Soft Computing: Theories and Applications : Proceedings of SoCTA 2025, Volume 2.DE (Lecture Notes in Networks and Systems)

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Soft Computing: Theories and Applications : Proceedings of SoCTA 2025, Volume 2.DE (Lecture Notes in Networks and Systems)

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Description

The book is a collection of high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2025), held at National Institute of Technology Jalandhar, India, during 27-29 December 2025. This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing, and cryptanalysis. The book offers valuable insights into soft computing for teachers and researchers alike; the book inspires further research in this dynamic field.

Comparative Life-Cycle Assessment of HDDs vs SSDs: Energy Efficiency and Carbon Footprint in Data-Centric Workloads.- A Committee-Guided Social Algorithm for Few-Feature Selection.- Multi-Class Dental Structures Detection via Deep Learning Based Instance Segmentation.- Performance Analysis of Range Sensor for Autonomous Mobile Robots in Indoor Environments .- Quantifying the Path Dependence Theory in Institutions.- The Artificial Intelligence in Marketing Management: The Collaboration of Decision-Makers and Machines.- Fractal-Based Statistical Framework for Detecting Unusual Patterns in Blockchain Transactions.- An Integrated AI Ecosystem for Emotionally Aware and Productive: MIRA 1.0 .- Enhancing Clinical Reliability in Diabetic Retinopathy Detection.- A Sustainable Inventory Framework for Deteriorating Items Considering Inspection, Advanced Payment, and Carbon-Reducing Green Technology Investment.- Comparative Analysis of Carbon Footprint Predictions for Electronic Product Categories Using Random Forest, Federated Learning, and Contrastive Learning Models.- Real-Time Intraday Trading Using Renko-MACD Strategy: Design, Implementation and Empirical Evaluation.- Beyond the Black Box: Counterfactual and Reward-Based Interpretations for Transparent Reinforcement Learning.- Real-Time Diabetic Retinopathy Detection using Convolutional Neural Networks.- Advanced Machine Learning Models for Prediction, and Performance Optimization in Renewable Energy.- A Comparative and Ensemble Learning Approach to Citrus Leaf Disease Classification.

Dr. Tarun K. Sharma is the Professor & Research Mentor - CSE, School of Engineering & Technology, and Dean Academics at Shobhit University Gangoh. He has supervised 10 Ph.D., 20 M.Tech Dissertations, several MCA and B.Tech Projects. He has over 120 research publications in his credit. He is a founding member of International Conference on Soft Computing: Theories and Applications (SoCTA Series). He has (co-)edited 12 volumes of Conference Proceedings published by AISC; LNNS series of Springer (SCOPUS) Publication and four edited books with SpringerNature. His areas of interest include Nature Inspired Computing, Swarm Intelligence and Machine Learning.

Dr. Lipo Wang is presently on the faculty of the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interest is artificial intelligence with applications to image/video processing, biomedical engineering, communications, control, and power systems. He has 350+ publications, a U.S. patent in neural networks and a patent in systems. He has co-authored 2 monographs and (co-)edited 15 books. He is/was Associate Editor/Editorial Board Member of 30 international journals, including 4 IEEE Transactions, and guest editor for 15 journal special issues. He was a member of the Board of Governors of the International Neural Network Society, IEEE Computational Intelligence Society (CIS), and the IEEE Biometrics Council. He served as CIS Vice President for Technical Activities and Chair of Emergent Technologies Technical Committee, as well as Chair of Education Committee of the IEEE Engineering in Medicine and Biology Society (EMBS). He was President of the Asia-Pacific Neural Network Assembly (APNNA) and received the APNNA Excellent Service Award. He was founding Chair of both the EMBS Singapore Chapter and CIS Singapore Chapter.

Dr. Om Prakash Verma is currently serving as Assistant Professor in the Department of Instrumentation and Control Engineering, Dr B R Ambedkar NIT Jalandhar. His research interests includes: Machine Vision, Machine, Deep and Quantum Learning, Applied Soft-Computing and UAV Autonomous System. He has credit for publishing more than 100+ research publications including international peer-reviewed SCI journals, patent applications, edited books, conferences and book chapters. He has associated with 06 research projects as PI and Co-PI funded by various funding agencies such as ISRO, MeitY, CSIR,etc. He has supervised 2 Ph.D and currently supervising 3 Ph.D students. He is a Senior Member of IEEE, and Member of IEEE Computational Intelligence Society, IEEE Control Systems Society, Automatic Control and Dynamic Optimization Society and life time member of Instrument Society of India and STEM Research Society. He is an associate editor of the International Journal of Security and Privacy in Pervasive Computing.

Dr Jitendra Rajpurohit, a PhD in Nature Inspired Computing has over 15 years of experience in academics and research. He has been associated with many reputed institutions like Amity University, UPES and Manipal University in the past. Currently, he is serving as an Associate Professor at Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune. He has published more than 30 research articles in indexed journals and reputed conferences. He has also been an investigator for two projects funded by national and state level agencies. He is also associated as an organizer with two international conferences and an editorial board member for several international journals. At present he is guiding two PhD scholars. His areas of interest include Nature Inspired Computing, Swarm Intelligence, Image Processing and Machine Learning.


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