Intelligent Solutions for Smart Adaptation in Digital Era
Description
This book comprises the select peer-reviewed proceedings of the 4th International Conference on Information Technology (InCITe-2024). It aims to provide a comprehensive knowledge base highlighting state-of-the-art research and development and best practices for intelligent solutions in the digital era. It covers adaptive intelligence, decision intelligence, artificial intelligence, deep learning, machine learning, data science, and enabling technologies for IoT, blockchain, and other futuristic technologies. The content would serve as a rich knowledge repository on information & communication technologies, neural networks, fuzzy systems, natural language processing, data mining & warehousing, big data analytics, cloud computing, social networks and intelligence, decision-making, and modeling, information systems, IT architectures, and security related aspects. This book provides a valuable resource for those in academia and industry.
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Persons
Dr. Nitasha Hasteer is a Professor & Head of the Information Technology Department and Dy. Director (Academics) at Amity School of Engineering and Technology, Amity University, India. She has 22 years of teaching, research, and administrative experience in academics and industry. She holds a Ph.D. in Computer Science and Engineering, and her interest areas are machine learning, cloud computing, crowdsourced software development, software project management, and process modeling through multi-criteria decision-making techniques. She has published more than 60 papers in various journals and international conferences in these areas and has guided many postgraduate students in their dissertations. She has been on the editorial board of many international conferences and obtained funding from government agencies such as the Science and Engineering Research Board, Department of Science Technology (DST), Defence Research and Development Organization (DRDO), Indian National ScienceAcademy (INSA), and Council of Scientific & Industrial Research (CSIR) for organizing conferences in the area of Information Technology. She is a member of the International Association of Computer Science & Information Technology (IACSIT), Singapore, the Institution of Engineering and Technology (IET), UK, and various other professional bodies.
Dr. Christian Blum holds the permanent post of Senior Research Scientist at the Artificial Intelligence Research Institute (IIIA) of the Spanish National Research Council (CSIC) in Bellaterra, Spain. Before that, from 2012 to 2016, he was an Ikerbasque Research Professor at the University of the Basque Country in San Sebastian, Spain. Dr. Blum obtained a PhD in Applied Sciences from the Free University of Brussels in 2004 and a Diploma (equivalent to a Masters Degree) in Mathematics from the University of Kaiserslautern, Germany, in 1998. His main research interests are in swarm intelligence techniques for optimization and control, and the hybridization of metaheuristics with other techniques for large-scale optimization problems arising, for example, in bioinformatics or transportation. During the last 20 years, Dr. Blum has co-authored more than 200 publications in international journals, books, and peer-reviewed conference proceedings. In total, his work has currently received around 18.000 citations, and his current H-index is 43 (Google Scholar). Apart from acting as editor for the journal Computers & Operations Research (responsible for heuristics and metaheuristics), he currently is also an associate editor for journals such as the Artificial Intelligence Journal and Engineering Applications of Artificial Intelligence.
Dr. Deepti Mehrotra is working as a Professor at Amity University Uttar Pradesh. She obtained her Ph.D. from Lucknow University and has more than 25 years of experience in research and teaching. She is actively involved in research activities and has published more than 200 research papers and has been a reviewer for many reputed journals. She has been invited as a resource person for faculty development programs and to deliver talks at national and international conferences. She is a reviewer and member of the editorial board for many journals. She has guided more than 20 Ph.D. scholars and 25 postgraduate students in their thesis work.
Dr. Hari Mohan Pandey is working with Bournemouth University, United Kingdom. He received his B.Tech. Degree from Uttar Pradesh Technical University, India, the M.Tech. Degree from the Narsee Monjee Institute of Management Studies, India, and a Ph.D. degree in Computer Science and Engineering from Amity University, India. He worked as a Postdoctoral Research Fellow with the Middlesex University, London, U.K. He specializes in computer science and engineering and his research area includes artificial intelligence, soft computing, natural language process, language acquisition, machine learning, and deep learning. He is the author of various books in computer science and engineering, published over 50 scientific papers in reputed journals and conferences. He has delivered keynotes, invited lectures, and served as session chair for international conferences. He has served as a leading guest editor for several journals such as swarm and evolutionary computation, neural commutating and applications, neural processing letter, intelligent decision technology, and International Journal of artificial intelligence and soft computing. Dr. Pandey has served as a reviewer for several reputed journals.
Content
Integrated Industrial Supply Chain with Intelligent Decision-Support Tools to achieve the Sustainable Developments Goals.- Alzheimer Disease Diagnosis using Multimodal data: A literature Review.- Advancements in Curvature Optimization for Millimeter-Wave Antennas in Cutting-Edge Communication Systems.- Exploring Defect Density Prediction: A Comparative Analysis of Feature Selection Techniques and Stacking Methodology.- Optimizing Disaster Recovery: A Comprehensive Study on Global Server Load Balancing in Network Solutions.- Query Assist: A Multimodal Verbal Specifications to Structured Query Conversion Model Using Word Vector Based Semantic Analysis.- Predicting Software Reliability through Machine Learning Analysis of Code Smells.- A High QoS Cluster Routing Scheme for Wireless Sensor Networks in Smart Agriculture Application.- Automatic Drowsiness Detection to Minimize Road Accident.- Development of ML Model For Road Lane Line Detection In Self Driving Cars by Using Concept of Computer Vision Techniques.- Advancements in Iris Recognition: A Comprehensive Review for Biometric Systems.- Plant Leaf Disease Detection using a Hybrid Model.- Image Caption Generator using Multimodal Techniques.- Image Caption Generator using Multimodal Techniques.- Customer Segmentation with RFM Analysis using Support Vector Machine.- Semi-Occluded Fire Detection in Buildings Through Deep Learning Approaches.- AI-Driven DevOps: A Tool Selection Guide.- Text Summarization and Sentiment Analysis using Transformer-based Models: Comparative Analysis.- Detection of Dysgraphia through Convolution Neural Networks.- An Empirical Review of Machine Learning Algorithms for Heart Disease Diagnosis.- Improved SOM and Hybrid Filtering Techniques for Recommending Next-Generation Movies in the Entertainment Industry.- Enhancing Customer Engagement through Generative AI-Driven Predictive Marketing - A Bibliometric analysis.- Performance Analysis of Machine Learning Classifiers on CICIDS2017 Dataset.- Analysing Refactoring Strategy for Handling Code Smell for Python Codes.- Exploring the Nexus of Deepfakes and VFX Technology: Unveiling Insights, Challenges, and Innovations.- Efficient Light Gradient Boosting Machine (LGBM) Framework for Early-Stage Diagnosis of lzheimer's Disease.
