dependable and efficient for the intended applications. As a result, we were able to achieve good return loss of -22.44 db and enhanced band-width of more than 10 GHz with lower range of VSWR. The proposed (or) suggested antenna also applicable for body mount antenna. In the proposed antenna we are using the feeding methods which are combination of transmission line feeding and co axial feeding. When co-axial feeding is active and transmission line feeding acts as a parasitic element, the antenna resonates at 9.44 GHz with 16.71 dB return loss whereas when both feed are active, the proposed antenna useful for UWB antenna with more than 10 GHz bandwidth and good return loss. The suggested antenna is applicable for ultra wide band application when both ports are active and antenna applicable for X-band application when co-axial feed are active.

Paper Presenter

Ediga Chandramohan Goud

India

Thursday August 8, 2024 3:15pm - 3:27pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

3:15pm IST

EduVR: A Virtual Reality Tool for Intuitive Statistical Education on Machine Learning Algorithms

Thursday August 8, 2024 3:15pm - 3:27pm IST

Debate

Authors - G Sornavalli, B Mitul Krishna, Mythreya Kesavan
Abstract - Understanding and visualizing data, a fundamental concept in statistics and machine learning, can often pose significant challenges due to its abstract nature and multidimensional complexity. In this paper, we introduce a groundbreaking approach to address this challenge through the utilization of Virtual Reality (VR) technology. Leveraging Unity, a versatile game development platform, we construct an immersive VR environment where users, especially students, can witness the dynamic adjustment of a regression plane to accurately fit the data points. This innovative method offers a dynamic, interactive way to comprehend the complexities of multiple linear regression, rendering it more accessible and intuitive. The VR simulation addresses the challenge of visualizing and understanding high-dimensional data by providing a tangible, three-dimensional representation, thus enhancing the learning experience for students Our research revolutionizes statistical education by bridging abstract concepts with tangible visualizations, transforming interpretations of multiple linear regression and opening new avenues in data science methodologies.

Paper Presenter

Mythreya Kesavan

India

Thursday August 8, 2024 3:15pm - 3:27pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

3:27pm IST

Implementation Paper on Text Summarization and Visualization Using NLP

Thursday August 8, 2024 3:27pm - 3:39pm IST

Tango 1

Authors - Priti T. Chorade, Preeti D.Chandanshive, Sneha Deepak Shinde, Vaishnavi Biradar, Mrunali Gaikwad
Abstract - Text analysis involves uncovering and extracting valuable insights from unstructured text data. It spans various tasks such as information retrieval (e.g., retrieving reports or website content), text classification, clustering, and more recently, entity, relation, and event extraction. Natural Language Processing (NLP) aims to derive comprehensive meaning from free text, essentially deciphering who did what to whom, when, where, how, and why. NLP relies on linguistic principles like part-of-speech tagging and grammatical structure analysis. As the volume of data continues to grow annually, there is a pressing need to synthesize and extract insights from vast amounts of literature. Text analysis and visualization are crucial for effective data interpretation, offering users the ability to comprehend information within constraints. In the corporate world, time is valued more than money, making quick comprehension of data essential for presentations and decision-making. This paper presents a case study on the application of computational methods, particularly Natural Language Processing (NLP), for text analytics and visualization using relevant libraries. At any moment the worker is instructed to provide presentation and it takes hundreds of time to apprehend what data is, for what it turned into created, what is cause the entirety has to be recognize. Natural language processing provides a very significant contribution to various application areas such as multilingual big data, information retrieval, data integration and multilingual web. However, handling linguistic knowledge to develop such lingware applications is a crucial issue, especially for linguistic novice users. To deal with this issue, a "smart" linguistic knowledge management may help the users to understand the meaning, scope and especially the use of related techniques and algorithms. we propose a semantic processing of linguistic knowledge based on a multilingual linguistic domain ontology, called LingOnto. Compared to related work, LingOnto does not only handles linguistic data, but also linguistic processing functionalities and linguistic processing features.

Paper Presenter

Priti Chorade

India

Thursday August 8, 2024 3:27pm - 3:39pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

3:27pm IST

Prediction of Cardiovascular Heart Disease: Unveiling Grandiose Precision Through Opulent Classifier Performance Evaluation Using Supervised Machine Learning

Thursday August 8, 2024 3:27pm - 3:39pm IST

Tango 2

Authors - Sonam Nagar, Karan Verma, Sachin Singh, Kumar Shashvat
Abstract - Every year, the National Institutes of Health (NIH) and the American Heart Association (AHA) collaborate to disseminate the most recent data on heart disease, stroke, and cardiovascular risk factors. These include basic health behaviors such as physical inactivity, diet, sleep habits, smoking, and obesity as well as health factors including blood pressure(bp), cholesterol, glucose regulation and metabolic syndrome, all of which have a substantial impact on cardiovascular health. Globally, these ailments account for 31% of all deaths and stand as the leading cause of mortality. Projections suggest that by 2030, the death toll from cardiovascular disease could climb to 22 million individuals. Presently, American Heart Association data indicates that half of all adults in the United States grapple with some form of cardiovascular disease. This paper conducts a comparative analysis of three classifiers to predict heart disease cases while minimizing the number of attributes required for accurate classification. We utilize a publicly accessible dataset for predicting heart failure, employing three supervised machine learning classification algorithms: SVC, DT, and RF. Achieving a significant accuracy of 90.21% with SVC on the public dataset is noteworthy. Additionally, Random Forest achieved 88.40%, while Decision Tree yielded 78.62%. Our study highlights the importance of employing different classifiers and underscores the advantages of employing a robust feature selection method for predicting heart disease with minimal attribute usage instead of considering all available features. In conclusion, the Support Vector Classifier (SVC) emerged as the most effective model for predicting heart disease in our experiment.

Paper Presenter

Sonam Nagar

India

Thursday August 8, 2024 3:27pm - 3:39pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

3:27pm IST

DESIGN OF SIZE DEDUCED PRINTED FORK ANTENNA FOR SATELLITE COMMUNICATION

Thursday August 8, 2024 3:27pm - 3:39pm IST

Strategy/Analysis

Authors - Y Divya, Samiran Chatterjee, D Shyam Prasad, Ediga Chandramohan Goud
Abstract - Regarding the proposed fork array antenna's design, which employs transmission line feed and is applicable for many applications and proposing as arranging three consecutive rectangular pieces in a single layer with triple feed. The proposed design has a 2:1 VSWR range and a significant coming back loss, when ports one and two function as dynamic ports and port three act as parasitic component, this design performs well. We accomplished dualistic resonant frequencies of around 2.41 GHz and 9.99 GHz with - 9.90 dB and - 12.50 dB revert loss, respectively, at the requirement. Additionally, the form's proposed structure makes extensive use of bandwidth. As proven by a 10 dB bandwidth of approximately 0.62 GHz. However as specifically, port three is operational and all other ports are parasitic, that situation likewise yields a substantial bandwidth gain. The suggested antenna, which serves as an ultra-wide bandwidth antenna, allows a frequency of 4.93 GHz. But when ports 1 or 2 are active separately and further ports operate as parasitic components, the antenna does not operate correctly. The recommended structure is ineffective for any resonant frequency under these circumstances. Additionally, it accomplishes negative absolute gain for each resonant occurrence. Enhanced frequency ratio lacking inter-symbol interference (ISI) is the key exploit of the suggested design..

Paper Presenter

D Shyam Prasad

India

Thursday August 8, 2024 3:27pm - 3:39pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

3:27pm IST

Creating an Effectual Representation of Pedagogical Associations for Improvement in Academic Inclusivity by Means of Machine Learning

Thursday August 8, 2024 3:27pm - 3:39pm IST

Debate

Authors - Supriya S. Gorde
Abstract - The present study endeavors to improve the relationship between educators and engineering students in India, since it is a crucial element that impacts the job marketability, personal development, and progress of graduates. Due to a lack of customization and efficient communication processes, traditional educational models frequently fail to create strong, lasting connections. Tailored learning as well as effective guidance levels is limited by the general nature of current methods to engineering pedagogy which ignores the requirements and career goals of individual students. The proposed study aims to close these gaps by introducing a complete framework based on machine learning (ML) that would transform the landscape of pedagogical relationships in an academic scenario. We make use of Support Vector Machine (SVM), Logistic Regression (LR) and Extended Gradient Boosting (XGB) as these approaches can improve student performance analysis for custommade learning routes. Leveraging these particular machine learning techniques makes sense because of their demonstrated capacity to analyze large, complicated datasets and derive actionable insights. These insights are essential for customizing education to student profiles, forecasting employment trends, and enhancing communication efficacy. When evaluated across numerous datasets, the suggested model significantly improved precision, accuracy, recall, and other important performance characteristics, demonstrating its profound influence. It makes sense to utilize these specific machine learning approaches since they have a track record of successfully analyzing vast, complex datasets and producing insightful results. These insights are critical for predicting job trends, personalizing instruction to each student's profile, and improving communication effectiveness. The proposed model had a remarkable effect on precision, accuracy, recall, and other key performance parameters when tested on many datasets.

Paper Presenter

Supriya S. Gorde

India

Thursday August 8, 2024 3:27pm - 3:39pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

3:39pm IST

SkillSet Sherpa: Career Counselling with Large Language Models

Thursday August 8, 2024 3:39pm - 3:51pm IST

Tango 1

Authors - Kanishk Arya, Vedant Deshmukh, Saahil Tamboli, Sarika Bobde, Ruhi Patankar, Anushka Wani, Ketaki Dabade, Sakshi Ubale
Abstract - In today’s day and age, students have a large number of career choices, which leads to a lot of ambiguity regarding their future. Traditional career guidance methods often fall short in providing personalized recommendations tailored to individual students’ unique aptitudes, academic performance, and preferences. This paper introduces Skillset Sherpa, an innovative software solution that utilizes artificial intelligence (AI) and natural language processing (NLP) to address these limitations. Skillset Sherpa integrates three key components: the RIASEC (Holland Codes) aptitude test, an optical character recognition (OCR) technique for extracting academic performance data from marksheets, and a large language model (LLM) to generate personalized career recommendations. This system considers a student’s strengths, interests, and academic record to provide data-driven guidance. Skillset Sherpa has the potential to bridge the gap between traditional career guidance methods and the growing need for individualized support, ultimately empowering students to make informed decisions about their future. The GitHub repository for the same can be found here: https://github.com/Parzival7566/SkillSet- Sherpa-Final

Paper Presenter

Saahil Tamboli

India

Thursday August 8, 2024 3:39pm - 3:51pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

3:39pm IST

Sensor Deployment and Architectural Framework Planning for IoT Based Pollution Monitoring System used for Urban Area

Thursday August 8, 2024 3:39pm - 3:51pm IST

Tango 2

Authors - S. B. Chavan, S. M. Bhosale, S. A. Shinde, K.R.Desai
Abstract - Internet of Things (IoT) technology is in great demand for monitoring the pollution level of a given geographical area. For correct monitoring of the pollution level the deployment of sensors, systems and an architectural framework is necessary. For monitoring the pollution level of an urban area, it is necessary to geographically divide the area into sub-areas like residential area, industrial area, highway area, forests, open spaces etc. and deploy the pollution monitoring stations at various locations. For correct monitoring of pollution levels of an urban area, the deployment of sensors and systems and their accessibility is important. This paper proposes a framework for deployment of sensors and pollution monitoring stations. It proposes to use one central master station and multiple pollution level monitoring stations at various places and location. Every pollution monitoring station have unique ID and location address. Central master station have access of all monitoring stations for data visibility. The pollution level at particular place, region can be observed and stored with time, day, date, month and year by the central master station.

Paper Presenter

S. B. Chavan

India

Thursday August 8, 2024 3:39pm - 3:51pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

3:39pm IST

Enhancing Emotional Well-being and Reducing Sleep Disturbances of Dementia Patients Living alone

Thursday August 8, 2024 3:39pm - 3:51pm IST

Strategy/Analysis

Authors - Hiba Rehman Subhani, Tarun Kumar
Abstract - This paper explores a comprehensive strategy aimed at encouraging the emotional well-being and reducing sleep disturbances among dementia patients, particularly those residing independently. As dementia progresses, patients encounter diverse behavioral challenges and struggles with daily tasks, necessitating increasingly attentive care. The research methodology employed enables a systematic examination of the multifaceted factors influencing the disorder, leading to the development of a robust solution. The framework undergoes evaluation utilizing Bloom's Taxonomy, incorporating a deep understanding of the variables contributing to dementia. Tailored to the specific needs of dementia patients, the framework focuses on emotional enhancements and sleep disturbance reduction. The devised solution endeavors to enhance patient well-being through animal therapy, music therapy, and aromatherapy, fostering a calming environment conducive to their comfort and safety, effectively addressing the identified challenges. Moreover, the solution comprises both physical products and a user-friendly app, facilitating seamless navigation. Thus, this paper seeks to address the demand for tools catering to emotional enhancement and sleep management tailored specifically to dementia patients living independently.

Paper Presenter

Hiba Rehman Subhani

India

Thursday August 8, 2024 3:39pm - 3:51pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

3:39pm IST

Empowering Elegance: A Study on the Integration of Women Safety in Jewelry Design

Thursday August 8, 2024 3:39pm - 3:51pm IST

Debate

Authors - Tadikamalla Prasrita, Tarun Kumar
Abstract - The study explores the junction between technology and personal safety for women through the creation of a multipurpose jewelry pendant. This wearable device, which includes an SOS alert system, a discreet camera, and GPS tracking capabilities, intends to solve the serious issue of women's safety. The research approach included a thorough evaluation of the present literature, in-depth interviews, and questionnaires performed on college students to learn about their safety concerns and preferences. Based on the findings of the research phase, the proposed framework and design concepts were created. The pendant aims to easily fit into women's lifestyles while offering an added level of security by utilizing user-centered design methodologies. Iterative variations in design were used during the evaluation phase to ensure that the final product met both functional and aesthetic objectives. In the end, the project aims to provide a complete safety solution, which will increase women's security and confidence. The wearable pendant aspires to enable women to overcome their everyday lives with an increased feeling of safety by blending technology and user-centric design, producing a more secure and inclusive environment.

Paper Presenter

Tadikamalla Prasrita

India

Thursday August 8, 2024 3:39pm - 3:51pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

3:51pm IST

Operational Availability Optimization of Turbo Generators using Nature-inspired Algorithms

Thursday August 8, 2024 3:51pm - 4:03pm IST

Tango 1

Authors - Deepak Sinwar
Abstract - A turbo generator is a turbine driven electricity generator that is generally powered by water, gas, or steam. Turbo generators are one of the major sources of electricity world wide. Reliability of the turbo generators is one of the major concerns that needs to be dealt with utmost care to avoid the unnecessary breakdown in the power supply. In this paper, we investigated the impact of nature-inspired algorithms in obtaining the optimal operational availability of turbo generators. After stochastic modeling of turbo generators using Markov birth–death process and Chapman–Kolmogorov differential–difference equations, the steady state availability of the turbo generator systems are optimized using four nature-inspired algorithms viz. Artificial Bee Colony (ABC), Ant Lion Optimizer (ALO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO). Experimental results indicated a significant impact of nature-inspired algorithms in obtaining the overall operational availability of turbo generators.

Paper Presenter

Deepak Sinwar

India

Thursday August 8, 2024 3:51pm - 4:03pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

3:51pm IST

Sustainability on Consumer Behavior in Smart Home

Thursday August 8, 2024 3:51pm - 4:03pm IST

Tango 2

Authors - Soundarya N.P., Tarun Kumar
Abstract - This paper investigates the integration of Carbon Capture and Utilisation (CCU) and holographic projection technologies within smart homes to address environmental challenges and promote sustainable living. Through a comprehensive research approach involving interviews, surveys, and competitor analysis, consumer perceptions and market trends and framework for integrating those technologies are developed. The findings underscore the potential of CCU and holographic projection to mitigate carbon emissions, enhance user experience, and drive profitability in the smart home sector. However, significant challenges such as technological complexity and implementation costs persist, necessitating collaborative efforts between government and industry stakeholders. Despite these obstacles, there are substantial prospects for advancing these technologies, which hold transformative potential in promoting ecoconscious living and fostering a harmonious relationship between humanity and the environment. This study contributes valuable insights to the growing body of research on sustainable technology integration, highlighting the importance of innovation in mitigating environmental impacts and promoting sustainable lifestyles.

Paper Presenter

Soundarya N.P.

India

Thursday August 8, 2024 3:51pm - 4:03pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

3:51pm IST

Harnessing AI for Education and Transforming learning

Thursday August 8, 2024 3:51pm - 4:03pm IST

Strategy/Analysis

Authors - Suruchi Pandey, Hemlata Gaikwad
Abstract - The use of artificial intelligence in education is examined in this study, which focuses on how it can affect and impact student-teacher interaction, pedagogy and some ethical issues. It employs a qualitative research approach and a thorough literature review methodology to examine how AI technology is used in education, teaching scenarios in real world. By checking the impact of AI systems on workload, pedagogy and student teacher interactions, the research focuses to provide information about technological and sociological complexity of AI tutors and Virtual Teaching Assistants. The aim of the research findings is to promote more personalized learning pathways in developing field of education technology, thereby encouraging practice among practitioners. This extensive study of AI in educational institutions aims to provide informative information on the dynamic between AI and human educators, focusing and enhancing the educational experience for all the who are participating in the system.

Paper Presenter

Suruchi Pandey

India

Thursday August 8, 2024 3:51pm - 4:03pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

3:51pm IST

Global Shoe Waste: The Environmental Impact of Footwear

Thursday August 8, 2024 3:51pm - 4:03pm IST

Debate

Authors - Smriti Jain, Shreya Agarwal
Abstract - This research investigates the environmental impact of disposable footwear choices within the context of throwaway culture. The study employs a mixed-methods approach to bridge the gap between consumer footwear preferences and ecological consequences. A consumer survey revealed a concerning disconnect between these two aspects, highlighting the significant ecological burden of the footwear industry, particularly regarding landfill waste and carbon footprint. The research acknowledges the nascent market for sustainable footwear options. However, it emphasizes the need for user-centered and ecofriendly solutions. The methodology leverages a comprehensive approach, including interviews, surveys, mind mapping, brainstorming, and prototyping. This iterative design process aims to develop solutions tailored to the target audience's needs and preferences, ultimately enhancing user engagement and a sustainable future. Furthermore, the research also calls for the creation of better ways to handle and reuse the parts of old shoes, with a focus on efficiency and minimizing environmental impact

Paper Presenter

Smriti Jain

India

Thursday August 8, 2024 3:51pm - 4:03pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

4:03pm IST

Designing a Power-Efficient Pseudo Random Pattern Generator for Low Power Built-In Self-Test

Thursday August 8, 2024 4:03pm - 4:15pm IST

Tango 1

Authors - Bakkesh V A, Suhas Shirol, Saroja V S, Vijay H M, Rajeshwari M
Abstract - Complex integrated circuits (ICs) are becoming more and more prevalent in a wide range of applications due to the ongoing development and integration of semiconductor technology, which highlights the necessity for trustworthy testing procedures to guarantee IC functionality. Techniques are known as Built-In Self-Test (BIST) have become a viable option for testing these integrated circuits (ICs) both during the manufacturing process and in the field. The pseudo-random pattern generator (PRPG), one of the essential parts of BIST, is essential for creating test patterns that identify circuitry flaws. A Pseudo Random Pattern Generator designed especially for Low Power BIST applications is proposed in this project. The design prioritizes power consumption optimization while preserving the fundamental properties of fault coverage and unpredictability required for thorough testing. Test efficacy and power efficiency are balanced in the suggested PRPG by employing practical algorithms and circuit-level improvements. The architecture is crafted to reduce power consumption without compromising the quality of generated test patterns. By utilizing methods like selective feedback, state encoding, and clock gating, the generator significantly reduces power consumption in comparison to traditional designs.

Paper Presenter

Bakkesh V A

India

Thursday August 8, 2024 4:03pm - 4:15pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

4:03pm IST

Unveiling Signs: Exploring the Distinctive Rhythms of Indian Sign Language amidst Global Sign Variants

Thursday August 8, 2024 4:03pm - 4:15pm IST

Tango 2

Authors - Shalini Puri, Anushka Saxena, Aamanya Shah, Vishal Choudhary
Abstract - This paper aims to present the unique characteristics of Indian Sign Language in comparison to other sign languages around the world. It delves into non-verbal communication and the diverse identities within the deaf community. The goal is to enhance the integration of ISL into society through in-depth learning to enhance communication. This study uncovers the sociocultural factors of ISL that highlight the importance of linguistic diversity and the cultural aspects of the deaf community. Despite the growing deaf population in India, research contributions on ISL remain limited, making this proposed study a significant contribution to the field. The paper focuses on breaking down communication barriers in India, as well as globally. Additionally, it compares various existing research contributions to identify areas where Indian Sign Language can be improved. This study is intended to help the deaf community feel included and to advocate for their language rights and resources by shedding light on these issues.

Paper Presenter

Shalini Puri

India

Thursday August 8, 2024 4:03pm - 4:15pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

4:03pm IST

An AI Companion for Blind and Visually Impaired People for Sustainable Development and Creating a Supportive Ecosystem in Society

Thursday August 8, 2024 4:03pm - 4:15pm IST

Strategy/Analysis

Authors - Dipali Chandele, Bhavesh Chaudhari, Shantanu A. Lohi, Archana W. Bhade, Dilip R. Uike, Sakshi Khadilkar, Jaydeep Gedam, Rajesh M. Metkar
Abstract - This is an assistive device designed specifically to address the challenges faced by individuals who are blind or visually impaired. This product aims to enhance their daily lives by providing solutions to issues such as reading printed material and navigating their surroundings. Blind people will be able to understand what is written on a book's or document's page. Additionally, our flagship feature, Navigation Assistant, assists them in navigating unfamiliar places and provides guidance to reduce the risk of accidents. The knowledge acquired through our reading feature enhances the economic contribution of blind and visually impaired individuals and promotes their independence. Our device serves as an AI companion for blind and visually impaired individuals, thereby enhancing productivity.

Paper Presenter

Bhavesh Chaudhari

India

Thursday August 8, 2024 4:03pm - 4:15pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

4:03pm IST

Image Captioning System Using ResNet-50 and LSTM

Thursday August 8, 2024 4:03pm - 4:15pm IST

Debate

Authors - Harsh Chinchakar, Gaurav Ratnaparkhi, Atharva Tanawade, Saloni Raj Singh, Divyansh Modi, Amaan Shaikh, Vidya Patil
Abstract - Generating informative descriptions for photographs automatically has become an interesting but challenging endeavor. This paper introduces AI Image Captioning using ResNet-50 and LSTM (AICRL), a unified model that uses LSTM with ResNet50 for automatic image captioning. AICRL combines an encoder that uses ResNet50 to build a full image representation with a decoder that uses LSTM and a soft attention mechanism to predict the next phrase while highlighting particular features of the image. AICRL is evaluated using metrics like BLEU. It was trained on the Flickr8k and COCO 2017 dataset individually and optimizes the likelihood of the target description sentence given training photos. The results highlight the effectiveness of AICRL in creating image descriptions. Additionally, the PERSONALITY-CAPTIONS challenge is presented, to generate engaging captions through the integration of configurable characteristics of personality and style. A large dataset is applied to the models created by combining state-of-the-art methods in sentence and image representations. The proposed models demonstrate both robust performance on the unique PERSONALITY-CAPTIONS task and state-of-the-art performance on well-known datasets such as Flickr8k and COCO 2017. Online assessments confirm the best performance of the proposed model close to already existing models.

Paper Presenter

Harsh Chinchakar

India

Thursday August 8, 2024 4:03pm - 4:15pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

4:15pm IST

Addressing Gaps in Travel Booking System

Thursday August 8, 2024 4:15pm - 4:27pm IST

Tango 1

Authors - Rishita M Chowdary, Tarun Kumar
Abstract - This paper aims to explore the issues faced by online booking users in the Indian market. Although it is easy and diverse. Major issues include difficulty finding travel packages, poor customer support, and lack of local transportation arrangements. This article focuses on understanding the user experience by exploring these challenges and suggests ways to improve these platforms to better serve Indian tourists. By exploring these challenges, this paper aims to investigate the challenges faced by users in the Indian online travel booking market, despite its convenience & diversity and guide improvements in these platforms, leading to more efficient services for Indian travellers. In addition to the above challenges, another significant issue faced by users is the lack of transparent pricing. Often, users find that the final price at the time of payment is significantly higher than what was initially displayed. This is due to the addition of various hidden charges and fees, which leads to a poor user experience. Addressing this issue by providing clear, upfront pricing could greatly enhance user satisfaction and trust in online travel booking platforms. Moreover, users also report difficulties with understanding the terms and conditions of their bookings. This data is often long and filled with legal jargon, making them difficult to comprehend for the average user. This can lead to misunderstandings and disputes down the line. Simplifying these documents and making them easier to understand could go a long way in improving the user experience. Lastly, the lack of personalised recommendations based on past bookings or searches is another area where these platforms could potentially improve. By using data analysis and machine learning algorithms, these platforms could provide more personalised and relevant recommendations, thus improving user engagement and satisfaction.

Paper Presenter

Rishita M Chowdary

India

Thursday August 8, 2024 4:15pm - 4:27pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

4:15pm IST

Itihasa- An Interactive Learning Experience of Indian Mythology

Thursday August 8, 2024 4:15pm - 4:27pm IST

Tango 2

Authors - Dara Shashank, Tarun Kumar
Abstract - This paper focuses on integrating present-day innovative technology with the cultural history of our Indian mythology through an interactive platform, “Itihasa – An interactive learning experience of Indian mythology” It is an approach to create one platform to help youngsters learn about Indian mythology in various formats by going beyond the conventional methods of learning and narrative boundaries”. Itihasa offers an interactive learning experience of fascinating Indian epics, folklore and spiritual teachings. It is a trial being made for cultural preservation, using modern teaching techniques by providing a broad range of content types such as interactive 3D walkthroughs where users can move around in the form of various characters in environments inspired by Indian mythological sites, blogs, short videos and interactive forums, encouraging present youth to learn and understand about Indian cultural history through mythologies and its importance.

Paper Presenter

Dara Shashank

India

Thursday August 8, 2024 4:15pm - 4:27pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

4:15pm IST

Open Government Data Platform: A Standards-Enforcing SaaS Solution for India’s Open Government Data Ecosystem

Thursday August 8, 2024 4:15pm - 4:27pm IST

Strategy/Analysis

Authors - Alka Misra, Durga Prasad Misra, Usha Saxena, Ritu Ghai, Sanjay Mahendru, Sitansu Sekhar Mahapatra, Sumandro Chattapadhyay
Abstract - The landscape of datasets across government entities is not only divided in domain- and entity-wise silos but there are also significant challenges of technical and semantic interoperability. Standardisation of vocabulary for common data/metadata fields across data resources shared by various sources is key for ensuring semantic interoperability of such resources. Further, seamless and trusted data sharing requires standardisation of legal framework, data management operations as well as user experience for data contributors and consumers. This paper describes how such challenges and opportunities of enforcing standards were navigated during the journey of the Open Government Data (OGD) Platform India. Over the last decade or so, shareable non-personal non-sensitive data collected, compiled or generated by various Central and State/Union Territory government entities of India have been made available on the OGD platform under Open Access. Moreover, many government and non-government stakeholders have played crucial roles in analysing available data, demanding datasets of national or sectoral importance and sharing insights harnessed from the shared OGD in public interest. The aim of this paper is to present the OGD platform initiative against the background of the OGD ecosystem in India; its technical architecture and software components; and the challenges experienced and opportunities explored to improve proactive disclosure practices of Indian Government entities by enforcing standards on various aspects of data sharing.

Paper Presenter

Sanjay Mahendru

India

Thursday August 8, 2024 4:15pm - 4:27pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

4:15pm IST

AgriPredict: Machine Learning Based Agricultural Commodity Price Prediction

Thursday August 8, 2024 4:15pm - 4:27pm IST

Debate

Authors - Ashwani Kumar, Prathamesh Kusalkar, Sanket Naitam, Harsh Pande, S. N. Ghotkar, S. S. Kumbhar, Shanu Kumar, Sanket Jiwane
Abstract - The goal of this paper is to create a machine learning based system for seasonal pricing patterns and dynamic pricing [1] of vegetables in wholesale markets across the country. Using machine learning algorithms, the system optimizes prices by taking advantage of quantity, seasonal, and regional aspects. Regression analysis and tree based machine learning techniques are used by the system to create customized predictions for various crops, analyze historical data, and use models for price forecasting [2]. Planning and profit-maximizing techniques work together to maximize resources, cut waste, and promote sustainable farming methods

Paper Presenter

Shanu Kumar

Thursday August 8, 2024 4:15pm - 4:27pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

4:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 4:27pm - 4:30pm IST

Tango 1

Invited Guests/ Session Chairs

Prof. Annie Rajan

Associate Professor, Dhempe College, Goa, India

Thursday August 8, 2024 4:27pm - 4:30pm IST
Tango 1 Hotel Vivanta by Taj, Goa, India

Physical Session 3A, Tango 1

Host Organization Global Knowledge Research Foundation

4:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 4:27pm - 4:30pm IST

Tango 2

Invited Guests/ Session Chairs

Prof. Nikita Bhatt

Head, Department of Computer Engineering IST, Charotar University of Science and Technology, India

Thursday August 8, 2024 4:27pm - 4:30pm IST
Tango 2 Hotel Vivanta by Taj, Goa, India

Physical Session 3B, Tango 2

Host Organization Global Knowledge Research Foundation

4:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 4:27pm - 4:30pm IST

Strategy/Analysis

Invited Guests/ Session Chairs

Prof. Parth Shah

Professor and Head of the Department, Charotar University of Science & Technology, India

Thursday August 8, 2024 4:27pm - 4:30pm IST
Strategy/Analysis Hotel Vivanta by Taj, Goa, India

Physical Session 3C, Strategy/Analysis

Host Organization Global Knowledge Research Foundation

4:27pm IST

Session Chair Remarks & Closing Remarks

Thursday August 8, 2024 4:27pm - 4:30pm IST

Debate

Thursday August 8, 2024 4:27pm - 4:30pm IST
Debate Hotel Vivanta by Taj, Goa, India

Physical Session 3D, Debate

Host Organization Global Knowledge Research Foundation

4:45pm IST

Session Chair Remarks

Thursday August 8, 2024 4:45pm - 4:50pm IST

Virtual Room A

Thursday August 8, 2024 4:45pm - 4:50pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

4:45pm IST

Session Chair Remarks

Thursday August 8, 2024 4:45pm - 4:50pm IST

Virtual Room B

Thursday August 8, 2024 4:45pm - 4:50pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

4:45pm IST

Session Chair Remarks

Thursday August 8, 2024 4:45pm - 4:50pm IST

Virtual Room C

Thursday August 8, 2024 4:45pm - 4:50pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

4:45pm IST

Session Chair Remarks

Thursday August 8, 2024 4:45pm - 4:50pm IST

Virtual Room D

Thursday August 8, 2024 4:45pm - 4:50pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

4:50pm IST

Closing Remarks

Thursday August 8, 2024 4:50pm - 5:00pm IST

Virtual Room A

Thursday August 8, 2024 4:50pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 6A, Virtual Room A

Host Organization Global Knowledge Research Foundation

4:50pm IST

Closing Remarks

Thursday August 8, 2024 4:50pm - 5:00pm IST

Virtual Room B

Thursday August 8, 2024 4:50pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 6B, Virtual Room B

Host Organization Global Knowledge Research Foundation

4:50pm IST

Closing Remarks

Thursday August 8, 2024 4:50pm - 5:00pm IST

Virtual Room C

Thursday August 8, 2024 4:50pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 6C, Virtual Room C

Host Organization Global Knowledge Research Foundation

4:50pm IST

Closing Remarks

Thursday August 8, 2024 4:50pm - 5:00pm IST

Virtual Room D

Thursday August 8, 2024 4:50pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 6D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Opening Remarks

Friday August 9, 2024 9:30am - 9:35am IST

Virtual Room A

Friday August 9, 2024 9:30am - 9:35am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Opening Remarks

Friday August 9, 2024 9:30am - 9:35am IST

Virtual Room B

Friday August 9, 2024 9:30am - 9:35am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Opening Remarks

Friday August 9, 2024 9:30am - 9:35am IST

Virtual Room C

Friday August 9, 2024 9:30am - 9:35am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Opening Remarks

Friday August 9, 2024 9:30am - 9:35am IST

Virtual Room D

Friday August 9, 2024 9:30am - 9:35am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

A Study on Existing Deep Learning Models for Deepfake Detection

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Aanya Rawat, Shubhi Yadav, Vanshika Choudhary, Ishita Jain, K.R. Seeja
Abstract - In recent times, the proliferation of deepfake videos, generated through sophisticated deep learning algorithms, has garnered significant attention. These videos, capable of convincingly manipulating faces, have inundated the internet, often targeting celebrities and politicians. This trend poses a grave threat to social stability as these manipulated videos are frequently employed to tarnish reputations and manipulate public opinion. People can simply learn how to create deepfake films using a small number of victims or target photos with little to no effort. As a result, numerous research initiatives have been launched, with a primary emphasis on refining detection techniques and creating thorough benchmarks within the academic domain. In this paper, we have reviewed some of the recent works done in deepfake detection, through deep learning methods. Additionally, we also look at the bench-mark datasets in this domain, highlighting potential avenues for future research.

Paper Presenter

Ishita Jain

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Augmenting Learning in the Theory of Computation through student created short Videos

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Rashmi Dixit, Manisha Nirgude
Abstract - Acknowledging the growing inclination towards video content in the realm of social media, we integrated student-created short videos as a pedagogical tool to enhance learning in the Theory of Computation course. In this activity, students were tasked with producing concise educational videos covering different topics within the course with a specific focus on engaging students through the creation of short educational videos. The aim was to enhance the learning experience, encourage active participation, and foster a deeper understanding of complex theoretical concepts. The study assesses the impact of video creation activity on student engagement, knowledge retention, and overall satisfaction with the learning process.

Paper Presenter

Manisha Nirgude

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Enhancing Healthcare Ecosystem: Cloud-Based Blood Bank System for Efficient Communication and Collaboration between Blood Banks and Donors

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Shailesh Gahane, Sejal Kombe, Gayatri Bhoyar, Pankajkumar Anawade, Deepak Sharma
Abstract - Blood banks are essential to healthcare systems worldwide because they give patients in need life-saving blood transfusions. However, blood banks in India face a number of challenges, including limited resources, high demand, and geographic barriers. Cloud computing offers a promising solution to these challenges, providing blood banks with a scalable, accessible, and cost-effective platform to develop and deploy innovative blood bank systems. This paper will begin by reviewing the challenges faced by blood banks in India and the potential benefits of using cloud computing. The paper will then discuss specific examples of how cloud computing can be used to develop a blood bank system, such as donor management, inventory management, transfusion management, and communication and collaboration. The paper will conclude by discussing the future of cloud computing in blood banking and the potential benefits for patients, donors, and healthcare providers in India. The objective of paper is to create an online blood bank system based on the cloud with the following goals in mind: to enabling the real-time tracking of blood availability and to Enhance communication and collaboration between blood banks, hospitals, and donors.

Paper Presenter

Sejal Kombe

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Fast Bowler Injury Prediction and Rectification System

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Kumar Sampurn, Archit Anand, Pratyush Jaishankar, Tanya Bajaj, Amogh Firke, R. Bharathi
Abstract - Cricket is a highly demanding sport that places the body under a significant amount of strain on a player’s body. Amongst cricketers, fast bowlers face the maximum plunge due to the physically taxing nature of their skill set. To address these challenges, the proposed model aims to offer a unique view to injury prevention. Unlike the existing solutions which are mostly analytical in their scope and rational in their mannerism, the proposed model strives to provide a predictive analysis that is intelligent in its behavior. The presented model captures the posture of the bowler at their landing stage. It analyses his/her actions for potential injury scares. If the inference of the analysis labels the test action as injury-prone, it is moved to the next stage which is reverse image search. Here, the model showcases its predictive prowess and predicts an action that is less prone to injuries and can be attained by making the minimum number of adjustments to the original action.

Paper Presenter

Kumar Sampurn

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Generative Image Mapping: Harnessing GANs for Intelligent Image Retrieval and Synthesis

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Aditya Naidu Kolluru, G. Ram Sundar, Sindhu C, P. Arun Prakash, Kaila Jagadish Reddy
Abstract - The common medium of computer vision and natural language processing, text-prompted face detection with Generative Adversarial Networks (GANs) is a developing field. The architecture, techniques, and applications of GAN-based models for producing lifelike face images under the guidance of textual cues are thoroughly examined in this paper. Based on the semantic information contained in textual descriptions, our suggested framework uses a conditional GAN architecture to generate facial features that match given text prompts. The model acquires the ability to produce face images that correspond with specific traits or features mentioned in the text through adversarial training. We examined generator and discriminator networks, joint training strategies, text encoding, and fine-tuning techniques customized for text-prompted face detection tasks. The effectiveness and promise of the suggested strategy are shown by empirical analysis and case studies in a range of fields, from creative expression and entertainment to security and surveillance. We also explore future research directions, opportunities, and challenges in enhancing text-prompted face detection with GANs. To bridge the gap between textual cues and visual content, this research advances the field of artificial intelligence and computer vision research, opening the door to new applications and advancements.

Paper Presenter

Kaila Jagadish Reddy

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Interactive Tree Based Zero Knowledge Protocol for secure auditing check

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Rashmi Dixit, K. Ravindranath
Abstract - The widespread use of cloud storage has made cloud security a crucial issue. Related efforts have addressed security concerns including data integrity and confidentiality, which guarantee that the cloud will properly retain the remotely stored data. We think it's crucial that the cloud server is unable to divulge any pertinent details on the data that is being kept. We introduce an interactive tree-based Zero Knowledge protocol in this work. A Interactive tree based zero knowledge-based algorithm in which prover and the verifier are the two parties who participate in the authentication procedure. In this, the prover, or one party, refrains from disclosing anything that could enhance the risk to the secret's confidentiality. The prover need only demonstrate to the verifier that it is aware of a secret without disclosing it to the other portion. The exchanges are not intended to divulge or reveal any secrets. The verifier can only determine whether the prover has the secret after exchanging messages.

Paper Presenter

Rashmi Dixit

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

Research Study on the Potential Threats and Challenges of Additional Data Security, Security Measures and Protocols faced by Organizations in Cloud Environment

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Shailesh Gahane, Deepak Sharma, Pankajkumar Anawade
Abstract - The security issues of cloud computing are examined in this paper. Using a cloud computing architecture, users can access a pool of shared computer resources on-demand or for a fee. Cloud-based computing offers both individuals and businesses a number of benefits in terms of a capital investment and a reduction in operating costs. Cloud computing adoption is nevertheless constrained by a number of issues, despite these benefits. Security is an important issue that is frequently considered. The computing paradigm has a detrimental impact without this essential component, which leads to suffering on the personal, ethical, and economic levels. The security challenges that cloud companies must address are the focus of this research paper. As examples of cloud computing paradigms, we looked at the employment of private, hybrid, and public clouds in this study. The Internet is vital to cloud computing, which also has the most dependable computational architecture. As more individuals become familiar with the technology, it becomes simpler for them to access numerous clouds and obtain the information they need. In this paper we have proposed the consents about the challenges about data security faced by organizations, the sensitive and confidential cloud data storage, the security measures and their protocols for securing the data in cloud, the level of transparency provided by the Cloud Service Providers and last but not the least additional security measures or technologies to address the data security challenges in cloud.

Paper Presenter

Shailesh Gahane

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

The Design and Implementation of Cloud Based Paediatrician Healthcare Management System w.r.t. Needs and Challenges of Children Age from 5 to 15 Years

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Shailesh Gahane, Payal Khode, Deepak Sharma, Pankajkumar Anawade
Abstract - The research work on Cloud Computing Based on Child Healthcare Management has the main theme of addressing the age-specific healthcare system. This research work will have a specific concentration on children age range between 5 and 15 years. These are the most important years of a child's life, as this specific age range is the beginning stage of a child's life. This age range from 5 to 15 years, is an important period of growth and development for children. Children in this age group are developing their own personalities, gradually building self-esteem, and becoming more independent. Children have unique needs and vulnerabilities that must be considered when designing healthcare facilities. Children experience a wide range of behavioural and emotional challenges that can impact their overall well-being and development. As healthcare professionals working in child healthcare management, it is crucial to have the knowledge and skills to effectively manage these challenges. To evaluate the physical health of children in healthcare management systems, various assessments and measurements can be conducted. These include evaluating growth and development, conducting physical examinations, screening for common illnesses and conditions, and monitoring immunization status. The objective of this research work is to investigate the specific healthcare needs and challenges faced by children and accordingly propose a user-friendly child healthcare management system to meet the unique needs of children age from 5 to 15 years. Also this research is focusing on the effectiveness of existing child healthcare management systems in addressing the physical, mental, and emotional well-being of children age from 5 to 15 years.

Paper Presenter

Payal Khode

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

The Identification of Cloud Data Security, Confidentiality Protocols and Level of Compliance with Privacy Regulations in Handling Paediatric Healthcare Records

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Shailesh Gahane, Payal Khode, Prateek Verma
Abstract - In the field of child healthcare, maintaining accurate and up-to-date medical histories is of utmost importance. Electronic Health Record Privacy and Confidentiality has covered the essential topics related to the protection of sensitive patient information. The Legal and Ethical Considerations in EHR Privacy and Confidentiality emphasized the importance of maintaining patient privacy and complying with laws and regulations. Lastly, the Implementing Privacy and Security Measures in EHR Systems discussed the key steps and measures to ensure the confidentiality and security of electronic health records. Implementing proper security measures is crucial to ensure the integrity and availability of child healthcare data. This ensures that healthcare providers have access to the necessary information about a child's health, enabling them to provide appropriate and effective care. Electronic Health Records (EHRs) revolutionize healthcare with enhanced accessibility, efficiency, and care coordination, ensuring accurate documentation and improving patient safety through data analytics and research. Effective management of child healthcare and medical history data also plays a vital role in ensuring data security and privacy. By using encryption techniques, regularly updating security systems, and implementing access controls, healthcare organizations can safeguard the integrity and privacy of child healthcare data. This topic delves into the various aspects of child healthcare and medical history management, including documentation, storage, and data security protocols. The paper provides a comprehensive overview of the importance of data security and confidentiality in child healthcare management. The inclusion of legal considerations such as HIPAA and GDPR adds depth to the discussion on privacy regulations. and considering the incorporating real-world examples or case studies to illustrate the application of security measures in child healthcare settings.

Paper Presenter

Payal Khode

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

The Study of Security Issues and Challenges in Big Data with Cloud Environment in Organization

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room A

Authors - Shailesh Gahane, Pankajkumar Anawade, Deepak Sharma
Abstract - A computer system's on-demand accessibility to resources, especially data storage and processing power, is what is simply referred to as cloud computing. Users of cloud computing commonly have access to, use, work on, and change their work while connecting with peers. Big data simply refers to extremely large amounts of data. Using 5V's, the typical data qualities can be explained. Digital security is one of the most crucial elements today. Security is vitally essential when dealing with huge data since it contains private information, code words, and passwords that, if compromised, might have disastrous effects. When contemplating big data and cloud computing, security issues are very crucial. This system's nodes for authentication, encryption, access control etc. may run into a number of issues, including ones involving data storage, transmission, security, processing, and quality. Cloud computing and big data have applications in a variety of industries, including management, finance, Information Technology, etc. Users may work whenever it's convenient for them thanks to cloud computing, and big data delivers expertise and information. Techniques for handling data, whether for analysis, systematically extracting information from data, or in any other way. Collections that conventional data-processing application software cannot handle due to their size or complexity are referred to as big data techniques. This research paper focusing on the various patterns of Big Data, the big data collaboration with Cloud environment and then the data processing in Data Science and discussing the issues and challenges of big data in cloud environment. The proposed objectives of this research is about to know the improve decision making process in organization and real time analytics to gain insights from data as it is generated from outside the world. The data governance policies to ensure data quality and security and usage of machine learning algorithm for data analysis and leverage the big data analytics to enhance customer experience and engagement the challenges in recruiting and retaining skilled big data Analytics or data scientist. The term "Big Data in the Cloud" to extraordinarily huge datasets, possibly numbering in the hundreds of terabytes and petabytes, making it very tough to work with them using a typical database administration system run on a local computer.

Paper Presenter

Shailesh Gahane

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

9:30am IST

An Enhanced Smell Detection Algorithm for Optimized Feature Selection in Cyber Threat Detection

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Arun K, Anilkumar K G, Aji S, Vinod Chandra S S, D Muhammad Noorul Mubarak
Abstract - In the current era, there has been a significant increase in the utilization of digital devices, highlighting the critical importance of securing the data stored within them. Research initiatives are being conducted to enhance the security of these devices. Nevertheless, with the continuous advancement of machine learning algorithms, there remains a demand for more effective and efficient models. The feature selection technique we have proposed, known as the enhanced smell detection algorithm (ESDAM), in conjunction with the CatBoost classifier, significantly enhances the detection of cyber threats relating to intrusion detection and suspicious communications. The datasets utilized include NSL KDD, CICIDS 2017, UNR-IDD, and the CIC Darknet 2020 dataset. The ESDAM method selects the most relevant features from the large dataset, leading to reduced computational complexity, and the CatBoost classifier’s iterative approach ensures consistent and higher performance.

Paper Presenter

Arun K

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Digital Footprints: Navigating the Nexus of Gaming, Sleep, and Social Media on Academic Achievement

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Vinayak Hegde, Darshan T C, Manoj K S, Pallavi M S
Abstract - This study delves into the intricate relationship between extraneous factors and academic performance, focusing on gaming behavior, sleep patterns, and social media usage. A substantial negative association (rho = -0.463, p < 0.001) has been shown between gaming behavior and academic performance using Spearman's Rank association Coefficient analysis, suggesting that excessive gaming may detrimentally impact students' educational outcomes. Similarly, Kendall's Rank Correlation Coefficient analysis demonstrates a substantial inverse relationship (tau = -0.494, p < 0.001) between sleep patterns and academic performance, underscoring the crucial role of adequate sleep in fostering academic success. Furthermore, a Chi-squared Test of Independence uncovers a significant association (χ² = 191.34, p < 0.001) link to academic achievement and social media use, indicating that heightened engagement with social media platforms may adversely affect students' educational attainment. These findings shed light on the multifaceted influences shaping academic performance and underscore the importance of considering factors beyond traditional academic metrics. By recognizing the impact of gaming behavior, sleep patterns, and social media usage, educators and policymakers can implement targeted interventions to support students in achieving academic success while navigating the challenges posed by modern technological environments

Paper Presenter

Darshan T C

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Effective methods of waste management practices in green hotels towards green brand image: An Empirical Study

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Sheela Hundekari, Smriti Khanna, Kamal Upreti, Sonali Gaur, Dolly Kumar, Akhilesh Tiwari
Abstract - The changes in consumer tastes are a significant motivating factor for hotels to adopt environmentally friendly practices. Recently, there has been a significant focus on the perils of climate change and the significance of adopting sustainable practices. As a result, environmentalism now influences almost every consumer decision. With the increasing awareness of environmental sustainability in the hospitality industry, the options for eco-friendly hotels are expanding, providing a wider range of choices for potential customers. Thus, this study seeks to examine the efficient strategies employed by green hotels for trash management to enhance their green brand image. Customer data from hotels was gathered and examined using SPSS 25 software. The findings suggest that implementing energy efficiency measures, promoting water conservation, and adopting sustainable and environmentally conscious building practices are effective approaches to waste management that can improve a company's brand image.

Paper Presenter

Kamal Upreti

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Harnessing the Power of Cloud Computing for Advanced Business and Economic Research

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Virendra Singh Kushwah, Kamal Upreti, Fariyah Banu Jamaluddin Saiyad, Prakash Divakaran, Vandana Mishra Chaturvedi, Khadilkar Sujay Madhukar
Abstract - Cloud computing has surfaced as a significant influence in the domain of business and economic research. Its ability to deliver vast computational resources, scalable storage, and unparalleled accessibility has revolutionized the way researchers analyze complex datasets, conduct simulations, and collaborate on ground-breaking projects. This paper delves into the myriad ways cloud computing is empowering researchers to unlock unprecedented economic insights. This research article delves into the key dimensions of leveraging cloud computing for advanced business and economic research. It investigates the scalability and flexibility of cloud-based infrastructure, enabling researchers to process and analyze extensive datasets, conduct complex simulations, and implement machine learning algorithms for predictive modelling. Moreover, the cloud facilitates real-time collaboration and data sharing, fostering a global research community that transcends geographical boundaries.

Paper Presenter

Kamal Upreti

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

IoT Enabled Smart Agricultural Monitoring And Management System For Sustainable Farming

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Priyanka Devi S, Bharath K R, Bandla Vishnu Swaroop, Daniel Steve Gladson S, Heartlin Maria H
Abstract - In response to the uncertainties facing the future of agriculture, this research addresses the crucial need for sustainable and efficient crop management by introducing an innovative indoor farming system. Positioned as a compelling alternative to traditional outdoor farming, indoor agriculture ensures year-round crop cultivation independent of unpredictable weather and diminishing arable land. The project focuses on overcoming key challenges in vertical farming, such as insufficient monitoring, limited precision, resource optimization, crop health, and the imperative for remote management. The proposed system integrates IoT sensors and advanced remote sensing technologies to enable continuous monitoring of critical parameters like pH, TDS, water humidity, temperature, UV, and FR light exposure in a synchronized manner. This approach not only enhances precision but also promotes sustainability and environmental friendliness. Notably, the incorporation of FR lights and UV light addresses shadowing effects, contributing to improved plant growth within controlled environments. In conclusion, this work offers a comprehensive solution for advancing indoor agriculture, emphasizing sustainability and efficient crop management, with potential implications for the future of global food production.

Paper Presenter

Bharath K R

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Leveraging Deep Learning for Lip Reading: A Comprehensive Analysis

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Gaurav Boob, Somya Maheshwari, Abhishek Jain, R Sreemathy
Abstract - Delving into the realm of automated lip-reading systems, this study conducts a comprehensive evaluation, centering its examination on pivotal components such as audio-visual datasets, feature extraction techniques, classification networks, and frameworks. Through this analysis, significant gaps and shortcomings in existing systems are uncovered. Initially, the study aims to assess the advantages of various architectural approaches, including Attention- Transformers, Temporal Convolutional Networks (TCNs), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). Additionally, it reviews the most recent lip-reading devices available on the market as of early 2023. The goal of this survey is to inform and shape future research in automated lip-reading by shedding light on current approaches.

Paper Presenter

Somya Maheshwari

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Morphed Face Detection

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Kotha Chakradhar, Kotte Thulasi Tharun, Periyavaram Sandesh Kumar Reddy, Sagala Sai Anvitha, Thangam S
Abstract - The increase in digitally altered images creates a big problem for regular face detection systems, as altered faces can easily avoid detection. This study introduces a new method to improve face detection accuracy with altered images using advanced deep learning techniques. Our model uses a selected dataset of altered faces for training and validation. The deep neural network includes YoloV8, CNN, VGG16, RESNET50, and Inceptionv3 to accurately differentiate between real and altered facial features. Test results show the effectiveness of our method, achieving high accuracy. We also compare our approach with current face detection methods.

Paper Presenter

Kotha Chakradhar

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Study on Intelligent Cloud Based Smart E-Health Card for Child HealthCare Management

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Shailesh Gahane, Aastha Dubey, Deepak Sharma, Pankajkumar Anawade
Abstract - This paper provides us with an overview of the most significant security and privacy issues now facing cloud computing (CC), with a particular focus on the issue of confidentiality. Since everything is now connected due to the advancements in computing, these ideas have received extensive study in the literature. Researchers have been concentrating on different ways to implement the concepts of safety and confidentiality in order to address this issue. The most widely used method for guaranteeing the idea of secrecy is called encryption. But encryption alone doesn't provide us more protection regarding to the data in the cloud storage. Utilizing a method and a key, encryption transforms readable text into unintelligible form. Compatibility and distribution of health data systems supporting shared lookouts are planned. Authorized Third Party services and Health Professional Cards form the foundation of the solution. In addition to the DIABCARD workstations' safe management of patient data and chip cards, encrypted communication between the two workstations and associated administrative systems has been put into place. In addition to being utilized both a national ID along with a health insurance card, the smart card chip technology will be incorporated into other cards. In addition, a number of contentious issues are thoroughly examined in order to shed light on the drawbacks of chip-based national ID cards. These issues include issues with databases, privacy invasion and anonymity, information management, insider threats, technological challenges, crime, biometrics, and issues with multipurpose cards. This Study offers a comprehensive overview of significant security and privacy issues in cloud computing, with a specific focus on confidentiality. By addressing encryption methods, smart card technology, and the integration of cloud-based e-health card management systems, the study covers various aspects related to data protection and healthcare management in the cloud.

Paper Presenter

Aastha Dubey

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

The use of Artificial Intelligence and Predictive Data Analytics Approaches and Techniques in AI Driven Modern Applications and Sectors

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Shailesh Gahane, Aastha Dubey, Pankajkumar Anawade, Deepak Sharma
Abstract - This research paper presents the role of data analytics in artificial intelligence. It talks about how data analytics is incorporated in AI. It delves into the realms of data analytics and predictive modelling, elucidating the distinctions between data analytics and data analysis. The process of gathering, organizing, and transforming data in order to produce forecasts and conclusions for well-informed decision-making is known as data analytics. It highlights the transformative role of technology over decades and how predictive analysis aids in modelling future outcomes. Predictive analytics, a focal point of the discussion, involves the use of data to forecast future results. It employs tools, algorithms, and techniques from machine learning, artificial intelligence, and statistical models to anticipate forthcoming trends. The narrative underlines the significance of predictive modelling across diverse industries, including insurance, marketing, finance, sports, and healthcare. It expounds upon supervised and unsupervised predictive models, which respectively involve labelled and unlabelled datasets. The integration of artificial intelligence into predictive analytics is a central theme. The fusion of AI and predictive modelling empowers businesses to comprehend customer behaviour, enhance sales, and optimize decision-making processes. Machine learning's role is highlighted as it enables machines to learn from data and make informed choices. The advantages of AI-driven approaches, such as reduced human error, constant availability, risk mitigation, and innovative breakthroughs, are detailed. The abstract concludes by underscoring the applications of AI-driven data analytics, highlighting how it enables businesses to gain insights, enhance efficiency, predict demand, and ultimately make more informed decisions. These machines can very accurately replicate human skills thanks to technological advancements. The industries that use big data and artificial intelligence (AI) include those that have benefited from the growing demand for smart production that is safe, affordable, and sustainable, as well as from new technical enablers. Finally, through comprehensive studies and conversations, we investigate the importance of AI and the massive towards 4.0 applications. Finally, through comprehensive studies and conversations, we investigate the importance of AI and the Future studies in the field are anticipated to use this work as a baseline. The paper provides a comprehensive overview of the role of data analytics in artificial intelligence, covering various techniques and approaches. The inclusion of applications of AI-driven data analytics offers practical insights into its implementation.

Paper Presenter

Aastha Dubey

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

Unveiling Academic Triumphs: Insights into Student Well-Being and Social Dynamics

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room B

Authors - Vinayak Hegde, Manoj S, Eshwar H S, Pallavi M S
Abstract - The research desire to better comprehend the complex interplay that leads to student success in college and universities is the main motive behind this research where three hypotheses on psychological well-being, social interaction, and academic performance were tested. It was observed, based on Pearson correlation results that there is a positive correlation coefficient of: r = 0.79, p < 0.001 between happiness, as measured by the Oxford Happiness Questionnaire Short Form, and student’s performance. As a result, the null hypothesis was rejected, showing that increased happiness is related positively to higher academic performance. Multiple regression also demonstrates that social support and family time share a positive effect on students’ happiness, as can be seen with factors and their positive coefficients. This confirms our conjecture that social support and family time hint towards better or worse psychological wellness. Finally, using Multi-Layer Perceptron neural network classifier, the model is 79% accurate in discerning academic successes or failures by evaluating past trauma and substance addiction of students. As evident in the confusion matrix, the model can accurately categorize 54 out of 68 observations, with 10 false negatives and 4 false positives. These mathematical representations suggest that the model can be trusted in marking the association between past trauma, substance addiction and academic performance. Overall, the results indicate that student wellbeing and social factors are central to academic outcomes. They also provide a measure of student indicators that can inform the creation of intervention programs to enhance student wellness and academic progress.

Paper Presenter

Manoj S

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

9:30am IST

A Blockchain-based E-Voting System for Secure and Transparent Elections

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Vrinda Ghosh, Himanshu Gupta
Abstract - Blockchain-based e-voting system offers a promising solution to enhance the security and transparency of electoral processes. These systems leverage the inherent properties of blockchain, such as immutability, transparency, and decentralized consensus, to address various challenges associated with traditional electronic voting methods. The use of secure consensus algorithms in blockchain ensures the integrity of the voting process, making it extremely difficult for any single entity to manipulate the results. Additionally, the use of cryptographic techniques in blockchain-based e-voting systems can provide a high level of voter anonymity and privacy protection. Research articles emphasize that the transparency of the voting records in a blockchain-based system can enable voters to independently verify the integrity of the election results, thereby increasing trust in the electoral process. However, the implementation of blockchain-based e-voting systems also presents several challenges that need to be carefully addressed. These include the need to ensure the scalability of the system to accommodate a huge number of transactions, the requirement for fast transaction processing to prevent delays in the voting process, and the necessity to navigate regulatory and governance issues related to the use of this technology in elections. In summary, while the potential benefits of blockchain based e-voting systems are significant, it is essential to address the associated challenges to ensure their security, reliability, and viability in real-world electoral scenarios. Ongoing research and development efforts are focused on overcoming these challenges to realize the full potential of blockchain technology in revolutionizing the electoral process.

Paper Presenter

Vrinda Ghosh

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

A Comprehensive Analysis of Pre-trained NLP Models

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Sanjana Kumari, Nandini Verma, Shailesh Kamble, Praful V. Barekar
Abstract - This paper presents a systematic evaluation and comparison of various pre-trained Natural Language Processing (NLP) models across diverse NLP tasks, encompassing question-answering (QA) and text summarization. Our objective is to discern the most efficient and effective models tailored for specific applications. Through meticulous analysis, we delve into the nuanced strengths and weaknesses of each model, shedding light on their performance metrics. By contributing empirical insights, this research aims to propel the advancement of NLP technology. Our findings serve as a valuable resource for decision-makers, offering guidance in the selection of appropriate models for real-world use cases. Overall, this study bridges the gap between theory and practice, paving the way for enhanced NLP applications across various domains.

Paper Presenter

Sanjana Kumari

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

AES CBC 128 Implementation on Resource-Constrained Platforms:A Case Study on Raspberry Pi and Cortex-M

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Shradha B.Hiremath, Sakshi Heblikar, Manjunath S.Javali, Tejas M, Nalini.C.Iyer
Abstract - In resource-constrained devices such as Raspberry Pi and Cortex-M3, the implementation of AES Cipher Block Chaining (CBC) with a 128-bit key is discussed. It addresses problems like low processing power and memory while concentrating on delivering effective encryption. Trade-offs between power consumption and memory use, algorithmic efficiency, and performance optimization within platform limits are all examined in this study. All in all, it offers information about safely putting AES CBC 128 into practice on low-resource platforms for low-processor scenarios.

Paper Presenter

Manjunath S.Javali

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Beyond DNS poisoning: HTTP/3 Request Forgery through packet Data Tampering

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - B. Shebu, Chungath Srinivasan, Amritha P.P.
Abstract - This paper investigates security vulnerabilities in the HTTP/3 protocol, particularly focusing on client-side request forgery attacks. We analyze different attack vectors, including server initial request forgery and connection migration request forgery, to comprehensively assess the associated risks. Our research employs simulations involving a vulnerable HTTP/3 website to expose potential weaknesses in both the protocol design and its implementation. These findings highlight the critical need for robust security measures to mitigate the threat of request forgery in modern web communication protocols. Notably, this work explores an alternative approach to traditional DNS-based request forgery by manipulating data directly within HTTP/3 packets.

Paper Presenter

B. Shebu

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Customer Segmentation And Purchase Prediction System

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - A.V. Dehankar, Suraj Bangade, Tanay Tijare, Ayush Wankhede, Akash Tidke, Samyak Meshram
Abstract - In the fast-paced world of retail analytics, using data to make important decisions has become a key part of doing well in business. To do data analytics, a lot of expense is encountered. This paper explains a system that helps with customer behavior analysis and prediction. This paper’s principal goal is to create a system that can enhance retail analytics by developing a comprehensive framework for understanding and predicting customer behavior. This involves leveraging advanced analytical techniques to segment customers, analyze their purchasing patterns, and predict churn, to drive strategic decision-making and improve customer satisfaction. The paper proposes a multi-faceted approach, integrating multi-attribute segmentation, visualization of customer data, and customer behavior analysis. Market basket analysis is used for product prediction, while Artificial Neural Networks (ANN) are applied for RFM segmentation and churn prediction that can predict the outcome with an accuracy of 83%. These approaches are made to offer a thorough comprehension of customer segments and their purchasing behaviors, as well as to predict future customer actions and retention.

Paper Presenter

Suraj Bangade

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Enhanced Communication Security: Leveraging Quantum Cryptography

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Saee Desai, Priyanka More, Shubham Deshpande, Harsha Thakur, Vaishnavi Todkar
Abstract - This paper explores the foundations of quantum computing, delving into the principles of quantum mechanics and their application in quantum gate operations. Furthermore, it investigates quantum key distribution protocols, such as the BB84 and E91 protocols, which leverage quantum properties to establish secure communication channels. The paper also examines various cyber- attacks that pose threats to quantum communication systems, including man-in-the-middle attacks and brute-force attacks. The paper proposes a system enhanced by Quantum Key Distribution (QKD), coupled with symmetric encryption algorithms like AES-128, to ensure the confidentiality and integrity of transmitted data. Additionally, the paper presents a literature survey, summarizing recent advancements and challenges in the field of quantum computing and cryptography, emphasizing the importance of quantum key distribution in bolstering communication security.

Paper Presenter

Saee Desai

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Navigating the Future: Indoor Navigation using Augmented Reality

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Abia Merrila Pereira, Arzu Dawood Shaikh, Jane Mellita D’Souza, Cynara Silveira
Abstract - With the growth in architectural intricacy of indoor spaces, individuals encounter challenges in orienting themselves within such spaces which underscores the need for user-centric navigation solutions. Using this application, users can find their way around the grocery aisles to grab what they need, or locate a store within an intricate market by providing the visual guidance through their smartphone. 2-D Visual markers are the core components used in this proposed system which is fueled by augmented reality. Multiple visual markers are scattered within the indoor space which upon scanning relocates the user and assists them using arrows on their screen to their desired destination

Paper Presenter

Abia Merrila Pereira

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Side Channel Analysis And Hardware Implementation Of AES CBC Algorithm On ARTIX A7 FPGA Development Boards

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Shradha B.Hiremath, Sakshi Heblikar, Manjunath S.Javali, Tejas M, Nalini.C.Iyer
Abstract - The increasing importance for data security makes the implementation of encryption methods on platforms with limited resources imperative. The Advanced Encryption Standard (AES) is a popular protocol for sending data securely since it provides different key sizes for different security levels. The implementation of AES Cipher Block Chaining (CBC) with a 128-bit key on systems with limited resources—the Artix A7 FPGA DEVELOPMENT BOARD is the subject of a case study presented in this paper. We ensure efficient encryption while addressing the issues of constrained resources, such as computing power and memory. Our implementation relies on performance optimization within these platforms’ limits. Our study’s findings provide information on how to implement AES CBC 128 on platforms with limited resources, allowing for safe communication in low-processor scenarios.

Paper Presenter

Tejas M

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Trajectory Prediction of Multi-Traffic Agents

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Prajwal Sangalad, Vijeta Chitragar, Prajwal Bolabandi, Prabha C Nissimagoudar, Kaushik Mallibhat, Nalini C Iyer
Abstract - To navigate safely, driving requires engaging with other drivers and forecasting their future actions. This work presents a probabilistic future prediction model that uses a Full-Spectrum single camera to provide an aerial view. The model projects dynamic agent motion and instance segmentation into the future, converting them into statistical trajectories. Our approach involves directly predicting aerial view representations from surrounding Full-Spectrum single camera inputs by incorporating the sensing, integration of sensors, and future projection units within a conventional autonomous driving stack. With no requirement for HD maps, our model, trained on end-to-end video driving data, captures the underlying unpredictable dynamics of the future. It outperforms earlier prediction baselines on the NuScenes dataset in forecasting multimodal future trajectories with an IoU of 59.4% for short (30m x 30m) situations and 36.7% for long (100m x 100m) scenarios. The Video Panoptic Quality (VPQ) values improved as well, reaching 50.2% for short instances and 29.8% for long instances.

Paper Presenter

Vijeta Chitragar

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

Vehicle License Plate Detection Based on Look Only Once and Optical Character Recognition Techniques

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room C

Authors - Aishwarya G, Divya Prasan Karoshi, Laxmi Koutanali, Kaushik Mallibhat
Abstract - The license plate recognition system has emerged as a crucial component in the creation of smart cities, primarily to manage traffic, investigate stolen automobiles, and manage vehicles. The authors in this paper propose a method that consists of the three primary components of license plate recognition. It includes pre-trained model YOLOv8 towards localizing the license plate of the vehicle, cropping the image based on the detected bounding box, and further employing the Optical Character Recognition (OCR) algorithm to identify the characters. Compared to state of art algorithms, the testing results demonstrate 83.65 percent accuracy and faster execution times.

Paper Presenter

Laxmi Koutanali

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

9:30am IST

A Study on Smart Greenhouse Monitoring System Using Blynk IoT Application

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Shailesh Gahane, Gayatri Bhoyar, Sejal Kombe, Deepak Sharma, Pankajkumar Anawade
Abstract - The increasing demand for sustainable agriculture practices has led to the development of innovative technologies to improve crop yield and resource efficiency. One such advancement is the implementation of smart greenhouse monitoring systems. This paper proposes a smart greenhouse monitoring system utilizing the Blynk application, a user-friendly platform for IoT projects. The system integrates various sensors to monitor crucial environmental parameters within the greenhouse, including temperature, humidity, soil moisture, and light intensity. These sensors provide real-time data, which is wirelessly transmitted to the Blynk application running on a smartphone or tablet. Through the Blynk interface, users can remotely monitor the greenhouse conditions and receive notifications/alerts regarding any deviations from optimal parameters. Moreover, the system incorporates actuators for automated control of environmental conditions, such as adjusting ventilation, irrigation, and shading systems. These actuators can be remotely controlled via the Blynk application, allowing users to optimize growing conditions and respond promptly to changing environmental factors. The proposed smart greenhouse monitoring system offers several benefits, including improved crop yield, resource efficiency, and convenience for greenhouse operators. By leveraging the Blynk application, the system provides a user-friendly interface for monitoring and controlling greenhouse operations, thereby empowering users to make informed decisions and maximize productivity. The integration of Blynk IoT application with smart greenhouse monitoring is innovative and promises enhanced efficiency. The inclusion of actuators for automated control adds a layer of convenience and adaptability to the system.

Paper Presenter

Gayatri Bhoyar

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Auto-Insight: An Automobile Strategic Analyser for Customer Insights and Market Positioning

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Bandaru Bhaskar Sai Madhava Krishna, Shashwath Suvarna, Sindhu C, Vadivu G, Pao-Ann
Abstract - Auto-Insight emerges as a trailblazing initiative in the automotive realm, exemplifying the powerful integration and strategic use of classical NLP methods, coupled with the advanced capabilities of Long Short-Term Memory (LSTM) networks. This combination forms a comprehensive and unique approach for the in-depth analysis of customer feedback drawn from car reviews. With the utilization of Python libraries such as NLTK and Pandas, car reviews are subjected to a thorough cleaning and preparation process. This critical step ensures the data's compatibility for complex analysis, laying a strong foundation for subsequent stages. In the initial phase of insight extraction, a dual strategy was implemented. It begins with TF-IDF vectorization and K-Means clustering, systematically categorizing reviews into specific themes like performance, design, and comfort. This method effectively distills key elements from customer feedback. Parallel to this, the project employs the VADER tool from NLTK for sentiment analysis, adeptly classifying reviews across a wide range of sentiments. This two-pronged approach leads to an initial yet profound understanding of consumer opinions and market trends. The innovation of "Auto- Insight" primarily lies in the subsequent phase, where it utilizes LSTM networks. The LSTM model is adept at processing sequential data and capturing long-term contextual dependencies, these networks are trained using the insights gained from the NLP analysis.

Paper Presenter

Bandaru Bhaskar Sai Madhava Krishna

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Comparative analysis of agile software development methodologies: A Literature Review

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Sona Gadani, Urja Mankad, Monica Gahlawat
Abstract - The contemporary realm of software development methodologies is witnessing a significant shift towards agility, with "agile" emerging as a central theme. In contrast to traditional heavyweight approaches, numerous lightweight agile development methodologies have been devised. This study delves into the examination of prominent agile methodologies, including Crystal, Dynamic Systems Development, Feature-Driven Development, Kanban, Scrum, and Extreme Programming. Each methodology possesses distinct characteristics, operational frameworks, as well as advantages and constraints. Through a comprehensive survey and analysis of these methodologies, this paper aims to assist researchers in identifying the most suitable approach for further investigation. Additionally, insights gleaned from current software development statistics contribute to informed decision-making regarding methodology selection. Subsequently, a specific methodology will be chosen for detailed exploration, focusing on identifying relevant key parameters for subsequent research pursuits.

Paper Presenter

Sona Gadani

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Exploring ICT-Based Techniques for Curriculum Enhancement in Primary Schools in India: A Comparative Study

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Kamiya Vats, Harishchandra Singh, Prashant Vats
Abstract - This comparative study delves into the realm of Information and Communication Technology (ICT) to explore its potential for enhancing curriculum-based learning in primary schools across India. With the rapid advancement of technology, integrating ICT tools into education has become increasingly vital. This study evaluates various ICT based techniques, considering their effectiveness in supplementing traditional teaching methods and improving learning outcomes. Through a comprehensive analysis of different approaches, including digital content, interactive learning platforms, and educational software, this research aims to identify the most promising strategies for curriculum enrichment in the Indian primary education context. By examining factors such as accessibility, affordability, and pedagogical suitability, this study offers insights into the challenges and opportunities associated with implementing ICT interventions in primary education settings. The findings of this study contribute to the ongoing discourse on leveraging technology to enhance educational practices, particularly in the context of primary schooling in India.

Paper Presenter

Prashant Vats

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Guarding Privacy in Federated Learning: Exploring Threat Landscapes and Countermeasures with Case Studies

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Jalpesh Vasa, Amit Thakkar, Dev Bhavsar, Pratham Patel
Abstract - Federated learning (FL) emerges as a revolutionary paradigm for collaborative machine learning, enabling training on decentralized, privacy-sensitive data. With its distributed nature, FL holds immense potential in various domains, encompassing healthcare, finance, and smart cities. However, this very decentralization introduces unique vulnerabilities susceptible to diverse attacks. This paper presents a comprehensive analysis of FL, delving into its architecture, applications, and potential attack vectors. This paper investigates a range of attacks, such as poisoning attacks, Sybil attacks, and reconstruction attacks, which pose threats to the integrity of models and the privacy of data within the context of Federated Learning (FL). We propose robust solutions to counter these threats, employing methodologies such as differential privacy, secure aggregation, and adversarial training. Through rigorous analysis and innovative solutions, our study aims to strengthen the implementation of FL while preserving its security and privacy aspects. Additionally, we showcase the diverse applications of FL across various sectors, demonstrating its potential for transformative impact. Ultimately, this paper contributes to a comprehensive understanding of FL, facilitating its secure and ethical advancement in today's data-driven world.

Paper Presenter

Jalpesh Vasa

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Human Sound Detection for Multiple Disease Classification using CNN

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Ezhilazhagan Chenguttuvan, Lakshmi Prabha K, Sakthisudhan K, Nithyadevi S
Abstract - Coughing is a everyday sign of various respiratory infections. The sound and type of coughing are significant features to consider while identifying a condition. Respiratory infections are a global health risk and economic burden, especially in nations with limited treatment options. This study observes the current technology proposing multiple disease classification used to control the impact of respiratory disorders. Artificial Intelligence (AI)-based models have been implemented in the everyday life to identify various diseases using human-generated sounds for example voice, dry cough, and breath. The Convolutional Neural Network (CNN) is utilized to tackle numerous real-world problems using AI devices. We suggested and constructed a Modified CNN to automatically diagnose disease using human respiratory noises like voice, dry cough, and breath. This paper discusses the utmost current difficulties, answers, and chances in respiratory disease recognition and analysis, allowing physicians and investigators to build new strategies that will provide greater accuracy and performance than prior models.

Paper Presenter

Ezhilazhagan Chenguttuvan

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Revolutionizing Contract Execution: Exploring the Promise and Challenges of Smart Contracts on Blockchain Platforms

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Shailender Kumar Vats, Prasadu Peddi, Prashant Vats
Abstract - A lot of attention has been paid to blockchain technology because of its potential to completely transform several sectors, including contract execution. By automating procedures and doing away with the need for middlemen, smart contracts—self-executing contracts programmed directly onto blockchain platforms like Ethereum—represent a fundamental change in the execution of traditional contracts. Removing middlemen and automating procedures, block-chain technology, smart contracts, and self-executing contracts programmed directly onto blockchain platforms like Ethereum transform the way traditional contract execution is carried out. We go over the main features of them, such as decentralization, openness, security, effectiveness, affordability, and related difficulties.

Paper Presenter

Prashant Vats

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Securing the Digital Frontier: Transitioning from Pre-Quantum to Post-Quantum Internet Security

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Shivansh Dhar Singh, Tanay Mathur, Vanshita Verma, Rahul Chhabra, Imran Sayyed, Prashant Vats
Abstract - A meticulous analysis of cryptographic protocols is required as the world of internet security experiences a revolutionary change with the approaching era of quantum computing. The dangers that quantum computing poses to present encryption standards are highlighted in this study piece, which explores the development of security systems from the prequantum to the post-quantum eras. In this transitional period, we examine the dangers and problems that internet security may face and offer a comprehensive examination of cryptographic solutions that are immune to quantum errors. Furthermore, we talk about the consequences for data integrity, secrecy, and authentication, among other areas of internet security. This study advances knowledge about the steps needed to protect our digital infrastructure from the impending age of quantum computing by thoroughly examining the transition from pre-quantum to post-quantum security.

Paper Presenter

Prashant Vats

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

See Through Technology- Virtual Try-On For Spectacles

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Abhishek Magajikondi, Sampath G Meti, Manojkumar, Kaushik Mallibhat
Abstract - The paper proposes a simplified approach towards virtual try-on for spectacle through natural and realistic experiences. The input is captured through a webcam or camera, and the system renders the spectacle onto the user’s face. The virtual try-on for spectacle follows the position of facial landmarks. The experimental results show that the proposed model can provide a natural and realistic experience of a virtual try-on with proper alignment of spectacle. Qualitative and quantitative analysis of the results and their comparison with state of the art is presented in the paper. The performance of the model exhibited training loss of 1.123 and test loss of 1.3850 with MAE 1.8226 and 6.6908 respectively.

Paper Presenter

Abhishek Magajikondi

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

9:30am IST

Towards Enhanced Primary Education: A Framework Proposal for Integrating Active Teaching Methods and ICT to Foster Knowledge Growth

Friday August 9, 2024 9:30am - 11:30am IST

Virtual Room D

Authors - Kamiya Vats, Harishchandra Singh, Prashant Vats
Abstract - This paper proposes a comprehensive framework for advancing primary education by integrating active teaching methods and Information and Communication Technology (ICT) to enhance knowledge acquisition. Recognizing the pivotal role of innovative pedagogical strategies in improving learning outcomes, the framework aims to synergize active learning approaches with the potential of ICT tools. Through methods like experiential learning, collaborative projects, and problem-based learning, complemented by the effective use of digital resources, the framework creates an engaging learning environment conducive to knowledge expansion. Emphasizing teacher training and professional development, as well as the need for supportive infrastructure, the framework seeks to facilitate seamless integration into primary education curricula. By adopting this framework, educators and policymakers can cultivate a holistic approach to empowering primary education, equipping students with the essential skills and competencies for success in the 21st century.

Paper Presenter

Prashant Vats

India

Friday August 9, 2024 9:30am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Friday August 9, 2024 11:15am - 11:20am IST

Virtual Room A

Friday August 9, 2024 11:15am - 11:20am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Friday August 9, 2024 11:15am - 11:20am IST

Virtual Room B

Friday August 9, 2024 11:15am - 11:20am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Friday August 9, 2024 11:15am - 11:20am IST

Virtual Room C

Friday August 9, 2024 11:15am - 11:20am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

11:15am IST

Session Chair Remarks

Friday August 9, 2024 11:15am - 11:20am IST

Virtual Room D

Friday August 9, 2024 11:15am - 11:20am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Friday August 9, 2024 11:20am - 11:30am IST

Virtual Room A

Friday August 9, 2024 11:20am - 11:30am IST
Virtual Room A Goa, India

Virtual Room 7A, Virtual Room A

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Friday August 9, 2024 11:20am - 11:30am IST

Virtual Room B

Friday August 9, 2024 11:20am - 11:30am IST
Virtual Room B Goa, India

Virtual Room 7B, Virtual Room B

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Friday August 9, 2024 11:20am - 11:30am IST

Virtual Room C

Friday August 9, 2024 11:20am - 11:30am IST
Virtual Room C Goa, India

Virtual Room 7C, Virtual Room C

Host Organization Global Knowledge Research Foundation

11:20am IST

Closing Remarks

Friday August 9, 2024 11:20am - 11:30am IST

Virtual Room D

Friday August 9, 2024 11:20am - 11:30am IST
Virtual Room D Goa, India

Virtual Room 7D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Friday August 9, 2024 12:15pm - 12:20pm IST

Virtual Room A

Friday August 9, 2024 12:15pm - 12:20pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Friday August 9, 2024 12:15pm - 12:20pm IST

Virtual Room B

Friday August 9, 2024 12:15pm - 12:20pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Friday August 9, 2024 12:15pm - 12:20pm IST

Virtual Room C

Friday August 9, 2024 12:15pm - 12:20pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Friday August 9, 2024 12:15pm - 12:20pm IST

Virtual Room D

Friday August 9, 2024 12:15pm - 12:20pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Opening Remarks

Friday August 9, 2024 12:15pm - 12:20pm IST

Virtual Room E

Friday August 9, 2024 12:15pm - 12:20pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

A Study of the User Perception on the Role of AI in E-Commerce

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Aswathi S, Vaisakh J, Vignesh A V, Parvathy Venugopal
Abstract - This study explores how users view artificial intelligence (AI) in the context of online shopping. It aims to understand three primary areas: first, how users perceive artificial intelligence (AI) in their e-commerce experience; second, which AI features are most appealing to them; and third, the challenges users face when utilizing AI technology on these platforms. According to the analysis, features like chatbots, AI-powered filtering, and personalized recommendations show promise for improving user perception. This is to user wants for enhanced search capabilities, suggestions, and personalization. These results provide insightful information that e-commerce platforms (like Flipkart and Amazon) can use to improve user experience through smart AI deployment. However, consumer worries about inappropriate recommendations, data privacy, and losing control as a result of unwanted AI features were also noted. Resolving these concerns is essential to establishing confidence and promoting a satisfying user experience. This research allows e-commerce companies to employ AI responsibly by understanding user perception, resulting in positive outcomes for companies and their clients.

Paper Presenter

Vaisakh J

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

An Arduino-Powered Morse Code Encoder and Decoder for Modern Communication

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Advik Narendran, Anantha Hothri, Manyam Yashaswini, Srinidhi Sundaram, Vishwas H.N.
Abstract - In today’s rapidly evolving technological landscape, the utilization of traditional Morse code faces challenges in seamlessly integrating into modern environments, encountering specific difficulties along the way. Acknowledging these limitations, this paper endeavors to overcome these obstacles by proposing the construction of an Arduino-based machine capable of effortlessly converting text into Morse code and vice versa. Leveraging the versatile input/output capabilities of Arduino, this endeavor incorporates a user-friendly interface for text input, thoughtfully complemented by hardware components such as LEDs and buzzers. This holistic approach not only streamlines the translation process but also enhances user interface and educational experiences. Analysis of the data reveals the system’s adeptness in converting text to Morse code and vice versa, ensuring a seamless communication experience for users. Furthermore, through the integration of feedback mechanisms and interactive features like LEDs and buzzers, the system emerges as a potent tool for learning Morse code. Beyond showcasing Arduino’s prowess in addressing communication challenges, this paper offers a glimpse into its potential role in shaping future communication systems.

Paper Presenter

Advik Narendran

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Artificial Intelligence in Talent Acquisition: A Comparative Study

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Aparna Anoop, Devika S Kumar, Gopika S, Vandana Madhavan
Abstract - The digital age has transformed talent acquisition, with many organizations embracing artificial intelligence (AI) to streamline and enhance their recruitment processes. This research study investigates the impact of AI on talent acquisition by comparing companies that utilize AI and those that do not, thereby understanding the reasons for adoption and also examining the inhibitions behind AI adoption. Primary data was collected through in-depth interviews with 20 HR professionals actively involved in recruitment. Purposive sampling ensured participants had relevant experience. This methodology provided a comprehensive look at how AI is being used in talent acquisition practices and the factors influencing its adoption within different organizations and what are the reasons for the under-utilization of AI across various businesses. The results show that the businesses that have adopted AI for talent acquisition have gained benefits from the same and the ones that haven’t incorporated AI into their HR function are because of various reasons including cost, potential bias, data breach threat, etc. Quality of hire, efficiency, time, etc. were the factors that turned out to be good for organizations that use AI.

Paper Presenter

Aparna Anoop

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Blockchain-based Authentication, Authorization and Accounting Mechanisms used for Data Security

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Nilesh T.Gole, Javed Shaikh, Aditya Patil, Nilesh P.Bodne, Priya Nitin Khobragade, Syed Umar
Abstract - The rapid growth of the internet and the telecommunications industry has led to a huge Abstract— In today's world, issues like data breach and identity theft are major concerns. Therefore, every network must have good protection in terms of authentication and authorization. Block chain, a network of distributed systems, is one of the best solutions to these problems. The main features of block chain are the keys it generates and the encryption methods it uses. Here, we propose a block chain-based model that can be used to transfer data across a distributed network with all the relevant problems involved. The encryption algorithm used here is a modified elliptic curve algorithm, it is an algorithm that controls data transfer in the network. Authentication is handled by another encryption algorithm, and this encryption is done before the data is encrypted using the elliptic curve algorithm and the abstracted data is sent to the network. Keywords—Block chain, ECC, Authentication, Authorization, Cryptography

Paper Presenter

Nilesh T.Gole

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Content Marketing, Internet Experience, And Online Customer Review On Housewives’ Purchase Intention On Meesho

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Saaveri B, Sheetal A V, Vaishnavi M
Abstract - In today's technological era, it is basic for organizations, particularly those working on Meesho platforms, to comprehend how online assessments, web encounters, and digital storytelling influence consumers' intention to purchase. With Meesho, a well-known e-commerce location, housewives are the center of this quantitative think about, which looks for to decide the effect of digital storytelling, online encounters, and online client surveys. This quantitative consideration points to exploring the adequacy of story-driven marketing, web involvement, and online client surveys on housewives' buying, eagerly on Meesho, a prevalent e-commerce stage. Through user satisfaction testing, information is being collected through a survey of 131 housewives. A basic fundamental condition and rate investigation are utilized to analyze the information. The study's objective is to reveal the degree to which information marketing, web encounters, and online client audits impact housewives' buying. By analysing these variables, businesses can refine their showcasing techniques, to way better cater to their target group of onlookers and improve client engagement. Marketers within the e-commerce industry may pick up noteworthy data by comprehending the relationship between online audits, information marketing, web encounters, and purchase entomb. The study adds to the existing body of information by uncovering genuine information about the effect of online client surveys, web intuition, and content promotion on Meesho and other comparable platforms.

Paper Presenter

Vaishnavi M

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Design of triangular array antenna for 5G applications

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Smrity Dwivedi
Abstract - In this paper, design and simulation of high frequency antennas for 5G and its scope for extension of 5G have been proposed and investigated. As new era has come in which fifth generation system antennas are being used and several research on this topic still going on to improve its performance up to maximum data rate for the users as their demand of wide bandwidth and high rate of data is increasing as time passes. Here, in this paper, microwave frequency region 3 to 6 GHz has been explored and used for fifth generation systems. FR4 material has been used as substrate formation having capability of operating at both low and high frequency and also copper has been used for base material for design triangular shape array 1x4 structures to achieve high gain. Structure is simulated with the help of CST microwave studio complete ground. Results obtained from these designs are 7.18dBi, 7.22dBi, 7.24dBi and 7.2dBi for all four ports excited separately or simultaneously. The S11 parameter is -19.64dB for frequency 4.135GHz. Similar procedure has been used to simulate the single triangular structure with complete ground with gain of 7.16dBi. This comparison shows about structure durability and enhancement for 5G design. To improve the quality of work many research papers have been read and used to compare the results. Also, all advantages and disadvantages have been discussed by using the results. Here, the bandwidth is increased from 0.29 GHz to 0.32 GHz. Here, a simple structure has been discussed without using any slots and simple ground structure has been taken and discussed in coming sections with simple feeding.

Paper Presenter

Smrity Dwivedi

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Development of Medical Chabot’s Using Aho-Corasick and Siamese-LSTM Algorithm

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Manik Pratapwar, Priyank Shah, Suraj Padia, Sanjay T Gandhe
Abstract - This paper introduces a novel chatbot system designed to aid in the diagnosis of diseases. Leveraging advanced deep learning techniques such as Siamese Long Short-Term Memory, attention algorithm, and the Aho-Corasick algorithm. The core of the chatbot's intelligence lies in its ability to analyze user input symptoms and provide relevant disease predictions. The Siamese LSTM architecture allows the model to effectively capture sequential dependencies in symptom descriptions, thereby improving the understanding of complex symptom patterns. Additionally, an attention mechanism is incorporated to focus on key symptoms and facilitate more accurate disease inference. Furthermore, the Aho-Corasick algorithm is utilized for efficient keyword matching, enabling the chatbot to recognize symptom keywords and extract pertinent information from user queries. The experimental results demonstrate the effectiveness of the proposed approach in disease diagnosis, achieving high accuracy rates and providing reliable recommendations to users. Moreover, user feedback indicates the usability and practicality of the chatbot in assisting individuals with symptom identification and health-related inquiries. Overall, this research contributes to the advancement of intelligent healthcare systems by leveraging advanced deep learning techniques and algorithmic innovations to enhance disease diagnosis and support patient care.

Paper Presenter

Priyank Shah

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Study on Individual Households' Level of Awareness Regarding the Adoption of Solar Panels

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Ananthakrishnan K P, Vivek V V, Sandhya G
Abstract - The research investigates how awareness influences the decision-making process regarding the adoption of panels, in Kerala, India under the Soura initiative. It aims to demonstrate the impact of awareness on individuals’ choices related to panel adoption by conducting interviews and surveys with households. The results indicate that maintenance expenses and limitations in infrastructure are factors affecting adoption rates. Information provided by the government is perceived as influential compared to sources such as media or journalism. The research proposes that policymakers could use this data to optimize the Soura program and improve communication strategies focusing on addressing misinformation and knowledge gaps. Targeted informational campaigns and support services could be developed to promote the adoption of panels. The primary goal is to enhance sustainability in Kerala households by increasing the utilization of energy. The study acknowledges limitations due to the sample size. Suggests that further research may offer additional insights for future planning. Overall this research deepens our comprehension of the factors influencing solar panel adoption. Provides suggestions for enhancing sustainability efforts, in Kerala.

Paper Presenter

Ananthakrishnan K P

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Tabular Deep Learning based light-weight Intrusion detection System for VANET system

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - Javed Shaikh, Vinay Yandrapalli, Nilesh T.Gole, Aditya Patil, Nilesh P.Bodne, Smitta Matte, Syed Umar
Abstract - The rapid growth of the internet and the telecommunications industry has led to a huge explosion of network size and data consistency. Therefore, when VANET grows and grows more and more in terms of transmission speed, network connectivity, security, and safety with the deployment of cutting applications, there will be major changes in wireless communication. In order to prevent external communications from being hacked, this study provides an intrusion detection system (IDS) for VANET that makes use of obfuscation. In this paper we proposed intrusion detection system for VANET which used the Attentive Interpretable Tabular Learning (Tab Net) architecture of deep learning. Tab Net model has characteristics of good interpretability and Fast training speed. we examined the existing machine and Deep learning framework and application in cyber security and VANET and PyTorch-Fast.ai is selected due to it is designed for CPU usage but because of training speed is high we changed data block fetching method from Tabular panda to NumPy array. Finally, from the evaluated metrics, we have proposed the best DNN design suitable for the IDS. With an accuracy of 98.12% and a False Alarm Rate (FAR) of 0.78 %.

Paper Presenter

Nilesh T.Gole

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Two Level Encryption and Decryption using Caeser Cipher and Morse Code with Word Censoring for a Chat Application

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room A

Authors - M.Yagnasri Priya, Samrudhi S.Kamble, Sanjivani P.Shendre, Swetha Sridhar, Vishwas H.N
Abstract - The current day chat applications are used by almost all our devices, they send and receive text messages, voicemail, documents, and images. These messages travel over a network to reach the receiver. The data in these chats require security, and to aid this, encryption of data is crucial. Caeser Encryption and Morse code are such algorithms that provide us with a solution to be able to securely conduct end-to-end transmission of data. This paper focuses on the design and implementation of an encryption algorithm that incorporates both Caeser encryption and Morse code to ensure secure data processing within a computer network environment.

Paper Presenter

M.Yagnasri Priya

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

12:15pm IST

Analyzing User Perception On Voice Ai In Banking And Financial Services

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Anjana Ajith, Kevin C Varghese
Abstract - The purpose of this study is to investigate how users in the banking and financial services industry see Voice Artificial Intelligence (Voice AI). The study investigates user views on Voice AI's usability, security, accessibility, and convenience of use for managing finances by utilizing survey data. The analysis also looks into how much users trust Voice AI for banking functions. The study intends to determine factors impacting user adoption of Voice AI in banking by comprehending these user perspectives. By addressing user issues and encouraging broader adoption, this knowledge can enable banks to create user-centric voice banking services that will influence the direction of financial management using speech artificial intelligence (AI).

Paper Presenter

Anjana Ajith

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

At the Heartbeat of the Smart City

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Vitor Alves, Florentino Fdez-Riverola, Jose Neves, Jorge Ribeiro, Henrique Vicente
Abstract - The evolution of Smart Cities (SCs) underscores the critical need to harmonize technological advancements with the human element. This study probes into the strategies and impacts of boosting inhabitant contentment and the efficacy of services by valuing the emotional and psychological needs of the populace in the digital urban milieu. We assert that the intelligence of a city transcends its technological base to include its attunement to the residents' emotional health. Employing an interdisciplinary lens, merging urban planning and psychological analysis, we scrutinize the ethical collection and incorporation of emotional and psychological data into municipal functions and policymaking. Moreover, are examined both the advantages and possible challenges of this empathetic approach, particularly privacy issues and the necessity for comprehensive frameworks to interpret emotional data or knowledge. One’s research indicates that SCs endeavors that integrate aspects of emotional intelligence cultivate an environment wherein technology amplifies the human experience, culminating in a more encompassing and reactive urban habitat.

Paper Presenter

Vitor Alves

Portugal

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Automatic Pronunciation Analysis Using Artificial Intelligence

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - V. Rajeshram, Abishek R, Ajay Vishwa R, Hemandh M S
Abstract - Automatic Pronunciation analysis (APA) is an innovative language learning tool designed to revolutionize the way individuals acquire and perfect their pronunciation skills. Built upon advanced speech recognition and machine learning technologies, offers a real-time, personalized, and effective solution for learners of all levels. This groundbreaking system operates by capturing the user's spoken language input and meticulously analyzing it in comparison to the desired target pronunciation. Leveraging deep neural networks, acoustic modelling, and phonetic analysis, then can swiftly identify and assess pronunciation errors, enabling users to pinpoint areas of improvement. The APA provides immediate, constructive feedback, highlighting specific mispronunciations and offering visual representations for enhanced learning. Key features of the APA include its adaptability to a wide range of languages and dialects, making it a versatile tool for learners from diverse linguistic backgrounds. It can be integrated seamlessly into language learning applications, e-learning platforms, or used as a standalone tool for self-improvement or by educators and speech therapists. In this survey, explore the APA's architecture, capabilities, and its transformative potential in the realm of language learning and education.

Paper Presenter

Abishek R

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Consumer Perception on The Effectiveness of Chatbots

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Cincy Lucy Abraham, Nidhin V R, Nikhil P Nair, Parvathy Venugopal
Abstract - The study aims to examine user satisfaction with chatbots used for customer service or grievance or, redressal, customer inquiry, focusing on problem solving efficiency, response accuracy, and overall user experience. Additionally, it evaluates the quality of communication and degree of personalization in chatbot interactions as well as how these factors influence consumer trust and perception of company image. The study uses a robust research design that outlines the methods of collecting and analyzing data to answer specific research questions. The formulation of a set of questions for each in depth interview is guided by the research objectives. These questions explore various aspects of chatbot interactions such as problem-solving process, response accuracy, communication clarity, user experience, personalization and influence on consumer trust. The findings obtained from this study provide valuable understandings into the effectiveness of chatbots in customer service roles along with suggestions for improving their problem-solving efficiency and personalization. The balance between scripted, automated and the chatbot’s ability to provide adaptive and personalized interactions are also discussed. This research adds to our knowledge about chatbot interactions and how they affect consumer satisfaction and company image.

Paper Presenter

Nidhin V R

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Generative Artificial Intelligence and Cybersecurity Risks: Issues and Challenges

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Amita Verma, Simran Sankhyayan, Karan Jawanda, Sasha Tandon
Abstract - Generative AI, with its wide range of advantages, has not only transformed the workings of the world but also proved itself as a hallmark of the digital revolution. Generative AI has found applications across various domains, from image and text generation to drug discovery and music composition. However, along with its potential benefits, generative AI also poses significant ethical concerns, including the potential for misuse and the perpetuation of biases present in the training data. Therefore, it is crucial to consider the risks and benefits of this technology. The intersection of generative AI and cybersecurity presents a complex landscape fraught with legal issues and technical challenges. The generation of synthetic data by AI models may inadvertently violate privacy laws, facilitate new ways of cyberattacks, raise questions about consent, anonymization, and data ownership. Detecting and mitigating threats stemming from AI-based content present formidable technical challenges for cybersecurity professionals. Traditional methods of threat detection may prove ineffective against sophisticated AI-generative attacks. Effectively navigating these challenges requires collaboration among policymakers, legal experts, technologists, and other stakeholders to develop comprehensive frameworks that promote innovation, protect individual rights, and safeguard against emerging cyber threats. Ethical development and deployment of generative AI systems requires a holistic approach that prioritizes transparency, accountability, and societal well-being. By addressing these issues proactively, we can harness the transformative potential of generative AI while ensuring a secure and resilient cyber landscape for the future.

Paper Presenter

Simran Sankhyayan

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

HD Map Generation with LiDAR using Open Source Framework

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Ritesh Vernekar, Ashok S. D., Raghuttam P. B., Nalini C. I., P.C.Nissimagoudar
Abstract - This study employs the Velodyne VLP-16 LiDAR sensor alongside the LeGO-LOAM algorithm to generate high-definition (HD) maps. Known as LeGO-LOAM HD, our approach focuses on accurately estimating the posture of objects in real-time across different environments. Lightweight nature of our architecture enables efficient posture evaluation on low-power embedded systems. LeGO-LOAM HD effectively utilizes the ground plane for point cloud segmentation and optimization, effectively eliminating noise and identifying planar and edge characteristics. To modify the posture with six degrees of freedom between consecutive scans, a twostep Levenberg-Marquardt optimization strategy is employed. Comparative tests have proven that LeGO-LOAM HD delivers reliable outcomes while demanding less processing power. This system has been seamlessly integrated into a SLAM framework designed to cater to various mapping applications. By introducing a customized strategy, this research contributes to the field of autonomous navigation and mapping, enhancing the creation of high-definition maps even in challenging conditions.

Paper Presenter

Ritesh Vernekar

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

IOT for digital product passport system in India

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Deepshikha, Avinav Krishna
Abstract - The purpose of the Digital Product Passport (DPP) is to offer standardised "track and trace" data on a product's origin, composition, possibilities for repair and disassembly, and management at the end of its useful life. In addition to supporting a low-carbon transition by advancing a circular economy, the DPP seeks to remove current barriers including communication gaps. The DPP has the ability to push decisions towards sustainable development by giving relevant information about a product to various actors, including waste management firms and consumers. This information can be given to consumers during the procurement and utilisation phase of the product, and to waste management units during the disassembly and recycle or reuse phase. In this paper we discuss an IOT based system in context of India since EU nations are pursuing DPP with great concern. Possible challenges and expert reviews have also been discussed.

Paper Presenter

Deepshikha

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Metaverse learning landscapes: Unrevealing training and development patterns through Bibliometric and content analysis

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Suruchi Pandey, Rajesh Chandwadkar
Abstract - Metaverse is emerging technology evolution, touching human species in immersive way through virtual with real world interactions. Metaverse applications are gaining popularity in various industries and academic fields, including marketing, art, design, manufacturing, analytics, training, and development. This study provides a prospective on uses of Metaverse for training and development within human resource management function of companies. Organizations need effective ways for skills enhancement for its workforce to ensure sustainability of its resources in sync with business needs. The study explores the emerging trends in training and development using the metaverse based technologies. In this review paper bibliometric and content analysis methods were used. In this study a total of 293 articles and 20 case studies were explored in the field of metaverse application in training and development. This comprehensive analysis provides insight into latest trends in researcher community as well the industry practitioners working in the field of Metaverse. .

Paper Presenter

Rajesh Chandwadkar

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Smart Traffic Analyser Using Deep Learning

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Vijay Khare, Vidhi Gupta, Lakshya Agarwal, Ramit kumar
Abstract - In today's rapidly changing world the number of vehicles is increasing along with the population. Large flow of automobiles causes traffic congestion especially due to poor traffic management. Traffic jams not only leads to significant time wastage for commuters but are also economically expensive in terms of fuel consumption and environmental hazards. Many recent studies have shown how traffic jams increase stress levels and thus can have negative psychological impacts. Therefore, our proposed system, which is a real-time vehicle counting model is integrated with traffic signal control systems to optimize traffic flow which helps to potentially achieve more efficient traffic management, reduce congestion, and enhance overall transportation operations.

Paper Presenter

Vijay Khare

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Unique Land Parcel Identification Number (ULPIN) (Bhu-Aadhaar) in Land Records

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room B

Authors - Seemantinee Sengupta, D.S.Venkatesh, Ganesh Khadanga, Sunish Kumar, Shanmuga Sundari.S, Surendranath Karupothu, Saurav Chaudhary, Deepak Chandra Misra
Abstract - The Digital India-Land Records Management Programme (DILRMP) has been given top priority by the Indian government. Approximately 98 million land parcels are distributed across 6.54 lakh revenue villages in the country1. Conclusive land titling is becoming more and more important, thus it is now essential to give each plot a Parcel ID in order to identify it clearly and uniquely. Other nations (the US, Europe, etc.) have also started similar parcel-pixel connection projects. In order to facilitate the same, the Department of Land Resources (DoLR) (https://dolr.gov.in) requested NIC to devise a scientific approach for developing a formula or algorithm. It is anticipated that the following concept and algorithm will be practically implementable in our nation based on NIC's experience in the development and maintenance of land records and cadastral map management software, across the states. This flagship initiative includes the Unique Land Parcel Identification Number (ULPIN). Based on the land parcel's longitude and latitude coordinates, the identification is made possible thorough surveys and georeferenced cadastral maps. NIC's cadastral mapping software BhuNaksha uses the geo-referenced revenue village shape file to generate the ULPIN based on the Electronic Commerce Code Manufacturers Association (ECCMA) guidelines. A land parcel is assigned a 14-digit identifying number. It has undergone extensive testing on agricultural land parcels of diverse sizes, forms, and geometries. This work presents a scientific attempt to create a unique identifier for an agricultural land parcel using the parcel's geo-coordinates while also adhering to established international standards and best practices for land management worldwide.

Paper Presenter

D.S.Venkatesh

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

12:15pm IST

Analyzing The Customer Sentiments Towards Hybrid Cars

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Anaswara Murali, Ananthakrishnan P, NRM Shaliq, Dhanya M
Abstract - The prices of fossil fuels used in vehicles are increasing day by day along with that there is a growing concern towards environment safety. People have started looking for more sustainable options. This research was intended to find out the view of customers of hybrid cars in India. Techniques like reviewing previous literature and using machine learning algorithms to do the analysis of online reviews of hybrid vehicles were done. Environmental safety, cost effectiveness, and societal views were the influencing factors for them to purchase hybrid cars. In spite of all these, the consumers of hybrid vehicles in India care mostly about the amount they spend, the quality, and the performance of these vehicles. The availability of charging places was also a concern. Two thousand online reviews Indian hybrid car user reviews were taken and most of them were positive suggesting a positive sentiment towards hybrid cars. With the sentimental analysis and word cloud analysis, consumer perception could be found out and they include quality, efficiency, safety, and comfort. This information can be useful for companies as well as other stakeholders in making consumers purchase hybrid cars in India and adopt them better.

Paper Presenter

Anaswara Murali

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Automatic Subjective Assessment using Natural Language Processing and Machine Learning

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Sherin Mariam George, Narendrasinh C Chauhan
Abstract - Around the globe, the assessment of subjective answer plays an important role in the education system. This assessment helps to evaluate the performance of a student to a certain extent. However, there are a few shortcomings to the conventional human evaluation method, which makes it less practical. The manual evaluation, though essential, is a bit tiresome and time consuming task. Currently we have a reliable system for automatically assessing objective answers. Over the years, researchers are putting their efforts on automatic assessment of descriptive answers. But this research is still at its infancy. In this research work, we demonstrate the use of natural language processing and machine learning techniques for the automatic subjective assessment. We demonstrate and compare semantic similarity measures. The available pre-trained deep learning models like sentence transformers are used in this research. Finally, we have developed regression models and demonstrated performance of the proposed approach.

Paper Presenter

Sherin Mariam George

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Deep Learning for Breast Cancer Classification: A Comparative Study of pre-trained CNN Models

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Aneri Pandya, Nesh Rochwani, Rudra Patel, Hemant Yadav, Nirav Bhatt
Abstract - A total of 2.3 million cases of breast cancer are discovered globally each year, making it one of the top causes of fatalities for women. Early diagnosis and intervention are critical for improving patient outcomes. There are several ways to classify breast cancer. There's been a recent spike in interest in deep learning algorithms for the classification of breast cancer because of their superior prediction accuracy over traditional techniques. This work uses a dataset with two classes of pictures to train several pre-trained CNN models. The models underwent processing utilizing several hyperparameters. With the greatest accuracy of 99.99%, the Xception transfer learning model outperformed the others.

Paper Presenter

Aneri Pandya

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Efficient Text Summarization with Hierarchical Neural Auto-Encoders

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Shreyas Unnibhavi, Nishant Deshpande, Srinivas Surpur, Satish chikkamath, Nirmala S R, Suneeta V Budihal
Abstract - The study focuses on enhancing text summarization techniques. Summarization is a key preprocessing step that aids in the extraction of essential features from the text. This helps to understand whole content in less time. The purposed model employs LSTM(long short term memory) network. LSTM is more handy in capturing conceptual information. A hierarchical LSTM is more efficient in capturing and preserving the data than that of standard LSTM. The three components of the model being an encoder, decoder and funnel network. funnel network connects the components to flow the information. Text preprocessing is important forensuring the quality and cleanliness of the input data. The model aims to enhance the text summarization methodologies and improved representation of textual information. Transformer model is used for extracting the text. Category Cross-entropy is a way for the computer to measure how different is the predicted summary from that of the actual summary sparse represent each target word in the main text with an integer index corresponding to its position in the vocabulary. Sparse category crossentropy is the loss function in this model. Optimizer used in this model is root mean square propogation.

Paper Presenter

Srinivas Surpur

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Fake Signature Detection

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Juhi Nathani, Smit Madhani, Ishika Khokhani, Parag Patel, Shanthi Therese S.
Abstract - Forgery of signatures remains a prevalent issue in various sectors such as banking, legal, and governmental agencies, leading to significant financial losses and legal complications. Many properties of a signature may vary even when two signatures are made by same person. So, detecting a forgery becomes a challenging task. Hence the proposed solution detects fake signatures using VGG-16 for properties extraction and Convolution Neural Network for signature verification process thus building an automated system which accurately detects whether a handwritten signature is real or forged.

Paper Presenter

Juhi Nathani

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Heart Disease Prediction Using Different Different Machine Learning Approaches

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Akash Kumar Sinha, Geddam Varahagiri, K. Suresh Babu, Vikram Neerugatti, Santhosh Boddupalli, J Somasekar
Abstract - Machine learning algorithms are essential for deriving actionable insights and forecasts from large datasets in the big data era. This study explores the field of machine learning by examining how various algorithms are applied and performed on a particular dataset. The goal is to determine which machine learning algorithms produce the most accurate and dependable results by comparing how well they handle the complexities of the provided dataset. Heart disease is a major cause of morbidity and death as well as a major global health concern. Preventive healthcare relies heavily on the early identification and precise prediction of heart diseases. In the field of medicine, machine learning techniques have proven to be effective tools for diagnosing and predicting a wide range of illnesses, including heart diseases. This study explores Heart Diseases through the application of Artificial Intelligence and Machine Learning (AIML) techniques, with a particular emphasis on a large dataset that offers priceless insights into this important subject.

Paper Presenter

Akash Kumar Sinha

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Securing Data Beyond Encryption: A Comprehensive Review of Steganography Techniques

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Aditya Deepak Kadam, Siddhi Subhashsing Pardeshi, Abhiram Rajesh Joshi, Rupesh Chandrakant Jaiswal
Abstract - The rise of communication technologies and open channels like the internet has simplified data transfer, but also increased vulnerability to security breaches. Encryption secures data during transmission, but once decrypted, it's exposed. Steganography offers an alternative by hiding secret messages within digital media (images, text, audio, video) without revealing their existence. This paper offers a critical review of steganography, analyzing the different Techniques and their effects on the different steganographic parameters. This article also includes detailed algorithms for the most prominent steganographic techniques, providing a comprehensive overview of their implementation and operation.

Paper Presenter

Aditya Deepak Kadam

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Securing Health Data With Blockchain

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Priti Bhise, Vaishnavi Kshirsagar, Neha Rathod, A. A. Bidkar
Abstract - With the rapid digitization of healthcare systems, Electronic Health Record (EHR) management has become crucial for efficient healthcare delivery. Traditional EHR systems face challenges related to security, interoperability, and trustworthiness of data. Block chain technology offers a promising solution to address these challenges by providing a decentralized and immutable platform for EHRs system. This survey paper explores the landscape of block chain-based EHRs systems, examining various approaches, architectures, and applications in the healthcare domain. Key areas of examination include the secure storage of EHRs on block chain, ensuring integrity of the data and confidentiality while granting patients greater dominance over their health information. The paper discusses the integration of block chain with EHRs systems, exploring different consensus mechanisms, data models, and encryption techniques used to ensure the integrity and privacy of patient records.

Paper Presenter

Neha Rathod

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Sentiment Analysis on Indian Stock Market Using StockTwits Tweets: A Machine Learning Approach

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Ruthvik Reddy Gaddam, Rutvik Nelluri, Dandu Samir Varma, Sagar Basavaraju
Abstract - The movement of a stock can be known by following the news about the company from various sources. One of the largest sources of this is social media, where many discuss various stocks and how the stock price may change based on their analysis. Using these sources of information one can try to classify the movement of a stock as bullish or bearish in nature. Data consisting of tweets from StockTwits mainly about Indian stocks is selected and gathered. The tweets are mainly taken from the IT and Banking sectors as they are volatile even for a slight change in the market and more people tend to buy these stocks. Most recent research in the analysis of stock trends is centered around sentiment analysis. By using natural language processing techniques and sentiment analysis models, data from Stocktwits can be processed and used to train machine learning models to classify them and help traders make more robust decisions. From analysis, it is found that the Artificial Neural Network has performed better with an accuracy of nearly 80% which is backed up by classification done on newly gathered data from Stocktwits where 8 out of the 10 tweets were correctly classified. The Random Forest model has been trained with an accuracy of 70%. The results obtained from this analysis are found to be on par with other research work in this domain.

Paper Presenter

Dandu Samir Varma

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

Text-Driven Image Synthesis: Optimizing Prompts with ChatGPT in DF-GAN Framework

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room C

Authors - Karan Chopra, Vatsal Mehta, Jayu Jain, Gayatri Joshi, Shanthi Therese
Abstract - The goal of this project is to increase the quality of the images generated using textual description by combining DF-GAN with ChatGPT. Initially, we experimented with GAN on MNIST dataset, and then we tried stackedGAN on Oxford-102 datasets. Unfortunately, these approaches had issues such as sub-par image quality and long training times. So, we moved onto DF-GAN with CUB & COCO dataset and saw the impact of better user prompts on improving image generation. A key development in this project is the integration of ChatGPT into the backend to improve prompt quality. By using ChatGPT, we can create more nuanced & contextually relevant prompts that significantly improve the expressiveness & accuracy of the images generated. The evaluation process includes metrics like sharpness & noise to provide an evaluation of the image quality that adds some value. In addition, the user-friendly interface using Streamlit improves accessibility, allowing a wider range of users to interact with our image generating model. This project develops as a systematic analysis of different GAN architectures and dataset combinations. It provides an extensive approach for advancing text to image generation, with an emphasis on practical usability.

Paper Presenter

Jayu Jain

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

12:15pm IST

A Framework for QoS-Driven Radar Resource Management in V2X Communication Networks

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Srinidhi S Kulkarni, Kushal B Kokatnur, Shamshuddin K, Suneetha V B
Abstract - Effective resource management is critical for optimizing the performance of multifunction phased array radar (MPAR) systems in dynamic environments. This example explores a quality-of-service (QoS) optimization approach for MPAR surveillance resource allocation across multiple search sectors. Traditionally, resource management in MPAR systems focuses on maximizing radar performance metrics like cumulative detection range. However, with the emergence of Vehicle-to-Vehicle (V2V) communication networks, there is a growing need to integrate radar surveillance with communication functions. This example addresses this challenge by developing a resource management scheme that balances radar resources between surveillance tasks and V2V communication requirements. By considering the unique characteristics of both radar surveillance and V2V communication, the proposed approach aims to enhance situational awareness and safety in complex environments. Through numeric optimization techniques, the allocation of power-aperture product (PAP) to each search sector is optimized to maximize QoS, leading to more efficient and effective MPAR surveillance in integrated radar-communication systems.

Paper Presenter

Srinidhi S Kulkarni

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

A Review on the 3D Reconstruction of Objects from Multiple 2D Images

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Mohan K. Warbhe, Purva Chaudhari, Palash Gourshettiwar, Prateek Verma, Swapnil Gundewar
Abstract - The development of 3D reconstruction technology in recent years has been nothing short of revolutionary, changing the way we interact with digital content, view spatial surroundings, and approach challenging problems in a variety of industries. This research explores the extensive applications of 3D reconstruction in a variety of domains, including as engineering, architecture, healthcare, entertainment, environmental monitoring, cultural heritage protection, and scientific research. In the medical domain, complex 3D reconstruction techniques provide medical practitioners with accurate anatomical models that aid in diagnosis, surgical planning, and patient-specific therapy planning. Similar to this, in engineering and manufacturing, quick prototyping and simplified product design procedures promote creativity and increase competitiveness internationally. Immersive 3D reconstructions are a vital tool for sustainable development initiatives and educated decision-making in urban planning and architectural visualization. In the meanwhile, efforts to preserve cultural heritage use 3D reconstruction to share and preserve historical artefacts, enhancing learning opportunities and promoting cultural awareness. The entertainment sector uses 3D reconstruction to create breath-taking visual effects and immersive settings that push the boundaries of gaming and storytelling. Furthermore, by improving resource management, disaster planning, and conservation activities, improved reconstructions are essential to environmental monitoring and disaster response operations. The progress made in 3D reconstruction is driving forward societal trends and igniting the development of novel technology across a range of industries. By realizing its potential, we may foster a more dynamic environment, advance progress, and unleash the potential of creativity.

Paper Presenter

Purva Chaudhari

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Enhancing Attendance Tracking Efficiency with RFID-based Smart Attendance Management System (SAMS)

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Rachit Mahajan, Aryan Singhal, Prashant Vats
Abstract - In recent times, Radio Frequency Identification (RFID) systems have seen a surge in applications across various sectors including transportation, healthcare, agriculture, and hospitality. These systems utilize electronic tags and readers to enable wireless identification. This paper focuses on utilizing RFID technology to address the persistent issue of tracking lecture attendance, particularly prevalent in developing nations. By implementing RFID for student attendance monitoring, this study aims to eradicate the inefficiencies associated with manual attendance collection. Moreover, it provides educational administrators with real-time classroom data for accurate attendance scoring and informed decision-making. This innovative approach not only saves time but also enhances the management of educational resources.

Paper Presenter

Prashant Vats

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Explainable AI Solutions for Emotion Understanding in Autism Spectrum Disorder

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Ayain John, S.Santhanalakshmi
Abstract - Emotions serve as a unique psychological mechanism through which individuals communicate their subjective experiences of both their interactions with the external world and their internal state. Emotions are crucial in daily life and communication between individuals. They can be conveyed through different channels and in various forms, including facial expressions, physical movements, body posture, physical reactions, and speech patterns. The authors employed MOD_DHGN (Modified Deep Hour Glass Network) techniques to detect Autism Spectrum Disorder (ASD) in a grouped image with less sampling. The MOD_DHGN shows that it is capable of detecting emotion in images of autistic faces through augmentation and preprocessing. This study is unique because it constructed a system that uses facial emotion pictures from an extensive database, only targeting the distinct facial expressions of those affected by this condition for ASD-related emotion detection. Extensive testing revealed that the method's emotion detection accuracy was 92% in MOD_DHGN, 88% in DCNN, 72% in VGG-16, and 55% in RestNet classifiers.

Paper Presenter

Ayain John

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Facial emotion recognition: Review and Perspectives

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Gobind Kumar, Mandeep Kaur, Ritika Dhaneshwar
Abstract - A facial emotion recognition system enables a computer to read people's feelings by looking at their faces. Due to enhancements in the field of facial expression detection, machines can now recognize and interpret a wide range of human emotions by merely examining the facial expressions in photos or videos. This technical innovation has enormous potential in various domains such as marketing research, security systems, and helping people with autism understand social signs. An in-depth review of recent advances in facial expression identification is presented in this paper, focusing specifically on the contributions of deep learning techniques in identifying both macro and micro-expressions. A critical analysis of various available datasets is also presented, contrasting datasets gathered in naturalistic environments with those acquired in controlled laboratory settings. The study also highlights the necessity for ongoing innovation in algorithm development and the incorporation of multimodal techniques to improve accuracy and resilience. The present study will facilitate researchers in exploring facial expression recognition as a technological instrument with a broad range of applications, and provide future directions for research.

Paper Presenter

Gobind Kumar

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Investigating the Efficacy of Gradient Boosting for Skin Type Classification

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Pratiksha Limbulkar, Shagun Gupta, Pooja Gawade, Kumkum Saxena
Abstract - In today's world, maintaining a healthy skin has become a priority for many individuals. Glowing and clear skin is considered to be a reflection of a healthy person. People explore and try a wide range of skin products to achieve clear, smooth, better-looking skin but often end up choosing the wrong ones due to lack of knowledge about their own skin. We’ll explore the intriguing realm of skin type classification using different machine learning algorithms in this paper. Our approach uses advanced techniques like Random Forest, Support Vector Machine, Ensemble methods like Stacking, Bagging and Boosting to classify skin types as dry, normal and oily through image analysis. Our research aims at examining the performance of various algorithms on our personalized dataset which contains a variety of data images divided into dry, normal and oily. After performance evaluation, Gradient Boosting surpasses all other algorithms by achieving maximum accuracy and precision, highlighting its importance in cosmetic and dermatology industry.

Paper Presenter

Pratiksha Limbulkar

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Performance Evaluation and Comparison of LANMAR and LAR1 Routing Protocols using QualNet

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Siddhi Ove, Piyush More, Prem Chikode, Vedant Badade, Shravani Kamthankar, Rupesh Jaiswal
Abstract - Routing protocols are pivotal in determining communication network efficiency and reliability, particularly in mobile-ad-hoc networks. LANMAR (Land-mark Routing)- and LAR1 (Location-Aided Routing) are two notable protocols in this domain, each offering distinct approaches to route discovery and maintenance. In this research, we conducted an in-depth comparative simulation study between LANMAR and LAR1 routing protocols using QualNet software. The primary aim was to assess and contrast their performance across essential metrics such as packet total packet enqueued, carried load Broadcast, Average Jitter Broadcast, and Originated Carried Load. Through extensive simulations performed under varied network scenarios and traffic conditions, we analyzed the behavior and efficacy of both protocols. The results obtained offer valuable intuition into the pros and cons of LANMAR and LAR1, aiding network designers and researchers in selecting the most appropriate routing protocol for specific MANET applications. This research provides to a thoughtful analysis of LANMAR & LAR1 routing protocols' performance in MANETs, enabling informed decision-making for network deployments and protocol enhancements. This research not only shows the relevance of routing protocols in contemporary networking but also highlights the critical role of QualNet in advancing the field of network simulation.

Paper Presenter

Siddhi Ove

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Prognostic Predictions in Lung Diseases using Convolutional Neural Network and Attention Mechanism

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Vivekanand Thakare, Shailendra S. Aote
Abstract - Prognostic predictions play a crucial role in guiding clinical decision-making and optimizing patient care pathways in lung diseases. The innovative perspective has been proposed here using a Hybrid Convolutional Neural Network (CNN) architecture with an integrated Attention Mechanism for prognostic predictions in respiratory diseases. Leveraging the rich spatial information encoded in chest computed tomography (CT) images, our model aims to accurately predict disease progression, severity, and treatment outcomes across a spectrum of lung diseases, including lung cancer, COVID-19, chronic obstructive pulmonary disease (COPD), tuberculosis (TB), and pneumonia. The Hybrid CNN architecture combines convolutional layers for feature extraction with attention mechanisms for focusing on informative regions and features within the CT images. The evaluation has been performed on our model with the available dataset using CT scan as well as X-ray images diagnosed with various lung diseases. The results demonstrate the efficacy of our approach in achieving high accuracy and precision in prognostic predictions, with promising clinical implications for finalizing treatment tactics in order to improve patient outcomes. Our study especially focuses on Hybrid CNN with Attention Mechanism of deep learning techniques, in advancing prognostic assessment and clinical decision-making in pulmonary medicine.

Paper Presenter

Vivekanand Thakare

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Tool For Ground Personnel Monitoring

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Madhura Santosh Chavan, Aditya Dilipkumar Wagh, Pranjali Umesh Padole, Anirudha Dharmendra Singh, Sarita Rathod
Abstract - The project is dedicated to the creation of a mobile application tailored to the specific needs of organizations and industries that rely on the real-time tracking and geofencing of their ground personnel. This application offers a vital tool for both field workers and administrators, enhancing safety, efficiency, and situational awareness. Ground personnel, including construction workers, security staff, and emergency responders, can be accurately tracked using GPS-enabled devices or smartphones, ensuring their safety and providing improved operational visibility. Administrators have the ability to define and manage geofences, enabling the efficient management of work zones and critical areas, with the application sending alerts when personnel inside or outside these designated zones. The application's robust user management system empowers administrators with the ability to efficiently manage user accounts, assign personnel to specific geofences, and oversee the entire monitoring ecosystem. This feature simplifies the allocation of task areas, facilitates resource management, and enables responsive decision-making by administrators. Overall, this project can achieve the well-being of ground personnel engaged in vital tasks.

Paper Presenter

Aditya Dilipkumar Wagh

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

Voluntary Carbon Markets: Bridging Climate Solutions Through Sustainable Finance

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room D

Authors - Akshita Bipin, Abhinav Satish Pillai, Jerush John Joseph
Abstract - Voluntary Carbon Markets (VCMs) enable companies and individuals to offset their carbon footprint by acquiring carbon credits from programs that decrease or eliminate emissions, such as renewable energy or forest conservation activities. As climate change mitigation becomes more prominent on corporate and investor agendas, voluntary carbon markets provide a framework for channeling funding towards emissions-reduction operations. The threat of climate change necessitates immediate action, pushing Sustainable Finance to the forefront. Carbon offsetting appears as an intriguing but contentious option in this changing ecology. It enables entities to compensate for their greenhouse gas emissions by funding programs that reduce emissions elsewhere. However, worries about the integrity of some offsets remain, emphasizing the need for strong standards and verification systems. This includes aligning lending, insurance, and investment agendas with sustainability objectives such as the Paris Agreement. As the global economy undergoes structural transformations to meet climate targets, sustainable finance invests in VCM projects to direct funds towards programs that reduce carbon emissions, boost renewable energy use, and support sustainable practices. This linkage strengthens the financial sector's role in combating climate change while also promoting economic growth and resilience. Integrating VCMs into sustainable finance strategies improves transparency and accountability in carbon offsetting methods, ensuring that investments contribute to emissions reductions and environmental benefits. This conceptual study seeks to contribute to a thorough understanding of the collaboration between VCMs, sustainable finance, and climate action emphasizing the significance of collective action in companies and individuals achieving environmental sustainability and minimizer by the effects of climate change.

Paper Presenter

Abhinav Satish Pillai

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

12:15pm IST

A Review on the Applications of Cyber security in IoT– Integrated Robotics

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Mohan K. Warbhe, Prateek Verma, Swapnil Gundewar, Amit Gudadhe
Abstract - IoT-Integrated Robotics is the fusion of Internet of Things (IoT) technology and robotics that transforms robotics system by improving their usefulness through seamless connectivity. The integration of sensors, actuators, connectivity, data processing, and automation is a crucial element that facilitates real-time data interchange and cognitive decision-making. Applications promise efficiency and adaptability in complicated circumstances, ranging from smart manufacturing to healthcare robotics. Robotics finds its applications in various domains nowadays such as national security, industry 4.0, healthcare and defense. Strong cyber security is required in critical industries like manufacturing, transportation, and healthcare because failures can affect patient safety, production efficiency, and transportation safety in addition to causing data loss. Frameworks, authentication techniques, block chain technology, network security solutions, and cloud security measures are all part of the current cyber security strategies. But it is imperative to anticipate potential future dangers, such as worries about the increased attack surface, risks associated with 5G, environmental hazards, issues related to quantum computing, and vulnerabilities in human-machine interfaces. The establishment of cyber security frameworks is essential and recommended to be set up for optimal use of IoT integrated robotics to avoid any kind of cyber-attack. To ensure the continued growth and stability in the field of IoT-Integrated Robotics, proactive measures, adaptability to new threats, and stakeholder cooperation are essential as the technology advances.

Paper Presenter

Mohan K. Warbhe

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Envision – AI and Blockchain Transforming Disability Employment and Entrepreneurship

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Mrunmayi Parker, Aditya Surve, Nahush Patil, Priyal Jain, Kumkum Saxena
Abstract - Disabled people possess great skills in various domains but struggle to find opportunities due to their condition. There are not a lot of solutions that focus on this problem. Therefore, “Envision” solves this issue by acting as a unified solution to promote employment and entrepreneurship among disabled people. “Envision” helps in searching for jobs that are meant for disabled people. Further, it allows users to prepare for interviews, create resumes, and connect with industry experts through mentorship sessions. It also has a blockchain-powered marketplace that enables users to pitch their business ideas to potential investors while maintaining secure transactions through blockchain technology. This helps to create a secured and validated platform to maintain the legitimacy of the information provided on the website.

Paper Presenter

Aditya Surve

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Expanding the Catalogue of Code Smells in Multi-Language Systems: Definition, Consequences, Detection, and Empirical Analysis

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Md. Shahrukh Ansari, Salman Abdul Moiz
Abstract - In software development, it’s common to employ multiple programming languages within a single project, known as multilingual development. While this approach offers significant advantages such as legacy integration and performance optimization, integrating code from different languages can introduce code smells that negatively impact the overall readability, maintainability, and performance of the systems. These issues are known as multi-language code smells, and although several studies have identified various code and design smells related to multi-language systems, the catalog of these smells is not exhaustive. This paper introduces two new code smells, namely, Language Envy and Cross-Responsibility Declaration, for multi-language systems. It also proposes a mechanism to detect these smells and evaluates their presence in open-source projects. The results indicate that 9% of non-native methods, which call a native method, exhibit the Language Envy code smell, while 37% of the classes that declare at least one native method suffer from the Cross-Responsibility Declaration code smell.

Paper Presenter

Md. Shahrukh Ansari

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Leveraging Text-to-Image Generation Models for Automated Creative Processes in Corporate Marketing

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Sharmila Sengupta, Gauri Nagral, Meera Sawantdesai, Kritika Yadav, Yashraj Mulwani
Abstract - In this day and age, advertisements play a huge role for businesses to flourish in competitive economies. It is said that an attractive ad is worth more than a thousand words. Creating an advertisement involves conceptualizing an idea, designing visual and textual content, and strategically placing it across media platforms to reach and influence the target audience. This entire process can take anywhere from a few hours to several months, depending on the complexity and medium of the advertisement. However, the tremendous growth in technology can turn those hours and months into just a few seconds. This paper explores the capabilities of Generative Artificial Intelligence (GenAI) for visual element generation through advanced techniques like text-to-image generation. It analyzes leading models like StackGAN, Stable Diffusion - DreamBooth, and LoRA, identifying the most efficient among them. The research then focuses on implementing these models to automate advertisement creation for product-based companies, aiming to replace manual efforts in the creative department while maintaining privacy and security of proprietary company information. The proposed system, ADGenAI offers insights into the transformative potential of GenAI in streamlining creative processes, fostering efficiency, and envisioning the future of the advertising industry. Specifically designed to alleviate the pressures faced by creative teams, such as the demand for high-quality content under tight deadlines, this system enhances creativity and productivity by automating the initial stages of ad production and enabling the exploration of new advertising concepts with minimal resource investment.

Paper Presenter

Gauri Nagral

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Potato Plant Leaf Disease Detection Using Customized Deep Learning

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Deepak Mane, Palaash Padman, Aditya Narsale, Nikita Supekar, Koushal Patil
Abstract - The significance of plants as a primary energy source for humanity cannot be overstated. However, the susceptibility of plant leaves to diseases at any point between sowing and harvesting poses a significant threat to crop production and market value. Detecting these leaf diseases is pivotal in agriculture, but conventional methods demand substantial manpower, time, and an in-depth understanding of plant diseases. In response to these challenges, machine learning along with image processing emerges as a promising solution for disease detection in plant leaves. Here, we proposed customized deep learning model to thoroughly analyze potato plant leaf data, categorizing it into predefined sets. The classification process considers structural features and properties such as color, intensity, and dimensions of the plant leaves. Leveraging machine learning enables a more streamlined and accurate identification of diseases across various plant species. The proposed model offers a comprehensive overview of potato plant diseases and explores customized deep learning classification techniques applied in disease identification. By synthesizing these approaches, the study contributes to the development of automated systems for potato plant disease detection, addressing the limitations of traditional methodologies. This study stands out for its innovative combination of deep learning method with image processing to tackle the complexities of identifying diseases in potato plant leaves. The proposed model improved the overall detection process, offering a more efficient and dependable solution compared to traditional techniques. The proposed model using CNN given an accuracy of 99.6%, generated using 2173 images from the standard dataset.

Paper Presenter

Deepak Mane

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Systematic Access for Layer 7 Attacks and Mitigation

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - V. Ramakrishna, P.M.S.S. Chandu, S. Vaithyasubramanian, Y. Immanuel
Abstract - Layer 7 DDOS attacks - At layer 7, the DDOS attack is the most devastating. It will bring down the organization’s servers. DoS is an automated attack that makes websites (servers) and applications unavailable. Cyber attackers will make most Dos attacks to make the system down. DDoS attacks multiple attackers will target one system. Attackers will send requests more than the application server can handle so that genuine users can’t get access. Distributed denial of service (DDoS) will cause application downtime and server crashes so legitimate users/traffic can’t access web applications. DDoS is used to break the reputation and brand of a business.

Paper Presenter

V. Ramakrishna

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Unmanned Aerial Vehicles (UAVs) for High-Altitude Human Detection: A Review and Prospects

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Shaswat Bhardwaj, Vyom Agrawal, Prashant Vats
Abstract - This research paper presents a comprehensive utilization of Unmanned Aerial Vehicles (UAVs) in disaster response, leveraging the YOLOv8 (You Only Look Once) object detection model for real-time human identification. The UAVs, equipped with this state-of-the-art model, efficiently capture and transmit images of human subjects to a ground station, serving as a centralized hub for further analysis. This human detection system significantly enhances situational awareness during search and rescue operations, contributing to quicker response times in disaster-stricken areas. Additionally, our UAVs are outfitted with devices designed to extend WiFi signals, thereby establishing a robust communication network in disaster zones where traditional infra-structure may be compromised. This dual-functionality approach, integrating advanced computer vision and communication technology, represents a holistic solution to the challenges faced in disaster management, positioning UAVs as versatile tools for responsive and efficient disaster response systems. This framework serves as a foundational structure, laying the groundwork for the development of more dependable, swifter disaster event detection, and energy-efficient disaster management systems based on UAV networks.

Paper Presenter

Vyom Agrawal

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

12:15pm IST

Virtual Question Answering (vehicle to vehicle security)

Friday August 9, 2024 12:15pm - 2:15pm IST

Virtual Room E

Authors - Ishan Rai Agarwal, Sahil Dhanani, Shikha Mundra, Ankit Mundra
Abstract - Vehicle-to-vehicle (V2V) communication technology advancements have changed traffic safety and efficiency recently. It has improved traffic flow and significantly reduced the risk of accidents by exchanging real-time information about their surroundings. This work offers a distinctive study which uses computer vision and natural language processing to give a ground-breaking analysis of Visual Question Answering (VQA), which improves inter-vehicle communication security. For experimentation and analysis we have created a small dataset and conducted rigorous testing to demonstrate the effectiveness of VQA in improving V2V communication and authentication by adopting multimodal features such as text and images. In order to learn multimodal features, recent deep learning networks like Visual Transformer and BERT is adopted. Overall, it is observed that even in contexts with limited resources, our findings highlight the potential of VQA to strengthen networked vehicles against new security threats.

Paper Presenter

Ishan Rai Agarwal

India

Friday August 9, 2024 12:15pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Friday August 9, 2024 2:00pm - 2:05pm IST

Virtual Room A

Friday August 9, 2024 2:00pm - 2:05pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Friday August 9, 2024 2:00pm - 2:05pm IST

Virtual Room B

Friday August 9, 2024 2:00pm - 2:05pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Friday August 9, 2024 2:00pm - 2:05pm IST

Virtual Room C

Friday August 9, 2024 2:00pm - 2:05pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Friday August 9, 2024 2:00pm - 2:05pm IST

Virtual Room D

Friday August 9, 2024 2:00pm - 2:05pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

2:00pm IST

Session Chair Remarks

Friday August 9, 2024 2:00pm - 2:05pm IST

Virtual Room E

Friday August 9, 2024 2:00pm - 2:05pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Friday August 9, 2024 2:05pm - 2:15pm IST

Virtual Room A

Friday August 9, 2024 2:05pm - 2:15pm IST
Virtual Room A Goa, India

Virtual Room 8A, Virtual Room A

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Friday August 9, 2024 2:05pm - 2:15pm IST

Virtual Room B

Friday August 9, 2024 2:05pm - 2:15pm IST
Virtual Room B Goa, India

Virtual Room 8B, Virtual Room B

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Friday August 9, 2024 2:05pm - 2:15pm IST

Virtual Room C

Friday August 9, 2024 2:05pm - 2:15pm IST
Virtual Room C Goa, India

Virtual Room 8C, Virtual Room C

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Friday August 9, 2024 2:05pm - 2:15pm IST

Virtual Room D

Friday August 9, 2024 2:05pm - 2:15pm IST
Virtual Room D Goa, India

Virtual Room 8D, Virtual Room D

Host Organization Global Knowledge Research Foundation

2:05pm IST

Closing Remarks

Friday August 9, 2024 2:05pm - 2:15pm IST

Virtual Room E

Friday August 9, 2024 2:05pm - 2:15pm IST
Virtual Room E Goa, India

Virtual Room 8E, Virtual Room E

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Friday August 9, 2024 3:00pm - 3:05pm IST

Virtual Room A

Friday August 9, 2024 3:00pm - 3:05pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Friday August 9, 2024 3:00pm - 3:05pm IST

Virtual Room B

Friday August 9, 2024 3:00pm - 3:05pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Friday August 9, 2024 3:00pm - 3:05pm IST

Virtual Room C

Friday August 9, 2024 3:00pm - 3:05pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Opening Remarks

Friday August 9, 2024 3:00pm - 3:05pm IST

Virtual Room D

Friday August 9, 2024 3:00pm - 3:05pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Comparative Analysis of Multilabel Emotion Recognition in Music

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Avni Uplabdhee, Vaishali Singh, Palak Jain, K.R Seeja
Abstract - Emotions are inherently complex, and music has the remarkable ability to evoke multiple emotions simultaneously in listeners. Traditional methods of emotion detection, which focus on recognizing single emotions, may not adequately capture this richness and complexity in music. To address this challenge, a comparative analysis has been conducted to compare and analyze various multilabel emotion detection classifiers. These classifiers include RAKeL, multi-label backpropagation, Binary Relevance (BR), Two-Label Relevance (2BR), Label Powerset, ranking pairwise comparison, and calibrated label ranking classifier. The primary objective of this study is to evaluate and compare the effectiveness of these classifiers in detecting multiple emotions concurrently in music. By assessing their performance across different datasets and scenarios, we aim to identify the strengths and weaknesses of each classifier in handling the complexity of emotional expression in music. By examining how each classifier handles various musical elements such as tempo, key, instrumentation, and lyrical content, we can gain deeper insights into the nuances of emotional expression in music. Through this comparative analysis, insights can be gained into which classifiers are better suited for capturing the nuanced interplay of emotions present in music. This knowledge can inform the development of more sophisticated and accurate emotion detection systems, ultimately enhancing our understanding and appreciation of the emotional impact of music.

Paper Presenter

Avni Uplabdhee

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

An Analytical Overview Of Sustainable Strategies Of Hindustan Unilever And Samsung Electroniics In Business Sustainability

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Rita Ghial, Diksha Pundir, Rajinder Kaur, Karan Jawanda
Abstract - Sustainable development has emerged as buzzword in today’s global discourse amongst environ-mentalists, politics, corporate world, in media and elite masses. To be sustainable, development must possess both economic and ecological sustainability. It has become an imperative for businesses operating in globalized and integrated world. Business entities are gradually more recognizing the significance of social consideration and welfare into their administrative functioning as a strategic business decision. This research paper explores the contributions of business sectors to the sustainable development of the economy. Sustainable development obliges business entities to set their priorities and take initiatives in the implementations of the SDGs catering to the diversity in global markets. Further this paper examines the strategies of big business industries to achieve the goals of sustainable development with special reference to Hindustan Unilever and Samsung Electronics Ltd. The main object of the paper is to find out that whether the engagement of the SDGs and the prioritizing these goals differ across the business entities.

Paper Presenter

Rita Ghial

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Attribute-Driven Overlapping Community Detection in Complex Networks

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Venkata Siva Naga Sai Mohan Vennam, Jagadananda Tharaka Boora, Vishal Reddy Mudiyala, Hemanth Balla, Deepthi L R
Abstract - Community detection on attributed networks has gained attention due to its ability to reveal complex relationships by considering topological and attributed features. Real-world networks generally have multiple attributes leading to overlapping memberships across communities. This paper proposes an Attributed Overlapping Community detection (AttrOverlapComm) algorithm that can effectively detect overlapping communities by combining the information from node attributes and the network topology. This problem is relevant as it has applications in various domains, including social network analysis and recommendation systems. The experiments are conducted on real-world datasets to validate the proposed approach’s effectiveness across diverse network structures and attribute characteristics.

Paper Presenter

Venkata Siva Naga Sai Mohan Vennam

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Exploring AI's Impact on the Apparel Industry: A TCCM Framework Analysis

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Vinay S, Navaneeth R S, Nair Rohit Muralidharan
Abstract - This study investigates the dynamic landscape of artificial intelligence (AI) applications in the apparel industry using the comprehensive Theory-Context-Characteristics-Methodology (TCCM) framework. Motivated by the increasing adoption of AI technologies in apparel manufacturing and retailing, we aim to provide a structured analysis of relevant literature. The background of the research stems from the growing importance of AI in enhancing efficiency and decision-making processes within the apparel sector. We contextualize our study within the broader framework of AI adoption trends in the industry. Employing the TCCM framework offers a systematic approach to exploring AI applications, guiding our selection of dimensions for analysis. These dimensions include manufacturing processes, production planning and control, retailing, supply chain management, and customer behaviour modelling.

Paper Presenter

Nair Rohit Muralidharan

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Implementation of Edtech Platform

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Tejas Methawade, Rujul Nipane, Rajas Doshi, Nilesh Nirmal
Abstract - This research paper explores the transformative impact of EdTech platforms on education, scrutinizing their evolution, key features, applications, benefits, challenges, and future prospects. Investigating the past, present, and future of EdTech, the study aims to provide a comprehensive understanding of its profound influence on teaching, learning, and educational administration. Emphasizing both the revolutionary changes witnessed in recent years and the ongoing efforts shaping the future of education, this paper offers valuable insights supported by concrete results. The research contributes to scholarly discourse by presenting a nuanced examination of how modern technology is reshaping traditional educational methods, with implications for a new era of learning. This work aligns with the rigorous standards of Scopus indexed journals, presenting findings that contribute to the broader academic conversation on educational technology.

Paper Presenter

Tejas Methawade

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

IOT based Smart Monitoring of Sandalwood Plant

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Prathamesh Dhulam, Prashant Gosavi, Sandesh Darekar, Yashraj Oza, D.S. Jadhav
Abstract - Sandalwood is an economically valuable tree crop grown for its fragrant heartwood used in pharmaceuticals, cosmetics and religious ceremonies. Optimizing the yield from sandalwood plantations is vital but challenged by the dependence on various interconnected environmental factors like temperature, soil moisture and nutrition. This paper surveys past research on smart IoT-enabled systems to monitor sandalwood crop health and machine learning models for predictive yield analytics. The real-time data insights from sensors tracking soil humidity, ambient temperature, leaf-wetness and other parameters correlated with tree growth empower data-driven interventions. Advanced machine learning algorithms, especially deep neural networks, show potential in effectively modelling the complex multivariate interactions between climatic conditions, soil properties and sandalwood yields. However, challenges remain in building representative labelled sandalwood datasets from sensors, maintaining reliable field sensor networks, and accurate multivariate time-series forecasting of yields. Further research to create robust IoT architectures coupled with deep learning predictive models is imperative for realizing precision sandalwood agriculture to improve farmer incomes and industry growth.

Paper Presenter

Prathamesh Dhulam

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Material Twins for Sustainable Interiors: A Data-Driven Approach to Building Finish Optimization

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - P M Vishnu, Drisya Murali, Suresh M
Abstract - The research paper investigates the diverse aspects affecting the data-driven and material twin approach to achieve sustainable interior and building finish optimization. Through an extensive review of existing literature and insights gleaned from experts in the field, the study aims not only to identify but also to comprehensively analyze the critical factors that influence the process of material twin the materials that need to be replaced from the database based on their parameters. The research uses Grey Influence Analysis (GINA) to reveal and quantify the complex connections among these identified factors. This methodology offers a detailed understanding of how these factors interplay and impact one another within the context of bringing material twin of interiors to make it sustainable and optimized from the database on components used for building finish. The primary goals include pinpointing the most impactful factors and evaluating their strengths in shaping the study. Employing GINA enables the study to precisely identify the primary factor steering the system and gauge its level of influence. The outcomes of this research hold substantial significance for policymakers, industry practitioners, and stakeholders by providing crucial insights to enhance sustainable practices within the building finish. Ultimately, this contributes towards establishing a more efficient and seamless use of sustainable interiors with more efficiency.

Paper Presenter

P M Vishnu

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

Pneumonia Detection With Super Resoluted Chest X-Ray Images Using Vgg16

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Pritee Parwekar, Kushagra Gupta, Archita Sharda, Balraj J Pachorkar, Aryan Arora
Abstract - This project aims to improve the detection of pneumonia by using Convolutional Neural Networks (CNN) with Generative AI (SRGAN), providing a solution to the global health concern of inaccurate and delayed diagnoses. Our aim is to create an accurate model that efficiently detects pneumonia in medical images. Pneumonia diagnosis is challenging due to the limitations of existing methods, which struggle to identify intricate patterns in chest X-rays, leading to misdiagnosis. We suggest using Convolutional Neural Networks (CNNs) to solve this problem. CNNs are a powerful deep learning method that have shown impressive results in identifying images. VGG16 Architecture is used for better accuracy. By leveraging CNNs, we can increase the precision of pneumonia diagnosis and reduce the number of misdiagnoses, ultimately leading to better patient outcomes. Accuracy of the Model is increased with the use of SRGAN. SR is the supersampling of low-resolution images to higher resolution while minimizing information distortion. We follow a specific methodology that involves gathering and preparing a wide-ranging chest X-ray dataset. Automated diagnostic tools have the potential to revolutionize pneumonia detection, providing a valuable resource for healthcare professionals.

Paper Presenter

Archita Sharda

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

The Green Evolution: Transforming Supply Chains for a Sustainable Future

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Levin K Antony, S Ritheesh Sriram, Amala Siby
Abstract - The paper analyses systemic, multi-stakeholder effort required to overcome continual challenges. Proactive solutions that prioritize supplier collaboration and transparency, aided by emerging technologies and public-policy guidance, can drive the necessary sustainability transformation. The required sustainability change can be initiated by proactive solutions that place a high priority on supplier collaboration and transparency, supported by new technology and recommendations from public policy.

Paper Presenter

Levin K Antony

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

The Systematic Review of Indoor Autonomous Navigation

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room A

Authors - Kartik Pathak, Sakshi Kaushal, Amita Chauhan
Abstract - The realm of autonomous navigation stands at the vanguard of technological progress, witnessing the integration of robotics, drones, and vehicles endowed with the capability to independently perceive, interact with, and traverse dynamic environments. Autonomous navigation systems have permeated various industries, ushering in transformative changes in logistics, manufacturing, healthcare, and agriculture. The comprehensive overview delves into recent research within autonomous navigation, illuminating the remarkable advancements and untapped potential in the swiftly evolving domain. The studies span an array of autonomous systems, spanning ground-based robots to aerial drones, and leverage cutting-edge technologies, including advanced sensor fusion, path planning algorithms, machine learning, and deep reinforcement learning. Significantly, research breakthroughs feature Lidar-based Rao-Blackwell Particle Filters, elevating localization and path planning proficiency in indoor environments, as well as online decision-making algorithms tailored for autonomous robot navigation. The vision-based navigation for UAVs and the infusion of deep learning techniques to augment navigation, object detection, and avoidance constitute pivotal areas of exploration. As the field continues its trajectory of evolution, the collective insights encapsulated in the overview emerge as a valuable resource for researchers and developers along with the challenges and opportunities.

Paper Presenter

Kartik Pathak

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room A Goa, India

Virtual Room 9A, Virtual Room A

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Detailed Exploration of the Security Issues in Educational Applications

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Rushin Bhatt, Kaushal Shah
Abstract - In an era dominated by digital technologies, because of the integration of computer systems and online platforms used by academic institutions likes schools, it is vitally important that sensitive data has to be safeguarded in a dynamic environment. This review article focuses on the complex landscape of network security in the education sector, offering a practical solution to prevent cyberattacks. As part of our study, we have created an Entity-Relationship (ER) diagram that shows how stakeholders in the education sector are related, and how they interact with each another. We will be exploring the use of advanced cryptography algorithms as well, for enhancing security measures. Our aim is to provide educational institutes with a comprehensive understanding of security considerations, enabling them to implement strong security measures for the safety of all stakeholders- students, teachers, and administrators. Through this exploration, we contribute to establishing a robust digital foundation for the education sector.

Paper Presenter

Rushin Bhatt

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Brain Tumor Detection using Extreme Learning Machine

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Shantala Giraddi, Prema Akkasaligar, Bushra Mthaigar, Pritam Shetty, Sneha Biradar, Sridhar Shetti
Abstract - This study presents a new method for brain tumour detection employing the Extreme Learning Machine (ELM) algorithm, focusing on medical imaging. The approach emphasizes image pre processing to enhance significant features and minimize noise before inputting them into the ELM-based classifier which is known for its fast learning and efficient data handling because of its single hidden layer, the ELM algorithm outperforms previous methods, as evidenced by multiple trials on publicly available data. The system demonstrates high accuracy, sensitivity, and specificity, making it suitable for real-time applications in medical imaging. This advancement has the potential to improve computer-aided diagnosis systems by enabling early and reliable identification of brain tumors, thereby enhancing patient care.

Paper Presenter

Bushra Mthaigar

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Detection of Age-Related Macular Degeneration using Machine Learning and Deep Learning: A Systematic Review

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Priyanka Gulhane, Himangi Pande
Abstract - The Eyes are highly developed sensory organ of human body. In fact, major part of brain is dedicated to the functions of eyesight than those of other sensory organs. According to WHO almost 285 million people are visually impaired [1]. Approximately 8.7% of visual impairment is caused by ARMD [1]. Retinal images have achieved a vital role in detection and diagnosis of various eye diseases like DR, Macular hole, Age-Related Macular Degeneration, Cataract, Glaucoma etc. These diseases are primary cause of blindness and vision impairment in India. These diseases can cause severe conditions like blurred vision, vision loss or photophobia. Ocular diseases symptoms are not shown in early stage and they are not diagnosed till advanced stage. Age-related macular degeneration is the popular eye disease that mostly affects the elderly population having age above 50 years. ARMD is responsible for blurring the central vision of an individual. Many eye abnormalities are prominently visible in retina than any other part of the human eye. Growing number of retinal disease patient, hospital expenses and shortage in no. of ophthalmologists are barriers to attain recommended screening in the patients who are at the risk of retinal diseases.

Paper Presenter

Priyanka Gulhane

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Enhanced Online Proctoring: Leveraging Client-Side Deep Learning

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Devesh Bedmutha, Purva Bapecha, Digambar Chaure, Piyush Bora, Rachna Karnavat
Abstract - This paper presents the implementation of an online proctoring system designed to operate entirely on the client side, addressing the inherent challenges associated with server-side processing in existing exam portals. By shifting the processing tasks to the client side, our system aims to alleviate the burden on servers and reduce network dependency, while ensuring robust face detection and suspicious activity detection capabilities. We have used siamese technique for face verification and MobileNet Model for object detection. Additionally, We have developed a custom browser extension that will detect and disable flagged extensions during the exam. Our system also has the support of a variety of question types including coding, subjective and multiple-choice (MCQ) questions. Through our implementation, we aim to enhance the efficiency, cost-effectiveness, and security of online exam proctoring, offering a solution that minimizes server load and maximizes performance by leveraging client-side resources

Paper Presenter

Piyush Bora

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Enhancing Spam Email Classification through Ensemble Learning, SMOTE Oversampling, and Hyperparameter Tuning

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Gayatri Joshi, Soham Joshi, Vatsal Mehta, Kumkum Saxena
Abstract - Emails have become a centre for a large user base, leading it to be a platform for reaching large crowds with minimum effort and enabling an effortless spread of information to larger audiences. But on the downside, it has also led to an increase of user traffic in email, which also consists of some unwanted marketing and promotion-related emails. Several users' private data is being extracted, and such superfluous emails are sent which are largely known as spam. The paper aims to combat the problems by making use of different machine learning approaches. Despite the multitude of available classifiers to build classification models for an imbalanced dataset, the main task was to reduce the bias of the majority class. This paper aims to restructure the imbalanced nature of the dataset and apply different machine learning algorithms, like Support Vector Machine, Random Forest, Multinomial Naive Bayes and XGBoost. In addition to this, the paper also compares between different ensemble techniques used. Not only does this avoid erroneous categorisation of legitimate emails as spam, but also provides insightful knowledge to rectify imbalanced dataset problems. It underscores the potential of using different methods to enhance the accuracy and combating the problem.

Paper Presenter

Vatsal Mehta

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Health Monitoring for Parents Away: A Wearable IoT Solution for Rural and Urban Areas

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - D.S. Jadhav, Avinash Andhale, Avinash Padale, Anjana Auti, Neha Bokfode, Supriya Mane, Avinash Golande
Abstract - This research introduces an extensive health monitoring solution designed for parents or elderly family members, addressing the challenges of separation due to work. The proposed system is structured into three key stages: hardware, cloud, and a React Native-based mobile application. In the hardware phase, various sensors (MAX30102 for pulse rate and SpO2, DS18B20 for temperature) are intricately connected to the ESP8266 microchip. Utilizing the Arduino IDE, the microchip enables seamless communication, efficiently collecting health data. The ESP8266 WiFi module in the second phase establishes robust communication with Thingspeak cloud, enhancing data comprehensibility through graph visualization on the Thingspeak website. The system ensures data security with a unique API key. In the final phase, meticulously processed data is transmitted to a React Native mobile app, supporting Android platforms. The app features a user-friendly interface with login, signup, and a main home screen displaying health data through a circular progress bar. Abnormal readings trigger push notifications, prompting timely investigation of potential health issues, such as elevated heart rate indicating a possible heart attack. The integrated system provides a secure and user-friendly platform for remote health monitoring, ensuring caregivers receive timely alerts regarding their loved ones' health concerns. The system's combination of hardware, cloud, and mobile application promotes peace of mind and facilitates swift intervention, contributing to an elevated level of care and well-being. The system architecture includes three layers: device layer (ESP8266, MAX30102), cloud layer (data processing and storage), and web app layer (real-time data visualization and alerts). The methodology involves data collection by ESP8266, transmission to Thingspeak cloud via API, and real-time monitoring through the web application.

Paper Presenter

Avinash Andhale

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Image Restoration for Heritage Places Using GAN

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Tarang Boharupi, S. Poonkuntran
Abstract - Preserving the cultural heritage of iconic landmarks is paramount in maintaining their historical significance. This research focuses on the restoration of damaged images of the Mysore Palace, a heritage site of immense cultural importance. A dataset comprising 171 real and damaged images of the palace, captured with a OnePlus mobile device, forms the basis of this study. The proposed methodology leverages an inpainting technique to generate mask images, which are subsequently utilized in the training of a Generative Adversarial Network (GAN). The GAN architecture is employed to learn the intricate patterns and details necessary for reconstructing the damaged portions of the images. The training process resulted in a model with a PSNR (Peak Signal-to-Noise Ratio) value of 16.5 and SSIM (Structural Similarity Index) of 0.023. The outcomes of this research showcase the efficacy of the developed GAN model in restoring damaged images of heritage structures. The achieved PSNR value indicates a notable improvement in image quality, while the SSIM metric reflects the preservation of structural details. The study contributes to the field of image restoration, especially concerning heritage conservation, offering a novel approach that can be extended to safeguard other cultural landmarks.

Paper Presenter

Tarang Boharupi

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Makara App: A Case Study in Digital Innovation for Enhanced Agricultural Productivity and Sustainability

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Ramesh Guntha, Aiswarya A, Soham Adla, Maya Presannakumar, Mario Alberto Ponce Pacheco, Saket Pande
Abstract - The agricultural sector, particularly in rural areas, faces numerous challenges including labor shortages, fluctuating costs, and unpredictable weather patterns. The Makara app emerges as a pioneering digital solution, specifically designed to address the multifaceted needs of small-scale farmers. This paper presents a case study on the Makara app, highlighting its role in transforming agricultural practices through digital innovation. The app provides a comprehensive platform for farmers to manage their land, crops, and financials effectively. It offers detailed land and crop management, budgeting, and activity management. Additionally, Makara's day-to-day advisory service and risk prediction module assist farmers in optimizing resource use and enhancing productivity. The app's multilingual interface and offline mode ensure accessibility and usability in remote areas. This study analyzes the software development, farmer engagement, feedback collection, software refinement, and deployment process of the Makara app among the select farmers of the Nagpur region in Maharashtra, India. The Makara app exemplifies the potential of digital tools in promoting sustainable and profitable farming practices in rural communities.

Paper Presenter

Ramesh Guntha

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Mineworkers Fatigue Detection Using Machine Learning based Techniques

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - Samuel Nghidengwa Nakale, Fungai Bhunu Shava, Gloria Iyawa
Abstract - Employee fatigue is one of the major risk factors across different industries. Consequences of fatigue include injuries and fatalities which in turn affect employee productivity and results in various economic and social costs. Artificial Intelligence (AI) especially Machine Learning (ML) techniques have been used to develop data driven solutions for fatigue monitoring and detection in various industries. However, the fatigue detection systems proposed in literature were predominantly evaluated on simulated data which may not capture some of the real-world driving conditions like in the mining environment. This study deploys three ML classifiers (Support Vector Classifier, Random Forest Classifier and the K-Nearest Neighbor Classifier) to investigate the performance of ML based fatigue detection systems for drivers in the mining industry. The proposed system is implemented in Python and evaluated on a simulated dataset, the Yawning Detection Dataset (YawDD), and a real-world mining operation dataset. All three models achieved a fatigue prediction accuracy above 90% for both datasets. The major challenge to developing behavioral based fatigue detection systems for real world setting like the mining environment is face detection accuracy which is affected by factors such as low image resolution due to poor and variable lighting conditions, face orientation to camera and proximity of face to the camera. The significant contribution of this study is the use of real-world dataset to evaluate the performance of ML based fatigue detection models.

Paper Presenter

Samuel Nghidengwa Nakale

Namibia

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Technology's Green Revolution: Advancing Sustainability in Industry and Society

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room B

Authors - MARTIN H MOLLAY, Deepak Sharma
Abstract - With an emphasis on sustainability's environmental, economic, and social aspects, this literature review critically investigates the complex relationship between technology and sustainability. It summarizes the body of research to offer a thorough grasp of the application of sustainable technology practices, their influence on various industries, and their wider consequences for preserving the environment and reducing the effects of climate change. This component examines how initial investment costs, ongoing operating costs, and possible returns on investment can be used to analyze how sustainable technologies can reduce costs over time. The necessity for a comprehensive strategy that balances economic growth, ecological preservation, and social well-being is underscored by key results that stress the significance of incorporating sustainability principles into technology breakthroughs. The review emphasizes the importance of using renewable energy sources, energy-efficient improvements, afforestation and reforestation programs, sustainable land management practices, and sustainable manufacturing practices to reduce climate change and promote environmental preservation. This study, which synthesizes the body of literature already in existence, highlights research gaps and essential areas of interest, providing guidance for future studies and valuable takeaways for stakeholders such as corporations and governments. The results demonstrate how vital technology is to achieving sustainability goals and stress the importance of teamwork in tackling global issues like climate change and environmental degradation. The present literature review adds to the recent knowledge and its offers a vivid synopsis of the relationship between technology and sustainability. It also illuminates prospective directions for further investigation and real-world implementations across multiple industries.

Paper Presenter

Martin H Mollay

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room B Goa, India

Virtual Room 9B, Virtual Room B

Host Organization Global Knowledge Research Foundation

3:00pm IST

Advanced User Interface for Cardiovascular Risk Forecasting using Artificial Neural Network

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Shyam Desai, Shridhar Naragund, Ravindra Radder, Satish chikkamath, Nirmala S R, Suneeta V Budihal
Abstract - Now days heart failure is the main issue because of food habits and the lifestyle of the people. The number of people losing life due to heart failure is increasing every year. This demands for the early prediction to treat and manage heart failure. Many researchers worked on this issue based on ML models. In our work, we are using a deep learning technique that is an artificial neural network (ANN) and ML models-KNN, SVM, Logistic regression, Gaussian Naive Bayes. ANN model has performed with better accuracy compared to ML models. We achieved higher accuracy compared to previous works and we have developed user friendly GUI for our model. This GUI predicts heart failure based on given features.

Paper Presenter

Shyam Desai

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Artificial Intelligence and Cybersecurity: Challenges, Opportunities, and Defensive Techniques

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Edidiong Akpabio, Supriya Narad
Abstract - Fighting the constantly changing terrain of cyber threats has advanced significantly with the combination of cybersecurity and artificial intelligence (AI). This research examines how AI applications— such as speech recognition, image comprehension, and natural language understanding—can revolutionize cybersecurity protocols. Recent studies demonstrating exceptional accuracy rates in speech recognition and visual understanding illustrate the effectiveness of AI in fortifying defences against cyberattacks. However, there are new difficulties and moral problems brought about by the incorporation of AI into cybersecurity. Robust security protocols and ethical standards are required in light of the severe threats posed by adversarial assaults, data poisoning, and weaknesses in AI systems. As a result, numerous methods and instruments, including secure communication protocols and adversarial training, are being used to improve AI security. Furthermore, new ideas with the potential to address these issues include blockchain technology, secure collaborative learning, and federated learning. However, their application necessitates cautious thought and additional study to guarantee their efficacy and scalability. Proactive solutions can be established to manage risks and protect against emerging threats through coordinated efforts among cybersecurity specialists, legislators, and AI researchers. To fully utilize AI in cybersecurity and increase our collective resistance to cyberattacks, this paper emphasizes the significance of ongoing adaptation and ethical inspection.

Paper Presenter

Edidiong Akpabio

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Data Storage with Attribute-based Encryption and De-duplication Filter on Hybrid Cloud

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - A. A. Manjrekar, A. H. Bhosale, H. P. Khandagale, S. S. Nikam
Abstract - Cloud storage has emerged as the most convenient and cost-effective solution for sharing, maintaining, and handling all types of data in the modern digital era. However, simply storing and sharing data is no longer sufficient - data secrecy has become an equally pressing concern. Even storage space cost is an important factor these days. Here we will use ABE for the secrecy of data and de-duplication technique to avoid data redundancy. Many users use the cloud system to store the data but sometimes data may get duplicated on the system as multiple users upload the same file. Here the situation is handled using a de-duplication filter. In the system, ABE generates a unique secret key with the help of user attributes as well as data attributes. This key is useful for secret data transmission between two parties. Here additional feature of dynamic revocation of a user is also provided if the user tries to misuse access policies provided by the authority if the user leaves the system in that case dynamic revocation and reassignment are carried out based on a set of revocation policies. In general, this system gives a complete solution for data storage, data secrecy and user revocation.

Paper Presenter

A. A. Manjrekar

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

DishKit - Integrated Dish Preparation and Ingredient Delivery System

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Pendry Pavan Sai Reddy, Ratnala Sashank, Atla Suraj Reddy, Sharan Jaya Kumar, Varsha P Suresh
Abstract - Long-term productivity and personal health depend on having a healthy diet. However, this is jeopardised in the modern world due to time consuming processes like gathering raw materials according to cooking size, cooking time, and not enough knowledge of cooking instructions. Thus, there is a greater propensity to purchase fast food, order food online, and eat out. In this paper we propose an integrated dish preparation and ingredient delivery system. By cutting down on raw material collection time and offering cooking instructions, the method helps encourage people to cook at home. In addition to making grocery shopping simpler, this initiative aims to address the growing need for healthier eating habits by facilitating the preparation of wholesome, fresh meals at home. The approach is implemented as a web application, DishKit. Preliminary findings indicate a significant rise in the number of consumers opting for home cooking that prioritizes convenience and wellness.

Paper Presenter

Atla Suraj Reddy

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Innovativeness or Competence: A Self-Determination Theory Model of How Students Use Generative AI in Higher Education

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Monisha Thangam KS, Anju S, Shobhana Palat Madhavan, Deepak Gupta
Abstract - Generative Artificial Intelligence (GenAI) is a rapidly advancing field shaping various industries, including higher education. Despite its growing impact, the factors influencing student usage of GenAI tools has yet to be fully explored. This study aims to bridge this gap by examining how student personality characteristics influence the type of usage of GenAI such as idea generation or editing. The theoretical framework of Self-Determination Theory was employed along with the Technology Readiness and Acceptance Model. Analysis of data from 448 respondents pan India using ordinal logit regression found that higher their perceived competence, the higher the likelihood of using GenAI for academics. Students high in innovativeness are more like to use GenAI for idea generation and cohesive structuring. These findings can contribute to designing effective course structures incorporating AI for academic assessment.

Paper Presenter

Monisha Thangam KS

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Money, Fame, or Something Embedded Within – Factors Influencing an Individual’s Choice to Identify as an Instagram Influencer

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Soundarya Shankar, Srinidhi S, Deepak Gupta, Shobhana Madhavan
Abstract - The rapid rise of Instagram influencers has transformed the social media landscape, blurring the boundaries between entertainment, marketing, and personal branding. From fashionistas to fitness gurus, these individuals captivate millions with their meticulously maintained online personas, holding enormous power over consumer choices and cultural trends. But what motivates an individual to take this path, investing time and attention into establishing a digital presence for themselves? What are some of the intrinsic and extrinsic factors that inspire people to become Instagram influencers? This study seeks to examine the intricate incentives that drive individuals to become influencers, expanding on previous findings from studies. The study investigates the influence of factors like social norms, social cause, desire for fame, desire for money, and other variables on the intention of an individual to become an Instagram influencer. Primary data was collected through an online questionnaire from 361 respondents through non-probabilistic purposive sampling, of which 316 responses were usable. The analysis was done using Structural Equation Modelling (SEM) and Medsem was used to perform mediation analysis in Stata. From the study, it was inferred that desire for fame was the key variable that drives an individual’s choice to identify as an Instagram influencer. The desire to use the platform for social good also had a significant impact. The research can help businesses identify the right influencers to promote their products by understanding what motivates people to become influencers and can help businesses develop more targeted influencer marketing campaigns. By understanding influencer motivations, social media platforms can also develop strategies to promote positive and realistic portrayals of online life.

Paper Presenter

Soundarya Shankar

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Prototype Development And Testing Of An Adaptive Real Time Operating System Based Density Oriented Traffic Signal Control

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Pradhangouda Patil, Srujan Hiremath, Punit Mudishennavar, Prakash Bandi, Anupama R Itagi, Jayashree Mallidu, Anupkumar Patil
Abstract - The escalating urbanization and increasing vehicular density in modern cities demand innovative solutions to manage traffic efficiently and mitigate congestion-related challenges. This paper introduces a simple and efficient approach to developing an adaptive traffic control system using RTX Real-Time Operating Systems (RTOS). The work involves the formulation of an algorithm. The proposed system leverages real-time data from sensors to dynamically adjust traffic signal timings in response to varying traffic densities. To implement the system, a network of Infrared (IR) sensors is deployed at strategic locations, collecting data on traffic densities. This information is processed in real time by the Cortex M3 microcontroller with the RTX RTOS kernel, applying suitable optimization techniques. The control signals thus generated are used to dynamically alter signal timings. The system is designed to be scalable, allowing for seamless integration with existing traffic infrastructure.

Paper Presenter

Pradhangouda Patil

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Sentiment analysis on Indian Regional Languages

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Kiran V. Sonkamble, Saroj S. Date, Sachin N.Deshmukh
Abstract - Sentiment analysis is a method in the processing of natural language that uses machine learning to detect and extract the polarity of sentiments represented in a text, including positive, negative, or neutral. Due to the increasing acceptance of social media and the increased use of Indian languages, there has been an increase in interest in sentiment analysis in Indian languages in recent years. Machine learning is utilized to analyze and categorize subjective data, such as opinions, sentiments, and attitudes, expressed in text. This approach has been used in a variety of languages, such as Telugu, Marathi, and Bengali. Within this particular context, the evaluation of the models was evaluated in Bengali language including comparing their accuracy, precision, recall, and F1 score. A comparison was made with models applied to different languages, and it was seen that both KNN and SVM consistently performed well across all three languages. However, the presentation of the LR model differed. In phrase of F1 ratings, KNN and LR performed the best in Bengali compared to Telugu, whereas SVM obtained the highest F1 score. Among the Marathi language models, KNN had the greatest F1 score, while SVM achieved the highest recall score. Hence, it is essential to carefully choose the suitable machine-learning algorithm for each language in order to get the utmost precision in sentiment analysis. The sentiment classification step involves categorizing the sentiment expressed in the text using machine learning techniques. For sentiment analysis in Indian regional languages, machine learning techniques such as KNN, Support Vector Machines (SVM), and Logistic regression have been applied. Logistic regressions have demonstrated superior accuracy compared to KNN and SVMs. Accuracy, precision, recall, and F1 score are essential performance analysis approaches to evaluate. These indicators can aid in measuring the effective the algorithms are at identifying sentiment in text.

Paper Presenter

Kiran V. Sonkamble

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Traffic Object Detection Using YOLO-V8

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Madhura M. Bhosale, Yogesh S. Angal
Abstract - Object detection is very prominent task in autonomous vehicle domain. Evolution in the area of deep-learning provides great edge for object detection. In this paper we have worked on traffic object detection using YOLO-V8 with model x version on KITTI dataset with adam optimizer, batch size is 8, epoch is 150 and learning rate 0.001. we have used 80% images for training which around 5000 and for remaining 20 % which is around 1500 used for validation. In this experimentation we have used NVIDIA RTX A5000 GPU for model training and we have got mAP accuracy 80%.

Paper Presenter

Madhura M. Bhosale

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

Understanding User Attitudes and Intentions Towards using Robo-Advisors for Wealth Management in India

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room C

Authors - Divyasree N, Sandra Vinod, Varsha Sajan
Abstract - Robo-advisors are digital platforms which use computer algorithms in order to offer financial advice and manage clients’ investment portfolios more efficiently. The utilization of robo-advisors for managing wealth is not as widespread in India compared to other countries. This research paper aims to uncover the reasons behind this and focuses on the factors that influence the acceptance of robo-advisors in the Indian context. Using established technology acceptance models, we seek to gain a better understanding of this phenomenon. This study mainly focuses on perceived ease of use [PEU] (how easy it is to use robo-advisors), perceived usefulness [PU] (how beneficial robo-advisors are perceived to be), Attitude towards the technology [ATT], subjective norms [SN] (the influence of others' opinions), and behavioral intentions [BI] (the likelihood of using robo-advisors). An online survey was conducted with 210 respondents using convenience sampling, adopting this variable from the established technology acceptance models. By analyzing these factors, our goal is to shed light on the inclination towards adopting robo-advisory services in India. Our findings reveal strong positive correlations among these factors, indicating a favorable attitude towards adopting robo-advisory services in India's wealth management sector. Specifically, perceived usefulness and attitude towards technology emerge as crucial elements influencing this inclination. Understanding these insights is crucial in devising effective strategies to promote the adoption of robo-advisors in India's wealth management sector. By addressing concerns related to ease of use, highlighting the usefulness of robo-advisors, and fostering positive attitudes towards the technology, we can encourage more individuals to embrace these innovative wealth management solutions in India.

Paper Presenter

Divyasree N

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room C Goa, India

Virtual Room 9C, Virtual Room C

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Systematic review of Free-Living Human Activity Recognition(FL-HAR)methods for health research

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Arpitha S, Manjaiah D H, Yogesh K M
Abstract - This extensive review aims to provide an in-depth analysis of the latest FLHAR (Free-Living Human Activity Recognition) methods and their applications in health research. As sedentary lifestyles become more and more common, accurate and scalable technology for detecting human activity in free-living situations are crucial for enhancing public health programs. The aim of this research project is to collect high-quality accelerometer data from a range of strategically placed sensors on the human body. After improving the raw accelerometer signals through pre-processing, relevant data representing different activities is extracted using feature extraction algorithms. A range of state-of-the-art machine learning algorithms, including deep learning models, are used to train and optimize the recognition system. Furthermore, the research delves into potential applications of the created HAR system in many domains such as human-computer interaction, sports surveillance, and medical area. In view of this, the review paper focuses on new models for machine learning in the temporal domain and hybrid feature selection methods. The article examines several benchmark datasets used in current methods. The report concludes with a list of problems and concerns that need more investigation and development.

Paper Presenter

Arpitha S

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Systematic Survey of Datasets used in Face Generation using Deep Learning

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Punam Dawgotra
Abstract - This systematic study presents a comprehensive analysis of datasets utilized in deep learning-based face generation research. Datasets in face generation using deep learning serve as the foundation upon which models learn to generate realistic human faces. This systematic survey explores various datasets comprising of human face images collected from various sources like Internet, social media platforms or photo gallery portals like Flickr and provides insights into their characteristics, such as size, resolution, annotations, and applications. By examining the evolution of datasets over time, from early benchmarks to recent high-resolution collections, this survey highlights the importance of dataset quality and diversity in implementing deep learning models in face generation techniques. It discusses various widely popular deep learning algorithms like GAN based DCGAN, CycleGAN, CGAN, StyleGAN, PGGAN, StyleGAN2, AttentionGAN and Autoencoder based VAE Model which are currently being utilized in human face generation. Through this survey, researchers and developers gain valuable insights into the landscape of face generation datasets, facilitating informed decision-making and advancements in the field of face generation applications.

Paper Presenter

Punam Dawgotra

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

A Taxonomy of Big Data Challenges in Social Sciences Research

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Kanika Panwar, Vikas Sihag
Abstract - Big data analytics has revolutionized social science research by enabling the extraction of valuable insights from extensive and diverse datasets. This paper examines the challenges and methodologies involved in the big data analytics process within the realm of social science research. The paper presents a concise overview of research challenges in big data analysis for social science researchers, beginning with an exploration of the architecture of big data analytics. Additionally, it provides a taxonomy of big data research specific to social science, outlining key considerations and methodologies. Finally, the paper concludes by discussing future directions for advancing big data analytics in social science research.

Paper Presenter

Kanika Panwar

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Gig Economy, Analysis and monitoring prioritising privacy, dedication, performance, and accuracy

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Anuj Verma, Devarshi Mehta
Abstract - The gig economy, characterized by temporary, freelance, and temporary jobs facilitated by digital platforms, presents a unique set of challenges for employers in terms of monitoring and analyzing worker activity. Key features of the gig economy include flexibility, a variety of work opportunities, and reliance on digital platforms for job matching. However, challenges such as income instability, lack of benefits, and legal and regulatory risks exist for gig workers. To address these challenges, various solutions are available, including time tracking software, performance analytics platforms, GPS and location tracking tools, task management systems, rating and feedback systems, blockchain-based reputation systems, and integrated platform solutions. Each solution has its strengths and weaknesses, with considerations regarding accuracy, privacy, fairness, and complexity. The main purpose of research in this area is to find the best possible solution to overcome the biggest challenges employers face, including lack of direct oversight, quality control, and feedback mechanisms. By understanding and addressing these challenges, employers can better manage gig economy workers and maximize the benefits of flexible work arrangements while mitigating potential risks.

Paper Presenter

Anuj Verma

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Integrated Micro Pillar Microcantilever Double Square Split Ring Resonator for Optical Sensing in Air and Water Mediums

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Afzal Shaikh, Manju Devi, Ramjan Khatik, Shaista Shaikh
Abstract - Invention of optical sensor has been received considerable attention in both biological and chemical applications. In the proposed work double, micro pillar integrated with microcantilever has been investigated with double square split ring resonator. In this work sensor is analyzed for both air and water medium. Principle operation of proposed sensor design involves integrated moving mechanical pillar will continuously get deflected and fill the two air holes in the double square split resonator. Defected tip of microcantilever will fill the two air holes in the double square split ring resonator structure. As the pressure on the microcantilever increases depth of penetration of micro pillar in the cavities increases. This penetration of micro pillar in the cavity will alter the propagation of light. Shift in wavelength is obtained for pressure generated. Power transmitted up to 45% in air and 48% in water. Sensitivity of 230nm/GPa for air medium and 120nm/GPa obtained for water.

Paper Presenter

Afzal Shaikh

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Streamlining Classroom Operations: Prototyping an RTOS Based Smart Time Table Scheduling and Attendance Monitoring System

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Shankar.I.Badiger, T. M. Krupa, Ansh Singh, Nazeeb Mulla, Anupama R Itagi, Jayashree Mallidu, Anupkumar Patil
Abstract - This paper presents an integrated solution for Time table and attendance monitoring. The developed prototype introduces dynamic display of essential information oftime table such as classroom, Time, division, and course names on an LCD screen, driven by the user input. Real-time attendance monitoring is achieved through Radio- Frequency IDentification (RFID) technology, where each student is assigned a unique RFID card. The system prototype harnesses the capabilities of the EM18 RFID sensor and UART communication, incorporating a Cortex M3 microcontroller within an RTOS environment powered by the RTX kernel. Round Robin Scheduling ensures the efficient execution of tasks, guaranteeing accurate attendance records on the LCD screen. Optimization techniques like header files and global variable declarations are used to enhance code efficiency. This comprehensive approach simplifies attendance tracking and classroom management, thereby enhancing productivity in teaching-learning activities. Seamlessly integrating technology, it furnishes educators with a powerful tool to streamline administrative tasks, ultimately fostering a more efficient learning environment.

Paper Presenter

Shankar.I.Badiger

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Studies in the intricacies involved in the Development of Antimicrobial Foam formulation for the Treatment of Bacterial Vaginosis

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Janki Patel, Vaishali Thakkar, Tejas Thakkar, Saloni Dalwadi
Abstract - Bacterial vaginosis (BV) is the prevailing vaginal condition among women in the reproductive age group (14-49). The reported prevalence of BV is 50 % of total vaginal infections. Present investigation was aimed at developing the propellants and hormonal free Metronidazole (MTZ) vaginal foam formulation for the treatment of Bacterial Vaginosis using lactic acid, polysorbate 80, lecithin, and water. Mucoadhesion of the formulation was accomplished by adding different concentrations of HPMC E5 and HPMC K4M. The formulation optimization was conducted using a 23 complete factorial design, taking in-to account the cumulative percent drug released and viscosity. Drug release studies of optimized batch showed 96% release within 20 min. Formulation was also subjected to foaming tendency, foam stability, dose per actuation, antimicrobial study. An artificial neural network (ANN) was utilized as a statistical tool to enhance predictive accuracy. The results obtained from the ANN were then compared to those generated by the design expert software (DOE). To study the effectiveness, Optimized batch was subjected to antimicrobial study against varies species in comparison with commercially available metronidazole gel, Metrogyl®. Result revealed that optimized batch having greater zone of inhibition as compare to marketed formulation, because of its greater diffusivity compared to gel form.

Paper Presenter

Vaishali Thakkar

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Technology as an Enabler of Sustainable Smart Cities

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Naval Lawande
Abstract - The phenomenon of rapid urbanization has presented cities world-wide with a range of complex issues, including the management of resources, the utilization of technology, and the promotion of sustainable practices. In response, the concept of sustainable smart cities has emerged as a practical solution, offering a revolutionary framework for the future of urban living. To scrutinize the research conducted on smart cities, technology, and sustainability in the past decade (2005–2023), a bibliometric analysis was carried out using the biblioshiny platform. The Scopus database was utilized to extract bibliometric data from 1828 articles. Co-authorship, co-occurrence, citation analysis, and bibliographic coupling of author keywords were employed to analyze the data, and the results were presented graphically. The bibliometric analysis divulged that the most frequently encountered themes in academic journals were "sustainability," "smart city," "smart technologies," and "sustainable smart cities." These findings serve as a sound foundation for future research in this field, which is an emerging issue that requires further exploration. The research work has the potential to pave the way for future studies in related areas and issues of the domain, as many problems are still unexplored.

Paper Presenter

Naval Lawande

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

The Challenges in Developing Assistive Technologies for the Hearing Impaired: Proposal for an Alternative Socially Sustainable Approach

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Varghese Kandathil, Anie Mathew
Abstract - We critically review the existing studies on ICT-based assistive technologies for the Hearing Impaired (HI) with a specific focus on Sign Language Automating Assistive Technologies (SLAAT). The review reveals the underlying user-centered design approach which has exclusionary implications for the HI. Hence, we analyze the linguistic processes that inform SLAAT which again shows the user-centered approach and its associated limitations for HI learners’ acquisition of language and socialization from the Deaf community’s cultural perspective. We find that the user-centered processes and design of SLAAT can isolate the HI from their immediate society and its linguistic heritage. Thus, while SLAAT is inclusive by facilitating the interactions of others with the HI and vice versa and increasing the access of the HI, it simultaneously produces socio-cultural and ecological linguistic exclusion. Technologies with such exclusions are considered socially unsustainable within the ESG framework of sustainability. Hence, to mitigate the exclusion and increase the social sustainability, we propose a human-centered design approach which is an expansion of the culture-centered design approach. We further suggest broad initial steps to develop human-centered designs which can be combined with the currently prevalent user-centered design approach.

Paper Presenter

Varghese Kandathil

India

Friday August 9, 2024 3:00pm - 5:00pm IST
Virtual Room D Goa, India

Virtual Room 9D, Virtual Room D

Host Organization Global Knowledge Research Foundation

3:00pm IST

Toward’s Continuous Availability: Implementing Proactive Monitoring for AWS-hosted Web Applications with Jenkins and Bitbucket

Friday August 9, 2024 3:00pm - 5:00pm IST

Virtual Room D

Authors - Sk Tausif Rahman, Vijay Verma
Abstract - This study portrays the deployment of a monitoring and alert system intended to identify and notify instances of downtime or unavailability of a Bit-bucket instance hosted on an Amazon Web Service (AWS) EC2 instance. The system utilizes Jenkins, an open-source automation application, and a Python script to continuously monitor the accessibility of the Bitbucket URL. In circumstances when the URL will not be accessible, the Python Script initiates email notifications to a predetermined group of recipients, informing them of potential service interruptions. The implementation specifics around the usage of AWS EC2 Ubuntu Linux Instance, the installation and setup of Bitbucket, the creation of a Security group, the configuration of Jenkins on a local Windows host, and the use of a Python Script for monitoring and automation. The study reveals the efficiency of the above system through testing scenarios, constraints, and potential improvements. Through the integration of this proactive monitoring and notification mechanism, the study seeks to improve the dependability and accessibility of cloud-based web applications, enhancing a smooth user experience and lessening the impact of approaches for cloud-based services.

Paper Presenter