Preface -- Acknowledgment -- 1 Performance Evaluation of Avionics System Under Hardware-In- Loop Simulation Framework with Implementation of an AS9100 Quality Management System 1 Rajesh Shankar Karvande and Tatineni Madhavi -- 1.1 Introduction -- 1.2 HILS Process and Quality Management System -- 1.3 HILS Testing Phase -- 1.4 AS9100 QMS Integrated with HILS Process -- 1.5 Conclusion and Suggestions -- References -- 2 YouTube Comment Summarizer and Time-Based Analysis 13 Preeti Bailke, Rugved Junghare, Prajakta Kumbhare, Pratik Mandalkar, Pratik Mane and Netra Mohekar -- 2.1 Introduction -- 2.2 Literature Review -- 2.3 Methodology -- 2.3.1 YouTube Comments Data Collection -- 2.3.1.1 YouTube Data API Integration -- 2.3.1.2 get_video_comments Function -- 2.3.1.3 Comment Processing -- 2.3.1.4 Handling Pagination with get_all_video_ comments -- 2.3.1.5 Excel File Creation with save_to_excel -- 2.3.2 Datasets -- 2.3.3 Extractive Summarization -- 2.4 Result -- 2.5 Performance -- 2.6 Conclusion -- References -- 3 Enhancing Gait Recognition Using YOLOv8 and Robust Video Matting for Low-Light and Adverse Conditions 33 Premanand Ghadekar, Aadesh Chawla, Sakshi Bodhe, Sharvari Bawane and Dhruv Kshirsagar -- 3.1 Introduction -- 3.2 Related Works -- 3.3 Methodology -- 3.4 Comparision with Existing Systems -- 3.5 Future Scope -- 3.6 Conclusion -- Acknowledgment -- References -- 4 An Ensemble-Based Machine Learning Framework for Breast Cancer Prediction 51 Ramya Palaniappan, Maha Lakshmi, Namitha, Nirmala Devi and Naga Phani -- 4.1 Introduction -- 4.2 Related Works -- 4.3 Proposed Framework -- 4.3.1 ML Models and Ablation Study -- 4.3.2 Building Ensemble Model Using AdaBoost -- 4.4 Experimental Setup -- 4.4.1 Dataset -- 4.4.2 Data Visualization -- 4.4.3 Data Pre-Processing Phase -- 4.4.4 Proposed Methodology -- 4.4.5 Performance Metrics -- 4.5 Results and Discussion -- 4.5.1 Comparison with Baseline Models -- 4.5.2 Comparison with Existing Literature Works -- 4.6 Existing Works -- 4.7 Conclusion and Future Work -- Dataset -- References -- 5 Proactive Fault Detection in Weather Forecast Control Systems Through Heartbeat Monitoring and Cloud-Based Analytics 73 Shelly Prakash and Vaibhav Vyas -- 5.1 Introduction -- 5.1.1 Cloud Computing -- 5.1.1.1 Fault, Error, Failure -- 5.2 Related Work -- 5.3 Proposed Proactive Fault Detection Architecture -- 5.4 Conclusion -- References -- 6 FlowGuard: Efficient Traffic Monitoring System 99 Varsha Dange, Atharva Bonde, Om Borse, Harshal Chaudhari and Sanskar Chaudhari -- 6.1 Introduction -- 6.2 Literature Review -- 6.3 Methodology -- 6.3.1 Theory -- 6.3.2 Requirement -- 6.3.2.1 Hardware Requirements -- 6.3.2.2 Software Requirements -- 6.3.3 Workflow -- 6.3.4 Flowchart -- 6.4 Results and Discussions -- 6.5 Conclusion -- 6.6 Future Scope -- Acknowledgment -- References -- References for Pictures of Components Used -- 7 A Survey on Heart Disease Prediction Using Ensemble Techniques in ml 125 Sudhakar Vecha and M.V.P. Chandra Sekhara Rao -- 7.1 Introduction -- 7.2 Literature Survey -- 7.3 Datasets -- 7.4 Ensemble Learning in Heart Disease -- 7.5 Challenges and Limitations -- 7.6 Future Directions -- 7.7 Conclusion -- References -- 8 A Video Surveillance: Crowd Anomaly Detection and Management Alert System 139 Anitha Ponraj, Umasree Mariappan, M. J. Sai Kiran, S. Tejeswar Reddy, N. Vinay and P. Bharath -- 8.1 Introduction -- 8.2 Related Work -- 8.3 Dataset Description -- 8.4 Problem Definition -- 8.5 Proposed Methodology and System -- 8.5.1 Proposed Methodology -- 8.5.2 Proposed System -- 8.6 Results -- 8.7 Conclusion and Future Scope -- 8.7.1 Conclusion -- 8.7.2 Future Scope -- References -- 9 Revolutionizing Learning with Qubits: A Review of Quantum Machine Learning Advances 153 Shatakshi Bhusari, Aniket Badakh, Kalyani Daine, Nikita Gagare and Prasad Raghunath Mutkule -- 9.1 Introduction -- 9.1.1 Parallelism -- 9.1.2 Quantum Speedup -- 9.1.3 Quantum Entanglement -- 9.1.4 Quantum Fourier Transform -- 9.1.5 Quantum Machine Learning Algorithms -- 9.1.6 Quantum Data Representation -- 9.1.7 Quantum Sampling -- 9.1.8 Quantum Annealing -- 9.1.9 Hybrid Quantum-Classical Approaches -- 9.2 Review of Literature -- 9.2.1 Overview of Key Quantum Computing Principles -- 9.2.1.1 Qubits (Quantum Bits) -- 9.2.1.2 Quantum Gates -- 9.2.1.3 Quantum Parallelism -- 9.2.1.4 Quantum Measurement -- 9.2.1.5 Quantum Fourier Transform -- 9.2.1.6 Quantum Entanglement-Based Algorithms -- 9.3 Basic Quantum Operations, Qubits, and Quantum Gates -- 9.3.1 Basic Quantum Operations -- 9.3.2 Quantum Bits (Qubits) -- 9.3.3 Quantum Gates -- 9.4 Quantum Machine Learning Algorithms -- 9.4.1 Quantum Support Vector Machines (QSVM) -- 9.4.2 Quantum Neural Networks (QNN) -- 9.4.3 Quantum Clustering Algorithms -- 9.4.4 Quantum Principal Component Analysis (QPCA) -- 9.4.5 Quantum Boltzmann Machines -- 9.4.6 Quantum Support Vector Clustering (QSVC) -- 9.5 Quantum Hardware for Machine Learning -- 9.6 Challenges in Building Scalable and Error-Resistant Quantum Hardware -- 9.6.1 Decoherence and Quantum Error Correction -- 9.6.2 Quantum Gate Fidelity -- 9.6.3 Scalability -- 9.6.4 Qubit Connectivity and Crosstalk -- 9.6.5 Material Science and Qubit Implementation -- 9.6.6 Quantum Interconnects -- 9.6.7 Thermal Management -- 9.6.8 Error Mitigation Strategies -- 9.7 Challenges and Limitations in Quantum Machine Learning -- 9.7.1 Quantum Computational Overheads -- 9.7.2 Hybrid Quantum-Classical System Integration -- 9.7.3 Limited Quantum Expressibility -- 9.7.4 Data Preprocessing Challenges -- 9.7.5 Quantum Algorithm Verification -- 9.7.6 Quantum Resource Requirements -- 9.7.7 Adaptation to Quantum Hardware Constraints -- 9.7.8 Limited Quantum Hardware Availability -- 9.7.9 Algorithmic Complexity -- 9.7.10 Quantum Model Interpretability -- 9.8 Future Directions -- 9.9 Conclusion -- References -- 10 Multi-Band Self-Grounding Antenna for Wireless Technologies 169 Ch. Siva Rama Krishna, P. Livingston, S. Jaya Chandra, J. Hari Babu and K. Sai Babu -- 10.1 Introduction -- 10.1.1 Literature Review -- 10.2 Design of Antenna -- 10.2.1 Design and Results at Primary Level of Antenna -- 10.2.2 Design and Results at Secondary Level of Antenna -- 10.3 Actual Design of Antenna -- 10.4 Results of Antenna -- 10.4.1 Mathematical Analysis -- 10.4.2 3D Polar Plot -- 10.5 Conclusions -- References -- 11 Navigating Network Security: A Study on Contemporary Anomaly Detection Technologies 183 Sai Ramya, Smera C. and Sandeep J. -- 11.1 Introduction -- 11.2 Related Work -- 11.3 Methodology -- 11.4 Conclusion -- References -- 12 File Fragment Classification: A Comprehensive Survey of Research Advances 201 Teena Mary and Sreeja C.S. -- 12.1 Introduction -- 12.2 Methodology -- 12.2.1 Selection Criteria -- 12.2.2 Structure of the Paper -- 12.3 Approaches for File Fragment Classification -- 12.3.1 Signature-Based Approaches -- 12.3.2 Content-Based Approaches -- 12.3.3 Deep Learning-Based Approaches -- 12.3.3.1 Convolutional Neural Networks (CNNs) -- 12.3.3.2 Feed Forward Neural Networks (FFNNs) -- 12.3.4 Hierarchical Classification Methods -- 12.4 Survey Findings -- 12.5 Challenges and Future Directions -- 12.6 Conclusion -- References -- 13 Deepfake Detection and Forensic Precision for Online Harassment 219 K. Gouthami, K. Sunitha, D.U. Durgarani and M. Prathyusha -- 13.1 Introduction -- 13.2 Literature -- 13.3 Theoretical Analysis and Software Simulation -- 13.3.1 Theoretical Analysis -- 13.3.2 Software Simulation -- 13.3.3 Testing and Optimization -- References -- 14 Design of Automatic Seed Sowing Machine 227 Chiluka Ramesh, K. Sarada, V. Ajay Shankar and K. Ravi Kumar -- 14.1 Introduction -- 14.2 Literature Survey -- 14.3 Proposed System -- 14.4 Conclusions -- References -- 15 In Motion: Exploring Urban Rides Through Data Analytics 237 Rajkumar Sai Varun, Nimmagadda Narayana, Dudam Vipassana and Mohan Dholvan -- 15.1 Introduction -- 15.2 Literature Survey -- 15.3 Proposed Methodology -- 15.4 Result Analysis -- 15.5 Conclusion -- References -- 16 Design of Novel Chatbot Using Generative Artificial Intelligence 251 Sk. Khader Zelani,.