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

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

12:03pm 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

12:15pm 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

12:27pm 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

12:39pm 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

12:51pm IST

Real-Time Object Detection and Recognition on Jetson Nano

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

Tango Hall 1

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

Dhruvi J. Patel

India

Jaykumar B. Patel

India

Mahek D. Viradiya

India

Priyanshi S. Patel

India

Trupal J. Patel

India

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

Physical Session 1A, Tango 1

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

1:15pm 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

1:27pm IST

Session Chair Remarks & Closing Remarks

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

Tango 1

Invited Guests/ Session Chairs

Prof. Sangeeta Chakrabarty

Vice Principal, Professor, Co-Ordinator, 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