Recent Advances in Multidisciplinary Engineering: Taylor and Francis Proceedings in Computer Science and Engineering
Editat de Rakesh Kumar Yadav, Shivam, Shailendra Kumar Bhaskeren Limba Engleză Hardback – 3 dec 2026
The book emphasizes cross-domain collaboration, covering key areas such as Computer Science, Electrical and Electronics Engineering, Mechanical Engineering, Civil Engineering, and emerging interdisciplinary applications. Major focus areas include Artificial Intelligence, Machine Learning, IoT, Smart Systems, Sustainable Technologies, Robotics, and Data-Driven Engineering solutions. The proceedings, published under international standards, highlight innovative methodologies and practical implementations addressing real-world challenges. By fostering interaction between academia, industry, and research communities, the volume promotes knowledge exchange, technological advancement, and collaborative innovation aligned with global engineering trends.
This book is intended for researchers, academicians, industry professionals, and postgraduate students working in engineering and technology. It serves as a valuable reference for those interested in emerging trends, interdisciplinary research, and innovative solutions, as well as for practitioners aiming to translate research into practical applications.
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Specificații
ISBN-13: 9781041457206
ISBN-10: 1041457200
Pagini: 674
Dimensiuni: 210 x 280 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Taylor and Francis Proceedings in Computer Science and Engineering
ISBN-10: 1041457200
Pagini: 674
Dimensiuni: 210 x 280 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Taylor and Francis Proceedings in Computer Science and Engineering
Public țintă
Academic and GeneralCuprins
Session 1: Computer Science & Engineering – I. Next Generation Assessment Learning Platform: Generative intelligent system for Adaptive & Contextual Assessment and Retrieval-Augmented Generation Feedback. TAS-SD: Topology-Aware Self-Supervised Learning for Network Intrusion Detection. Deepfake Detection Using Convolutional Neural Networks for Robust Digital Media Forensics. Interactive Platform for Secure File Sharing with Blockchain. A Survey on Honeypot-Based Cyber Attack Detection Systems for IoT Devices. Detection and Mitigation of APK-Based Cyber Attacks in Android Mobile Applications. Detection of Malware Intrusions in Android Devices – A Deep Learning Approach. Review on Optimized Hybrid Deep Learning Framework for Enhanced Classification of Medicinal Plant Leaves Using Metaheuristic and Score Voting Techniques. Tree Based and Ensemble Machine Learning Models for Occupational and Life Style Driven Depression Risk Analysis. Blockchain-Integrated Edge Computing for Enhanced Agri-Supply Chain Traceability: A Decentralized Framework for Food Safety and Quality Assurance. Metamaterial-Enhanced Dual-Band CP MIMO DRA with Independent Terahertz Frequency Tuning Capabilities. Agentic Artificial Intelligence in Smart Agriculture: Architectures, Applications, Challenges, and Future Directions. Optimized CNN Model for Real World Plant Disease Detection. Symmetric Feature Enhancement DenseNet for Explainable Brain Tumor Classification. Proactive Academic Wellness: Leveraging Multimodal Data for Early Detection of Sleep Disorders in Students. Session 2: Computer Science & Engineering – II. Identification and Prediction of Tomato Plant Disease by Using Machine Learning System. A Metadata-Driven Agentic Analytics Assistant for Charging Data Analysis. CABiL: A Lightweight CNN–Attention–BiLSTM Framework for Hate Speech Detection in Social Networks. Q-Learning-Augmented Deep Learning Model for High-Recall Hate Speech Detection in Social Media. A Dual-Branched Hybrid Model with Adaptive Token Pruning for Multi-Crop Disease Diagnosis. Real-Time Monitoring Patient Engagement with Autonomous Agents: Data-Driven Diagnosis, Precision Medicine, and Medical Data Analytics. Real-Time Collaborative Coding Platform: Enhancing Developer Productivity. A Deep Learning Based Approach for Automated Fish Species Classification. Underwater Image Enhancement: A Review of Physics-Based, Non-Physics, and Deep Learning Models. Navigating Emotions: A Systematic Review of Sentiment Analysis Techniques for Mental Health Support in Conversational Systems and Mobile Platforms. Predicting and Analyzing the Academic Outcomes of Engineering Students Using Random Forest. A Hybrid Semantic Segmentation Approach Using U-Net and DeepLabV3+ for Automated Bio-fouling Detection on Ship Hulls. AI-Driven Automated Blood Cell Classification and Disease Diagnosis with Explainable AI Techniques. Deep-Learning-Based Criminal Identification Using Face Recognition. Analyzing Smartphone Usage Patterns for Early Detection of Mobile Addiction and Prediction of Depression and Anxiety Risks for Cognitive Wellness in the Young Generation. Vision-Based Violence Detection for Women Safety Using Lightweight and YOLO-Based CNN Learning Models. Session 3: Computer Science & Engineering – III. A Hybrid SVM-BiLSTM Approach for Detecting Fake Profiles on Instagram and Facebook. Data Gathering for Machine Learning: A Comprehensive Examination of Techniques and Challenges. Threat Alerting System for Surveillance Camera Using Ensemble Model. AI Powered Resume Job Matcher & Career Agent. GAN and Diffusion Model Based Super-Resolution for Low-Quality CCTV Footage. SafeSteps: A Women-Centric Navigation System Using Real-Time Safety Scoring and Multi-Parameter Route Optimization. LiveFit: An AI-Driven Personalized Nutrition, Meal Planning, and Subscription-Based Health Ecosystem. Early Detection of Coronary Artery Disease Using Machine Learning: A Framework for Enhanced Diagnosis. The Suggested Approaches for Diabetes Identification in Medical Decision-Making. Identification of Effective Nodes for Cybercrime Control in Social Media Networks: A Review Summary Based on Multi-Criteria Decision Analysis (MCDM) Techniques. Server Fan Aware Cooling: A Model-Free Reinforcement Learning Strategy for Energy Efficiency. Multicriteria Model: Prominent Person Identification Using Perception Grading Approach for Cybercrime in Social Media Networks. Forensic Memory-Based Approach to Fileless Malware Identification Using Deep Learning Techniques. Multi-Persistence Integrated Model Using Federated Learning for Big Data Analytics. Overview of Intelligent Computer-Aided Systems for Lung Disease Detection and Classification. Image-Based Breed Recognition for Cattle & Buffaloes in India Using Deep Learning. Session 4: Computer Science & Engineering – IV. Leveraging AI and ML in Big Data Analytics for Enhanced Data Insights. Cyber Security: Impact of Internet on Children and Women Safety. Adaptive Knowledge Graphs for Context-Aware Recommendations in E-Learning Platforms. Research on Synchronizing and Translating Consensus Mechanisms Between Different Blockchain Networks: A Comprehensive Framework for Cross-Chain Interoperability. Explainable Multimodal Framework for Tuberculosis Screening and Drug Resistance Estimation in High-Burden Districts of Karnataka. Securing the Swarm: A Multi-Boundary Federated Intrusion Detection System for UAV Networks Using Dynamic Spatio-Temporal Thresholding. AI Powered Legal Research Retriever. AI Driven Real Time Animal Intrusion Monitoring. Drug Target Interaction: Predicting Molecular Properties Using GNN. Blockchain Enabled Decentralized Authentication and Secure Communication for IoT Systems. AI and Automation in Healthcare Using Deep Convolutional Neural Networks. Deep Learning Based Cyberbullying Detection with Cross-Platform Evaluation on Social Media Platforms. Vulnerability-Assisted Local Privilege Escalation for Full File System Extraction from Android Smartphones. Quantum Security Protection for Micro Transactions in Banking Industry. Cloud-Based EEG Digital Twin Framework for Real-Time Mental Monitoring Using Machine Learning. XAI Enabled Hybrid Approach for Detection of Cyberterrorism. Deterministic Simulation of Human Survivability in Venus-Like Atmospheres Using Anthropometric Parameters. Unsupervised Representation Learning for Temporal Pattern Discovery in IoT Sensor Streams. Session 5: Civil Engineering. Influence of Carbon Black and Nickel Powder on the Mechanical and Electrical Properties of Smart-Sensing Cementitious Composites. Taguchi Optimization Study of EC Process for Cr6+ Removal Using Vertical Rotating Aluminum Anode. Session 6: Electrical and Electronics Engineering. Performance Assessment of Conventional and Solar-Energized Power Converter-Based Air Conditioning System. Performance Optimisation of Solar Arrays Using a Spatial Rush-Hour Algorithm Under Static Shadings. Adaptive Prognostic-Aware Fault-Tolerant Model Predictive Control with Constraint Filtering for Unmanned Aerial Vehicle Motor Failure. A Study of the Design Factors of Electromagnetic Forming Instruments to Improve the Performance of the Process. Machine Learning-Enhanced Solar Tracking: A Data-Driven Irradiance Forecasting for Optimal Tilt Control. Short-Term Electric Vehicle Charging Demand Forecasting Using LSTM. Energy-Efficient 4×2 Priority Encoder in 45 nm CMOS Using MTCMOS, Power Gating and SVL. Modeling and Control Methods for Comparing Electric Vehicle Drive Systems Using Various Types of Motors. Thermo-Electrical Performance Analysis of Cylindrical Surrounding Double-Gate MOSFETs Under Nanoscale Regimes. A Decoder-Centric Canonical Huffman for Lossless Decompression of High-Speed Event-Driven Data Streams. Smart Saline Infusion Care Unit (S2ICU) with Air Bubble Detection Mechanism. An Energy Efficient 4:2 Compressors Using Hybrid Logic Gate Structures. IoT-Based Adaptive Noise Control System for Urban Homes. Design of Magnitude Comparator Using Reversible Gates and FinFET Technology. Active Cell Balancing in Battery Management Systems: Optimising Energy Transfer via Flyback Converter Methodology. Electric Vehicle Charging Optimization Using Spot Electricity Markets: Economic Feasibility and Business Model Opportunities.
Session 7: Interdisciplinary. CNN-Transformer Framework for Failure-Aware Remaining Useful Life Prediction of Turbofan Engines. Performance Evaluation of Pre-trained CNN Architectures for COVID-19 Detection on ERBMAHE-Enhanced Chest X-Rays. Arduino-Based Multi-Probe Heat Pulse Sensor for Detection of Soil Thermal Properties and Soil Water Content. Artificial Intelligence Adoption in HRM and Its Impact on Employee Performance: Evidence from Emerging Economies. Transformer-Based Speech Emotion Recognition Using Log-Mel Spectrogram and Self-Attention Modeling. ConvNeXtV2-Fusion: A Multi-Scale Convolutional Framework for Same-Modality MRI Image Fusion. Low-Carbon Cement Manufacturing Using Green Hydrogen: A Case Study of Dalmia Cement, Karnataka, India. Exposure to Inhalable, Thoracic and Alveolar Particles among Commuters Using Different Transport Modes in Delhi. PapayaNet: A Public Dataset for Multi-Class Papaya Image Classification. A Hybrid Generative and Multimodal Learning Architecture for Early and Explainable Plant Disease Detection. AI Driven Efficient Resource Allocation for Internet of Vehicles Using Compressive Sensing. Hybrid Machine Learning Approach for Heart Attack Prediction. Role of process Parameters of Laser Cutting Machine by Using ANOVA Method on SS-304. Session 8: Mechanical Engineering. Multi-Agent Framework for Disagreement-Aware Narrative Risk Modelling from Financial News. Terrain Aware Wheelchair Navigation in Outdoor Spaces Using Hybrid Fuzzy A* Algorithm.
Session 7: Interdisciplinary. CNN-Transformer Framework for Failure-Aware Remaining Useful Life Prediction of Turbofan Engines. Performance Evaluation of Pre-trained CNN Architectures for COVID-19 Detection on ERBMAHE-Enhanced Chest X-Rays. Arduino-Based Multi-Probe Heat Pulse Sensor for Detection of Soil Thermal Properties and Soil Water Content. Artificial Intelligence Adoption in HRM and Its Impact on Employee Performance: Evidence from Emerging Economies. Transformer-Based Speech Emotion Recognition Using Log-Mel Spectrogram and Self-Attention Modeling. ConvNeXtV2-Fusion: A Multi-Scale Convolutional Framework for Same-Modality MRI Image Fusion. Low-Carbon Cement Manufacturing Using Green Hydrogen: A Case Study of Dalmia Cement, Karnataka, India. Exposure to Inhalable, Thoracic and Alveolar Particles among Commuters Using Different Transport Modes in Delhi. PapayaNet: A Public Dataset for Multi-Class Papaya Image Classification. A Hybrid Generative and Multimodal Learning Architecture for Early and Explainable Plant Disease Detection. AI Driven Efficient Resource Allocation for Internet of Vehicles Using Compressive Sensing. Hybrid Machine Learning Approach for Heart Attack Prediction. Role of process Parameters of Laser Cutting Machine by Using ANOVA Method on SS-304. Session 8: Mechanical Engineering. Multi-Agent Framework for Disagreement-Aware Narrative Risk Modelling from Financial News. Terrain Aware Wheelchair Navigation in Outdoor Spaces Using Hybrid Fuzzy A* Algorithm.
Notă biografică
Rakesh Kumar Yadav is an Associate Professor at Maharishi University of Information Technology (MUIT), Lucknow, with over 19 years of experience in teaching, research, and academic administration. He has held key leadership positions including Deputy Dean and Head of the Department of Computer Science and Engineering. His research interests include Artificial Intelligence, Machine Learning, Deep Learning, Data Structures, Algorithms, Cloud Computing, and emerging interdisciplinary technologies. He has published over 50 papers in reputed Scopus/SCI-indexed journals and holds multiple patents in his areas of expertise. He has successfully supervised several Ph.D. scholars and M.Tech students and actively contributes as a reviewer and editorial board member for reputed journals. Dr. Yadav has organized and contributed to numerous national and international conferences, delivering invited talks, coordinating special sessions, and serving as a session chair. He is also the author of three books published by reputed publishers and has played a key role in organizing academic events, including serving as Convener of ICRAME 2026. His contributions have been recognized through several awards for excellence in research and academics.
Shivam is an Assistant Professor-I in the Department of Electrical Engineering at the National Institute of Technology (NIT) Kurukshetra, with over a decade of academic and industrial experience. He completed his Ph.D. from NIT Kurukshetra in DC microgrid control and previously worked as a Design Engineer in the power sector. His research interests include hybrid microgrids, renewable energy integration, power quality, and power converter topologies. He has published several research papers in SCI/Scopus-indexed journals and international conferences, authored book chapters with reputed publishers, and is actively supervising Ph.D., M.Tech., and B.Tech. students. He has secured government-funded research projects, organized faculty development programs and international conferences, and contributed significantly to teaching and research in electrical engineering.
Shailendra Kumar Bhasker is an Assistant Professor in the Department of Electrical Engineering at Harcourt Butler Technical University (HBTU), Kanpur, with significant academic and research experience. He holds a Ph.D. from the Indian Institute of Technology (IIT) Roorkee, specializing in power system protection, particularly transformer protection algorithms. His research interests include Power System Protection, Artificial Intelligence and Machine Learning, and Signal Processing. Dr. Bhasker has published several research papers in reputed journals and IEEE conferences and has contributed to book chapters in emerging areas of renewable energy. He has supervised B.Tech projects and is currently guiding Ph.D. research scholars. He has also held important administrative roles, organized conferences and training programs, and served as a session chair at international conferences. Additionally, he is actively involved in academic development activities and is a member of professional bodies and editorial boards.
Shivam is an Assistant Professor-I in the Department of Electrical Engineering at the National Institute of Technology (NIT) Kurukshetra, with over a decade of academic and industrial experience. He completed his Ph.D. from NIT Kurukshetra in DC microgrid control and previously worked as a Design Engineer in the power sector. His research interests include hybrid microgrids, renewable energy integration, power quality, and power converter topologies. He has published several research papers in SCI/Scopus-indexed journals and international conferences, authored book chapters with reputed publishers, and is actively supervising Ph.D., M.Tech., and B.Tech. students. He has secured government-funded research projects, organized faculty development programs and international conferences, and contributed significantly to teaching and research in electrical engineering.
Shailendra Kumar Bhasker is an Assistant Professor in the Department of Electrical Engineering at Harcourt Butler Technical University (HBTU), Kanpur, with significant academic and research experience. He holds a Ph.D. from the Indian Institute of Technology (IIT) Roorkee, specializing in power system protection, particularly transformer protection algorithms. His research interests include Power System Protection, Artificial Intelligence and Machine Learning, and Signal Processing. Dr. Bhasker has published several research papers in reputed journals and IEEE conferences and has contributed to book chapters in emerging areas of renewable energy. He has supervised B.Tech projects and is currently guiding Ph.D. research scholars. He has also held important administrative roles, organized conferences and training programs, and served as a session chair at international conferences. Additionally, he is actively involved in academic development activities and is a member of professional bodies and editorial boards.
Descriere
The book comprises of peer-reviewed research papers presented at the International Conference on Recent Advances in Multidisciplinary Engineering (ICRAME 2026). The volume brings together researchers, academicians, industry experts, and innovators to explore cutting-edge developments across diverse engineering domains.