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.
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
Alzheimers 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.
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.
Pawe 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. Pawe 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.
