Proceedings of Second International Conference on Computational Technologies and Electronics
Description
This book presents best-selected papers presented at the Second International Conference on Computational Technologies and Electronics (ICCTE 2025), organized by Department of Computer Science & Technology, University of North Bengal, Darjeeling, West Bengal, India, from 20-22 November 2025. The book targets current research in the areas of pattern recognition, data communication, applied electronics, artificial intelligence, and related application areas.
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Persons
Dr. Ardhendu Mandal completed his dual degree courses B.S.I.T. from Preston University, U.S.A. (India Campus) and B.C.A. from M.S. University, India. Further, he acquired M.C.A. degree from Biju Patnaik University of Technology (BPUT), India. He qualified for the UGC-NET (LS and JRF) in June 2005. In 2007, he joined the Department of Computer Science and Technology (formerly the Department of Computer Science and Application), University of North Bengal as Assistant Professor (formally known as Lecturer). He subsequently earned his Ph.D. from the University of North Bengal and is currently serving as an Associate Professor in the Department of Computer Science & Technology at the same university.
Dr. J K M Sadique Uz Zaman is an Assistant Professor at the Department of Computer Science & Technology, University of North Bengal since 2018. Before joining this University, he was Assistant Professor at Department of Computer Science, Acharya Prafulla Chandra Roy Govt. College, Siliguri, from 2015 to 2018. Prior to this, he was Guest Lecturer at Department of Computer Science and Engineering, Aliah University, Kolkata from 2013 to 2014. He also taught at Institute of Engineering and Management (IEM), Salt Lake during 2012.
Dr. Chandan Karfa is currently an Associate Professor in the Department of Computer Science and Engineering, IIT Guwahati where he is working since August 2016. Prior to that, he has worked for five years as Sr. R&D Engineer in Synopsys (India) Pvt. Ltd. He visited New York University during the summer of 2019. He has obtained his MS and PhD degrees in Computer Science and Engineering from IIT Kharagpur. His research interests include electronic design automation (EDA), formal verification, high-level synthesis, hardware security and ML for EDA. He has published more than eighty research papers in reputed international journals and conferences.
Prof. Dr. Sudan Jha is a Professor in Computer Science & Engineering at Kathmandu University, where he also serves as Associate Director of the IT Center and Lead Researcher of the IoT R&D Lab. He is currently on deputation as a Member of Nepal's National Planning Commission
With over 24 years of experience across academia, industry, and national policy, his research spans AI, IoT, Neutrosophic Systems, Reconfigurable Intelligent Surfaces (RIS), and Small Language Modeling (SLM). A Senior Member of IEEE, he has published 100+ SCI/SCIE articles, secured three patents, and authored/edited over 14 books with publishers like Elsevier and CRC Press, including Cognitive Security for Industrial IoT and Cognitive Security and Predictive Health Monitoring.
He is Editor-in-Chief of Engineering Issues and Solutions and a guest editor for several indexed journals. Prof. Jha is listed among Elsevier's top 2% Scientists (2025) and ranked Nepal's #1 scientist in Engineering & Technology and Computer Science (AD Scientific Index 2026). He received the NAST Technology Award 2082 B.S. and contributed to drafting Nepal's National AI Policy 2081. A celebrated keynote speaker, he has delivered over 100 invited lectures.
Content
Machine Learning for Precision Agriculture: A Hybrid GBDNN Model for Soil Analysis and Enhanced Crop Yield Prediction.- Comprehensive Evaluation of Different Approaches for Electricity Load/Demand Forecasting - Machine Learning, Deep Learning, and Hybrid Models.- Bridging Logic and Learning in AI: A Neuro-Symbolic Framework for Relation Prediction from Knowledge-Enriched Text.- Impact Assessment of Noise, Resolution, and Spectral Features on Deep Learning-Based Change Detection in Satellite Images.- Prediction of Indian Stock Market Trend using Seasonality with LSTM.- Prediction of Hereditary Cancer Disease using Machine Learning: A Study.- CSPDarkNet53-ViT: A Hybrid Deep Learning Architecture for Nail Disease Diagnosis.- A CNN-BiLSTM Hybrid Architecture for Binary Classification of Eczema from Skin Lesion Images.- Formal Constraint-Guided Neural Network Design for Safe and Trustworthy AI.- A Computationally Efficient Method for Road Segmentation and Statistics Based Classification on Low-Power Devices.