T. S. Arun Samuel, PhD is a Professor on the Department of Electronics and Communication Engineering, National Engineering College, Tamil Nadu, India with more than two decades of experience. He has authored more than 65 research articles published in prestigious international journals, 15 articles in international conferences, one patent, and three edited books. His research interests are focused on advancing the frontiers of nanoelectronic device technologies through innovative modeling and simulation techniques.L. Jerart Julus, PhD is an Assistant Professor in the Department of IT, School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India. He is a member of IEEE, the Computer Society of India, and the Optical Society of India. His research interests include multicarrier communications systems, radio over fiber, and visible light communication.P. Kanimozhi, PhD is a Professor of Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India with more than 19 years of teaching experience. She has published more than 17 research papers in national and international journals. Her current areas of interest include cloud computing security, data mining, and blockchain.T. Ananth Kumar, PhD is an Associate Professor of Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India. He has presented papers in national and international conferences and journals, holds patents in various domains, and has edited six books and numerous book chapters. His fields of interest are networks on chips, computer architecture, and application-specific integrated circuit design.S. Balamurugan, PhD is the Director of Research at iRCS, an Indian Technological Research and Consulting Firm. He has published more than 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of research on various cutting-edge technologies, he provides expert guidance in technology forecasting and decision-making for leading companies and startups.

• Series Preface xvPreface xviiAcknowledgement xixPart I: Foundational Concepts and Emerging Trends in Composite AI 11 Data Fusion Techniques in Composite AI 3S. Sowmyayani, D. Dhanya, J. Kavitha and R. Roselinkiruba1.1 Introduction 11.2 Data Fusion Techniques in Composite AI 31.4 Proposed Methodology Using Composite AI 121.5 Experimental Results 171.6 Conclusion 262 Composite AI in Natural Language Processing: A Paradigm Shift in Understanding and Generating Human Language 33Narendran M., M. Beema Meharaj, D. Diana Julie, Sowmya Banala, G. Umadevi and A. Devi2.1 Introduction to Composite Artificial Intelligence (AI) 342.2 Role of Composite AI in NLP 372.3 Fundamental Elements of NLP Composite AI 422.4 Case Studies and Use Cases of Composite AI in NLP 492.5 Challenges and Future Directions 602.6 Conclusion 623 A Composite Artificial Intelligence Framework for Enhanced and Intelligent Word Recognition of Handwritten Hindi 65R. S. Rampriya, Sabarinathan, SahayaBeni Prathiba, C. Renit, R. Arumuga Arun and S. Bhuvana3.1 Introduction 663.2 Related Work 683.3 Proposed Methodology 693.4 Experimental Result and Analysis 753.5 Conclusion 814 Machine Learning-Driven Optimization for Composite AI in Wireless Body Area Networks (WBAN) 85Krishna Kumar M., Pricilla Mary S., James Nesaratnam R. and Sharon Geege A.4.1 Prelude 864.2 Architectural Framework of WBAN Integrated with Composite AI 874.3 Machine Learning Models for WBAN Optimization 894.4 Deep Learning for Signal Processing in WBAN 914.5 Security Challenges and AI-Based Solutions in WBAN 924.6 AI-Driven Antenna Optimization in WBANs 944.7 Conclusion and Research Trajectories 97Part II: Advanced Methods and Technical Challenges in Composite AI 1015 AI-Driven Hybrid Ant Colony and Golden Jackal Optimization Algorithm for Lung Disease Prediction and Classification 103Karthikeyan A., Pradeep S., Boorneush M. and Dhivya P.5.1 Introduction 1045.2 Literature Survey 1065.3 System Design 1095.4 Results and Discussion 1145.5 Conclusion 1205.6 Future Scope 1216 Removing Bias in Maritime Imagery: Advancing Gender Equality through Data-Driven Methods 125Jordan Taylor and J. Padmapriya6.1 Introduction 1266.2 Literature Review 1296.3 Methodology 1346.4 Results and Discussion 1436.5 Conclusion 1467 Text-Based Analysis of Twitter Data with Machine Learning Models 151N. Malathy, G. Sharmila, R. Yuvarshini and R. Lavanya7.1 Introduction 1527.2 Objective 1577.3 Classification of Tweets 1587.4 Evaluation Metrics 1727.5 Conclusion and Future Work 1758 Fingerprint Registration and Matching Based on Improved Convolutional Neural Network 181Lakshmanan B., Selvakumar B., Kasthuri K., Nivashini S. and Swetha R.8.1 Introduction 1828.2 Related Works 1828.3 Dataset Description 1858.4 Proposed Work 1858.5 Results and Discussion 1918.6 Conclusion 195Part III: Real-World Applications of Composite AI in Healthcare and Beyond 1999 A Novel Transfer Learning-Based Composite AI Model for Skin Disease Classification 201R. Karthick Manoj and S. Aasha Nandhini9.1 Introduction 2029.2 Literature Survey 2039.3 Proposed Methodology 2089.4 Result and Discussion 2139.5 Conclusion 21810 Composite AI-Driven Music Recommendation: Integrating Emotion, Aural Analysis and Song Similarity 223Ayushmaan Das and Rajalakshmi Shenbaga Moorthy10.1 Introduction 22410.2 Literature Survey 22810.3 Proposed Composite AI-Driven Music Recommendation Engine 23210.4 Results and Discussions 23910.5 Conclusion 24411 A Composite Artificial Intelligence Based Framework for Heart Disease Prediction 249M. Suresh, M. S. Anbarasi, R. Rajmohan and A. Anbarasi11.1 Introduction 25011.2 Smart Health Monitoring Systems 25411.3 Materials and Methods 25711.4 Results and Discussions 27011.5 Conclusions 27512 Composite AI for Predictive Analysis of Autism Spectrum Disorder Using Facial Features 279S. Usharani, A. Ganesh, N. Muralidharan and G. Glorindal12.1 Introduction 28012.2 Related Work 28012.3 Overview of Composite AI in Predictive Analysis 28412.4 Proposed Methodology 28512.5 Experimental Setup 29112.6 Results and Outputs 29512.7 Conclusion 29613 Integrating Imaging and Genomic Data with Composite AI to Enhance Breast Cancer Diagnosis and Early Detection 303P. Manju Bala, S. Usharani, A. Balachandar, Sunday Adeola Ajagbe and Matthew Olusegun Adigun13.1 Introduction 30413.2 Materials and Methods 30713.3 Model Training and Evaluation 31313.4 Evaluation Results 31413.5 Conclusion 31914 Cognitive Analytics AI for Predictive Diagnostics and Neurological Forecasting in Brain Tumor Management 325S. Usharani, P. Manju Bala, A. Balachandar and Olukayode A.14.1 Introduction 32614.2 Related Works 32714.3 Proposed Predictive Analytics Framework for Predicting Brain Tumors and Neurological Disorders 33114.4 Experimental Setup for Predictive Analytics in Prediction of Brain Tumor and Neurological Disorder 33414.5 Results and Analysis 34014.6 Conclusion 34115 Applications for Composite AI in Healthcare 345R. Vijayarajeswari, David Samuel Azariya S., Anto Lourdu Xavier Raj Arockia Selvarathinam, Priyabrata Thatoi, Abhinaya Saravanan and Nisha Soms15.1 Introduction 34615.2 Fundamentals of Composite AI 34715.3 Applications for Composite AI in Healthcare 35115.4 Case Studies in Composite AI Applications in Healthcare 35615.5 Challenges and Future Directions 35715.6 Conclusion 362References 364Index 367

T. S. Arun Samuel, PhD is a Professor on the Department of Electronics and Communication Engineering, National Engineering College, Tamil Nadu, India with more than two decades of experience. He has authored more than 65 research articles published in prestigious international journals, 15 articles in international conferences, one patent, and three edited books. His research interests are focused on advancing the frontiers of nanoelectronic device technologies through innovative modeling and simulation techniques.L. Jerart Julus, PhD is an Assistant Professor in the Department of IT, School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India. He is a member of IEEE, the Computer Society of India, and the Optical Society of India. His research interests include multicarrier communications systems, radio over fiber, and visible light communication.P. Kanimozhi, PhD is a Professor of Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India with more than 19 years of teaching experience. She has published more than 17 research papers in national and international journals. Her current areas of interest include cloud computing security, data mining, and blockchain.T. Ananth Kumar, PhD is an Associate Professor of Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India. He has presented papers in national and international conferences and journals, holds patents in various domains, and has edited six books and numerous book chapters. His fields of interest are networks on chips, computer architecture, and application-specific integrated circuit design.S. Balamurugan, PhD is the Director of Research at iRCS, an Indian Technological Research and Consulting Firm. He has published more than 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of research on various cutting-edge technologies, he provides expert guidance in technology forecasting and decision-making for leading companies and startups.

• Series Preface xvPreface xviiAcknowledgement xixPart I: Foundational Concepts and Emerging Trends in Composite AI 11 Data Fusion Techniques in Composite AI 3S. Sowmyayani, D. Dhanya, J. Kavitha and R. Roselinkiruba1.1 Introduction 11.2 Data Fusion Techniques in Composite AI 31.4 Proposed Methodology Using Composite AI 121.5 Experimental Results 171.6 Conclusion 262 Composite AI in Natural Language Processing: A Paradigm Shift in Understanding and Generating Human Language 33Narendran M., M. Beema Meharaj, D. Diana Julie, Sowmya Banala, G. Umadevi and A. Devi2.1 Introduction to Composite Artificial Intelligence (AI) 342.2 Role of Composite AI in NLP 372.3 Fundamental Elements of NLP Composite AI 422.4 Case Studies and Use Cases of Composite AI in NLP 492.5 Challenges and Future Directions 602.6 Conclusion 623 A Composite Artificial Intelligence Framework for Enhanced and Intelligent Word Recognition of Handwritten Hindi 65R. S. Rampriya, Sabarinathan, SahayaBeni Prathiba, C. Renit, R. Arumuga Arun and S. Bhuvana3.1 Introduction 663.2 Related Work 683.3 Proposed Methodology 693.4 Experimental Result and Analysis 753.5 Conclusion 814 Machine Learning-Driven Optimization for Composite AI in Wireless Body Area Networks (WBAN) 85Krishna Kumar M., Pricilla Mary S., James Nesaratnam R. and Sharon Geege A.4.1 Prelude 864.2 Architectural Framework of WBAN Integrated with Composite AI 874.3 Machine Learning Models for WBAN Optimization 894.4 Deep Learning for Signal Processing in WBAN 914.5 Security Challenges and AI-Based Solutions in WBAN 924.6 AI-Driven Antenna Optimization in WBANs 944.7 Conclusion and Research Trajectories 97Part II: Advanced Methods and Technical Challenges in Composite AI 1015 AI-Driven Hybrid Ant Colony and Golden Jackal Optimization Algorithm for Lung Disease Prediction and Classification 103Karthikeyan A., Pradeep S., Boorneush M. and Dhivya P.5.1 Introduction 1045.2 Literature Survey 1065.3 System Design 1095.4 Results and Discussion 1145.5 Conclusion 1205.6 Future Scope 1216 Removing Bias in Maritime Imagery: Advancing Gender Equality through Data-Driven Methods 125Jordan Taylor and J. Padmapriya6.1 Introduction 1266.2 Literature Review 1296.3 Methodology 1346.4 Results and Discussion 1436.5 Conclusion 1467 Text-Based Analysis of Twitter Data with Machine Learning Models 151N. Malathy, G. Sharmila, R. Yuvarshini and R. Lavanya7.1 Introduction 1527.2 Objective 1577.3 Classification of Tweets 1587.4 Evaluation Metrics 1727.5 Conclusion and Future Work 1758 Fingerprint Registration and Matching Based on Improved Convolutional Neural Network 181Lakshmanan B., Selvakumar B., Kasthuri K., Nivashini S. and Swetha R.8.1 Introduction 1828.2 Related Works 1828.3 Dataset Description 1858.4 Proposed Work 1858.5 Results and Discussion 1918.6 Conclusion 195Part III: Real-World Applications of Composite AI in Healthcare and Beyond 1999 A Novel Transfer Learning-Based Composite AI Model for Skin Disease Classification 201R. Karthick Manoj and S. Aasha Nandhini9.1 Introduction 2029.2 Literature Survey 2039.3 Proposed Methodology 2089.4 Result and Discussion 2139.5 Conclusion 21810 Composite AI-Driven Music Recommendation: Integrating Emotion, Aural Analysis and Song Similarity 223Ayushmaan Das and Rajalakshmi Shenbaga Moorthy10.1 Introduction 22410.2 Literature Survey 22810.3 Proposed Composite AI-Driven Music Recommendation Engine 23210.4 Results and Discussions 23910.5 Conclusion 24411 A Composite Artificial Intelligence Based Framework for Heart Disease Prediction 249M. Suresh, M. S. Anbarasi, R. Rajmohan and A. Anbarasi11.1 Introduction 25011.2 Smart Health Monitoring Systems 25411.3 Materials and Methods 25711.4 Results and Discussions 27011.5 Conclusions 27512 Composite AI for Predictive Analysis of Autism Spectrum Disorder Using Facial Features 279S. Usharani, A. Ganesh, N. Muralidharan and G. Glorindal12.1 Introduction 28012.2 Related Work 28012.3 Overview of Composite AI in Predictive Analysis 28412.4 Proposed Methodology 28512.5 Experimental Setup 29112.6 Results and Outputs 29512.7 Conclusion 29613 Integrating Imaging and Genomic Data with Composite AI to Enhance Breast Cancer Diagnosis and Early Detection 303P. Manju Bala, S. Usharani, A. Balachandar, Sunday Adeola Ajagbe and Matthew Olusegun Adigun13.1 Introduction 30413.2 Materials and Methods 30713.3 Model Training and Evaluation 31313.4 Evaluation Results 31413.5 Conclusion 31914 Cognitive Analytics AI for Predictive Diagnostics and Neurological Forecasting in Brain Tumor Management 325S. Usharani, P. Manju Bala, A. Balachandar and Olukayode A.14.1 Introduction 32614.2 Related Works 32714.3 Proposed Predictive Analytics Framework for Predicting Brain Tumors and Neurological Disorders 33114.4 Experimental Setup for Predictive Analytics in Prediction of Brain Tumor and Neurological Disorder 33414.5 Results and Analysis 34014.6 Conclusion 34115 Applications for Composite AI in Healthcare 345R. Vijayarajeswari, David Samuel Azariya S., Anto Lourdu Xavier Raj Arockia Selvarathinam, Priyabrata Thatoi, Abhinaya Saravanan and Nisha Soms15.1 Introduction 34615.2 Fundamentals of Composite AI 34715.3 Applications for Composite AI in Healthcare 35115.4 Case Studies in Composite AI Applications in Healthcare 35615.5 Challenges and Future Directions 35715.6 Conclusion 362References 364Index 367

T. S. Arun Samuel, PhD is a Professor on the Department of Electronics and Communication Engineering, National Engineering College, Tamil Nadu, India with more than two decades of experience. He has authored more than 65 research articles published in prestigious international journals, 15 articles in international conferences, one patent, and three edited books. His research interests are focused on advancing the frontiers of nanoelectronic device technologies through innovative modeling and simulation techniques.L. Jerart Julus, PhD is an Assistant Professor in the Department of IT, School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India. He is a member of IEEE, the Computer Society of India, and the Optical Society of India. His research interests include multicarrier communications systems, radio over fiber, and visible light communication.P. Kanimozhi, PhD is a Professor of Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India with more than 19 years of teaching experience. She has published more than 17 research papers in national and international journals. Her current areas of interest include cloud computing security, data mining, and blockchain.T. Ananth Kumar, PhD is an Associate Professor of Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India. He has presented papers in national and international conferences and journals, holds patents in various domains, and has edited six books and numerous book chapters. His fields of interest are networks on chips, computer architecture, and application-specific integrated circuit design.S. Balamurugan, PhD is the Director of Research at iRCS, an Indian Technological Research and Consulting Firm. He has published more than 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of research on various cutting-edge technologies, he provides expert guidance in technology forecasting and decision-making for leading companies and startups.

• Series Preface xvPreface xviiAcknowledgement xixPart I: Foundational Concepts and Emerging Trends in Composite AI 11 Data Fusion Techniques in Composite AI 3S. Sowmyayani, D. Dhanya, J. Kavitha and R. Roselinkiruba1.1 Introduction 11.2 Data Fusion Techniques in Composite AI 31.4 Proposed Methodology Using Composite AI 121.5 Experimental Results 171.6 Conclusion 262 Composite AI in Natural Language Processing: A Paradigm Shift in Understanding and Generating Human Language 33Narendran M., M. Beema Meharaj, D. Diana Julie, Sowmya Banala, G. Umadevi and A. Devi2.1 Introduction to Composite Artificial Intelligence (AI) 342.2 Role of Composite AI in NLP 372.3 Fundamental Elements of NLP Composite AI 422.4 Case Studies and Use Cases of Composite AI in NLP 492.5 Challenges and Future Directions 602.6 Conclusion 623 A Composite Artificial Intelligence Framework for Enhanced and Intelligent Word Recognition of Handwritten Hindi 65R. S. Rampriya, Sabarinathan, SahayaBeni Prathiba, C. Renit, R. Arumuga Arun and S. Bhuvana3.1 Introduction 663.2 Related Work 683.3 Proposed Methodology 693.4 Experimental Result and Analysis 753.5 Conclusion 814 Machine Learning-Driven Optimization for Composite AI in Wireless Body Area Networks (WBAN) 85Krishna Kumar M., Pricilla Mary S., James Nesaratnam R. and Sharon Geege A.4.1 Prelude 864.2 Architectural Framework of WBAN Integrated with Composite AI 874.3 Machine Learning Models for WBAN Optimization 894.4 Deep Learning for Signal Processing in WBAN 914.5 Security Challenges and AI-Based Solutions in WBAN 924.6 AI-Driven Antenna Optimization in WBANs 944.7 Conclusion and Research Trajectories 97Part II: Advanced Methods and Technical Challenges in Composite AI 1015 AI-Driven Hybrid Ant Colony and Golden Jackal Optimization Algorithm for Lung Disease Prediction and Classification 103Karthikeyan A., Pradeep S., Boorneush M. and Dhivya P.5.1 Introduction 1045.2 Literature Survey 1065.3 System Design 1095.4 Results and Discussion 1145.5 Conclusion 1205.6 Future Scope 1216 Removing Bias in Maritime Imagery: Advancing Gender Equality through Data-Driven Methods 125Jordan Taylor and J. Padmapriya6.1 Introduction 1266.2 Literature Review 1296.3 Methodology 1346.4 Results and Discussion 1436.5 Conclusion 1467 Text-Based Analysis of Twitter Data with Machine Learning Models 151N. Malathy, G. Sharmila, R. Yuvarshini and R. Lavanya7.1 Introduction 1527.2 Objective 1577.3 Classification of Tweets 1587.4 Evaluation Metrics 1727.5 Conclusion and Future Work 1758 Fingerprint Registration and Matching Based on Improved Convolutional Neural Network 181Lakshmanan B., Selvakumar B., Kasthuri K., Nivashini S. and Swetha R.8.1 Introduction 1828.2 Related Works 1828.3 Dataset Description 1858.4 Proposed Work 1858.5 Results and Discussion 1918.6 Conclusion 195Part III: Real-World Applications of Composite AI in Healthcare and Beyond 1999 A Novel Transfer Learning-Based Composite AI Model for Skin Disease Classification 201R. Karthick Manoj and S. Aasha Nandhini9.1 Introduction 2029.2 Literature Survey 2039.3 Proposed Methodology 2089.4 Result and Discussion 2139.5 Conclusion 21810 Composite AI-Driven Music Recommendation: Integrating Emotion, Aural Analysis and Song Similarity 223Ayushmaan Das and Rajalakshmi Shenbaga Moorthy10.1 Introduction 22410.2 Literature Survey 22810.3 Proposed Composite AI-Driven Music Recommendation Engine 23210.4 Results and Discussions 23910.5 Conclusion 24411 A Composite Artificial Intelligence Based Framework for Heart Disease Prediction 249M. Suresh, M. S. Anbarasi, R. Rajmohan and A. Anbarasi11.1 Introduction 25011.2 Smart Health Monitoring Systems 25411.3 Materials and Methods 25711.4 Results and Discussions 27011.5 Conclusions 27512 Composite AI for Predictive Analysis of Autism Spectrum Disorder Using Facial Features 279S. Usharani, A. Ganesh, N. Muralidharan and G. Glorindal12.1 Introduction 28012.2 Related Work 28012.3 Overview of Composite AI in Predictive Analysis 28412.4 Proposed Methodology 28512.5 Experimental Setup 29112.6 Results and Outputs 29512.7 Conclusion 29613 Integrating Imaging and Genomic Data with Composite AI to Enhance Breast Cancer Diagnosis and Early Detection 303P. Manju Bala, S. Usharani, A. Balachandar, Sunday Adeola Ajagbe and Matthew Olusegun Adigun13.1 Introduction 30413.2 Materials and Methods 30713.3 Model Training and Evaluation 31313.4 Evaluation Results 31413.5 Conclusion 31914 Cognitive Analytics AI for Predictive Diagnostics and Neurological Forecasting in Brain Tumor Management 325S. Usharani, P. Manju Bala, A. Balachandar and Olukayode A.14.1 Introduction 32614.2 Related Works 32714.3 Proposed Predictive Analytics Framework for Predicting Brain Tumors and Neurological Disorders 33114.4 Experimental Setup for Predictive Analytics in Prediction of Brain Tumor and Neurological Disorder 33414.5 Results and Analysis 34014.6 Conclusion 34115 Applications for Composite AI in Healthcare 345R. Vijayarajeswari, David Samuel Azariya S., Anto Lourdu Xavier Raj Arockia Selvarathinam, Priyabrata Thatoi, Abhinaya Saravanan and Nisha Soms15.1 Introduction 34615.2 Fundamentals of Composite AI 34715.3 Applications for Composite AI in Healthcare 35115.4 Case Studies in Composite AI Applications in Healthcare 35615.5 Challenges and Future Directions 35715.6 Conclusion 362References 364Index 367