This book gathers selected high-quality research papers presented at International Conference on Advanced Computing and Intelligent Technologies (ICACIT 2024), which is jointly organized by Università degli Studi di Siena, Italy and ADSRS Education and Research during December 13–14, 2024. It discusses emerging topics pertaining to advanced computing, intelligent technologies and networks including AI and machine learning, data mining, big data analytics, high-performance computing network performance analysis, Internet of things networks, wireless sensor networks, and others. The book offers an asset for researchers from both academia and industries involved in advanced studies.
Table of Contents:
Chapter 1:Lung Cancer Stage Estimation Using EfficientNetV2B2: Formulating Gene Expression Data for Comparable ML Outcomes.- Chapter 2:Terra-Rover: IoT-Driven Autonomous Multi-Terrain Disaster Management System.- Chapter 3:Enhancing Heart Disease Diagnosis with Wearable IoT Devices and Machine Learning Models.- Chapter 4:Cardiovascular Disease Prediction using ECG Match.- Chapter 5:Deep Learning-Powered Diagnostic Model for Early Detection and Prognosis of Bone Diseases Using Radiographic Imaging.- Chapter 6:An advanced vision transformer technique for skin cancer identification.- Chapter 7:Applying Machine Learning and swarm optimisation Techniques for Real-Time Decision Making in Supply Chain Management.- Chapter 8:ResCrabNet: A Deep Transfer Learning Approach for Improved Crab Species Classification with Explainable AI.- Chapter 9:Machine Learning Approach for Classifying Shoulder Pain Pathologies Using Ultrasound Imaging.- Chapter 10:Attention-Augmented MobileNetV2 for MRI-Based Brain Tumor Classification: Cosine Annealing, and Advanced Metrics.- Chapter 11:BRAIN COMPUTER INTERFACE APPLICATION FOR SPEECH DECODING APPROACH USING EEG SIGNALS.- Chapter 12:Characterizing Shear Wave Propagatıon in an Anisotropic Layer under the Effect of Triangular Irregularity, Rigidity and Initial Stress.- Chapter 13:Assessing the Overall Quality of Red Wine Utilizing Classification Algorithms.- Chapter 14:Predicting Solar Energy Potential and Household Consumption Using Machine Learning and IoT.- Chapter 15:Novel Skin Cancer Detection Application Using Deep Learning Application.- Chapter 16:Modified Hippopotamus Optimization Algorithm for Numerical Optimization Problems.- Chapter 17:Emotion Recognition Using Deep Learning on EEG Data for Stress and Anxiety Detection.- Chapter 18:Evasion Attacks on Image Classification Models: A Comprehensive Review of Strategies and Defense Mechanisms.- Chapter 19:Design &Analysis of EBG Antenna with it’s Applications.- Chapter 20:Advancing Brain Tumor Detection with Deep Learning and Machine Learning: A performance Analysis of Different Deep Learning Models.- Chapter 21:Deep Learning Approaches for Optimizing Renewable Energy Generation and Consumption Forecasting in Smart Grids.- Chapter 22:A comprehensive deep learning approach for precise concrete crack detection and severity classification using ensemble learning.- Chapter 23erformance Evaluation of Edge and Cloud Technologies for Sentiment Analysis with IMDB Data.- Chapter 24:Predictive Analysis in Cardiovascular Health: Evaluating Machine Learning Algorithm for Enhanced Diagnostics Precision.- Chapter 25:Human activity recognition using machine learning.- Chapter 26:Earthquake Prediction and Alerting System Using Machine Learning and Raspberry Pi.- Chapter 27:Detection of Potholes using Deep Learning and Image Processing Techniques.- Chapter 28:Deep Learning-Based Solar Tracking System for Maximizing Solar Power Generation Efficiency.- Chapter 29:An Efficient and Cost Effective Approach for Smart Pharmaceutical Cold Chain Logistics using Internet of Things.- Chapter 30:DenseCucumberNet: An Enhanced Model for Interpretable Detection of Cucumber Diseases.- Chapter 31:Efficient Array Patch Antenna Design and Optimization for 5G Applications.- Chapter 32:Securing Media Integrity: A Blockchain-Based Approach against AI-Generated Deepfakes.- Chapter 33:Tumor Sight AI: Brain Tumor prediction system using Deep Learning and Explainable Artificial Intelligence (XAI).- Chapter 34:Deep Learning Driven Diabetic Retinopathy Detection Using CNN Application.- Chapter 35:Synergizing Generative Adversarial Network-Driven Synthetic Data Pipelines with Deep Neural Networks for Enhanced Breast Cancer Diagnosis.- Chapter 36:ResNet50 Outperforms VGG16 and VGG19 in Tomato Leaf Disease Classification.- Chapter 37:A Robust Framework for Internet of Things Harmonization in Critical Infrastructure.- Chapter 38:Vehicular Assistance Communication System for Road Blockage Using Multi-Hop V2X Architecture in Hilly Terrain.- Chapter 39:Occluded Face Image Inpainting using Generative Adversarial Networks.- Chapter 40:Vehicle Identification System Using Convolutional Neural Networks.- Chapter 41:A Review on Detection of Distributed Denial of Service Attacks Using Machine Learning Techniques.- Chapter 42:Analysis of EEG Signal for AAD Classification Using Deep Learning Approach.- Chapter 43:Federated Learning in Healthcare: Benchmarking In-sights for Diabetes Treatment.- Chapter 44:Deep Learning for Dermoscopic Diagnosis: High-Accuracy CNN in Skin Cancer Classification.- Chapter 45:Securing the Vote: Exploring the Potential of Blockchain-Based e-Voting System.- Chapter 46:Hybrid AI approach for melanoma diagnosis detection with image segmentation using mobile net and deep CNN algorithms.- Chapter 47:Machine Learning-Driven Design Enhancement of Microstrip Patch Antennas for Wireless Communication.- Chapter 48:Predictive Models of Compressive Strength of Concrete Containing Construction and Demolition Waste Using Artificial Neural Networks.- Chapter 49:Hybrid Bat Algorithm for Clustering.- Chapter 50:Designing IOT based Real Time Visual Paddy Leaf Pest Detection and Feature Extraction Algorithm.- Chapter 51:Optimizing Convolutional Neural Network for Accurate Digit Recognition.- Chapter 52:Enhancing Sentiment Analysis in Natural Language Processing: A Hybrid Approach of Machine Learning and Deep Learning Model for Emotion Classification.- Chapter 53:Satellite-Based Environmental Monitoring for Sustainable Well-being.- Chapter 54:ANALYSIS AND CHARACTERIZATION OF MULTI-EYE DISEASES USING DEEP LEARNING ALGORITHMS.- Chapter 55:Design and Development of Diverse Patch Antennas for 5G Wireless Networks Utilizing Various Materials.- Chapter 56:Optimized Deep Learning Approach for Accurate Poultry Disease Detection.- Chapter 57:Optimizing Stock Market Investment Decisions: A Comparative Analysis of Machine Learning and Deep Learning Algorithms.- Chapter 58:A Comprehensive study on Energy consumption analysis using Monte-Carlo simulation and Machine Learning.- Chapter 59:COMPUTATIONAL COGNITIVE ACTIVATION FUNCTION USING fMRI APPLICATION.- Chapter 60:Behavior Analysis In crowds.- Chapter 61:Integrating Data Science Methodologies in Crop Prediction to Reinforce Sustainable Agriculture.- Chapter 62:Detection and Mitigation of Wireless Network Attacks Using Artificial Intelligence.
About the Author :
Dr. Sanjoy Das is currently working as Professor, Department of Computer Science, Indira Gandhi National Tribal University (A Central Government University), Amarkantak, M.P. (Manipur Campus), India. He received his Ph.D. in Computer Science from Jawaharlal Nehru University, New Delhi, India. Before joining IGNTU, he has worked as Associate Professor, School of Computing Science and Engineering, Galgotias University, India, July 2012 to September 2017, and also, as Assistant Professor G. B. Pant Engineering College, Uttarakhand, and Assam University, Silchar, from 2001 to 2008. His current research interest includes Mobile Ad hoc Networks and Vehicular Ad hoc Networks, Distributed Systems, Data Mining. He has published numerous papers in international journals and conferences including IEEE and Springer.
Dr. Marcin Paprzycki received the MS degree from Adam Mickiewicz University, Poznań, Poland, the PhD degree from Southern Methodist University, Dallas, Texas, and the doctor of science degree from the Bulgarian Academy of Sciences, Sofia, Bulgaria. He is an associate professor with the Systems Research Institute, Polish Academy of Sciences. He is a senior member of the ACM, a senior fulbright lecturer, and an IEEE Computer Society distinguished visitor. He has contributed to more than 500 publications and was invited to the program committees of more than 800 international conferences.
Prof. Ankush Ghosh is Senior member of IEEE, Fellow of IETE currently working as Adjunct Professor, Chandigarh University, Chandigarh, India. He has received his Ph.D. (Engg.) degree from Jadavpur University, India in 2010. He was a research fellow of the Advanced Technology Cell- DRDO, Govt. of India. He was awarded National Scholarship by HRD, Govt. of India. He has outstanding research experiences and published 6 edited books; 4 from Springer & 2 from Elsevier; 3 National & 8 International patents and more than 120 research papers indexed in Scopus/Web of Science. He is serving as an editorial board member of several international journals including Chief Editor. He has more than 15 years of experience in teaching, research as well as industry. His UG and PG teaching assignments include Microprocessor and microcontroller, AI, IOT, Embedded and real time systems etc. He has delivered Keynote/Invited lecture in a number of international seminar/conferences, refreshers courses, and FDPs. He has guided a large number of M.Tech and Ph.D. students. Dr. Ghosh is an active member of IEEE and organized a number Seminars and workshops in association with IEEE. He is an editor & organizing committee member of the Conference series GUCON, ICCCA, ICEEE, ICACIT. He is a He is a Start-up India Mentor and Global Startup Advisor of Wadhwani NEN. He has reviewed and mentored more than 50 start-ups. He has received award for contributing in Innovate India programme from AICTE- DST, Govt. of India in 2019 and 2020. He has received an appreciation award from AICTE, DST, TI, IIMB, NSRCEL, and myGOV for fostering students to strengthen the ecosystem bridging Government, Academia, and Industry in the year 2021.
Dr. Monica Bianchini received the Laurea cum laude in Mathematics and the Ph.D. degree in Computer Science from the University of Florence, Italy, in 1989 and 1995, respectively. After receiving the Laurea, for two years, she was involved in a joint project of Bull HN Italia and the Department of Mathematics (University of Florence), aimed at designing parallel software for solving differential equations. From 1992 to 1998, she was a Ph.D. student and a Postdoc Fellow with the Computer Science Department.
