Advanced Computing and AI for Sustainable Environment, Energy, and Smart Manufacturing

AI-Driven Sustainability Across Environment, Energy, and Industry

This book presents an exploration of cutting-edge innovations driving sustainability across energy, environment, materials, and intelligent systems. Through multidisciplinary perspectives, the book highlights how advanced physics, chemistry, artificial intelligence, data science, and manufacturing technologies are shaping a resilient future.

Track 1: Energy Conversion and Storage Physics
1. Quantum Materials in Advanced Energy Conversion: Pathways to Future Technologies
Randeep Kaur, Apurba Tiwari, Harmandeep Singh
2. Potentialities and Challenges of Clean Energy Generation in India in the Context of Climate Variability/Change: Ongoing Programmes and Long-term Policy Frame-works in the Global Visions of United Nations
Prakash Ray
3. BRICS in the Green Fast Lane: Charting Renewable Energy Trajectories and Transformations
Mohini Reddy, Sachi Desai, Hilloni Shah
4. Recent Trends in Optimized Clustering Techniques for Energy-Efficient Wireless Sensor Networks: A Comprehensive Survey
Shinder Kaur, Satveer Kour, Manjit Singh
5. Sustainable Radiation Shielding Performance of BZT and BLT Ceramics: Evaluation Using HVL and TVL Parameters Across Broad Energy Spectrum
Joginder Singh, Meenu Mittal, Abhishek Chauhan, Rahul Kakkar, Sarabjeet Kaur
6. Machine Learning for Climate and Energy Forecasting: Advances and Challenges
Jagjit Singh Masoun
7. Materials and Device Physics for Next-Generation Photovoltaics
Neelima, Manju Bagga , Richa Datta, Surbhi Dhiman, Simran, Shilpa
8. Comparative Evaluation of Energy-Aware Heuristics for Virtual Machine Placement in Cloud Environment
Ajay Prashar, Jawahar Thakur
9. A hybrid AI models for renewable energy forecasting and intelligent grid balancing
Jagjit Singh Masoun
10. Advances in Sustainable Engineering and Green Technology: Integrating Renewable Systems, Materials, and Digital Innovation toward a Circular Economy
Rahul Mehra, Satish Kumar, Shaman Gupta, Sanjeev Saini, Harvinder Singh, Navneet Kumar Rajpoot
11. Reducing Energy Footprint in Machining Operations: An Analytical Evaluation
Satwant Singh, Raman Kumar, Harmeet Singh, Sehijpal Singh
12. Thermal performance analysis of sola

Advanced Computing and AI for Sustainable Environment, Energy, and Smart Manufacturing

AI-Driven Sustainability Across Environment, Energy, and Industry

This book presents an exploration of cutting-edge innovations driving sustainability across energy, environment, materials, and intelligent systems. Through multidisciplinary perspectives, the book highlights how advanced physics, chemistry, artificial intelligence, data science, and manufacturing technologies are shaping a resilient future.

Track 1: Energy Conversion and Storage Physics
1. Quantum Materials in Advanced Energy Conversion: Pathways to Future Technologies
Randeep Kaur, Apurba Tiwari, Harmandeep Singh
2. Potentialities and Challenges of Clean Energy Generation in India in the Context of Climate Variability/Change: Ongoing Programmes and Long-term Policy Frame-works in the Global Visions of United Nations
Prakash Ray
3. BRICS in the Green Fast Lane: Charting Renewable Energy Trajectories and Transformations
Mohini Reddy, Sachi Desai, Hilloni Shah
4. Recent Trends in Optimized Clustering Techniques for Energy-Efficient Wireless Sensor Networks: A Comprehensive Survey
Shinder Kaur, Satveer Kour, Manjit Singh
5. Sustainable Radiation Shielding Performance of BZT and BLT Ceramics: Evaluation Using HVL and TVL Parameters Across Broad Energy Spectrum
Joginder Singh, Meenu Mittal, Abhishek Chauhan, Rahul Kakkar, Sarabjeet Kaur
6. Machine Learning for Climate and Energy Forecasting: Advances and Challenges
Jagjit Singh Masoun
7. Materials and Device Physics for Next-Generation Photovoltaics
Neelima, Manju Bagga , Richa Datta, Surbhi Dhiman, Simran, Shilpa
8. Comparative Evaluation of Energy-Aware Heuristics for Virtual Machine Placement in Cloud Environment
Ajay Prashar, Jawahar Thakur
9. A hybrid AI models for renewable energy forecasting and intelligent grid balancing
Jagjit Singh Masoun
10. Advances in Sustainable Engineering and Green Technology: Integrating Renewable Systems, Materials, and Digital Innovation toward a Circular Economy
Rahul Mehra, Satish Kumar, Shaman Gupta, Sanjeev Saini, Harvinder Singh, Navneet Kumar Rajpoot
11. Reducing Energy Footprint in Machining Operations: An Analytical Evaluation
Satwant Singh, Raman Kumar, Harmeet Singh, Sehijpal Singh
12. Thermal performance analysis of sola

The International Conference Proceedings in Pathway of Electrical, Automation, Communication, and Electronics (PEACE-2025) s a premier platform dedicated to addressing the latest advancements, trends, and challenges in these rapidly evolving fields.

1. Credit Card Fraud Detection  2. A Hybrid Approach for Cardiovascular Disease Diagnosis: J48 Classifier  3. Perinatal Health Surveillance System: ESP32-Enabled GSM and GPRS Integration for Maternal Monitoring  4. Neurodegenerative Disorder Prognostics via Machine Learning: Predictive Modelling for Parkinson’s Disease  5. Leveraging Machine Learning for Personalized Medicine using Genomic Insights in Breast Cancer  6. Analysis of Earthquake Occurrence and Generating an Alert System Using Machine Learning Models  7. Early Prediction and Detection of Chronic Kidney Disease Using Multi-Input Model  8. OptiRAG: A Feedback-Driven Approach to Improving Retrieval-Augmented Generation  9. Panoramic Image Segmentation on Individual Object Instances.  10. Adaptive Energy Efficient Routing in Dynamic Network with Real Time Optimization  11. SiteSleuth: Dynamic Keyword Discovery and Data Scraping Tool  12. Advanced Early Warning System for Lightning and Heat Waves Using Deep Learning and Citizen Alerts  13. Marine Debris Movement Prediction using Deep Learning and Satellite Imagery  14. Privacy-Preserving of Hospital Data using Secure Multi-Party Computation and Federated Neural Models with Encrypted Inference Aggregation  15. Mathematical Reasoning Enhancement Through Fine-tuning: a Comparative Analysis of Gemma-2-2B-IT on GSM8K  16. Binary Magnificent Frigatebird Optimization: A Next-Generation Algorithm for Enhanced Feature Selection and Classification in High-Dimensional Data  17. Deep Learning-based Diagnosis and Impact Visualization of Tuberculosis using CXR Scanned Images  18. ERP System for Shopping Mall  19. Multi-Modal AI Framework for Cardiovascular Risk Prediction  20. Skin Disease Classification by Gabor and FCTH Filters with Ensemble Learning Models: A Machine Learning Approach in Dermatology  21. Integration of Feature Fusion Strategy on Efficient net for Skin Can

The International Conference Proceedings in Pathway of Electrical, Automation, Communication, and Electronics (PEACE-2025) s a premier platform dedicated to addressing the latest advancements, trends, and challenges in these rapidly evolving fields.

1. Credit Card Fraud Detection  2. A Hybrid Approach for Cardiovascular Disease Diagnosis: J48 Classifier  3. Perinatal Health Surveillance System: ESP32-Enabled GSM and GPRS Integration for Maternal Monitoring  4. Neurodegenerative Disorder Prognostics via Machine Learning: Predictive Modelling for Parkinson’s Disease  5. Leveraging Machine Learning for Personalized Medicine using Genomic Insights in Breast Cancer  6. Analysis of Earthquake Occurrence and Generating an Alert System Using Machine Learning Models  7. Early Prediction and Detection of Chronic Kidney Disease Using Multi-Input Model  8. OptiRAG: A Feedback-Driven Approach to Improving Retrieval-Augmented Generation  9. Panoramic Image Segmentation on Individual Object Instances.  10. Adaptive Energy Efficient Routing in Dynamic Network with Real Time Optimization  11. SiteSleuth: Dynamic Keyword Discovery and Data Scraping Tool  12. Advanced Early Warning System for Lightning and Heat Waves Using Deep Learning and Citizen Alerts  13. Marine Debris Movement Prediction using Deep Learning and Satellite Imagery  14. Privacy-Preserving of Hospital Data using Secure Multi-Party Computation and Federated Neural Models with Encrypted Inference Aggregation  15. Mathematical Reasoning Enhancement Through Fine-tuning: a Comparative Analysis of Gemma-2-2B-IT on GSM8K  16. Binary Magnificent Frigatebird Optimization: A Next-Generation Algorithm for Enhanced Feature Selection and Classification in High-Dimensional Data  17. Deep Learning-based Diagnosis and Impact Visualization of Tuberculosis using CXR Scanned Images  18. ERP System for Shopping Mall  19. Multi-Modal AI Framework for Cardiovascular Risk Prediction  20. Skin Disease Classification by Gabor and FCTH Filters with Ensemble Learning Models: A Machine Learning Approach in Dermatology  21. Integration of Feature Fusion Strategy on Efficient net for Skin Can

This book captures the proceedings of the International Conference on Advancement in Engineering & Science: Recent Trends & Applications, held at the Karmaveer Bhaurao Patil College of Engineering, Maharashtra, India. It highlights the synergy between research and practical applications to address pressing global and societal needs.

1.     Power System Stability Enhancement by Virtual Inertia Control Strategies for Renewable Energy Integration
M Mujtahid Ansari, Parashant J Gaidhane 
2.     Harnessing CNN based approach for Detection of Diseases in Ginger Plants
Ashok Sadavare, Priyanka Shinde
3.     Enhanced Stock Market Forecasting Using Hybrid BiLSTM-GRU Models
Kunal Sinha, Akshay Jadhav, Divya Thakur, Dhruv Mendiratta
4.     Enhancing Agricultural Sustainability Through Deep Learning: A Study on Image-Based Plant Disease Detection and Classification
Rupali Maske, B. Bharathit
5.     PVDF-Reinforced Hollow Fiber Membranes for Enhanced Biogas Methane Enrichment
Mr. Anant Awasare, Sanjay Yadav, Vahid Jamadar
6.     Engineering a Secure and Scalable Women's Safety Application: The Guardia Framework
Dr. Rashmi K. Dixit, Sujit Deshpande, Vrushali kondhalkar, Chetan Chauhan
7.     An overview of how nanosilica affects concrete's characteristics
Priyanka Ashok Salunkhe, Dr.Y.M.Patil
8.     Efficient and Effective Optimal Resource Allocation in Wireless Network
Sujeet More, Geetika Narang, Sneha Tirth, Rupali Maske, Amol Bhosale, Anil Sawant
9.     Optimization of Ultrasonic Flow Meter Performance Using ANSYS Adjoint Solver for Varying Flow Conditions
Atul Kolekar, R. B. Teltumade, Tushar Jadhav
10.  Activity Recommendation System Based On Emotion Recognition
Dr. Shilpa Khedkar, Dr. Shraddha Khonde, Mrs.Uma Mahesh Bhokare
11.  Exploring Machine and Ensemble Learning Techniques for Large-Scale Sentiment Analysis
Yamini Singh, Akshay Jadhav, Vipin Jain
12.  A Review on Phase Change Material Cooled Lithium-Ion Battery Thermal Management System
Ashish Rajkumar Devshette, Jitendra Atmaram Hole, Nilesh S Navagale, Nilesh G Jawarkar, Ashish Kumar
13.  A Review on Multisource Crop Mapping and Forecasting Usin

This book captures the proceedings of the International Conference on Advancement in Engineering & Science: Recent Trends & Applications, held at the Karmaveer Bhaurao Patil College of Engineering, Maharashtra, India. It highlights the synergy between research and practical applications to address pressing global and societal needs.

1.     Power System Stability Enhancement by Virtual Inertia Control Strategies for Renewable Energy Integration
M Mujtahid Ansari, Parashant J Gaidhane 
2.     Harnessing CNN based approach for Detection of Diseases in Ginger Plants
Ashok Sadavare, Priyanka Shinde
3.     Enhanced Stock Market Forecasting Using Hybrid BiLSTM-GRU Models
Kunal Sinha, Akshay Jadhav, Divya Thakur, Dhruv Mendiratta
4.     Enhancing Agricultural Sustainability Through Deep Learning: A Study on Image-Based Plant Disease Detection and Classification
Rupali Maske, B. Bharathit
5.     PVDF-Reinforced Hollow Fiber Membranes for Enhanced Biogas Methane Enrichment
Mr. Anant Awasare, Sanjay Yadav, Vahid Jamadar
6.     Engineering a Secure and Scalable Women's Safety Application: The Guardia Framework
Dr. Rashmi K. Dixit, Sujit Deshpande, Vrushali kondhalkar, Chetan Chauhan
7.     An overview of how nanosilica affects concrete's characteristics
Priyanka Ashok Salunkhe, Dr.Y.M.Patil
8.     Efficient and Effective Optimal Resource Allocation in Wireless Network
Sujeet More, Geetika Narang, Sneha Tirth, Rupali Maske, Amol Bhosale, Anil Sawant
9.     Optimization of Ultrasonic Flow Meter Performance Using ANSYS Adjoint Solver for Varying Flow Conditions
Atul Kolekar, R. B. Teltumade, Tushar Jadhav
10.  Activity Recommendation System Based On Emotion Recognition
Dr. Shilpa Khedkar, Dr. Shraddha Khonde, Mrs.Uma Mahesh Bhokare
11.  Exploring Machine and Ensemble Learning Techniques for Large-Scale Sentiment Analysis
Yamini Singh, Akshay Jadhav, Vipin Jain
12.  A Review on Phase Change Material Cooled Lithium-Ion Battery Thermal Management System
Ashish Rajkumar Devshette, Jitendra Atmaram Hole, Nilesh S Navagale, Nilesh G Jawarkar, Ashish Kumar
13.  A Review on Multisource Crop Mapping and Forecasting Usin

CAD CAE CAM - Computing & Information Technology

ICAST-2024 is the 7th International Conference organized by K. J Somaiya Institute of Technology, Sion, Mumbai in association with University of Mumbai.

CAD CAE CAM - Computing & Information Technology

ICAST-2024 is the 7th International Conference organized by K. J Somaiya Institute of Technology, Sion, Mumbai in association with University of Mumbai.

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR, consisting of demographics, medical history, and diagnosis.

1. An Introduction to Electronic Health Records 2. Challenges and Strategies for Extracting Secure Patterns by Using EHR 3. The Art of Organizing EHR Data: A Classification Journey Through Structured, Unstructured, and Semi-Structured Records 4. A blockchain Enabled Framework for Electronic Health Records 5. Cardio Vascular Disease Diagnosis using Deep Learning models 6. A Computational Analysis for the Diagnosis of Schizophrenia Disease Using Machine Learning Methods 7. Predicting Lung Cancer Using Supervised Algorithms:A Machine Learning Approach 8. Article summarising the application of Artificial Intelligence and Machine Learning Techniques to several forms of Electronic Health Records 9. Machine Learning Techniques to Predict the Risk of Chronic Obstructive Pulmonary Disease 10. Dynamic Learning Scheduling Algorithm and Multilayer Perceptron Model for Heart Disease Prediction System 11. Efficient Heart Disease Prediction using IBM Cloud Storage with Auto AI Service 12. Electronic Health Records-A survey

Advances using AI – The Next Wave offers a timely and comprehensive exploration of the latest breakthroughs and future directions in Artificial Intelligence, presenting a forward-looking perspective on how AI is reshaping industries and daily life. It brings together expert insights, making complex concepts accessible and relevant.

1. AI for Rural-Classrooms to Industry-Skilling  2. Decoding Emotions with AI  3. Probabilistic AI: Navigating Uncertainty  4. The Intelligent Journey  5. Harvesting the Stars  6. Stamped in Silicon: When Robots Queue at Customs  7. Smarter, Faster, Greener: AI’s Role in Sustainable 6G  8. Red Flags in Code: AI and the Future of Auditing  9. The Invisible Revolution

Advances using AI – The Next Wave offers a timely and comprehensive exploration of the latest breakthroughs and future directions in Artificial Intelligence, presenting a forward-looking perspective on how AI is reshaping industries and daily life. It brings together expert insights, making complex concepts accessible and relevant.

1. AI for Rural-Classrooms to Industry-Skilling  2. Decoding Emotions with AI  3. Probabilistic AI: Navigating Uncertainty  4. The Intelligent Journey  5. Harvesting the Stars  6. Stamped in Silicon: When Robots Queue at Customs  7. Smarter, Faster, Greener: AI’s Role in Sustainable 6G  8. Red Flags in Code: AI and the Future of Auditing  9. The Invisible Revolution

CAD CAE CAM - Computing & Information Technology

The International Conference on Microstructure, VLSI, Robotics, Communication, Electrical & Emerging Technologies using AI-ML Algorithms (ICMVRCET - 2025).

1 End-to-end AI framework for soil fertility, crop growth, and disease mitigationK. R. Harinath, V. Yagna Sri, A. Mamatha, K. Dileep Reddy and N. Naga Bharath Kumar2 Highly accurate calorie burn prediction using XGBoost regression modelK. R. Harinath, M. Harini, M. Pranitha, K. Prashanth and H. Nagesh3 Real time design of FPGA-based home automation scheme Rama Rao Chekuri, Nagababu Chekuri, Prabhakara Rao Kapula, D Hari krishna, Vurukonda Venkat and Valluri Sai Mahesh 4 AI powered facial recognition for secure banking authentication Alabazar Ramesh, Karanam Jyothirmayi, Kollu Vishnuvardhan, Dayyala Ajay Kiran and Ediga Sheshadri5 Performance comparison of machine learning algorithms in predicting telecom customer attritionPrathap Nayudu P., Venkata Sai S., Amrutha B., Sai Rupa J. and Vigneshwar Reddy K.6 Graphical representation of accuracy comparison among various machine learning algorithms to predict customer churnP. Prathap Nayudu, D. Srivani, N. Usha, S. Ayesha Tabassum, D. Sudheer and D. Sivaramakrishna7 PhishGuard – fake website detection using machine learning K. Janardhan, G. Brahmaiah, E. Abhilash, A. Mohan Vamsi Krishna and K. Prudhvi Raj Naik8 Prediction of chronic kidney disease using machine learning K. Viswanath, S. Durga Pavan Goud, K. Varshitha, S. Rahul and P. Harshitha9 Enhancing autonomous safety B. Swetha, B. Hima Teja, B. Narmada, M. D. S. Mahesh and P. R. Lahari10 Enhancing visual quality of images and videos with improved CNN and OpenCV B. Swetha, P. Suryanarayana, N. Munthaz Begam, A. Tanveer and K. Sai Jaswanth11 A comparative analysis of supervised machine learning algorithms for heart attack prediction K. Narasimhulu, M. Sruthi, P. Rajesh Reddy, C. Navaneeth Kumar and S. Nithin Kumar12 Skin cancer classification: a web-based machine learning approach for skin cancer classification N. R. Sathis Kumar, A

CAD CAE CAM - Computing & Information Technology

The International Conference on Microstructure, VLSI, Robotics, Communication, Electrical & Emerging Technologies using AI-ML Algorithms (ICMVRCET - 2025).

1 End-to-end AI framework for soil fertility, crop growth, and disease mitigationK. R. Harinath, V. Yagna Sri, A. Mamatha, K. Dileep Reddy and N. Naga Bharath Kumar2 Highly accurate calorie burn prediction using XGBoost regression modelK. R. Harinath, M. Harini, M. Pranitha, K. Prashanth and H. Nagesh3 Real time design of FPGA-based home automation scheme Rama Rao Chekuri, Nagababu Chekuri, Prabhakara Rao Kapula, D Hari krishna, Vurukonda Venkat and Valluri Sai Mahesh 4 AI powered facial recognition for secure banking authentication Alabazar Ramesh, Karanam Jyothirmayi, Kollu Vishnuvardhan, Dayyala Ajay Kiran and Ediga Sheshadri5 Performance comparison of machine learning algorithms in predicting telecom customer attritionPrathap Nayudu P., Venkata Sai S., Amrutha B., Sai Rupa J. and Vigneshwar Reddy K.6 Graphical representation of accuracy comparison among various machine learning algorithms to predict customer churnP. Prathap Nayudu, D. Srivani, N. Usha, S. Ayesha Tabassum, D. Sudheer and D. Sivaramakrishna7 PhishGuard – fake website detection using machine learning K. Janardhan, G. Brahmaiah, E. Abhilash, A. Mohan Vamsi Krishna and K. Prudhvi Raj Naik8 Prediction of chronic kidney disease using machine learning K. Viswanath, S. Durga Pavan Goud, K. Varshitha, S. Rahul and P. Harshitha9 Enhancing autonomous safety B. Swetha, B. Hima Teja, B. Narmada, M. D. S. Mahesh and P. R. Lahari10 Enhancing visual quality of images and videos with improved CNN and OpenCV B. Swetha, P. Suryanarayana, N. Munthaz Begam, A. Tanveer and K. Sai Jaswanth11 A comparative analysis of supervised machine learning algorithms for heart attack prediction K. Narasimhulu, M. Sruthi, P. Rajesh Reddy, C. Navaneeth Kumar and S. Nithin Kumar12 Skin cancer classification: a web-based machine learning approach for skin cancer classification N. R. Sathis Kumar, A

Responsible use of AI in public sector applications requires engagement with various technical and non-technical areas such as human rights, inclusion, diversity, innovation, and economic growth. The book covers topics spanning the technological socio-economic spectrum aimed at professionals and researchers. 

Preface ...................................................................................................................... viiAbout the Editors ...................................................................................................... ixList of Contributors ................................................................................................... xi
Chapter 1 Raising a Global Standard in the Procurement of ArtificialIntelligence and Automated Decision Systems .................................... 1Gisele Waters and Cari Miller
Chapter 2 Data Empowerment and Protection Architecture (DEPA)for Training Machine Learning (ML) Models ................................... 35Shyam Sundaram, Kapil Vaswani, Gaurav Agarwal,Sunu Engineer, and AVS Sridhar
Chapter 3 Generative AI Governance: Technological Monoculture, MarketStructure and the Risk of Correlated Failures.................................... 48Ramayya Krishnan, Prasanna Parasurama, Joao Sedoc, andArun Sundararajan
Chapter 4 Empowering Citizens through Responsible AI Governance:Policy Recommendations for Public Algorithm Registers .................51Jens Meijen and Niharika Gujela
Chapter 5 Responsible Adoption of Cloud-Based Artificial Intelligencein Health Care: A Validation Case Study of Multiple ArtificialIntelligence Algorithms for Diabetic Retinopathy Screeningin Public Health Settings .................................................................... 62Mona Duggal, Anshul Chauhan, Ankita Kankaria, Preeti Syal,Vishali Gupta, Priyanka Verma, Vaibhav Miglani,Deepmala Budhija, and Luke Vale
Chapter 6 Participation in AI: Notes from the Trenches .................................... 72Tarunima Prabhakar, Cheshta Arora, a

Advancing Societally Relevant Applications of Knowledge through Scientific Research

Advancements in science and technology are essential for driving research development toward higher goals.

1 Adaptive compression bandage for musculoskeletal injuryBrindha, D., Fasila Begum, A., Hanishka, K. R., Judy, S. M., Lavanya, M. andMohana Priya, V. M.Chape 2 MedForecast: a novel approach for web-based disease predictive healthcare system andpersonalized recommendationsAsqar Ali, S. M. S. A. N. Gnana Jeevan and Rishi Kumar, S.3 Reduction of defects and rework in die plate manufacturing using process improvementmethodologyPrasanth, A. and Prabukarthi, A.4 Glaucoma detection using multi-feature extraction and classification techniquesR. Sreepadmini, Jeya Jemima, V., Janani, P., SathishKumar, S. and Mathumitha, R.5 Improving the quality of injection-molded parts through the use of statisticalprocess control toolsRaghunanthan, R. and Syath Abuthakeer, S.6 Control of optimum argon shrouding practice – a water model studySoorya Prakash Jayaraj, Manjini Sambandam, Viswanathan, N. Nurni and Deepoo Kumar7 Minimum variance approach for sectoral diversification in long-term investment strategiesSai Sundara Krishnan, G., S. Rethika and S. Kathir Kaarthik8 Implementation of lean Six Sigma for reducing lead time and enhancing quality andproductivity in a manufacturing industryM. Gomathi Prabha and C. Emima9 Comparative analysis of K-medoids clustering and frequent episode mining forintrusion detectionShreya Venkatesh and K. Lakshmi Kalpana Roy10 Ultrasound-assisted biodiesel production from waste cooking oil using areca nuthusk derived heterogeneous catalystS. Kavinandhini and S. Niju11 Transporter engineering using GadC for enhanced GABA secretion in yeastSharuprabhaa, S. A., Bala Arun, P. and C. Vignesh Kumar12 siRNA design against DNMT1 overexpressed in triple-negative breast cancer patientsKarthikasri, K. and Shobana Sundar13 Functional foods: exploring meat alternatives with nutritional

Advancing Societally Relevant Applications of Knowledge through Scientific Research

Advancements in science and technology are essential for driving research development toward higher goals.

1 Adaptive compression bandage for musculoskeletal injuryBrindha, D., Fasila Begum, A., Hanishka, K. R., Judy, S. M., Lavanya, M. andMohana Priya, V. M.Chape 2 MedForecast: a novel approach for web-based disease predictive healthcare system andpersonalized recommendationsAsqar Ali, S. M. S. A. N. Gnana Jeevan and Rishi Kumar, S.3 Reduction of defects and rework in die plate manufacturing using process improvementmethodologyPrasanth, A. and Prabukarthi, A.4 Glaucoma detection using multi-feature extraction and classification techniquesR. Sreepadmini, Jeya Jemima, V., Janani, P., SathishKumar, S. and Mathumitha, R.5 Improving the quality of injection-molded parts through the use of statisticalprocess control toolsRaghunanthan, R. and Syath Abuthakeer, S.6 Control of optimum argon shrouding practice – a water model studySoorya Prakash Jayaraj, Manjini Sambandam, Viswanathan, N. Nurni and Deepoo Kumar7 Minimum variance approach for sectoral diversification in long-term investment strategiesSai Sundara Krishnan, G., S. Rethika and S. Kathir Kaarthik8 Implementation of lean Six Sigma for reducing lead time and enhancing quality andproductivity in a manufacturing industryM. Gomathi Prabha and C. Emima9 Comparative analysis of K-medoids clustering and frequent episode mining forintrusion detectionShreya Venkatesh and K. Lakshmi Kalpana Roy10 Ultrasound-assisted biodiesel production from waste cooking oil using areca nuthusk derived heterogeneous catalystS. Kavinandhini and S. Niju11 Transporter engineering using GadC for enhanced GABA secretion in yeastSharuprabhaa, S. A., Bala Arun, P. and C. Vignesh Kumar12 siRNA design against DNMT1 overexpressed in triple-negative breast cancer patientsKarthikasri, K. and Shobana Sundar13 Functional foods: exploring meat alternatives with nutritional

This book explores the exciting fields of Affective Learning, Serious Games, and next-generation educational technologies, shedding light on recent research and its implications for the future of education. These emerging disciplines leverage emotional engagement and game-based learning to enhance educational outcomes. 

Preface. SECTION 1: AFFECTIVE LEARNING. 1. Intelligent Tutoring System using Affective Interaction. 2. The Impact of Avatars Used in Online Education on Learning Effectiveness. 3. Emotion-Driven Story Generation for Game-Based Learning in Virtual Environments. SECTION 2: AFFECTIVE INTERACTION. 4. Pet-type Artifact That Promotes Behavior Change through Emotional Expression. 5. Affective Learning in Human-Robot Interaction. 6. Observation of Students’ Behavior for Affective Learning. 7. Cross-Cultural Perspectives on Persuasive Affective Learning through Information Media. Section 3: SERIOUS GAMES.  8. Serious Games for Teaching Social Media Etiquette Through Simulated Experience. 9. Learning English Through Etymology and Animation: A New Approach for Elementary Students. 10. Experiencing the Role of a Bully: A Serious Game for Anti-Bullying Education. 11. Motivating Athletic Performance: A Throwing Training System with Immersive Feedback. 12. Enhancing Spatial Cognition in Sports Through Virtual Reality Training. 13. Game with a Purpose: Building a Visual Effect Dictionary Through Engaging Gameplay. SECTION 4: XR AND BEYOND: THE FUTURE OF LEARNING. 14. Beyond Flatland: Mixed Reality Geometry for Immersive STEM Learning. 15. Mixed Reality and Generative Art in Mathematics and Programming Education. 16. Immersive Geography Education Through Digital Twins and Virtual Reality. Conclusion. 

Custom AI Solutions for Identity, Innovation, and Adaptive Learning

Framed at the intersection of artificial intelligence, cognitive science, ethics, and organizational practice, the book traces the conceptual foundations of agentic systems while rigorously interrogating their technical architectures and social implications. 

Dedication. Epigraph. Preface. Acknowledgements. List of Figures. List of Tables. Introduction—Agentic AI and the Evolution of Learning. Foundations of Modular AI—Shifting from Monolithic Systems. Fast Learning and AI—Rapid Generation and Iterative Refinement. Slow Learning and AI—Facilitating Reflective Critical Thinking. Identity and Agency—AI-Enhanced Credentialing Systems. Building AI-Ready Organizational Cultures. Custom AI Solutions—Practical Applications Across Domains. Training and Deploying AI Agents for Personal and Professional Use. Conclusion—Toward a New in AI-Enhanced Learning and Work. Index.

AI and Sustainable Transformations presents cutting-edge research and insights into the role of Artificial Intelligence and emerging technologies in driving human-centered innovation and sustainable transformation across various industries.

1. AI for sustainable human-centric solutions 2. Insights, ethics and frameworks in responsible AI

This book examines how contemporary artificial intelligence systems are reshaping social, political, and economic life with unequal consequences. Bringing together critical scholarship from across disciplines, it investigates how AI redistributes power, produces new forms of exclusion, and reconfigures longstanding structures of inequality.

Part 1: AI, Equity, and Health Justice  1. Artificial Intelligence and the Pursuit of Equity: A Scoping Review of Benefits, Harms, and Gaps  2. Beyond White Skin: The Need for Equitable AI in Healthcare  3. What the AI Doesn’t See: On Fairness Proxies in Medical AI  4. Aligning AI for Health Equity: Successes, Gaps, and Barriers in the Canadian Healthcare System  5. Benchmarking Bias: Expanding Clinical AI Model Card to Incorporate Bias Reporting of Social and Non-Social Factors  6. Responsible Foundation Models for Healthcare: Risks, Opportunities, and Pathways to Responsibility  7. Evaluating AI Safety, Hallucinations, Psychosis and Bias Using Clinical Simulations  8. Addressing Structural Bias in AI-Driven Healthcare: From Technical Fixes to Equity-by-Design  Part 2: Disability, Education, and Techno-Ableism  9. Disability-centered Policy Opportunities and Challenges for Accessible and Inclusive AI: A Scoping Review  10. Rethinking Artificial Intelligence for Sickle Cell Disease – A Bounded Justice and Disability Justice Approach  11. Beyond ‘Technoableism’: AI, Ableism, and Accommodations in Postsecondary/STEM Education  12. AI, Technoableism, and Computing Education: Assessing Conceptual Entry Points  13. AI, Social Media, and People with Disabilities: A Critical Review  14. Epistemic Injustice and Disability-Evasiveness  Part 3: AI in Society—Gender, Labor, and Relationships  15. Misogyny by Design: The Manosphere, AI, and Technology-Facilitated Gender-Based Violence  16. Intimate Inequities: Examining the Benefits and Risks of AI in Online Dating for Marginalized Populations  17. AI and Social Reproduction: Social Structures of Dominance and Control  Part 4: Governance, Power, and Bias in AI Systems  18. No More Radical Ethical Uncertainty: GenAI and Higher Education within Structures of Capital  19. A Cognitive Usability Engineering Approach to Understanding Bias in Human-AI Interaction  20. Toward a Leftist Artificial Intellig

This book discusses the adverse effects of climatic changes on our planet. It examines AI-based tools and technologies and how they can assist in identifying energy emission reductions, CO2 removal, and support the development of greener transportation networks, monitoring deforestation, and forecast extreme weather events.

Chapter 1- AI For Sustainable and Eco-Friendly Environment For Climate Change
Chapter 2- Enhancing Climate Change Prediction and Risk Assessment with Deep Learning: Architectural Approaches and Data Challenges
Chapter 3- AI- and IoT-Based Application for Rainfall Prediction: A Study
Chapter 4- Machine-Learning Based Prediction of Wind Speed for Ratnagiri Region, India
Chapter 5- Wind Power Forecasting with Machine Learning Approach
Chapter 6- IOT Communication Technologies                                                                                                                
Chapter 7- Machine Learning Models for Intelligent Hazard Management
Chapter 8- Optimal Dispatch of Distributed Renewable Energy Sources in Isolated Microgrid System Exploiting Metaheuristic Optimization Algorithms
Chapter 9- Leveraging Machine Learning Models for Intelligent Hazard Management
Chapter 10- Practical and Innovative Applications of IOT and IOT Networks (Smart Cities, Smart  Mobility, Smart Home, Smart Health, Smart Grid, etc.)
Chapter 11- Leveraging Artificial Intelligence in Climate Change Interpretation: Overcoming Challenges in Risk Management Approach
 
 

This edited book is a multi-disciplinary reference on how domain-aware AI models can outperform generic approaches by addressing sector-specific complexities. It is for academics and researchers in computer science, AI, and data science; industry professionals in transportation, software engineering, finance; and policymakers.

Part 1: Introduction  1. Introduction: From Generic AI to Domain-Aware Decision Systems  2. Comparative Analysis of CNN and Quaternion CNN for Image-Based Road Crack Detection in Computer Vision  3. Self-Structuring Neural Networks for Optimized Data Analytics Using EMANN-Like Algorithms  4. Scalable Data Science Workflow in the Cloud  5. Survey of Trustworthy AI Frameworks: Interpretability, Fairness, and Robustness Across Domains  Part 2: Connecting Foundations to Applied Trustworthy AI  6. AI-based Sustainability Supply Chain Experimental Observations System: A Comprehensive Analysis  7. Transforming Supply Chain Management Through AI-Driven Predictive Analytics  8. Predictive Maintenance in Critical Infrastructure Using Graph Neural Networks  9. AI for Smart Transportation: Road Safety, Traffic Flow, and Accident Prevention  Part 3: Decision Intelligence for Safer, Greener Infrastructure  10. Securing Critical E-commerce Infrastructure: Unsupervised Learning and LLM-Enhanced Anomaly Detection for Web-Based Attacks  11. Advancing Software Quality with Large Language Models, Deep Learning, and Cloud Infrastructure  12. Enhancing Software Reliability Prediction with Machine Learning: Addressing Data Noise and Model Consensus 13. AI for Cyber-Physical Security in Industrial IoT Systems  14. Trustworthy LLMs for Mission-Critical Applications: Benchmarks and Gaps  Part 4: Building Reliable and Secure AI Systems  15. Bridging Theory and Practice: A LangChain-Based Virtual Assistant for Corporate AI Integration  16. Uncovering Non-Linear Drivers of Equity Valuation Across Sectors  17. AI-Driven Risk Modeling and Stress Testing in Financial Services  18. Decision Intelligence in Healthcare Finance and Insurance Systems  Part 5: AI-Enhanced Decision-Making in Business and Finance  19. Unleashing Human Potential: Advancing Cognitive Capabilities Through AI-Designed Neural Interfaces  20

This edited book is a multi-disciplinary reference on how domain-aware AI models can outperform generic approaches by addressing sector-specific complexities. It is for academics and researchers in computer science, AI, and data science; industry professionals in transportation, software engineering, finance; and policymakers.

Part 1: Introduction  1. Introduction: From Generic AI to Domain-Aware Decision Systems  2. Comparative Analysis of CNN and Quaternion CNN for Image-Based Road Crack Detection in Computer Vision  3. Self-Structuring Neural Networks for Optimized Data Analytics Using EMANN-Like Algorithms  4. Scalable Data Science Workflow in the Cloud  5. Survey of Trustworthy AI Frameworks: Interpretability, Fairness, and Robustness Across Domains  Part 2: Connecting Foundations to Applied Trustworthy AI  6. AI-based Sustainability Supply Chain Experimental Observations System: A Comprehensive Analysis  7. Transforming Supply Chain Management Through AI-Driven Predictive Analytics  8. Predictive Maintenance in Critical Infrastructure Using Graph Neural Networks  9. AI for Smart Transportation: Road Safety, Traffic Flow, and Accident Prevention  Part 3: Decision Intelligence for Safer, Greener Infrastructure  10. Securing Critical E-commerce Infrastructure: Unsupervised Learning and LLM-Enhanced Anomaly Detection for Web-Based Attacks  11. Advancing Software Quality with Large Language Models, Deep Learning, and Cloud Infrastructure  12. Enhancing Software Reliability Prediction with Machine Learning: Addressing Data Noise and Model Consensus 13. AI for Cyber-Physical Security in Industrial IoT Systems  14. Trustworthy LLMs for Mission-Critical Applications: Benchmarks and Gaps  Part 4: Building Reliable and Secure AI Systems  15. Bridging Theory and Practice: A LangChain-Based Virtual Assistant for Corporate AI Integration  16. Uncovering Non-Linear Drivers of Equity Valuation Across Sectors  17. AI-Driven Risk Modeling and Stress Testing in Financial Services  18. Decision Intelligence in Healthcare Finance and Insurance Systems  Part 5: AI-Enhanced Decision-Making in Business and Finance  19. Unleashing Human Potential: Advancing Cognitive Capabilities Through AI-Designed Neural Interfaces  20

What if theology was never meant to be static? What happens when the act of faith is reimagined across generations, cultures, and now, code? How can diverse theological perspectives work together to build ethical AI?

1: Reimagining Genesis in the Age of AI 2: Incarnation in a Disembodied Age: The Flesh Shall Stream 3: Rewriting the Fall for the Algorithmic Age 4: Revelation, Silence, and Divine Disclosure in a Networked Age 5: Rituals of Code and the Search for Sacred Time 6: The Flesh Made Code and the Ethics of Embodied Flourishing 7: Hope, Judgment, and the End(s) of AI 8: Cyborgs, Care, and Christological Kinship 9: A Call to Digital Resistance and Holy Disruption 10: Case Studies in Theological Resistance Appendix: A Remix Manifesto for AI and the Church

This book examines the human side of AI adoption at a time when technology is advancing faster than consumer comfort. Millions use AI to search, plan, create, and make decisions, but trust remains fragile. Cakim explains why that gap persists, and what it means for marketers trying to reach audiences who are both curious and cautious.

Section 1: Understanding the AI Landscape from the Consumer Perspective.  1. The AI Trust Gap.  2. The Consumer Pain Points with AI.  3. The Opportunities for Growth.  4. Consumer Touchpoints and Comfort Zones.  5. AI Adoption Propellers.  6. The Gender Divide in AI Adoption.  7. Building Trust – The Human Foundations of AI Adoption.  8. The Reallocation Effect – How AI Re-Writes the Media Rules.  9. What’s Next for Brand Marketing Teams.  Section 2: The Evolving Landscape of AI in Marketing: Insights from Senior Business Leaders on Best Practices, Challenges and the Future.  10. Inside Today’s AI Marketing Landscape.  11. Challenges in AI Implementation.  12. Solutions and Best Practices.  13. The Future of Marketing – AI, Creativity and Human Connection.  Conclusion.  Epilogue.

This book examines the human side of AI adoption at a time when technology is advancing faster than consumer comfort. Millions use AI to search, plan, create, and make decisions, but trust remains fragile. Cakim explains why that gap persists, and what it means for marketers trying to reach audiences who are both curious and cautious.

Section 1: Understanding the AI Landscape from the Consumer Perspective.  1. The AI Trust Gap.  2. The Consumer Pain Points with AI.  3. The Opportunities for Growth.  4. Consumer Touchpoints and Comfort Zones.  5. AI Adoption Propellers.  6. The Gender Divide in AI Adoption.  7. Building Trust – The Human Foundations of AI Adoption.  8. The Reallocation Effect – How AI Re-Writes the Media Rules.  9. What’s Next for Brand Marketing Teams.  Section 2: The Evolving Landscape of AI in Marketing: Insights from Senior Business Leaders on Best Practices, Challenges and the Future.  10. Inside Today’s AI Marketing Landscape.  11. Challenges in AI Implementation.  12. Solutions and Best Practices.  13. The Future of Marketing – AI, Creativity and Human Connection.  Conclusion.  Epilogue.

Kowshik, Raghu Vijay | Sorenson, Peter Jay

AI for the Ordinary is a timely and accessible guide that demystifies artificial intelligence for everyday citizens and non-technical professionals. It makes a compelling case that AI is not the exclusive domain of coders and technologists – it is a civic, economic, and personal imperative for life and leadership in the 21st century.

Foreword. Preface. Acknowledgements.  Part 1  Foundations of Artificial Intelligence: Concepts, Personas, and Agents 1. What Is Artificial Intelligence?  2. The Core Types of AI  3. AI Across Industries: A Global Overview  4. The Ethical Challenges of AI  5. Understanding the AI Persona  6. AI Personas in Organizational Settings  7. Understanding the AI Agent  8. AI Agents in Organizational Settings  9. How AI Agents Differ from AI Personas  Part 2  AI in Everday Life: Global Influence and Human Experience 10. Revisiting AI: A Clearer Understanding  11. AI's Global Influence: Transforming Work, Society, and Opportunity  12. What AI Means for Ordinary People  13. AI in Daily Life: A Global Perspective  Part 3  Human-Centered and Ethical AI: Principles and Practice 14. What is Human-centered AI?: And Why It Matters 15. Strategies for Implementing Human-Centered AI  16. Ethical AI: Principles, Risks, and Responsibilities  Part 4  The Future of AI: Global Trends, Societal Change, and Human Possibility  17. The Future of AI: What to Expect  18. Preparing for an AI-Adaptive Society  19. AI Adoption Around the World  20. Global AI Trends: Impacts on Work, Innovation, and Society  21. AI's Impact on the Everday Lives of Ordinary People  22. Will AI Dominate Humanity? Understanding the Real Risks. Glossary of Key Terms. References. Index

Kowshik, Raghu Vijay | Sorenson, Peter Jay

AI for the Ordinary is a timely and accessible guide that demystifies artificial intelligence for everyday citizens and non-technical professionals. It makes a compelling case that AI is not the exclusive domain of coders and technologists – it is a civic, economic, and personal imperative for life and leadership in the 21st century.

Foreword. Preface. Acknowledgements.  Part 1  Foundations of Artificial Intelligence: Concepts, Personas, and Agents 1. What Is Artificial Intelligence?  2. The Core Types of AI  3. AI Across Industries: A Global Overview  4. The Ethical Challenges of AI  5. Understanding the AI Persona  6. AI Personas in Organizational Settings  7. Understanding the AI Agent  8. AI Agents in Organizational Settings  9. How AI Agents Differ from AI Personas  Part 2  AI in Everday Life: Global Influence and Human Experience 10. Revisiting AI: A Clearer Understanding  11. AI's Global Influence: Transforming Work, Society, and Opportunity  12. What AI Means for Ordinary People  13. AI in Daily Life: A Global Perspective  Part 3  Human-Centered and Ethical AI: Principles and Practice 14. What is Human-centered AI?: And Why It Matters 15. Strategies for Implementing Human-Centered AI  16. Ethical AI: Principles, Risks, and Responsibilities  Part 4  The Future of AI: Global Trends, Societal Change, and Human Possibility  17. The Future of AI: What to Expect  18. Preparing for an AI-Adaptive Society  19. AI Adoption Around the World  20. Global AI Trends: Impacts on Work, Innovation, and Society  21. AI's Impact on the Everday Lives of Ordinary People  22. Will AI Dominate Humanity? Understanding the Real Risks. Glossary of Key Terms. References. Index

This book provides a thorough exploration of the latest innovations in AI for general time series analysis, distribution shift and foundation models. It offers an in-depth look at cutting-edge techniques and methodologies, using advance algorithms that are transforming time series analysis across industries.

1 Introduction 2 Fedformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting 3 Fredf: Learning to Forecast in the Frequency Domain 4 PPGF: Probability Pattern-Guided Time Series Forecasting 5 Unlocking the Power of Lstm for Long Term Time Series Forecasting 6 Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification 7 Diffusion Language-Shapelets for Semi-Supervised Time-Series Classification 8 Graph-Aware Contrasting for Multivariate Time-Series Classification 9 Dcdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection 10 Multivariate Anomaly Detection with Self-Learning Graph Convolutional Networks 11 Self-Attention-Driven Imputation for Multivariate Time Series

This book provides a thorough exploration of the latest innovations in AI for general time series analysis, distribution shift and foundation models.

Section 1 Introduction on AI for Time Series Analysis 1. Introduction Chapter – Domain Adaptation and Foundation Models Section 2 AI for General Time Series Analysis 2. TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis 3. TSLANet: Rethinking Transformers for Time Series Representation Learning Section 3 AI for Distribution Shift in Time Series 4. OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling 5. SEA++: Multi-Graph-based Higher-Order Sensor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation 6. AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data Section 4 Time Series Foundation Models 7. Time-LLM: Time Series Forecasting by Reprogramming Large Language Models 8. LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization 9. Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting 10. Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts 11. EEG Foundation Model 12. PHM Foundation Model
 

This book provides a thorough exploration of the latest innovations in AI for general time series analysis, distribution shift and foundation models.

Section 1 Introduction on AI for Time Series Analysis 1. Introduction Chapter – Domain Adaptation and Foundation Models Section 2 AI for General Time Series Analysis 2. TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis 3. TSLANet: Rethinking Transformers for Time Series Representation Learning Section 3 AI for Distribution Shift in Time Series 4. OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling 5. SEA++: Multi-Graph-based Higher-Order Sensor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation 6. AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data Section 4 Time Series Foundation Models 7. Time-LLM: Time Series Forecasting by Reprogramming Large Language Models 8. LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization 9. Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting 10. Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts 11. EEG Foundation Model 12. PHM Foundation Model
 

AI Forensics provides a comprehensive framework for investigating artificial intelligence systems when they fail, cause harm, or become subjects of legal or regulatory scrutiny. As AI systems power critical decisions, traditional digital forensics proves inadequate for understanding their complex, opaque and dynamic behaviors.

1. Introduction to AI Forensics  2. Overview of AI Systems for Forensic Investigators  3. Knowledge Gathering and Scoping  4. Evidence Collection  5. Training Data Analysis  6. Model Investigation  7. Output Analysis  8. Documentation Analysis  9. Synthesis and Reporting  10. Appendix A: Glossary of Terms Appendix B: AI Forensic Collection and Analysis Environments Appendix C: LLM Resume Screening Sample Investigation Appendix D: AI Forensics Investigation Templates

AI Forensics provides a comprehensive framework for investigating artificial intelligence systems when they fail, cause harm, or become subjects of legal or regulatory scrutiny. As AI systems power critical decisions, traditional digital forensics proves inadequate for understanding their complex, opaque and dynamic behaviors.

1. Introduction to AI Forensics  2. Overview of AI Systems for Forensic Investigators  3. Knowledge Gathering and Scoping  4. Evidence Collection  5. Training Data Analysis  6. Model Investigation  7. Output Analysis  8. Documentation Analysis  9. Synthesis and Reporting  10. Appendix A: Glossary of Terms Appendix B: AI Forensic Collection and Analysis Environments Appendix C: LLM Resume Screening Sample Investigation Appendix D: AI Forensics Investigation Templates

This book explains the best practices and their respective outcomes in AI to meet sustainable development goals. It examines the practices, technologies, and innovations at the core of various research issues to meet the sustainable development demands in agriculture to balance social, economic, and environmental sustainability with AI.

1. Artificial Intelligence: Towards sustainable, smart, and green agriculture.  2. Artificial Intelligence in Achieving Sustainable Development Goals: Models and Approaches.  3. Smart Solutions for a Sustainable Future: Unlocking the Potential of AI for a Sustainable Future in Architecture, Energy, and Agriculture.  4. AI for Optimization of Farming Resources and their Management.  5. Democratising Intelligent Farming Solutions to Develop Sustainable Agricultural Practices.  6. AI- driven approach for Precision Agriculture.  7. Precision Agriculture and AI: Nurturing Sustainable Food Ecosystems.  8. Agriculture and AI: A Subtle Conjunction of Predictive Analysis and Voice Assistant in the World of Agriculture.  9. Machine Learning and IoT in Smart Agriculture.  10. Empowering Agriculture: IoT for Sustainable Farming Practices.  11. An Analysis Efficient Cloud Based Scheduling Infrastructure: Driving the Shift of Artificial Intelligence in Farming.  12. Animal Intrusion Detection System using Semantic Segmentation and YOLO V4 Object Detector.  13. Smart Farming for Sustainable Development – A Study at Sonepur District of Odisha.  14. Analytical Approaches to Sustainable Farming Systems.  15. Is Ethiopia Coffee Cooperatives Farmers Proficient to Predict Capital Structure with Mediation of AI Based Knowledge Systems and Asset Liquidity?.  16. Is Marketing Intermediaries’ Mediation required for Livestock and Products Marketing to uplift the Economic Status of Pastoralist Community in Ethiopia?.  

The rising demand for smart technologies necessitates the need of upgrading current systems to effectively cater to these expectations. This book serves as an extensive resource that aims to facilitate the integration of ancient and contemporary technologies, guiding readers during the whole process of conversion.

1. AI-Augmented IIoT: Using Edge-based Deep Learning to Improve Industrial Intelligence and Reduce Network Congestion  2. AI-Powered Deep Learning Methods for Intelligent Manufacturing's Real-Time Image Recognition  3. Autonomous Driving Using Reinforcement Learning in Real World  4. Integrating AI in Industry: Automation and Innovation  5. Smart Traffic Signal Integrated with AI Powered Drone Surveillance  6. An AI-Driven Framework for Emotion-Aware Script Generation Using Real-Time Facial Expression Recognition and GPT-2 Medium  7. Securing AI Systems: Strategies for Privacy and Protection  8. Building Trustworthy AI Systems: Ethics and Governance  9. Artificial Intelligence for Sustainable Design and Manufacturing  10. AI in Energy Management Strategies for Environmental Sustainability  11. The Impact of AI on Human-Machine Collaboration: Defining the Future of Work with AI  12. AI-Driven Scalable Deep Learning for Real-Time Industrial NLP with Hybrid and Multimodal Integration  13. Enhancing Human-Robot Collaboration through Neuro-Symbolic and Neuromorphic AI  14. Boosting Manufacturing Productivity with Robotics and AI  15. AI and Sustainability: Advancing Socially Responsible Practices  16. Al in Management: Challenges and Solutions in Implementation

AI, Cybersecurity and Data Science for Drone and Unmanned Aerial Vehicles

This book explores the transformative impact of drone technology and unmanned aerial systems (UAS) across diverse industries, from precision agriculture and logistics to disaster response and forensic investigations. 

1. Introduction to Drones, UAVs, and their applications 2. Precision Agriculture Takes Flight: Drone Technology in Crop Management 3. Drone Swarms and Autonomous System 4. Drones in Delivery and Logistics Transforming Transportation Systems 5. Utilizing AI and UAVs for Disaster Response in Smart Cities 6. Integrated Forensic Methodologies for UAS 7. Challenges and Risks of Drone Technology

The demand for telehealth solutions has been growing exponentially after the Covid-19 pandemic. Hospitals remain understaffed, which leads to staff burnouts and unsatisfactory patient experience.

Telehealth Solution Market Demands in China and in Europe (Germany, Denmark and Italy). Developing the Innovation Ecosystem: A Case Study on the Chinese Digital Healthcare Industry. Use of AI in Combating COVID-19: Practices in Different Economies. COVID-19 and the Digitalization of the Healthcare System.

AI-driven Cyber Risk Management explores cutting-edge AI applications in cybersecurity, covering threat detection, fraud prevention, and risk quantification. The book examines machine learning, big data analytics, XAI, and blockchain integration for resilient defense.

1. Foundations of Cyber Risk Management 2. The Rise of AI and Risk Management 3. The Future of Cyber Risk Management in an AI-driven World 4. Artificial Intelligence in Cyber Risk Management: Revolutionizing Threat Detection and Resilience 5. AI for Threat Detection and Intelligence 6. Empowering Cybersecurity with AI: Advanced Threat Detection, Predictive Intelligence, and Real-time Defense 7. AI-powered Risk Mitigation and Intelligent Incident Response in Cybersecurity 8. Challenges in Cyber Risk Analysis Using Big Data and AI Models 9. Rising Impact of AI in Cyber Risk Management in the Context of Small- and Medium-sized Enterprises 10. Toward Resilient Cyber Defense: Integrating AI and Blockchain for Smart Risk Management 11. Advanced Approaches to Fraud Detection and Financial Risk Mitigation Using Intelligent Analytics 12. XAI-driven Approaches to Detect Financial Frauds and Mitigate Risk 13. MIND-SHIELD: A Multi-Intelligence Deep Learning Framework for Hierarchical Threat Detection and Zero-shot Situational Intelligence Process 14. Integrating AI into Cybersecurity Infrastructure: A Case Study on Dynamic C&C Server Architecture (PhantomNet) 15. Automating Cybersecurity Risk Assessments with a Modern Penetration Testing Approach (PenTest Pro)

This book studies how AI technologies can be utilized to tackle the complex challenges encountered in urban areas, spanning from ethical, social, and environmental implications across urban governance and beyond.

1. AI-Driven Strategies: An Overview Towards Inclusive and Sustainable Urbanization. 2. Ethical Implications of AI in Urban Governance. 3. Community Engagement in AI-Driven Urban Development. 4. AI for Environmental Sustainability in Urban Areas. 5. Digital Inclusion and Accessible Technologies in Smart Cities. 6. Civic Technology and Open Data: Transforming Urban Governance for Participatory Democracy. 7. Adaptive Cities: AI-Based Climate Resilience Strategies from Sensor Networks. 8. AI Strategies for Effective Text Summarization in Urban Contexts: Insights and Developments. 9. Adopting AI in Local Government Green Infrastructure Procurement. 10. AI-Based Water Quality Detection and Monitoring in Urban Environments. 11. Building Inclusive Smart Cities: The Role of Mathematical Models and AI Applications. 12. Inclusive and Sustainable Urbanization Towards Sustainable Development Goals.

This book studies how AI technologies can be utilized to tackle the complex challenges encountered in urban areas, spanning from ethical, social, and environmental implications across urban governance and beyond.

1. AI-Driven Strategies: An Overview Towards Inclusive and Sustainable Urbanization. 2. Ethical Implications of AI in Urban Governance. 3. Community Engagement in AI-Driven Urban Development. 4. AI for Environmental Sustainability in Urban Areas. 5. Digital Inclusion and Accessible Technologies in Smart Cities. 6. Civic Technology and Open Data: Transforming Urban Governance for Participatory Democracy. 7. Adaptive Cities: AI-Based Climate Resilience Strategies from Sensor Networks. 8. AI Strategies for Effective Text Summarization in Urban Contexts: Insights and Developments. 9. Adopting AI in Local Government Green Infrastructure Procurement. 10. AI-Based Water Quality Detection and Monitoring in Urban Environments. 11. Building Inclusive Smart Cities: The Role of Mathematical Models and AI Applications. 12. Inclusive and Sustainable Urbanization Towards Sustainable Development Goals.

AI, Green Infrastructure, and Policy Innovation for Heat-Ready Cities

This book offers a comprehensive exploration of how artificial intelligence, ecological design, and governance reforms can be leveraged to tackle climate-induced urban heat.

Part I: Artificial Intelligence for Urban Climate Adaptation.  1. Integrating Machine Learning for Urban Sustainability.  2. Urban AI Applications in Heat Mapping.  3. Microclimate Risk Monitoring through Real-Time Platforms.  4. Integrated Planning for Climate-Resilient Cities.  Part II: Green Infrastructure and Design Innovation.  5. Vegetation Strategies for Urban Heat Mitigation.  6. Tree Placement for Cooling Microclimates.  7. AI-Driven Green Infrastructure Optimisation.  Part III: Policy, Planning, and Global Perspectives.  8. Urban Climate Policy in the Global South.  9. Transit-Oriented Development and Urban Heat.  10. Policy and Technology Responses to Urban Heat.

This book explores AI-driven gait analysis, assistive robotics, Blockchain incentives and AI-powered diet management. It transforms healthcare with AI, IoT, Blockchain, highlighting GAN-based emergency staffing, multisensory rooms for disabilities. It provides innovations, challenges, and future directions and enhancing quality of life.

1. Future Aspects of Assisted Living in the Transition from Healthcare 4.0 to Healthcare 5.0. 2. Cloud-Based Intelligent Remote Healthcare for Ambient Living Using Internet of Medical Things (IoMT). 3. Fog Computing and IoT-Based Smart Communication Architecture for Ambient Assisted Living. 4. Machine-Learning-Driven Gait Analysis and Motion Detection for Parkinson's Disease Classification. 5. AI for Disease Management, Medication Management, and Rehabilitation Care. 6. AI for Assistive Robots. 7. 5G Technology in Assisted Living: Revolutionizing Healthcare and Enhancing Quality of Life. 8. Enhancing Ambient Assisted Living with Blockchain and Token Incentives. 9. Diet Management for Diabetes Patients Using AI. 10. Large Language Models, Large Visual Models, and Big Data for Assisted Living in Healthcare 5.0. 11. Personalized Healthcare Services for Assisted Living in Healthcare 5.0. 12. Revolutionizing Clinical Decision-Making: The Role of NLP in Modern Healthcare. 13. Sentiment Analysis and Well-Being for Assisted Living in Healthcare 5.0. 14. Enhanced Language Support for Diversified Doctor–Patient Communication. 15. Optimizing Emergency Staffing Under Uncertainty: GAN-Driven Scheduling with Resilient Elephant Clan Optimization. 16. Technology in Disability Support: A Case Study of Teachers' Initial Experience of Using Multisensory Rooms to Engage Children with Disability in Learning. 17. Ethical Consideration in Assisted Living Technology in Healthcare.

This book covers most of the areas of DRL with a special focus on its mathematical and algorithmic foundations. It is a useful guide for undergraduate and early graduate students to the fast-developing areas of DRL and its myriad applications. 

This book covers most of the areas of DRL with a special focus on its mathematical and algorithmic foundations. It is a useful guide for undergraduate and early graduate students to the fast-developing areas of DRL and its myriad applications. 

In order to gather, integrate, and synthesise the many results and viewpoints in the connected domains, refer to it as interdisciplinary research. In light of this, the theory, techniques, and applications of machine learning and AI, as well as how they are utilised across disciplinary boundaries, are the main areas of this research topic.

Part I  Healthcare 
Chapter 1 ¿ Machine Learning-Based Prediction of Thyroid Disease
Tanjina Rhaman and Sukhpal Singh Gill
Chapter 2 ¿ HeartGuard: A Deep Learning Approach for Cardiovascular Risk Assessment Using Biomedical Indicators Using Cloud Computing
Parinaz Banifatemi and Sukhpal Singh Gill
Chapter 3 ¿ Deep Convolutional Neural Networks-Based Skin Lesion Classification for Cancer Prediction
Neelam Rathore and Sukhpal Singh Gill
Chapter 4 ¿ Explainable AI for Cancer Prediction: A Model Analysis
Aswin Kumar Govindan and Sukhpal Singh Gill
Chapter 5 ¿ Machine Learning-Based Web Application for Breast Cancer Prediction
Shabnam Manjuri and Sukhpal Singh Gill
Part II Natural Language Programming (NLP)
Chapter 6 ¿ Machine Learning-Based Opinion Mining and Visualization of News RSS Feeds for Efficient Information Gain
Jairaj Patil and Sukhpal Singh Gill
Part III Economics and Finance
Chapter 7 ¿ Advanced Machine Learning Models for Real Estate Price Prediction
Satyam Sharma and Sukhpal Singh Gill
Chapter 8 ¿ Stock Market Price Prediction: A Hybrid LSTM and Sequential Self-Attention-Based Approach
Karan Pardeshi, Sukhpal Singh Gill, and Ahmed M. Abdelmoniem
Chapter 9 ¿ Federated Learning for the Predicting Household Financial Expenditure
Ho Kuen Lai, Ahmed M. Abdelmoniem, and Sukhpal Singh Gill
Part IV Computing and Business
Chapter 10 ¿ Deep Neural Network-Based Prediction of Breast Cancer Using Cloud Computing
Sindhu Muthumanickam and Sukhpal Singh Gill
Chapter 11 ¿ Performance Analysis of Machine Learning Models for Data Visualisation in SME: Google Cloud vs. AWS Cloud
Jisma Choudhury and Sukhpal Singh Gill
Part V Security and Edge/Cloud Computing
Chapter 12 ¿ Enhancing Data Security for Cloud Service Provi

This book explores cutting-edge AI solutions for disease prediction, medical imaging, mental health analysis, and healthcare decision-making. A must-read for researchers, practitioners, and innovators, it offers insights into the future of AI-driven healthcare.

1. Explainable AI-based Heart Attack Prediction Model using Various Machine Learning and Ensemble Learning Approaches.   2. Predicting Heart Block and Its Type using Ensemble-based Machine Learning.   3. Towards COVID-19 Detection Information System based on AIoT.   4. Tomato Leaf Disease Detection Using Convolutional Neural Network.   5. An Automatic Recognition System for Thyroid Nodule in Ultrasound Images using Convolutional Neural Network.   6. Malnutrition prediction among under-five children using Machine learning techniques.   7. Prediction of Depression Severity via Feature Grouping and Machine Learning with Burn Depression Checklist.   8. Comparative Analysis of Machine Learning Methods for Symptoms based COVID-19 Detection.   9. BCNet-11: A dilated convolutional neural network for breast cancer classification using histopathology images.   10. Age Estimation from Human Facial Expression using Deep Neural Network.   11. Detecting Depression from Social Media Posts Using Comprehensive Machine Learning Approaches with TF-IDF and N-Grams.   12. An Ensemble Approach and Comparison of LSTM, Bi-LSTM, and GNN Models to Predict Protein Secondary Structure.   13. Psychological Stress Prediction of Human Using Machine Learning Algorithms.   14. Face Mask Detection Using CNN: Ensuring Safety During COVID-19.   15. Approximating the Survival Possibility of Post Thoracic Surgery for Lung Cancer using Machine Learning.   16. Time-Frequency Analysis using fNIRS Signal for Pain Detection on Hemodynamic Response.   17. A Study on Different SVM Kernels with Suitable Pre-Processing Technique and Parameter Optimization for Cardiovascular Disease Prediction.

This book explores the latest advancements in machine learning techniques and their transformative applications in the healthcare domain. It delves into the use of machine learning for disease diagnosis and prognosis, showcasing its potential to enable accurate disease identification, effective risk stratification, and treatment planning. 

1:  Ant Colony Optimization and Grey Wolf Optimization - A Comparative Study for Healthcare Resource Allocation During COVID-19 Across States in India 2: AI-Based Decision Support Systems for Personalized Maternal Health Management Before Pregnancy 3: Advances in Deep Neural Networks for Chronic Kidney Disease Diagnosis: A Systematic Review 4: Beyond Crystal Balls: Machine Learning's Role in Proactive Healthcare - Predicting and Preventing Disease Outcomes 5:  Unveiling the Veil: A Comprehensive Exploration of Interpretable Machine Learning for Healthcare and its Role in Elevating Transparency in Decision Support 6: A Comprehensive Exploration of How Deep Learning is Revolutionizing Patient Care in the Healthcare Landscape 7: Smart Healthcare Ecosystems: A Deep Dive into Applications, Advancements, and Ethical Considerations of Deep Learning Technologies 8: Healing Intelligence: A Deep Dive into the Cognitive Revolution of Healthcare through Advanced Deep Learning Technologies 9: Innovating at the Nexus: Unravelling the Impact of Deep Learning on Healthcare and Its Transformative Effect on Patient-Centric Solutions and Clinical Decision Support 10: Enhancing Healthcare Data Governance and Security: The Role of Adaptive Data Management Middleware in Federated Cloud Environments 11: Skin Cancer Detection Using U-Net 12: Revolutionizing Heart Disease Diagnosis using Machine Learning: A Case Study in Data-Driven Health care 13: Predicting drug response using Deep Learning techniques 14: Multimodal PCOS Detection: Combining XG Boost for Images with Zero Shot Learning for Textual Data 15:  Revolutionizing Healthcare: Leveraging Fine-Tuned Large Language Models for Personalized Question-Answering Chatbots 16:  Best Donor Selection for Liver Transplantation Using Artificial Neural Network and Machine Learning Algorithms 17: Clinical Decision Support Systems in Pre-Pregnancy Health: A Comparative Review of Traditional, Machine Learning,

The main objective of this conference is to encourage the integration of Mathematics, Automation and Computing, fostering interdisciplinary research that can address complex problems in Science, Engineering and Technology.

The main objective of this conference is to encourage the integration of Mathematics, Automation and Computing, fostering interdisciplinary research that can address complex problems in Science, Engineering and Technology.

This book provides an examination of cutting-edge research and developments in the field of Artificial Intelligence. It seeks to extend the view in technical and societal evaluations to ensure a well-defined balance for societal outcomes. It explores ot topics such as Generative Artificial Intelligence, and Quantum Artificial Intelligence. 

Chapter 1- Advancements in Remote Sensing of the Cryosphere in Polar Regions: Contributions of Artificial Intelligence Techniques Over the Last Decade
Chapter 2- An Empirical Study on Climate Change Using Geospatial Artificial Intelligence: Analysis of Particulate Matter 2.5
Chapter 3- Artificial Intelligence in Gaming
Chapter 4- Artificial Intelligence in Education and Its Applications in The World - Measurement and Assessment
Chapter 5- Positioning AI in Creative Industries: Challenges and Opportunities for Workforce
Chapter 6- Dynamical Systems and Artificial Intelligence
Chapter 7- Emerging Technologies and Power Asymmetry in International System: An Analysis over Artificial Intelligence
Chapter 8- Looking at Artificial Intelligence (AI) From Social Relations: Social Influence, Conformity and Bias
Chapter 9- Legal Aspects of Artificial Intelligence in Health: An Overview under Turkish and Comparative Law
Chapter 10- GPT-based Audience Attention and Emotion Analysis
Chapter 11- Artificial Intelligence and Patent Law: Patent Applications for DABUS
Chapter 12- Combining Blockchain and AI: The Two Disruptive Technology Cooperation Reshaping the New Era
Chapter 13- The Transformative Role of Artificial Intelligence in Finance and Economics
Chapter 14- Ex Machine, Next Machine, Still Biased Machine
Chapter 15- Artificial Intelligence in Education: Transformation and Opportunities
Chapter 16- Artificial Intelligence in Nuclear Physics and Its Worldwide Applications
Chapter 17- In Vitro Fertilization and Artificial Intelligence
Chapter 18- Towards Automatic Cybertroll Detection in Social Media: A Transformer-based Framework
Chapter 19- Assessment of Various Deep Learning Algorithms' Performance in Forecasting Stock Market Prices
Chapter 20- Artificial Intelligence Patentability Criteria of Countries and Country-Based

This book aims to explore how to automate, innovate, design, and deploy emerging technologies in Actuarial work transformations for the insurance and finance sector. It examines the role of artificial intelligence with process automation in daily monitoring solvency, governance, compliance, data processes, etc. 

Section A Introduction 1. Evolutions of Actuarial Systems in the Insurance Industry & challenges in the existing system Section B Application of AI 2. Experts Opinion on Generative AI: Adoption and Challenges in Actuarial Science 3. AI: A revolutionary tool for actuarial work in insurance 4. Explainability AI: A Key Driver for Enhanced Quality of Service in Actuarial Practices 5. Explainability of AI in improving the Quality of Service in the Actuarial Industry 6. AI Transformation of the Insurance Industry: A Systematic Review of Progress and Possibilities 7. Examining the factors influencing AI adoption in the insurance Industry specifically in actuarial process. 8. Role of Artificial Intelligence (AI) in Insurance Industry: Scope, Benefits, and Adoption Roadmap 9. AI’s role in improving the quality of Insurance services 10. Fuzzy Artificial Intelligence as A Technique to Find Relative Desirability for Automated Insurance Premium Assignment 11. Opportunities and Challenges of Combining Artificial Intelligence Power with the Richness of Healthcare Claims Data Section C Technological Advancement 12. Implementing Machine Learning in Actuarial Practice: Real World Applications and Insight  13. Telematics System in Usage Based Motor Insurance 14. Secured and Scalable: Integrating Blockchain Solutions for Health Insurance Claim Using Client Support Chatbot Automation Section D Conclusion 15. Law and AI-Powered Actuarial Revolution: Navigating the Future of Insurance Risk Assessment 16. Charting the Future: Artificial Intelligence’s Role in Revolutionizing Actuarial Work in Insurance Sector

 

Abdel-Basset, Mohamed | Hawash, Hossam | Abdel-Fatah, Laila

This book provides a broad overview of the areas of AI that can be used for smart farming applications, either through successful engineering or ground-breaking research. Among them, the highlighted tactics are soil management, water management, crop management, livestock management, harvesting, and the integration of IoT in smart farming.

1. Introduction to Smart Farming. 2. Big Data in Smart Farming. 3. Conceptualization of Machine Learning for Smart Farming. 4. From Field to Database: Sensors, Data Collection, and Efficient Management in Smart Farming. 5. Maximizing Yield, Minimizing Water: Machine Intelligence for Precision Irrigation and Water Management. 6. Innovations in Livestock Monitoring: A Machine Learning Journey. 7. Enhancing Crop Health with Machine Learning: Disease and Weed Identification Strategies. 8. Automated Harvesting and Robotics in Agriculture. 9. The Convergence of AI and IoT in Smart Farming. 10. Toward Agriculture 5.0: The Convergence of Machine Learning and Nanotechnology for Next-Generation Farming. 

This book offers a comprehensive overview of the current state of cybersecurity in smart cities and explores how AI and IoT technologies can be used to address cybersecurity challenges. 

1. Utilization of Artificial Intelligence and the Internet of Things in the Renewable Industry 2. Analyzing the Research Landscape of Smart Cities and Artificial Intelligence: A Study Utilizing R Studio and VOSviewer 3. Enhancing Digital Accessibility for AI powered interfaces in Smart Cities 4. Analyses of The Present State of IoT and AI Security 5. Smart City Establishment: AI & IoT’s Role, Vision, And Trends 6. Securing Smart Cities: Addressing Cyber Security Implications And Collaborative Measures 7. Security Challenges for Artificial Intelligence and IoT in Adoptability of Smart City 8. A Comprehensive Survey on Security Issue and Applications of Metaverse 9. Blockchain-based Shielding Framework to Enhance Security in smart cities 10.  Integrating Blockchain, The Internet of Things, And Artificial Intelligence Technologies in Developing Smart Cities

 
 
 
 
 
 

Computational Linguistic & Language Recognition

This book explores AI’s impact on legal evidence, with a particular focus on its use within Indian law, by identifying the key feature of an Artificial intelligence-driven Justice Delivery System. It will be useful for academicians and scholars interested in Artificial Intelligence’s impact and use in the legal system.

Chapter 1: Beyond Accuracy: Evaluating LLMs for Evidentiary Use in Legal Contexts. Chapter 2: From Paper Trails to Algorithms: AI Impact on Evidence in Law. Chapter 3: From Lab Bench to Legal Bench: The Role of AI in Evaluating Biological Evidence. Chapter 4: Digital Justice: How Technology Can Transform Evidence in India. Chapter 5: Recreating reality: testing the admissibility of ai-powered cyber crime scene reconstruction. Chapter 6: The dual role of artificial intelligence in anti-money laundering: challenges in evidence admissibility and governance in India. Chapter 7: Evolving Role of AI in Precedent Search. Chapter 8: Artificial intelligence driven evidence in arbitral proceedings: a panacea or an anathema? Chapter 9: Pioneering AI in Indian Sports Legal and Evidentiary Foundations for Tomorrow's Innovations. Chapter 10: Predictive policing meets procedural law—crafting admissibility standards for AI-driven forensic tools in indian criminal justice. Chapter 11: Telemedicine Platforms and AI: Legal Challenges in India. Chapter 12: Navigating ai in insurance: legal perspectives on evidence, fraud, and risk evaluation. Chapter 13: Regulating AI-Driven Facial Recognition in Policing: Legal and Ethical Imperatives for India. Chapter 14: Artificial intelligence and product liability- A Consumer Protection Act, 2019 perspective. Chapter 15: Ethical challenges in using artificial intelligence for evidence generation in criminal investigations: balancing innovation and justice. Chapter 16: Designing 'legitimate' AI-driven Evidence Mechanism from the Rule of Law perspective. Chapter 17: Honour Killings and Digital Justice: The Role of AI in Modernising Legal Evidence in India. Chapter 18: The Future of Due Diligence: Integrating Retrieval Augmented Generation into Corporate Legal Workflows. Chapter 19: Redefining Worker in the Age of AI: Challenges and Legal Reforms for Labour Laws in India. Chapter 20: The future of legal evidence with the help of artificial intell

Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications presents the evolution, challenges, and limitations of the application of machine learning and artificial intelligence to intelligent systems and smart communities.

Chapter 1. A Detailed Study on deep learning versus machine learning approaches for Pest Classification in Field Crops. Chapter 2. Integration of Artificial Intelligence (AI) and Other Edge Cutting Technologies. Chapter 3. A detailed case study on various challenges in Vehicular Networks for Smart Traffic Control System using Machine Learning Algorithms. Chapter 4. Revolutionizing Transportation: The Power of Artificial Intelligence. Chapter 5. Smart Education using Explainable Artificial Intelligence (XAI). Chapter 6. Smart Stock Prediction Techniques Using AI-ML. Chapter 7. Smart Community:  Concepts & Applications. Chapter 8. Disseminating dynamic traffic information for sustainable mobility and transport.   

Khanna, Charu | Khanna, Sahil

In a world where machines learn, evolve, and sometimes outthink us, Artificial Intelligence and Safety offers a rare, integrated lens into both the power and peril of intelligent systems. Drawing on the authors’ unique blend of programming mastery and enterprise risk leadership, this is your compass in the age of intelligent machines.

1. Mastering Uncertainty: The Strategic Role of Risk Management  2. Decoding Intelligence: Your Step-by-Step Guide on Artificial Intelligence  3. Machine Learning Foundations: From Theory to Your First Model  4. The Rise of Deep Learning  5. From Generative AI to Context-Aware Intelligence  6. Role of Artificial Intelligence in Risk Management and Vice Versa  7. Managing Emerging Risks Using Python: Your Detailed Guide on How to Enable Ethical AI for Better Data Risk Governance  8. Asking the Right Question: Bridge the Gap Between Risk and Artificial Intelligence  9. Case Study: Your Practical and Stepwise Guide to Build a RAG-Powered AI Assistant  10. Afterword: The Future of Risk Management in the Era of Artificial Intelligence

Khanna, Charu | Khanna, Sahil

In a world where machines learn, evolve, and sometimes outthink us, Artificial Intelligence and Safety offers a rare, integrated lens into both the power and peril of intelligent systems. Drawing on the authors’ unique blend of programming mastery and enterprise risk leadership, this is your compass in the age of intelligent machines.

1. Mastering Uncertainty: The Strategic Role of Risk Management  2. Decoding Intelligence: Your Step-by-Step Guide on Artificial Intelligence  3. Machine Learning Foundations: From Theory to Your First Model  4. The Rise of Deep Learning  5. From Generative AI to Context-Aware Intelligence  6. Role of Artificial Intelligence in Risk Management and Vice Versa  7. Managing Emerging Risks Using Python: Your Detailed Guide on How to Enable Ethical AI for Better Data Risk Governance  8. Asking the Right Question: Bridge the Gap Between Risk and Artificial Intelligence  9. Case Study: Your Practical and Stepwise Guide to Build a RAG-Powered AI Assistant  10. Afterword: The Future of Risk Management in the Era of Artificial Intelligence

This book discusses the development of the integration of artificial intelligence and digital health technologies within oncology care systems across Africa. It is for oncologists, AI researchers, public health professionals, policymakers, and development practitioners seeking to use AI for equitable and sustainable cancer care in Africa.

1. The Epidemiological Landscape of Cancer in Africa: Challenges and Opportunities  2. Digital Health Ecosystems in Africa: Readiness for Oncology Transformation  3. Artificial Intelligence in Global Oncology: Relevance and Adaptation to African Contexts  4. Ethical, Legal, and Social Implications of Artificial Intelligence in African Cancer Diagnosis and Care  5. Data Governance, Interoperability, and Equity in Digital Health Systems  6. Artificial Intelligence-Driven Cancer Imaging and Diagnostics: Deep Learning for Early Detection  7. Natural Language Processing and Clinical Decision Support in Oncology  8. Telepathology, Teleradiology, and Remote Diagnostics in Low-Resource African Settings  9. Precision Oncology in Africa: Genomic Data, Artificial Intelligence Algorithms, and Local Adaptation  10. Integrating Artificial Intelligence into National Cancer Treatment Guidelines and Protocols  11. Artificial Intelligence and Mobile Health Platforms for Cancer Treatment Monitoring and Adherence  12. Digital Navigation Tools for Cancer Survivorship and Follow-Up Care  13. Predictive Analytics for Managing Cancer Relapse and Long-Term Risk  14. Artificial Intelligence in Palliative Care: Personalizing Pain Management and End-of-Life Support  15. Building Resilient Digital Infrastructure for Cancer Care in Rural and Underserved Areas  16. Scaling Artificial Intelligence for Oncology Across African Health Systems: Frameworks and Best Practices  17. Public-Private Partnerships for Artificial Intelligence and Digital Health Integration in Cancer Care  18. Measuring Impact: Evaluation Metrics and Health Outcomes for Artificial Intelligence Interventions  19. Capacity Building, Training, and Workforce Development in Artificial Intelligence for Cancer Care  20. Future Horizons: Emerging Trends, Innovations, and a Vision for Equitable Cancer Care in Africa

Artificial Intelligence for Cyber Defence and Smart Policing will describe the best way of practising artificial intelligence for cyber defence and smart policing.

Chapter 1: Machine Learning in Cyber Threats Intelligent System. Chapter 2: Cybercrimes in the Associated World. Chapter 3: Recent Developments of Threat Intelligence and Challenges. Chapter 4: AI in Forensics: Data Analytics Perspective. Chapter 5: Big data for intelligence and security. Chapter 6: Deep Learning Decision Support Model for Police Investigation. Chapter 7: Big Data in Cyber Crime Investigation. Chapter 8: Low-cost high impact AI tools against cyber crime. Chapter 9: Computer based (AI) Intelligence in the Field of Defense. Chapter 10: Assembly of Cyber and Illegal Intimidation. Chapter 11: Computer based Intelligence and Security. Chapter 12: Case study: Artificial Intelligence and Machine Learning in Cyber security.

The book articulates how AI can be channeled to make a perceptible impact on agriculture through digital transformation. Use cases illustrate how AI can simplify and speed this agricultural transformation. Focusing on the distinct characteristics of AI, the book explains how to intelligently automate agriculture processes and practices.

1. Machine Learning Algorithms and Applications 2. Introduction to Deep Learning 3. Role of AI in the Field of Precision Agriculture 4. How AI Contributes to Precision Agriculture 5. AI Model Generation Platforms 6. AI Deployment Models in Precision Agriculture 7. AI Model Deployment: Enhanced Rice Plant Disease Detection and Classification Besides Improved Spatial Pyramid with Enhanced YOLOv7 8. Sustainable Farming through AI-Enabled Precision Agriculture 9. The Significance of Data Integration and Ingestion in Enhancing Agricultural Operations: A Comprehensive Exploration 10. Revolutionizing Crop Yield Prediction in Agriculture: Harnessing Machine Learning and Environment Factors for Effective Solutions in the Face of Climate Change 11. AI in Optimization of Agricultural Output in Precision Agriculture 12. Data Analytics Methods for Precision Agriculture 13. Data Analytics Methods: A Hands-On Approach for Precision Agriculture 14. Smart Sensing Technologies and Data Analytics for Precision Agriculture 15. Knowledge Visualization Tools Relating to Agriculture

Mohaghegh, Shahab D.

This book addresses the unique differences in how AI should be developed and used in science and engineering. Through inclusion of definitions and detailed examples, this book covers actual and realistic requirements as well as avoidance of certain characteristics for the correct and successful science and engineering application of AI.

1. Definition of Artificial Intelligence and Machine Learning, 2. Brief History of Artificial Intelligence, 3. Science and Engineering Application of Artificial Intelligence, 4. Modeling Physics Using Artificial Intelligence, 5. Artificial Intelligence versus Traditional Statistics, 6. Ethics of Artificial Intelligence (AI-Ethics) in Science and Engineering, 7. Explainable Artificial Intelligence (XAI)

This book presents a comprehensive exploration of how emerging Artificial Intelligence (AI) technologies are reshaping the future of mobility. From foundational principles and intelligent transportation systems to advanced applications, the book covers a wide spectrum.

Preface. 1. Role of Artificial Intelligence in Transportation Systems. 2. Intelligent Transportation Systems: A Comprehensive Review of Technologies, Applications, and Future Trends. 3. Role of AI in Traffic Safety and Prevention of Accidents. 4. Artificial Intelligence for Measuring Transportation Comfort: A Comprehensive Review. 5. AI-powered Driving Analytics: Understanding Driver Behavior through Data. 6. Smart Vision: Powering Vehicle Detection with Deep Learning. 7. Quantum Computing and Communication for Intelligent Transportation System Networks: Exploring Qubit-based Innovations in Cryptography and Optimization Frontiers. 8. Generative AI-based Framework for Road Infrastructure Design in Intelligent Transportation Systems. 9. Neural Network–driven Driver Wellness Analytics: Predicting Mental Fatigue through Whole-Body Vibration Patterns and Psychosocial Health Monitoring. 10. AR and AI for Driver Assistance and Navigation. 11. The Invisible Highway: Integrating Artificial Intelligence with 6G Next-Generation Mobility. 12. Development of Machine Intelligence for Self-driving Vehicles Through Video Capturing. 13. Harnessing Edge AI for Real-Time Telematics: A Framework for Low-Latency Vehicle Data Analytics. 14. Quantum Machine Learning for Next-Gen Wireless: Fundamentals and Path Ahead. 15. AI Foundations for Reliable V2V Communication.

This book presents a comprehensive overview of how Artificial Intelligence is revolutionizing the fields of biochemistry, biomedical sciences, and healthcare. With the ability to minimize human error, assist medical professionals, and provide round-the-clock patient services, AI has become an indispensable tool in modern medicine.

1. Role of artificial intelligence in healthcare and biomedical science 2. Applications of artificial intelligence in healthcare 3. Artificial intelligence in the treatment and diagnosis of infectious diseases 4. The role of artificial intelligence in diabetes: A review of recent advances 5. Artificial intelligence in gynecology 6. Role of AI in gastroenterology: Prevention, diagnostics, and treatment 7. Artificial intelligence in drug delivery 8. Artificial intelligence in genomics 9. Trends and challenges in the field of medical sciences using AI 10. A survey of clinical decision support systems

Artificial Intelligence in Operations: Strategy, Efficiency, and the Future of Execution

This book explores how AI is transforming operations across industries, from supply chains to public institutions. Focusing on real-world impact, it examines predictive planning, human–machine collaboration, and governance challenges, helping leaders adopt AI responsibly and strategically.

1. Artificial Intelligence in Operations: Transforming Business Efficiency and Strategy 2. Artificial Intelligence in Logistics and Supply Chain: Transforming the Future of Global Operations 3. Algorithms of War: The Rise of Generative AI on the Battlefield 4. Autonomous Warfare: How AI and Drones Are Replacing Human Soldiers on the Battlefield 5. Artificial Intelligence (AI) in Modern Military Applications 6. The Rise of Artificial Intelligence in Diplomacy and International Relations 7. Artificial Intelligence and National Security 8. AI and Higher Education: Transforming the Academic Landscape 9. The Use of AI in the Criminal Justice Field 10. AI in the Medical Field: Transforming Healthcare for the Future 11. The Impact of Artificial Intelligence on Space Technology: Present Innovations and Future Trajectories

The book bridges the gap between theoretical concepts and practical implementation, ensuring that readers develop a nuanced and practical grasp of AI's impact on healthcare systems. Moreover, the book serves as a roadmap for healthcare professionals and researchers looking to integrate AI solutions into their practices.

Preafce. Introduction to Artificial Intelligence in Smart Healthcare Systems, 2. Evolutions and Trends of Artificial Intelligence in Smart Healthcare Systems, 3. Clinical Decisions Support Systems: Enhancing Medical Decision-Making, 4. Predictive Analytics for Disease Prevention and Early Detection, 5. Health Monitoring and Wearable Technology Integration, 6. Medical Imaging Advancements: AI in Radiology and Pathology, 7. Natural Language Processing in Healthcare: Existing Insights from the Text Data, 8. Ethical Considerations in the Use of AI in Healthcare, 9. Regulatory Framework for AI in Smart Healthcare, 10. Patient Engagement through Artificial Intelligence-Driven Solutions, 11. Artificial Intelligence in Personalized Medicine, 12. Robotics in Healthcare: Surgical and Patient Care Automation, 13. Telemedicine and Remote Patient Monitoring: Transforming Healthcare Delivery, 14. Al in Drug Discovery and Pharmaceutical Research, 15. Healthcare Data Security and Privacy in the AI Era, 16. AI-driven Virtual Health Assistants: Enhancing Patient Communication, 17. The Role of Al in Mental Health Diagnosis and Treatment, 18. Insights from Global and UAE AI Applications in Public Health and Epidemiology, 19. Healthcare Robotics: Rehabilitation and Assistance Devices, 20. Artificial Intelligence for Population Health Management and Wellness Programs, 21. AI-Powered Clinical Trials: Optimizing Research Process, 22. Augmented Reality and Virtual Reality in Medical Training with AI, 23. AI in Healthcare Workforce: Opportunities and Challenges, 24. Future Directions: Emerging Technologies and Innovations in AI for Healthcare. 25. Interoperability Challenges and Solutions in AI-Driven Healthcare Systems

This book is devoted to the new standards, technologies, and communication systems for Artificial Intelligence of Things networks.It focuses on existing solutions in AIoT network technologies, applications, services, standards, architectures, and security provisions, as well as introducing new architectures and models for AIoT networks. 

This book focuses on the design, implementation, and management of secure Human Cyber-Physical Systems (HCPS s) in smart manufacturing environments. It covers a wide range of topics, including risk assessment, security architecture, data privacy, and standard specifications for HCPSs.

1. Enhancing the Power of Cyber Physical Systems Enabled with AI: An Introduction, Facts and Myths along with Modular Approach 2. AI for Secure and Resilient Cyber-Physical Systems 3. Power of Emotions in AI: Strengthening the Bond of Human-Machine with Heart 4. Advancing Manufacturing Excellence: ML and AI-driven Threat Detection Strategies 5. Enhancing Resilience in the Integration of Cybersecurity for Smart Manufacturing 6. Leveraging Artificial Intelligence and Machine Learning for Advanced Threat Detection in Smart Manufacturing 7. Integrating Cybersecurity Threats in Smart Manufacturing: Best Practices and Frameworks 8. Proactive Risk Management in Smart Manufacturing: A Comprehensive Approach to Risk Assessment and Mitigation 9. Entrepreneurial Strategies for Mitigating Risks in Smart Manufacturing Environments 10. Fortifying Smart Manufacturing against Cyber Threats: A Comprehensive Guide to Cybersecurity Integration, Best Practices, and Frameworks 11. Tagging Blockchain Technology Fostering Panacea for Data Privacy, Cloud Computing and Integrity: Legal Framework in India and across the Globe 12. Enhancing Human-Centered Security in Industry 4.0: Navigating Challenges and Seizing Opportunities 13. Using AI for Student Success: Early Warning, Performance Analytics, and Automated Grading in Education Cyber-Physical Systems 14. Securing Industrial Internet of Things (IIoT): A Review of Technologies, Strategies, Challenges and Future Trends 15. Strategic Management of Intelligent Robotics and Drones in Contemporary Industrial Operations: An Assessment of Roles and Integration Strategies 16. Digital Twins as a New for Bridging the Gap from Personalized Medicine to Specific Rural Public Health: Exploring Foundations, Legal Angels and Technologies for Health 5.0- Future Research Directions 17. Privacy-Preserving Strategies for Enhanced Big-Data Analytics in Evolving Healthcare Environments: A 5G and Beyond Perspective 18. Securing the Digital Realm: Unl

Artificial Intelligence, Machine Learning and IoT for Smart Business Management

This book investigates the transformative impact of AI, ML, Data Analytics, and IoT on modern business, emphasising their roles in strategic growth, operational efficiency, and data-driven decision-making. 

Evolution of AI, ML, and IoT in Business ManagementPoornima Tyagi, Shiv Narain Gupta, Divya Sahu, Mohd Firoz Waris, and Parvendra Kumar
Strategic Implementation of AI for Business AdvancementPriti Rai and Palanivel Rathinasabapathi Velmurugan
ML Techniques for Business Intelligence and Decision-MakingVijay Anand Rajasekaran, Magesh Gopu, Madala Guru Brahmam, and Veena Grover
Operational Excellence through AI, ML, and IoTA. Anitha, K. Anitha, Kashish Bhasin, Aditya Singh, and Balakrishnan Kamaraj
Technical Analysis for Traders: Stock Price PredictionPurnima Pal, Harshit Thakur, Meghali Das, Nisha, and Manju Nandal
Future Trends and Ethical Considerations in AI, ML, and IoTSarabjeet Kaur, Swarnima, Purnima Pal, and Nidhi Sharma
Voice Assisted Chat Bots in Enhancing CRM in Modern Marketing for Small BusinessesAditi Srivastava, Ajay Singh, and Brij Mohan Singh
IoT Applications in Business OperationsTaher Alkhalaf, Omar Durrah, and Monir Alkhalaf
Robotic Process Automation: Streamlining Business Processes for Operational ExcellenceMagesh Sankar, Vijayalakshmi Sivaramakrishnan, Palamadai Subramanian Rajakumar, S. Geetha, and R. Manikandan
Intelligent Forecasting Models Based on Neural Systems for Smart Business ManagementHina Riaz and Mohan Prasad Sharma
Customer Churn Prediction Using Machine LearningMeghali Das, Purnima Pal, and Garima Srivastava
Intelligent Techniques: Fuzzy Logic and Computational TechniquesSwarnima and Bhawna Khullar
 
 
 
 
 
 

This book is structured to guide readers through AGA's concepts, practical applications, and future directions.At its core, this book is an invitation to reimagine the boundaries of algorithmic design. It is crafted for researchers, practitioners, and enthusiasts in computer science, operations research, AI, and beyond.

1. Overview of Optimization
   1.1 Introduction 
   1.2 Combinatorial Optimization 
   1.3 NP-hardness 
   1.4 NP-hardness in Combinatorial Optimization 
   1.5 General Framework of a Combinatorial Optimization Problem 
   1.6 Methods for Combinatorial Optimization Problems 
   1.7 A General Optimization Algorithm 
   1.8 Summary 
 
2. The Master Problem
   2.1 Introduction 
   2.2 The Problem Statement 
   2.3 The Space of Instances 
   2.4 The Space of Algorithms 
   2.5 The Space of Parameters 
   2.6 Simultaneous Parameter Optimization with AGA 
   2.7 Independent Parameter Optimization 
   2.8 The Algorithm Selection Problem 
   2.9 The No-Free-Lunch in AGA 
   2.10 Summary 
 
3. Modeling Problems
   3.1 The Modeling Process 
   3.2 Identifying Problems 
   3.3 Approaching Practical Problems in Operations Research 
   3.4 Fundamental Models in OR 
   3.5 Approaching Practical Problems via AI 
   3.6 Fundamental Models in AI 
   3.7 Approaching Practical Problems by AGA 
   3.8 A Fundamental AGA Model 
   3.9 Summary 
 
4. AGA with Genetic Programming
   4.1 Introduction 
   4.2 The Master Problem in AGA 
   4.3 Genetic Programming 
      4.3.1 The General Algorithmic Evolutionary Process 
      4.3.2 Genetic Operations in GP 
   4.4 GP as a Metaheuristic 
   4.5 Modeling the Master Problem with GP 
      4.5.1 Solution Representation as a Tree 
      4.5.2 The Fitness Function 
   4.6 The Evolution of Algorithms 
   4.7 Constructive and Refinement Algorithms 
   4.8 Robustness Versus Specialization 
   4.9 AGA for Population-Based Algorithms 
   4.10 Rediscoveri

Dang, Wenshuan | Huang, River | Yu, Yijun | Zhang, Yong

This book describes the development history, application scenarios, theories, architectures, and key technologies of Huawei's Autonomous Driving Network (ADN) solution.

1. Introduction  2. Birth of ADN  3. Application Scenarios of ADN  4 . Fundamental Theories of ADN  5 . Reference Architecture of ADN  6 . Key Technologies of ADN  7 . Industry Standards  8 . Level Evaluation of ADN  9 . ADN Solution  10 . Summary and Outlook

CAD CAE CAM - Computing & Information Technology

What happens when humanity steps beyond the limits of biology and creates intelligence greater than its own? Becoming Homo lucidus offers a bold vision of that future and a roadmap for how to prepare. If you wonder what the rise of Digital Intelligence (DI) means, this is both a guide and an invitation.

Part 1: The Dawn of the Ageless Era   1. Digital Intelligence - The Dream Child of Biological Intelligence  2. Biological Intelligence Achieving Ageless  3. Homo lucidus - Ageless, Pinnacle Intelligence, and Enlightened Needs  4. Lucidus Society - Abundance, Fairness, and Peace  Part 2: Forging the New Human  5. Solid Body and Lucid Mind  6. Personal Network Rooted in Your Principles  7. Lucidus Learning  8. Lucidus Vocation   Part 3: Forging Tutelary Digital Intelligence  9. From Value Alignment to Tutelary Digital Intelligence  10. Architecture of Tutelary Digital Intelligence  11. Data Generation and Preservation for Tutelary Digital Intelligence  12. Thriving with Tutelary Digital Intelligence Part 4:  Seeking Vanguards for a Post-2045 World  13. The Inner Pursuits - Hedonist, Aesthete, Inquisitive, Cosmologist  14. The Outer Pursuits - Connector, Culturist, Anthroguard, Conservationist  15. Envision and Enabling Your Personal Future - Becoming a Vanguard of Homo lucidus Epilogue: To Prepare for the Future, Understand the Past

CAD CAE CAM - Computing & Information Technology

What happens when humanity steps beyond the limits of biology and creates intelligence greater than its own? Becoming Homo lucidus offers a bold vision of that future and a roadmap for how to prepare. If you wonder what the rise of Digital Intelligence (DI) means, this is both a guide and an invitation.

Part 1: The Dawn of the Ageless Era   1. Digital Intelligence - The Dream Child of Biological Intelligence  2. Biological Intelligence Achieving Ageless  3. Homo lucidus - Ageless, Pinnacle Intelligence, and Enlightened Needs  4. Lucidus Society - Abundance, Fairness, and Peace  Part 2: Forging the New Human  5. Solid Body and Lucid Mind  6. Personal Network Rooted in Your Principles  7. Lucidus Learning  8. Lucidus Vocation   Part 3: Forging Tutelary Digital Intelligence  9. From Value Alignment to Tutelary Digital Intelligence  10. Architecture of Tutelary Digital Intelligence  11. Data Generation and Preservation for Tutelary Digital Intelligence  12. Thriving with Tutelary Digital Intelligence Part 4:  Seeking Vanguards for a Post-2045 World  13. The Inner Pursuits - Hedonist, Aesthete, Inquisitive, Cosmologist  14. The Outer Pursuits - Connector, Culturist, Anthroguard, Conservationist  15. Envision and Enabling Your Personal Future - Becoming a Vanguard of Homo lucidus Epilogue: To Prepare for the Future, Understand the Past

The book offers a clear, timely framework for viewing and analyzing AI as intellectual capital rather than as autonomous intelligence. AI is presented as a tool that helps organize, expand, and apply knowledge to support human decision-making, improve institutional effectiveness, and promote social progress.

1. Artificial Intelligence at the Crossroads of Hype and Hope  2. The Balancing Act: AI, Society, and Capital Architecture  3. Human Capital in the Age of AI  4. Ethical Capital: AI Governance  5. Structures and Boundaries that Promote AI Creativity, Productivity, and Innovation  6. Where Mission Meets Machine: AI in Education, Government Services, and NGOs  7. Next-Generation Nets: From AI Misalignment to Capital-Driven Human Flourishing

The book offers a clear, timely framework for viewing and analyzing AI as intellectual capital rather than as autonomous intelligence. AI is presented as a tool that helps organize, expand, and apply knowledge to support human decision-making, improve institutional effectiveness, and promote social progress.

1. Artificial Intelligence at the Crossroads of Hype and Hope  2. The Balancing Act: AI, Society, and Capital Architecture  3. Human Capital in the Age of AI  4. Ethical Capital: AI Governance  5. Structures and Boundaries that Promote AI Creativity, Productivity, and Innovation  6. Where Mission Meets Machine: AI in Education, Government Services, and NGOs  7. Next-Generation Nets: From AI Misalignment to Capital-Driven Human Flourishing

This revised new edition provides up-to-date knowledge on the latest developments related to these three fields for solving geoinformatics problems. There are seven new chapters, and each of them focuses on a separate real-world problem to which deep learning is applied.

1. Distributed and Parallel Computing. 2. GEOSS Clearinghouse Integrating Geospatial Resources to Support the Global Earth Observation System of Systems. 3. Using a Cloud Computing Environment to Process Large 3D Spatial Datasets. 4. Building Open Environments to Meet Big Data Challenges in Earth Sciences. 5. Developing Online Visualization and Analysis Services for NASA Satellite-Derived Global Precipitation Products during the Big Geospatial Data Era. 6. Algorithmic Design Considerations for Geospatial and/or Temporal Big Data. 7. Machine Learning on Geospatial Big Data. 8. Spatial Big Data: Case Studies on Volume, Velocity, and Variety. 9. Exploiting Big VGI to Improve Routing and Navigation Services. 10. Efficient Frequent Sequence Mining on Taxi Trip Records Using Road Network Shortcuts. 11. Geoinformatics and Social Media: New Big Data Challenge. 12. Insights and Knowledge Discovery from Big Geospatial Data Using TMC-Pattern. 13. Geospatial Cyberinfrastructure for Addressing the Big Data Challenges on the Worldwide Sensor Web. 14. OGC Standards and Geospatial Big Data. 15. Advanced Deep Learning Models and Algorithms for Spatial-Temporal Data. 16. Deep Learning for Spatial Data: Heterogeneity and Adaptation. 17. Assessing Multilevel Environmental and Air Quality Changes in Australia Pre- and Post-COVID-19 Lockdown: A Spatial Machine Learning Approach Utilizing Earth Observation Data. 18. Fairness-Aware Deep Learning in Space. 19. Integrating Large Language Models and Qualitative Spatial Reasoning. 20. Toward a Spatial Metaverse: Building Immersive Virtual Experiences with Georeferenced Digital Twin and Game Engine. 21. A Topological Machine Learning Approach with Multichannel Integration for Detecting Geospatial Objects.

Blockchain and distributed-ledger technologies enable new modes of communication, synchronization, and transfer of value with a broad impact on IoT, Data Science, society, industry, commerce, and government. This book studies the potential impact of Blockchain and distributed-ledger technologies on IoT. 

 
1. Blockchain Technology: Applications and Challenges 2.Evolution of IoT in Various Application Domains 3.      Transforming Healthcare Crowdfunding: Integrating Blockchain and IoT for Transparency, Trust, and Accessibility 4.      Internet of Things Security: Techniques and Challenges 5.      Introduction to Blockchain Technology 6.      Trends and Prospectus of Blockchain Technology 7.      Developing Smart Cities by integrating Blockchain based GRNN with CSO-Transformed Paillier 8.    Blockchain Based Vehicle Information Management System 9.      A Survey on Issues in Integrating Blockchain and IoT Technologies 10.  Exploring the Integration of Blockchain and Internet of Things (IoT) Computing for Secure and Decentralized Data Management 11.  Empowering IoT Security: Enhancing Applications through Edge Computing and Blockchain 12.  Future Prospects of Blockchain for Secure IoT Systems 13.  Decentralized Finance: Towards the Evolution of FinTech 14.  Enhancing Access Control in Healthcare Blockchain Using LSTM Based Breast Cancer Detection and Blowfish Encryption 15.  Transforming Emergency Care: A Blockchain-Powered Smart Admission Monitoring System



 


             

 
 
 
 

Protocols, Application and Approaches for Future Generation Computing

This book provides a review blockchain technology, and current developments in research and business applications. It aims to explore the real-time applications and issues that will bring the synergy needed to materialize the goal of blockchain intelligence.

BLOCKCHAIN SOCIAL THEORY AND SOCIETAL IMPACT. COMPARABLE WORKS IN BLOCKCHAIN TECHNOLOGY. AN INTERGRATION OF IOT AND BLOCKCHAIN FOR MEDICAL APPLICATION. MEDICAL IOT APPLICATIONS USING BLOCKCHAIN. BLOCKCHAIN AND IOT FOR HEALTH-CARE APPLICATIONS. SECURE E-HEALTH SYSTEM USING BLOCKCHAIN TECHNOLOGY IN IOT ENVIRONMENT. MACHINE LEARNING MODEL FOR PREDICTING VIRAL DISEASES USING LINEAR REGRESSION. PATIENT WELLNESS: ETHEREUM BASED ELECTRONIC HEALTH RECORD STORAGE. SECURE IOT SMART HEALTH MONITORING SYSTEM (SHMS) FOR PATIENTS USING BLOCKCHAIN TECHNOLOGY. BLOCKCHAIN BASED E VOTING SYSTEM. A SECURE AND EFFICIENT STUDENT PERFORMANCE PREDICTION SYSTEM BASED ON BLOCKCHAIN AND DATA MINING TECHNOLOGIES.

Vuppalapati, Chandrasekar

Building Next-Gen ESG Platforms with IoT and AI for Sustainable Development Goals

Combining practical implementation - codes, training pipelines, and deployment guides - with strategic Environmental, Social, and Governance (ESG) insights, the book provides a cross-disciplinary framework to building transparent, scalable, and data-driven ESG platforms aligned with the UN Sustainable Development Goals.

Preface. 1. Artificial Intelligence. 2. IoT and AI Models. 3. Environmental, Social, and Governance (ESG). 4. IoT and Greenhouse Gas (GHG) Emissions Models for Creating Sustainable Communities. 5. AI, IoT, and Business Process Automation for Enhanced Productivity, Economic Sustainability, and Reduced Inequalities. 6. Next-Gen AI Climate Models Revolutionizing Agricultural Inputs and Boosting Biodiversity.

Discover the revolutionary potential of swarm intelligence in this groundbreaking book. Explore how predictive intelligence and advanced algorithms enhance autonomous systems across industries, from manufacturing to energy.

Preface. Fundamentals of Swarm Intelligence. Swarm Intelligence: Applications and Implementations in Autonomous Systems. Federated Learning in Shared Production Scenarios. Resilience-X: Towards Resilient Manufacturing Companies An In-depth Analysis of Requirements and Challenges. Multi-agent Reinforcement-Learning for Solving Flexible Job Shop Scheduling Problems. On Joint Exploration and Self-guided Task Allocation for Mobile Robots in an Industrial Environment. Advances in the Applications of Swarm Intelligence in Portfolio Optimization, Stock Price Prediction and Risk Management A Comparison with Traditional Methods. Towards Next Generation Data-Driven Management Leveraging Predictive Swarm Intelligence to Reason and Predict Market Dynamics. Parkinson’s Disease Detection with Deep Long Short-term Memory Networks Optimized by Modified Metaheuristic Algorithm. Emerald Evolution Charting the Next Phase of Global Sustainability with Collective Intelligence. Index.

The rapid advancement of Generative AI (GenAI) is revolutionizing and transforming a wide range of fields, with a notable impact on digital media and information dissemination. Digital platforms, including social media networks, have already grappled with the widespread proliferation of fake news at an increasing intensity.

Part I. Misinformation in the Age of GenAI: State-of-the-Art. Chapter 1 Social Awareness, Disinformation, and Reputational Management in the Age of Artificial Intelligence. Chapter 2 Aligning Generative AI with Educational Values: An Ethical Response to Digital Misinformation. Part II. Large Language Models (LLMS) for Misinformation Detection. Chapter 3 AI-Driven Threats and Countermeasures: Securing the Information Space Against Synthetic Media and Deepfakes. Chapter 4 Zero Trust Architectures and Cybersecurity Frameworks for Mitigating AI-Enabled Misinformation Campaigns. Chapter 5 Decentralizing Truth: A Blockchain-Based Framework for Trustworthy Information in the GenAI Era. Chapter 6 An AI-Augmented Human-in-the-Loop (HITL) Approach for Misinformation Prevention in the Digital Age. Part III. Case Studies and Practical Solutions. Chapter 7 Factors Influencing Misinformation in the Context of GenAI: The Case of Vietnam. Chapter 8 Analysis for Usage of ChatGPT by Students in Academic Contexts. Chapter 9 Mapping the Economics of Water Misinformation in the Generative AI–Driven Era: Modeling Insights on Education, Policy, and Smart Detection. Chapter 10 Quantifying the Economic Implications of AI-Driven Misinformation: Evidence from ESG, Global Trade, Logistics, Education, and Innovation for Sustainable Development. Part IV. Ethical Challenges and Future Trends. Chapter 11 Role of Data Protection Law in Combating Generative AI Misinformation: A Visible Threat to Privacy. Chapter 12 Emerging Trends and Challenges in Generative Artificial Intelligence (GenAI) and Misinformation: HR Perspectives. Chapter 13 Future Trends in AI-Driven Misinformation Detection and Prevention.

The book examines leading Industry 4.0 and 5.0 and Industrial Internet of Things technologies enhanced with computational intelligence (CI) techniques. The book covers modelling, controls, estimations, applications, and systems. It considers this multi-disciplinary domain that is based on data collected from smart sensors. 

1. Industry 4.0: Challenges and Issues Encountered in Manufacturing and Testing of MEMS Devices. 2. The Industrial Internet of Things (IIoT): Overview, Architecture, Challenges, and Possible Solutions. 3. Artificial Intelligence in Industry 5.0: Transforming Manufacturing through Machine Learning and Robotics in Collaborative Age. 4. Computational Intelligence in the Industrial Internet of Things. 5. Security, Privacy, Trust, and Other Issues in Industries 4.0 and 5.0. 6. Fine-Tuning for a Deep Learning Model in Optimizing Ransomware Attack Detection in the Industry 4.0 and 5.0 Era. 7. Blockchain in Industry 4.0 and Industry 5.0: A Shift towards Decentralized Efficiency and Autonomous Ecosystems. 8. Integration of Digital of Twins in Industries 4.0 and 5.0. 9. Computational Intelligence in Big Data Analytics. 10. The Role of Augmented Reality, Virtual Reality, and Mixed Reality in Industries 4.0 and 5.0. 11. Industry 4.0 Design Principles, Technologies, and Applications. 12. Industry 4.0 and Computational Intelligence for Fighting COVID-19: A Case Study.

Computer Graphics & Visualization

The book highlights various core challenges, constructive criticism, and solutions by leading researchers in the field. It covers timely and important aspects of computer vision and its applications, highlighting the challenges ahead and providing a range of perspectives, from top researchers around the world. 

Foreword by Takeo Kanade
1 Some Challenges and Solutions in Data-Driven AI
Rama Chellappa, Jiang Liu, Chun Pong Lau, and Prithviraj Dhar
2 Challenges of Computer Vision Research from an Industry Perspective
Fatih Porikli
3 Soft Biometrics for Human Identication
Mark S. Nixon and Emad Sami Jaha
4 Exploring Causes of Demographic Variations in Face Recognition Accuracy
Gabriella Pangelinan, K.S. Krishnapriya, Vitor Albiero, Grace Bezold, Kai Zhang, Kushal Vangara,
Michael C. King, and Kevin W. Bowyer
5 AI Knows What You Did Last Summer: Applications in Digital Forensics
Jing Yang, José Nascimento, Gabriel Bertocco, Antonio Theophilo, Rafael Padilha, Aurea Soriano-Vargas, Fernanda A. Andaló, and Anderson Rocha
6 Advances in Computer Vision for Home-Based Stroke Rehabilitation
7 U-Net-based Medical Image Segmentation: A Comparative Analysis and Future Trends
Sidike Paheding, Abel A. Reyes-Angulo, and Mohammad S. Alam
8 Robot-Mediated Assistance: Opportunities and Challenges in Computer Vision and Human—Robot Interaction
Md Alimoor Reza and Syed Masum Billah
9 Computer Vision Applications in Underwater Robotics and Oceanography
Md Jahidul Islam, Alberto Quattrini Li, Yogesh A Girdhar, and Ioannis Rekleitis
10 Applications of Computer Vision in Entertainment and Media Industry
Mahmudul Hasan, Kishan Shamsundar Athrey, Arfeen Khalid, Danfeng Xie, Ehsan Younessian, and Tony Braskich
11 Quality Assessment in Media and Entertainment: Challenges and Trends
Abhinau K. Venkataramanan, Zaixi Shang, Joshua P. Ebenezer, Meixu Chen, Zhengzhong Tu, and Alan C. Bovik
12 Immersive User Experiences: Trends and Challenges of Using XR Technologies
Vasudev Bhaskaran and Upal Mahbub
Kowshik Thopalli, Niccolo Meniconi, Tamim Ahmed, Sai Krishna Yeshala, Aisling Kelliher, Thanassis Rikakis, and

Computational Linguistic & Language Recognition

ICCIDC 2025 is a premier global event focused on the latest advancements in computational intelligence and data communication technologies.

1 Artificial intelligence in supply chain optimization: data driven strategiesSharath Chandra Macha and Sharath Chandra Kondaparthy2 Two-element narrowband planar fork antenna operating at 23.80 GHzAayush Kumar Singh, Ashish Raj, Tanweer Ali, Jagadeesh Chandra R. B and Soumil Jain3 A hybrid fin-shaped narrowband antenna for wireless applicationsAayush Kumar Singh, Ashish Raj, Tanweer Ali, Jagadeesh Chandra R. B and Soumil Jain4 Enhancing motor-imagery BCI robustness for edge computing applicationsSiddhartha Modi,Abhinav Verma and Sandhya Parasnath Dubey5 Comparative study of unsupervised and supervised learning analysis for the credit cardfraud identificationHitha L and Sandhya Prashanth Dubey6 Golden ratio assisted localization for wireless sensor networkHitesh Mohapatra and Soumya Ranjan Mishra7 Automated detection of chronic kidney disease using deep learningBindi Bhatt, Pooja Bhatt and Hima Bindu8 Deepfake image detection using different combinations of vision transformers and CNNsSoumya Ranjan Mishra and Hitesh Mohapatra9 Attention guided multimodal learning for classification of oral lesions using histopathologyand clinical dataDivya Rao10 Classification of target and non-target stimuli based on EEG signal during n-back workingmemory taskShrishail Bhat, Ananthakrishna Thalengala, Subramanya G. Nayak andIqbal Ahammed A Kaladgikar11 Evaluating the impact of preprocessing on deep learning-based dental decision supportsystemsAnupama S and Veena Mayya12 Enhancing SQL injection detection: a comparative study of SVM, Random Forest andhybrid modelsAdithya Rao Kalathur, Vaishnavi and Balachandra Muniyal13 Automation of Android-based actions using large action modelsSambhav Nath Jain, Jason Shaun Dmello, Rudra Patel, Mamatha Balachandra,Roshan David Jathanna, Sharmila Mani and P

Computational Linguistic & Language Recognition

ICCIDC 2025 is a premier global event focused on the latest advancements in computational intelligence and data communication technologies.

1 Artificial intelligence in supply chain optimization: data driven strategiesSharath Chandra Macha and Sharath Chandra Kondaparthy2 Two-element narrowband planar fork antenna operating at 23.80 GHzAayush Kumar Singh, Ashish Raj, Tanweer Ali, Jagadeesh Chandra R. B and Soumil Jain3 A hybrid fin-shaped narrowband antenna for wireless applicationsAayush Kumar Singh, Ashish Raj, Tanweer Ali, Jagadeesh Chandra R. B and Soumil Jain4 Enhancing motor-imagery BCI robustness for edge computing applicationsSiddhartha Modi,Abhinav Verma and Sandhya Parasnath Dubey5 Comparative study of unsupervised and supervised learning analysis for the credit cardfraud identificationHitha L and Sandhya Prashanth Dubey6 Golden ratio assisted localization for wireless sensor networkHitesh Mohapatra and Soumya Ranjan Mishra7 Automated detection of chronic kidney disease using deep learningBindi Bhatt, Pooja Bhatt and Hima Bindu8 Deepfake image detection using different combinations of vision transformers and CNNsSoumya Ranjan Mishra and Hitesh Mohapatra9 Attention guided multimodal learning for classification of oral lesions using histopathologyand clinical dataDivya Rao10 Classification of target and non-target stimuli based on EEG signal during n-back workingmemory taskShrishail Bhat, Ananthakrishna Thalengala, Subramanya G. Nayak andIqbal Ahammed A Kaladgikar11 Evaluating the impact of preprocessing on deep learning-based dental decision supportsystemsAnupama S and Veena Mayya12 Enhancing SQL injection detection: a comparative study of SVM, Random Forest andhybrid modelsAdithya Rao Kalathur, Vaishnavi and Balachandra Muniyal13 Automation of Android-based actions using large action modelsSambhav Nath Jain, Jason Shaun Dmello, Rudra Patel, Mamatha Balachandra,Roshan David Jathanna, Sharmila Mani and P

Agriculture & Environmental Sciences

Cutting-Edge Agri-Technologies for Next-Generation Farming explores how emerging innovations such as nanotechnology, genome editing, artificial intelligence, precision agriculture, and smart sensing systems are reshaping modern food production.

Preface. Section I: General 1. Nanotechnology and AI in Next-Generation Agriculture. Section II: Novel Nanotechnologies for Shaping Farming 2. Nanomaterials in Agriculture: Enhancing Soil Health and Plant Growth. 3. Seed Nanopriming for Sustainable Crop Production. 4. Emerging Nanopesticides: Opportunities and Challenges. 5. Nanofertilizers for Sustainable Agriculture: Limitations and Future Trends. 6. Next-Generation Farming: Crop Monitoring with Nanosensor Technologies. 7. Nanobiotechnology for the Management of Plant Diseases. 8. Nanotechnology for Plant Growth Promotion and Stress Tolerance. Section III: CRISPR-Cas9 Technology 9. CRISPR-Cas9 Editing Technology: Concept, Applications, and Prospects for Agriculture. 10. Genome Editing in Cereal Crops Using CRISPR-Cas9 Technology. 11. Genome Editing of Horticultural Crops Using CRISPR/Cas for Enhanced Improvement. 12. Opportunities and Challenges of CRISPR/Cas Systems in Crop Breeding. Section IV: Artificial Intelligence Technology 13. Introduction to the Application of Artificial Intelligence-based Solutions in Agriculture. 14. Deep Learning for Crop Improvement. 15. Precision Farming and Decision Support Systems, Utilizing Convolutional Networks for Plant Detection. 16. Leveraging Artificial Intelligence for the Detection, Monitoring, and Forecasting of Plant Diseases. 17. Application of AI in Identification of Pests and Weeds. 18. Ethical and Social Implications of AI in Agriculture. Index. Editors’ Biography.

1. Introduction to Learning Methods for Business Analytics 2. Emerging Cyber Security Challenges in the Business World 3. Cyber Security Issues and Challenges in E-shopping/E-commerce 4. Knowledge Representation of Various Business Models 5. Reactive vs. Proactive Cybersecurity & Real-Time Threat Protection 6. Exploring the Importance of Incident Management in Modern Organizations 7. Issues and Challenges in E-banking: Case Study 8. Cyber Security of Machine Learning Systems for Business Data 9. Privacy-Preserving Deep Learning Techniques for Business Big Data 10. Navigating Cybersecurity Tools: A Comprehensive Guide from Entry to Expert Level 11. Improving Cybersecurity Measures in Business Analytics for E-Commerce Platforms in Africa: Cyber Laws, Challenges, and Solutions 12. Optimizing User Engagement with Personalized Recommendations and Targeted Advertising
 

This book examines the potential benefits of cyber-physical systems (CPS) and applications for rural development. It provides an in-depth examination of theoretical concepts, in addition to presenting real-world case studies and methodological frameworks and ways of enabling effective CPS deployments in remote areas.

1. Bridging the Digital and Physical Worlds by Cyber-Physical Systems 2. IoT-Driven Stream Data Processing with Real-Time Analytics for Rural Development 3. Data Analytics for Rural Applications:Water Quality Irrigation System 4. Cyber-Physical Systems for overcoming Connectivity Challenges in Rural Areas 5. Healthcare Solutions for Remote Rural Areas 6. Ethical Considerations in Rural Cyber Physical Systems Deployment 7. Telemedicine Solutions for Remote Health Access 8. Challenges and Opportunities for Cyber-Physical Systems in Agriculture 9.Enhancing Connectivity in Remote Rural Areas  10. IoT-BasedWeather Forecasting: Predicting Rainfall in Rural Areas 11. Challenges of Cyber-Physical Systems in Rural Education12. Data-Driven Optimization of Mental Health Diagnosis in Rural Areas  13. Smart Villages: Transforming Rural Communities 14. Human-Centric Approaches to Rural CPS  15. Exploring How Humidity and Rainfall Patterns Drive Rural Transformation 16. Mobile Health Services for Rural Communities 

Karnati, Yashawi | Mahajan, Dhruv | Banerjee, Tania | Sengupta, Rahul | Clay, Packard | Casburn, Ryan | Agarwal, Nithin | Dilmore, Jeremy | Rangarajan, Anand | Ranka, Sanjay

This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.

Chapter 1 Introduction
Chapter 2 Traffic Engineering and operations background
Chapter 3 Integrated Corridor Management System
Chapter 4 Traffic Data Modalities
Chapter 5 Data Mining and Machine Learning
Chapter 6 Traffic Simulation Frameworks for Data Generation
Chapter 7 Intersection Detector Diagnostics
Chapter 8 Intersector Performance
Chapter 9 Interruption Detection
Chapter 10 Estimating Turning Movement Counts
Chapter 11 Coordinating Corridors
Chapter 12 Modeling Input Output Behavior of Intersection
Chapter 13 Modeling Measures of Effectiveness for Intersection Performance
Chapter 14 Signal Timing Optimizations
Chapter 15 Visualisation of Traffic Data

This book explores the need for a data-centric AI approach and its application in the multidisciplinary domain, compared to a model-centric approach.

I) Section I Recent developments in data-centric AI: 1. Advancements in Data-Centric AI Foundations, Ethics, and Emerging Technology 2. Emerging Development and Challenges in Data-Centric AI 3. Unleashing the Power of Industry 4.0: A Harmonious Blend of Data-Centric and Model- Centric AI 4. Data centric AI approaches for machine translation II) Section II Data Centric AI in Healthcare and Agriculture: 5. Case Study Medical Images Analysis and Classification with Data Centric Approach 6. Comparative Analysis of Machine Learning Classification Techniques for Kidney Disease Prediction 7. Fusion of Multi Modal Lumber Spine Scans Using Convolutional Neural Networks 8. Medical Image Analysis and Classification for Varicose Veins 9. Brain Tumor Detection using CNN 10. Explainable Artificial Intelligence in the Healthcare: An Era of Commercialization for AI Solutions 11. Role of Data centric artificial intelligence in agriculture 12. Detection and Classification of Mango Fruit based on Feature extraction applying optimized hybrid LA-FF algorithms III) Section III Building AI with quality Data for multidisciplinary domains: 13 Guiding Your Way: Solving Student Admission Woes 14. Melodic pattern recognition for ornamentation features in music computing 15. Content Analysis Framework for Skill Assessment 16. Machine learning techniques for effective text mining 17. Emails Classification and Anomaly Detection using Natural Language Processing

The International Conference on Data-Driven AI (ICDDA 2025) is a global platform dedicated to advancing the transformative potential of Artificial Intelligence (AI) and its interdisciplinary applications.

1 Optimising smart grid performance by integrating machine learning with PID control for sustainable energy management  2 AI-based software cost estimation using software metrics  3 A mathematical model for the application of induced magnetic field in blood flow through a bell-shaped stenosis artery  4 Enhancing time-series classification with autoencoder-driven feature and local attention in LSTM networks  5 Unravelling the functional role of PLRG-1 in development and lifespan in Caenorhabditis elegans  6 Artificial intelligence in education: Enhancing learning outcomes or replacing teachers  7 Steady state analysis of bi-criteria in queuing model comprising parallel servers with revisiting facility within stochastic environment  8 Spatial maps coupled vision transformers for skin cancer classification  9 Optimising rice leaf disease classification with ResNet50 and dense block integration  10 Utilising data-driven artificial intelligence to investigate plant-based compounds for neuroinflammation and inflammatory receptor modulation through polypharmacology  11 A deep learning-based technique for identifying the health of honeybee species  12 Supercapacitors in energy storage: Principles, materials, challenges, and applications  13 A comparative study on Fuzzy PERT with measures  14 Exploring the future of connectivity: A comprehensive review of wireless and optical communications  15 Proof-of-driving incentive mechanism for VANET to enhance traffic safety and efficiency  16 Agro automatic weather station  17 Optimisation of energy efficiency through prediction-based model of multiuser cognitive radio network  18 The paradox of AI and creativity: Enhancing or hindering innovation?  19 Human-AI interaction in language education: A comparative study of conversational chatbots  20 Implementation of Sukanya Samriddhi Yojana in incentivising development of girl child and wo

The book is a practical and comprehensive guide to the impact of deep learning in the real world across sectors like healthcare, finance, and autonomous systems.  Designed for researchers, practitioners, and students, it highlights how AI is transforming industries through innovative applications and intelligent solutions.

Preface. Smart Healthcare Solutions: The Role of Artificial Intelligence in Diagnosing and Treating Patients. Artificial Intelligence for Financial Market Forecasting: A Machine Learning Approach. Artificial Intelligence for Autonomous Systems: Innovations in Self-Driving Cars and Drones. The Integration of Artificial Intelligence and Robotics for Autonomous Systems. DD-SSD: Deep Detector for Strip Steel Defects. A Prospective study of Indoor Air Quality Monitoring System using IoT. Autonomous Plant Monitoring and Maintaining Robot to Identify Plant Diseases and Nutrient Deficiencies. Determination and Diagnosis of Diabetes Mellitus. Inflated 3D Convnet for Detection of Sign Language. Flora and Fauna Identification using YOLOv3 Algorithm. Thyroid Cancer Reoccurrence Prediction Using Machine Learning. Recommendation System for Social Media Using Graph and Web Analyti.  Rfid Car Using Arduino Mega 2560 by Dijkstra’s Algorithm. Stock Market Analysis Using Ensemble Learning Approach Deep Learning Applications: Select Topics. Detecting COVID-19 with Chest X-ray using PyTorch. Personalized News Recommendations System Based on Hybrid Filtering Techniques: a case study on user comments and readership history. Multilabel Classification of Arabic Articles Based on Mawjaz Topics Using Deep Learning Approaches. Data mining in health care sector: A review. Translation from Spoken Arabic Digits to Sign Language based on Deep Learning. Future Directions in Deep Learning: Challenges and Opportunities. Index.

This book explores advanced methodologies and empirical research in machine learning through data mining and GPU-based parallel programming. It highlights the integration of modern deep learning techniques with CUDA architecture for efficient big data processing.

Preface. Computation and Analysis for Genome Mapping using the Deep Learning-based Optimization Algorithm. Prediction for Genome Mapping with the Multi-objective Evolutionary Algorithm. Deep Learning and Medical Data Engineering for Knowledge Discovery. Integrating DL Techniques for Precise Genome Mapping: Methods and Applications. Analysing Genomes using Deep Learning and Image Processing Techniques. Introduction to Neural network and Machine Learning as a Subset of AI. Advancing Smart Healthcare: Enhanced Image Analysis and Feature Extraction through Integration of Sharpening Techniques and Edge Detection Algorithms. Optimizing Noise Reduction Strategies in Medical Imaging through Advanced Techniques and Performance Evaluation Metrics. Revolutionizing Medicine: Machine Learning Innovations in Medical Science. Development and Validation of an AI-Based Model for Heart Delineation in Chest X-Ray Images. Index.

From fundamental concepts to advanced implementations, this book thoroughly explores the DeepSeek-V3 model, focusing on its Transformer-based architecture, technological innovations, and applications.

Part I: Theoretical Foundations and Technical Architecture of Generative AI  1. Core Principles of Transformer and Attention Mechanisms  2 DeepSeek-V3 Core Architecture and its Training Techniques in Detail  3 Introduction to DeepSeek-V3 Model-Based Development  Part II: Development and Application of Generative AI and Advanced Prompt Design  4. A First Look at the DeepSeek-V3 Big Model  5. DeepSeek Open Platform and API Development Details  6. Dialogue Generation, Code Completion, and Customized Model Development  7. Conversation Prefix Completion, FIM and JSON Output Development Details  8. Callback Functions and Contextual Disk Caching  9. The DeepSeek Prompt Library: Exploring More Possibilities for Prompts  Part III: Integration of Practical Experience and Advanced Applications  10. Integration Practice 1: LLM-Based Chat Client Development  11. Integration Hands-On 2: AI Assisted Development  12. Integration Practice 3: Assisted Programming Plugin Development Based on VS Code