Recent Advances in Computational Methods in Science and Technology: Volume 1

This proceedings compilation emerges from the exchange of research insights and innovative ideas among academicians, researchers, practitioners, and students in the field of computer science. This book gathers peer-reviewed papers covering the most recent advances in Internet of Things (IoT), Cloud Computing, Machine Learning, Networking, System Design and Methodologies, Big Data Analytics and Applications, ICT for Sustainable Environment, and Artificial Intelligence. It presents cutting-edge developments that offer real-time support and enhanced security solutions for advanced learners, researchers, and academicians. This comprehensive resource can help promote translation of basic research into applied investigation and convert applied investigation into practice. This compilation is expected to be of significant value to a diverse audience, including researchers, academicians, undergraduate and postgraduate students, research scholars, professionals, technologists, and entrepreneurs.

Table of Contents:
1. The AI-Driven Investment Prediction: A Machine Learning Approach for Global Investment Analysis 2. Real-Time Event Detection for public Safety Using Deep Learning: Enhanced Model with Hybrid CNN-LSTM-Transformer and Noise Reduction 3. Architectural Insights and Scheduling Techniques in Fog Computing Challenges and Future Prospects 4. Advancements in Deep Learning Techniques for Diabetic Retinopathy Detection with Statistical Insights and Future Prospects 5. Intelligent Detection of Brain Haemorrhage using Deep Learning Algorithms: A Comprehensive Approach 6. A Hybrid Ensemble Model for Intrusion Detection in Cloud Environment with Transparent and Explainable AI Techniques 7. Real-time intrusion detection using deep neural networks 8. Crop Classification Using Deep Learning and Satellite Data for Precision Agriculture 9. A Hybrid Neural Network Approach Using LSTM and XGBoost for Network Intrusion Detection and Classification 10. Detection of fungal infection in dogs using deep learning techniques 11. Hybrid optimization algorithm for feature extraction with random forest for migraine detection 12. Face recognition door lock security system 13. WSHT: A Wavelet-Swin Hybrid Transformer for Accurate and Automated Lung Nodule Segmentation in CT Imaging 14. Exploring Speech Recognition and Pronunciation Accuracy Detection Techniques: A Comprehensive Review 15. Optimizing E-Commerce Insights Through Synthetic Data Generation and Big Data-Driven Machine Learning 16. Secure and Transparent Real Estate Price Predictions: Integrating Machine Learning and Blockchain 17. Air Quality Monitoring System Based on IoT 18. Intelligent Diagnosis of Neurological Diseases: A ML Model for Early Alzheimer's Detection 19. Detecting Fake Voices: Survey on Audio Deepfake Detection 20. Enhanced Flood Prediction and Risk Assessment using Machine and Deep Learning-Based Approaches 21. Early Prediction of Multi-Diseases Using AI Techniques to Promote Health and Well-Being 22. A Deep Hybrid Approach to Thyroid Detection: Integrating TabNet and Vision Transformers(ViT) 23. A Comprehensive Review of Sentiment Analysis and Content Prediction in Social Media: Techniques, Trends, and Applications 24. Automated System for Predicting Cardiovascular Disease Using Machine and Deep Learning 25. Object Detection for Blind Persons 26. Comorbidity Forecasting in Asthma: A Multimodal Learning Approach with Clinical and Environmental Data 27. Advancing brain tumor detection with deep learning: a comprehensive review 28. Implementation and Validation of an Onset Prediction Model for Seizure Detection 29. Hybrid Deep Learning Models For Automated Fetal Health Prediction Using Cardiotocograpghy Signals 30. A Comparative Study of Chaotic and DNA-Based Lightweight Cryptographic Schemes for IoT devices 31. Machine Learning based Optimized Water Assessment and Auto-Irrigation over Internet of Things Framework 32. MedXTech : Developing a Patient Condition Prediction System 33. A Comparative Analysis of Two Hyperchaotic Image Encryption Schemes: Dynamic DNA Encoding vs. ABC-Optimized Watermarking 34. Deep learning-based cyber threat detection in big data environments 35. Deep Learning-Based Plant Leaf Disease Detection Using CNNs and Hybrid Vision Transformer Architectures for Precision Agriculture 36. Deep Learning Applications in Thyroid Disease and Cancer Diagnosis 37. A Proactive Security Approach for Cyber-Physical Systems Using Modbus Honeypots 38. Review on feasibility of Underwater wireless Optical Communication 39. Multimodal Sentiment Analysis: Advances in Machine Learning and Deep Learning Approaches 40. Predicting Smartphone Addiction Using Machine Learning: A Behavioural and Neural Approach 41. Development of IoT Based Fruit Condition Monitoring System 42. Hybrid Machine Learning Models For The Prediction And Recommendation Of Different Types Of Crops Disease: A Review 43. Benchmarking Artifact-Based Deepfake Detection: Metrics- Driven Analysis of Model Performance 44. A Robust Multi-Class Text Classification Framework Using TF-IDF Features and Soft Voting Ensembles 45. Heart Attack Risk Prediction Using Ensemble Machine Learning Models on Clinical Data 46. Blockchain-Based Data Sharing Framework for Multi-Party Collaboration in Distributed System 47. EchoText: Integrating Whisper and YAMNet Models for Comprehensive Audio Analysis and Subtitle Generation 48. Comparison of Text Vectorization Techniques: TF-IDF, Word2Vec, BERT, and FastText 49. An Optimized Deep Learning-Based Intrusion Detection System for IoT Botnets Using Hybrid Feature Selection 50. Leveraging Machine Learning for Advanced Cyber Threat Detection in Network Traffic: A Comprehensive Review 51. A Novel LSTM-Based Method for Identifying Epileptic Seizures from EEG Data 52. Hybrid AI Models for Real-Time Intrusion Detection in Large-Scale Big Data 53. A Predictive Analysis of Network-Based Cybersecurity Threats Using Ensemble and Discriminant Learning Approaches 54. Machine Learning-Based Crop Recommendation System Using Agro-Environmental Parameters 55. Analyzing and Predicting CO₂ Emissions and Their Impact on Global Warming Using Linear Regression Techniques 56. The Digital Field: Integrating IoT and Deep Learning for Agricultural Excellence 57. Automated Transcription and Summarization of Video Content Using Whisper and Transformers: A Hybrid Deep Learning Approach 58. Enhancing Cardiovascular Illness Prediction with Machine Learning Algorithm-A Broad Review 59. Detection of Parkinson’s Disease Using Machine Learning and Deep Learning Techniques: A Review 60. A Bibliometric Analysis on Deep Learning and IoT Based Mushroom Cultivation 61. Advances in AI-Driven Optical Sensing for Aflatoxin Detection in Rice: A Review of UV Fluorescence and Hyperspectral Imaging 62. Applications and Monitoring System in IOT-driven healthcare technologies 63. Credit Card Fraud Detection using Machine Learning: A Comprehensive Survey and Analysis 64. Transformers and Capsule Networks for Accurate Cardiomegaly Detection in Medical Imaging 65. Harnessing YOLOv5 for Real-Time Object Detection: A Cloud-Based Approach 66. Generative AI Application for the Elderly with Dementia 67. Deep Learning Based Data Security in Mobile Networks 68. Role of Data Augmentation in Medical Image Analysis 69. Comparative Analysis of Deep Learning Architectures for Image Classification in Gastric Cancer Detection 70. CNN based Detection of Image Splicing: A Deep Learning Approach 71. Detecting Mental Health Influences on Night Eating Syndrome with Clustering Methods amongst University Students 72. Predictive Maintenance of Vehicles: A Comparative Study of Predictive Models 73. A Sequential CNN Framework for Accurate Brain Tumor Detection and Subtyping 74. Affective deep learning approach to personalised music recommendation 75. Breast Cancer Detection using Deep Learning on Medical Imaging Modalities: A Comprehensive Review 76. Machine Learning based Decision Tree for Hotspot Prediction in Cloud Computing Environment 77. A Comparative Study of Federated Learning Model Weight Aggregation Algorithms for Privacy-Preserving IoMT Applications 78. Transfer Learning Pipeline from VGGNet To ViT in Hybrid Image Processing 79. Analysis of energy-efficient task scheduling in IoT-fog-cloud environments using nature-inspired optimization algorithms 80. Towards Precision Agriculture: A Review of Image Segmentation Techniques and Their Future Prospects 81. A Hybrid Deep Learning Model for Robust Detection of Foliar Diseases in Cultivated Plants 82. Predicting Friendship and Followers Growth in Social Networks using ML-Based Link Prediction

About the Author :
Sukhpreet Kaur is a Professor at the Computer Science and Engineering, Chandigarh Engineering College - CGC Landran, Mohali. She has 18 years of experience in teaching and research. She earned her Ph. D in CSE from I K Gujral Punjab Technical University, Jalandhar and her master’s in technology in CSE from GNDEC, Ludhiana. Her research interests include Image Processing, Artificial Intelligence and Computer Vision. She has published more than 60 research papers in reputable Scopus-indexed international journals. She has also actively contributed to the academic community by organizing and conducting several international conferences, fostering collaborations and knowledge exchange in emerging areas of computer science. Amanpreet Kaur is a Professor at the Department of Information Technology, Chandigarh Engineering College - CGC Landran, Mohali. She earned her Ph.D. in Computer Science & Engineering from I.K. Gujral Punjab Technical University, Punjab, in 2020. She holds an M. Tech. in Information Technology with distinction from Guru Nanak Dev University, Amritsar, and B.Tech. in Computer Science & Engineering with honours and distinction. She has over 21 years of teaching experience at undergraduate and postgraduate levels. Dr. Kaur has been supervising many M. Tech. dissertations and Ph.D. research scholars. Her research contributions span multiple areas of computer science, with 40+ research publications in reputed international journals and 20+ papers presented at international conferences. She continues to contribute actively to academia through her teaching, mentorship, and research activities. Manish Kumar is a Professor at the Department of Computer Science and Engineering, Chandigarh Engineering College - CGC, Landran, Mohali. His academic career spans 20 years, with experience in teaching, research, and academic and administrative outreach activities. He completed his B.Tech., M. Tech. and Ph.D. degree in Computer Science and Engineering. His research specialization domains include wireless sensor network, data mining and machine learning. He has over 50 publications to his credit in widely circulated journals of national and international repute. He has also played a key role in the academic community by organizing several national and international conferences, fostering collaborations and advancing research in emerging domains of computer science.