Bhateja / Oroumchian / Tang | Information System Design: Sustainable Computing | Buch | 978-981-950377-3 | www.sack.de

Buch, Englisch, 614 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1051 g

Reihe: Lecture Notes in Networks and Systems

Bhateja / Oroumchian / Tang

Information System Design: Sustainable Computing

Proceedings of Ninth International Conference on Information System Design and Intelligent Applications (ISDIA 2025), Volume 5
Erscheinungsjahr 2026
ISBN: 978-981-950377-3
Verlag: Springer

Proceedings of Ninth International Conference on Information System Design and Intelligent Applications (ISDIA 2025), Volume 5

Buch, Englisch, 614 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1051 g

Reihe: Lecture Notes in Networks and Systems

ISBN: 978-981-950377-3
Verlag: Springer


This book presents a collection of high-quality, peer-reviewed research papers from 9th International Conference on Information System Design and Intelligent Applications (ISDIA 2025), held in Dubai, UAE, from January 3–4, 2025. It covers a wide range of topics in computer science and information technology, including data mining and data warehousing, high-performance computing, parallel and distributed computing, computational intelligence, soft computing, big data, cloud computing, grid computing, cognitive computing and information security.

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Research

Weitere Infos & Material


A Study of Digital Transformation for Banking and Finance Industry.- Using AI-driven code refactoring to reduce carbon emissions of software development.- Using Variable Sampling Intervals in EWMA Control Charts for Effective Gamma Process Monitoring.- IoT-Driven safety innovations: A framework for detecting and preventing intimate partner violence(IPV) in modern households.- Enhancing Productivity and Workflow Efficiency through an Innovative Application for Time-Sensitive Task Management.- NADER: Novel Adaptive Device Resolution Algorithm using device-account Relationships.- Deep Learning-Based Automated Structure Deterioration Detection for Building Structures: A Technological Advancement for Ensuring Structural Integrity.- LVDCS: Minimising Doubts in Distance Learning.- Leveraging Configurable SIMD Architecture in FPGA for Accelerated Software Testing.- Knowledge Management Practice using Multiple Intelligent Agents in Human Computer Cooperative System.- Exploring Child Online Protection in Lesotho: A Cross-Sectional Descriptive Study.- Leveraging GPT Embedding with Deep Learning for Malicious DGA-Generated Domain Detection.- Exploring Smart Tourism Technological Opportunities: Qualitative Perspectives from Malaysian Handicraft Product Tourism Service Providers' Stakeholders.


Vikrant Bhateja is an associate professor in Department of Electronics Engineering Faculty of Engineering and Technology (UNSIET), Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India. He holds a doctorate in ECE (bio-medical imaging) with a total academic teaching experience of 20 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.”

Farhad Oroumchian is a professor of Artificial Intelligence, Natural Language Processing and Machine Learning in University of Wollongong (Dubai Campus). He has 24 years of experience teaching AI, machine learning and databases. Dr Oroumchian has served at various capacities in the university ranging from acting chair of College to associate dean of Education. He is currently the head of AI & Intelligent Systems Research Cluster. Prof Oroumchian has developed several intelligent system, search engines and question answering systems that use human-like reasoning to find relevant information. He is a prominent researcher on Persian/Arabic text processing and retrieval as well as multilingual search engines.

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 four million dollars grants as a PI or Co-PI and has published more than 150+ 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.

Ahmad Taher Azar is a full professor at College of Computer and Information Sciences (CCIS), Prince Sultan University, Riyadh, Saudi Arabia. He is a leader of Automated Systems and Computing Lab (ASCL), Prince Sultan University, Saudi Arabia. He is currently an editor for IEEE Transactions on Fuzzy Systems, IEEE Systems Journal, IEEE Transactions on Neural Networks and Learning Systems, Springer's Human-centric Computing and Information Sciences and Elsevier's Engineering Applications of Artificial Intelligence. Prof. Azar was named one of the top 2% of scientists in the world in Artificial Intelligence by Stanford University, based on single-year impact and career-long impact. These rankings were published by Stanford University in the PLOS journal and were based on the SCOPUS database. Prof. Azar has expertise in artificial intelligence, control theory and applications, robotics, machine learning, computational intelligence and dynamical system modeling.



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