Proceedings of 5th International Conference on Frontiers in Computing and Systems
Description
This book gathers high-quality research papers presented at the 5th International Conference on Frontiers in Computing and Systems (COMSYS 2024) held at BITS Pilani K K Birla Goa Campus, Goa, India, during December 13 - 15, 2024. The book covers research in AI, machine learning, and data science; devices, circuits, and systems; computational biology, biomedical informatics, and network medicine; communication networks, cloud computing and IoT; image, video and signal processing; and security and privacy.
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Dipak Kumar Kole received the Ph.D. degree in Engineering from Bengal Engg. & Science University, which is currently known as IIEST, Shibpur, India in 2012. He also received an M.Tech. and B. Tech. in Computer Science & Engineering and B.Sc. in Mathematics Honours from Calcutta University. He has approximately 22 years of professional experience. Dr. Kole has been a faculty member of the Computer Science and Engineering Department of Jalpaiguri Government Engineering College since 2014, where he is currently working as a Full Professor. His research interests include Synthesis & Testing of Reversible Circuits, Social Network Analysis, Digital Watermarking & Agriculture Engineering. He published more than 67 research articles in various international journals, conference proceedings and book chapters in the areas of VLSI, Reversible Circuits, Social Network Analysis, Agriculture Engineering, Image & Video Processing and Cryptography.
Snehanshu Saha received the PhD degree in mathematical sciences from the University of Texas at Arlington. He is a senior member of ACM and a fellow of IETE. He is a professor of Artificial Intelligence with BITS Pilani K K Birla Goa Campus. His current and future research interests lie in the theory of optimization, learning theory, activation functions in deep neural networks and Astro Informatics.
Subhadip Basu is a Full Professor in the Computer Science and Engineering Department of Jadavpur University, where he joined in 2006. He received his PhD from Jadavpur University and did his postdocs from University of Iowa, USA, and University of Warsaw, Poland. Dr Basu holds an honorary position as a Research Scientist at the University of Iowa, USA, since 2016. He is the Co-Founder and Honorary Advisor of Infomaticae, a technology startup headquartered in Kolkata, India. He has also worked in reputed International Institutes like, Hitachi Central Research Laboratory, Japan, Bournemouth University, UK, University of Lorraine, France, Nencki Institute of Experimental Biology, Poland and Hannover Medical School, Germany. Dr Basu has 250+ international research publications in the areas of Pattern Recognition, Machine Learning, Bioinformatics, Biomedical Image Analysis etc. He has edited ten books, received two US patents, supervised 10 PhD students and received several major research grants from UGC, DST and DBT, Govt. of India. Dr Basu is the recipient of the 'Research Award' from UGC, Govt. of India in 2016. He also received the DAAD Senior-Scientist fellowship from Germany, Hitachi Visiting-Research fellowship from Japan, EMMA and CLINK Visiting-Researcher fellowships from the European Union, BOYSCAST and FASTTRACK Young-Scientist fellowships from DST, Govt. of India. He is the past Chairperson of the IEEE Computer Society Kolkata, a senior member of IEEE, member of ACM and life member of IUPRAI.
Pawel Górecki is an Associate Professor at the Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw. He also served as a Research Fellow at the Max Planck Institute for Molecular Genetics in Berlin. Pawel Górecki earned M.Sc. degrees in Computer Science and Mathematics from the University of Warsaw. In 2006, he completed his Ph.D. in mathematics with a focus on computer science, contributing theoretical and algorithmic advancements in detecting horizontal gene transfers and modelling evolutionary scenarios. As a member of the Polish Bioinformatics Society, his research centres on computational biology and bioinformatics, exploring mathematical properties, algorithms, and combinatorial optimization problems in phylogenetic tree and network models. Dr. Górecki's work is dedicated to advancing our understanding of complex biological relationships.
Debotosh Bhattacharjee is working as a full professor in the Department of Computer Science and Engineering, Jadavpur University with twenty-five years of experience. His research interests pertain to the applications of machine learning techniques for Face Recognition, Gait Analysis, Hand Geometry Recognition, and Diagnostic Image Analysis. He has authored or coauthored more than 332 journals, conference publications, including several book chapters in the areas of Biometrics and Medical Image Processing. Six patents have been granted on his works. Prof. Bhattacharjee has been granted sponsored projects by the Govt. of India funding agencies like Department of Biotechnology(DBT), Department of Electronics and Information Technology (DeitY), University Grants Commission(UGC) with a total amount of around INR 3 Crore. For postdoctoral research, Dr. Bhattacharjee has visited different universities abroad like the University of Twente, The Netherlands; Instituto Superior Técnico, Lisbon, Portugal; University of Bologna, Italy; ITMO National Research University, St. Petersburg, Russia; University of Ljubljana, Slovenia; Northumbria University, Newcastle Upon Tyne, UK and Heidelberg University, Germany. He is a life member of Indian Society for Technical Education (ISTE, New Delhi), Indian Unit for Pattern Recognition and Artificial Intelligence (IUPRAI), senior member of IEEE (USA) and a fellow of West Bengal Academy of Science and Technology.
Content
Automated Vision-Based System for Comprehensive and Real-Time Detection and Classification of Fruit Surface Damages.- Multi-objective optimization of envelope design for operational energy and emissions performance of high-rise apartment in warm and humid climate using genetic algorithm and IoT.- Efficient Computer Vision Model for Early Diagnosis of Type 2 Diabetes Mellitus Using CNN and SVM Techniques.- Developer Interaction across Experience Levels: A Study of Three Systems.- RavNet: Conditioning Retinal Vessel Identification using a cascaded multi objective U-Net.- Analysing the application of machine learning techniques for detecting SQL injection vulnerabilities in web applications.- MADNet: Multi-class Attack Detection Network for VANETs.- Mood based Quote Recommendation using Deep Learning.- An Effective CO2 Emission Prediction through Ensemble Learning: A Comparative Analysis of Various Models.- Unveiling Critical Insights using Predictive Analytics and Explainable AI: A Case Study on COVID-19 through Statistical Inference.- Industrial Safety Detecting Deviations and Monitoring Using IIoT 4.0.- Intelligent Analysis of Student Performance in Online Learning Platforms using Data Mining Techniques.- Support Vector Economics: From Polyvariant Functions to a Binary Classification Method.- Dual Selective Attention Model for Sentiment and Emotion Identification with Explainable Cause Generation.- Autonomous Vehicle Steering Angle Prediction using CNN and Computer Vision.- Analysis of Badminton playing techniques using Computer Vision and Deep Learning.- Detecting Depression in short text Using a new CSMI feature selection approach.- Multi-population Evolution for Noisy Multi-objective Optimization.- Multi-Objective Optimization for Cooperative PathPlanning of UAV-Network in Complex Terrain.- Real-Time Smart Bus Number Recognition and Audio Output System for the Visually Impaired.- Explainable Rumor Detection Using Topic Modeling.- A Multimodal Approach to Alzheimer's Disease Classification: Enhanced Detection through Pre-Trained Language and Vision Transformers in Comprehensive Speech and Text Analysis.- Harnessing Technological Solutions to Address Growing Demand for Healthcare Services: A Review.- Multiclass Brain Tumor Detection Using Deep Learning Algorithms.- A Comprehensive Survey: Identification of Bird Species Through Audio Recordings.- Brain Tumor Classification of MRI data using Deep Semi Transfer Learning Framework.- Incorporating Feature Importance for Enhanced Prediction of Chloride Permeability and Compressive Strength in Sustainable Green Concrete Using the ChloroNet-9 Deep Learning Model.- Oral lesions classification using Fusion based Deep Learning.- Bayesian physics-informed neural network for parameter estimation of mooring line.- Predicting Shear Capacity using the Explainable BeamNet-12 Model for Corrosion Prevention in CRC Beams.- Image-based identification of road conditions using deep learning based models by transferring domain knowledge with visual attention.- Solar Power Prediction Using Deep Learning Technique.- Yellow Vein Mosaic Virus Detection in Okra Plant Using Graph Convolution Network.- Early Detection of Alzheimer's Disease using Deep Learning and SMOTE for Class Imbalance Correction.- Location Metadata Extraction from Landslide Related Online News Articles Using LLM Based Approaches.- Leveraging Machine Learning and Streamlit for RealTime Stock Analysis and Prediction.- Hand-Gesture Based HCI for Application Control with Custom Action Mapping in Multi-modal Input-Interface.- Pose-Specific Adaptive ROI (PSAR) Extraction model for yoga pose detection.- Comparative Analysis of YOLO 7, 8, and 9 for Object Detection in Indian Food Items Using Auto Distillation.- Detecting Meditative States Through Heart Rate Variability and Machine Learning Techniques.- Scalable MapReduce based Fuzzy Min-Max Neural Network using knn-medoids for Pattern Classification.- Speech-To-Speech Translation Using NLP.- Analysis and Application of Various Naive Bayes Classifier.- Head and neck cancer detection with microarray gene expression data using mutual information and autoencoder.