Intelligent Data Engineering and Analytics
Description
The book presents the proceedings of the 13th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2025), held at Intelligent Systems Research Group (ISRG), London Metropolitan University, London, United Kingdom, during June 6-7, 2025. Researchers, scientists, engineers and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. This book is divided into four volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. This book is a valuable resource for postgraduate students in various engineering disciplines.
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Vikrant Bhateja is associate professor in Department of Electronics Engineering, Faculty of Engineering and Technology (UNSIET), Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India. He is also serving as Head: Computer Sc. Engg. & Information Technology in the same university. He holds a doctorate in ECE (Bio-Medical Imaging) with a total academic teaching experience of 21 years with around 190 publications in reputed international conferences, journals and online book chapter contributions; out of which 39 papers are published in SCIE indexed high impact factored journals. One of his papers published in Review of Scientific Instruments (RSI) Journal (under American International Publishers) has been selected as "Editor Choice Paper of the Issue'' in 2016. Among the international conference publications, four papers have received "Best Paper Award''. He has been instrumental in chairing/co-chairing around 30 international conferences in India and abroad as Publication/TPC chair and edited 55 book volumes from Springer-Nature as a corresponding/co-editor/author on date. He has delivered nearly 25 keynotes, invited talks in international conferences, ATAL, TEQIP and other AICTE sponsored FDPs and STTPs. He has been Editor-in-Chief of IGI Global--International Journal of Natural Computing and Research (IJNCR) an ACM & DBLP indexed journal from 2017-22. He has guest edited Special Issues in reputed SCIE indexed journals under SpringerNature and Elsevier. He is Senior Member of IEEE and Life Member of CSI.
Preeti Patel has been educated in the United Kingdom and holds a BSc in Computer Science (1986), an MSc in Database and Information Systems (1992) and a PhD in Computing (2017) from UK universities. She is currently the Head of Computer Science and Applied Computing at London Metropolitan University. Prior to entering the Higher Education sector, she worked within the IT industry for organisations including British Telecom, The Wellcome Foundation and General Electric Information Services. She has a keen interest in international education and has been previously involved with the NCC global programmes for a number of years and continues to work with international partners. She has been an External Advisor and an External Examiner at various UK universities, and regularly works with the UK QAA. Her current research interests include FAIR and FATE data challenges, synthetic data, big data fusion, the data science curriculum, AI-generative models for Data Science and learning-related issues for database environments and enhancement of student engagement. Professor Patel is a Principal Fellow of Higher Education Academy (Advance HE), a member of the British Computer Society, the Chartered Institute for IT and an associate Member of the Chartered Management Institute.
Jinshan Tang is a professor of Health Informatics in the Department of Health Administration and Policy. Before joining George Mason University, Dr. Tang was a full professor in the College of Computing at Michigan Technological University and a Founding Director of the Joint Center for Biocomputing and Digital Health. Dr. Tang's research covers broad areas related to image processing and artificial intelligence. His specific research interests include biomedical image analysis, biomedical imaging, artificial intelligence in medicine (e.g., computer-aided cancer detection, AI for COVID-19 detection). He has obtained over three million dollars grants as a PI or Co-PI and has published more than 110+ refereed journal and conference papers. He has also served as a committee member at various international conferences. He is a senior member of IEEE and a Co-chair of the Technical Committee on Information Assurance and Intelligent Multimedia-Mobile Communications, IEEE SMC society.
Content
Distinct between AI generated images and actual images using Swin Transformer.- Bayesian Modeling of Autoregressive Hurdle INGARCHX Models.- TinyML Applications Airwriting System Applied with TinyML for Vietnamese Handwriting Recognition.- NeuroViT Net A Study on Performance Improvement of a Transformer Based Brain Tumor Classification Model.- Evaluating NLP Strategies and Machine Learning Approaches for Detecting Rumors Across Multiple Sources.- Optimized Machine Learning Models for Efficient Protein Classification Using Sequence Composition Features.