Pawan Whig – författare & böcker

Artificial Intelligence and Machine Learning for Sustainable Development

Innovations, Challenges, and Applications

Inbunden, Engelska, 2024

2 051 kr

Skickas inom 10-15 vardagar

Artificial Intelligence and Machine Learning for Sustainable Development is a comprehensive exploration of how artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of sustainable development.The book examines cutting-edge innovations, practical applications, and potential challenges in harnessing AI and ML to address global sustainability issues. It offers insights into how these technologies can optimize resource management, improve environmental monitoring, enhance decision-making processes, and promote equitable, eco-friendly solutions. This book would be of special interest to researchers, policymakers, and practitioners seeking to leverage cutting-edge technology for a more sustainable future.

Nyhet

Artificial Intelligence and Machine Learning for Sustainable Development

Innovations, Challenges, and Applications

AvPawan Whig,Pavika Sharmam. fl.

Häftad, Engelska, 2026

777 kr

Skickas inom 10-15 vardagar

Artificial Intelligence and Machine Learning for Sustainable Development is a comprehensive exploration of how artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of sustainable development.The book examines cutting-edge innovations, practical applications, and potential challenges in harnessing AI and ML to address global sustainability issues. It offers insights into how these technologies can optimize resource management, improve environmental monitoring, enhance decision-making processes, and promote equitable, eco-friendly solutions. This book would be of special interest to researchers, policymakers, and practitioners seeking to leverage cutting-edge technology for a more sustainable future.

Artificial Intelligence and Machine Learning for Sustainable Development

Innovations, Challenges, and Applications

AvNuno Silva,Ahmed A. Elngarm. fl.

E-bok

PDF, Engelska, 2024

989 kr

Läs direkt efter köp

Artificial Intelligence and Machine Learning for Sustainable Development is a comprehensive exploration of how artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of sustainable development.

The book examines cutting-edge innovations, practical applications, and potential challenges in harnessing AI and ML to address global sustainability issues. It offers insights into how these technologies can optimize resource management, improve environmental monitoring, enhance decision-making processes, and promote equitable, eco-friendly solutions. This book would be of special interest to researchers, policymakers, and practitioners seeking to leverage cutting-edge technology for a more sustainable future.

Artificial Intelligence and Machine Learning for Sustainable Development

Innovations, Challenges, and Applications

AvNuno Silva,Ahmed A. Elngarm. fl.

E-bok

Engelska, 2024

989 kr

Läs direkt efter köp

Artificial Intelligence and Machine Learning for Sustainable Development is a comprehensive exploration of how artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of sustainable development.

The book examines cutting-edge innovations, practical applications, and potential challenges in harnessing AI and ML to address global sustainability issues. It offers insights into how these technologies can optimize resource management, improve environmental monitoring, enhance decision-making processes, and promote equitable, eco-friendly solutions. This book would be of special interest to researchers, policymakers, and practitioners seeking to leverage cutting-edge technology for a more sustainable future.

Quantum Learning

Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education

AvNuno Silva,Ahmad A. Elngarm. fl.

E-bok

PDF, Engelska, 2026

2 216 kr

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Quantum Learning: Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education explores the transformative intersection of three revolutionary technologies reshaping the future of learning. The concept of quantum learning provides a paradigm where quantum principles redefine machine learning models, enhance computational speed, and enable novel personalized education systems.

The book integrates artificial intelligence (AI), quantum algorithms, and data-driven pedagogy to reimagine classrooms and cognitive processes. Readers will discover how quantum-inspired neural networks, quantum data analysis, and intelligent tutoring systems can revolutionize educational delivery. Through interdisciplinary research, the work translates complex quantum and AI concepts into practical educational applications, featuring case studies and real-world insights that demonstrate how quantum-enhanced intelligence can personalize learning and improve outcomes. The text covers both theoretical frameworks and practical implementation strategies, offering a blueprint for adaptive, scalable learning ecosystems.

This wide-ranging book will appeal to a diverse audience of researchers, educators, technologists, and policymakers seeking to understand and shape the next generation of education innovation. By combining these domains into one book and using an accessible approach, it makes cutting-edge concepts comprehensible to both technical and non-technical readers, positioning it as an essential resource for anyone involved in educational technology, artificial intelligence research, or quantum computing applications in learning environments.

Quantum Learning

Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education

AvNuno Silva,Ahmad A. Elngarm. fl.

E-bok

Engelska, 2026

2 216 kr

Läs direkt efter köp

Quantum Learning: Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education explores the transformative intersection of three revolutionary technologies reshaping the future of learning. The concept of quantum learning provides a paradigm where quantum principles redefine machine learning models, enhance computational speed, and enable novel personalized education systems.

The book integrates artificial intelligence (AI), quantum algorithms, and data-driven pedagogy to reimagine classrooms and cognitive processes. Readers will discover how quantum-inspired neural networks, quantum data analysis, and intelligent tutoring systems can revolutionize educational delivery. Through interdisciplinary research, the work translates complex quantum and AI concepts into practical educational applications, featuring case studies and real-world insights that demonstrate how quantum-enhanced intelligence can personalize learning and improve outcomes. The text covers both theoretical frameworks and practical implementation strategies, offering a blueprint for adaptive, scalable learning ecosystems.

This wide-ranging book will appeal to a diverse audience of researchers, educators, technologists, and policymakers seeking to understand and shape the next generation of education innovation. By combining these domains into one book and using an accessible approach, it makes cutting-edge concepts comprehensible to both technical and non-technical readers, positioning it as an essential resource for anyone involved in educational technology, artificial intelligence research, or quantum computing applications in learning environments.

Quantum Learning

Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education

AvPawan Whig,Pavika Sharmam. fl.

Inbunden, Engelska, 2026

2 051 kr

Skickas inom 10-15 vardagar

Quantum Learning: Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education explores the transformative intersection of three revolutionary technologies reshaping the future of learning. The concept of quantum learning provides a paradigm where quantum principles redefine machine learning models, enhance computational speed, and enable novel personalized education systems.The book integrates artificial intelligence (AI), quantum algorithms, and data-driven pedagogy to reimagine classrooms and cognitive processes. Readers will discover how quantum-inspired neural networks, quantum data analysis, and intelligent tutoring systems can revolutionize educational delivery. Through interdisciplinary research, the work translates complex quantum and AI concepts into practical educational applications, featuring case studies and real-world insights that demonstrate how quantum-enhanced intelligence can personalize learning and improve outcomes. The text covers both theoretical frameworks and practical implementation strategies, offering a blueprint for adaptive, scalable learning ecosystems.This wide-ranging book will appeal to a diverse audience of researchers, educators, technologists, and policymakers seeking to understand and shape the next generation of education innovation. By combining these domains into one book and using an accessible approach, it makes cutting-edge concepts comprehensible to both technical and non-technical readers, positioning it as an essential resource for anyone involved in educational technology, artificial intelligence research, or quantum computing applications in learning environments.

AI for Cybersecurity

Standards and Regulations for Global Techno-Policy Framework

AvVinay Aseri,Pawan Whigm. fl.

Inbunden, Engelska, 2026

1 708 kr

Kommande

"AI for Cybersecurity: Standards and Regulations for Global Techno-Policy Framework" explores the intersection of artificial intelligence (AI) and cybersecurity, addressing the need for standardized regulations to protect digital infrastructures. With AI’s increasing role in threat detection and risk management, this book provides a comprehensive guide to balancing innovation with security and ethical considerations. The book delves into AI-driven cybersecurity technologies, covering topics such as machine learning-based threat detection, anomaly detection, and automated cyber defense mechanisms. It also examines adversarial AI threats and their implications for global security. On the policy side, the book discusses the importance of regulatory frameworks and the role of international organizations like the International Telecommunication Union (ITU) in setting cybersecurity standards. It aligns with the United Nations Sustainable Development Goals (SDGs), particularly Goals 9 (Industry, Innovation, and Infrastructure) and 16 (Peace, Justice, and Strong Institutions), ensuring a responsible and sustainable approach to AI in cybersecurity. Aimed at cybersecurity professionals, policymakers, business leaders, and researchers, this book offers real-world case studies, best practices, and strategic recommendations to strengthen cybersecurity at a global scale. Its interdisciplinary approach makes it a valuable resource for anyone looking to understand the future of AI-driven security governance.

AI-Enabled Social Robotics in Human Care Services

AvSandeep Kautish,Nirbhay Kumar Chaubeym. fl.

Inbunden, Engelska, 2023

3 612 kr

Skickas inom 5-8 vardagar

Del 1939 - Communications in Computer and Information Science

Sustainable Development through Machine Learning, AI and IoT

First International Conference, ICSD 2023, Delhi, India, July 15–16, 2023, Revised Selected Papers

AvPawan Whig,Nuno Silvam. fl.

Häftad, Engelska, 2023

890 kr

Skickas inom 5-8 vardagar

This book constitutes the revised selected papers of the First International Conference, ICSD 2023, virtually held in Delhi, India, during July 15–16, 2023.The book comprises 31 full papers that were selected from a total of 129 submissions. It provides insights into the latest research and advancements in sustainable development through the integration of machine learning, artificial intelligence, and IoT technologies. It serves as a valuable resource for researchers, practitioners, and policymakers working in the field of sustainable development.

Sustainable Development through Machine Learning, AI and IoT

First International Conference, ICSD 2023, Delhi, India, July 15–16, 2023, Revised Selected Papers

AvPavika Sharma,Nagender Anejam. fl.

E-bok

Engelska, 2023

1 138 kr

Läs direkt efter köp

This book constitutes the revised selected papers of the First International Conference, ICSD 2023, virtually held in Delhi, India, during July 15–16, 2023.

The book comprises 31 full papers that were selected from a total of 129 submissions. It provides insights into the latest research and advancements in sustainable development through the integration of machine learning, artificial intelligence, and IoT technologies. It serves as a valuable resource for researchers, practitioners, and policymakers working in the field of sustainable development.

Del 2196 - Communications in Computer and Information Science

Sustainable Development through Machine Learning, AI and IoT

Second International Conference, ICSD 2024, Virtual Event, April 27–28, 2024, Proceedings

AvPawan Whig,Nuno Silvam. fl.

Häftad, Engelska, 2024

1 000 kr

Skickas inom 10-15 vardagar

This book constitutes the refereed proceedings of the Second International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2024, held in Virtual Event, during April 27–28, 2024.The 38 full papers presented here were carefully reviewed and selected from 167 submissions. These papers have been categorized into the following sections: This volume encompassing a diverse array of topics at the intersection of cutting-edge technologies and practical applications. Each chapter delves into innovative approaches and solutions, providing valuable insights into contemporary challenges and opportunities in various domains. Here, we explore the realms of blockchain, data science, machine learning, artificial intelligence, and more, offering in-depth analyses and practical implementations.

Sustainable Development through Machine Learning, AI and IoT

Second International Conference, ICSD 2024, Virtual Event, April 27–28, 2024, Proceedings

AvPavika Sharma,Nagender Anejam. fl.

E-bok

Engelska, 2024

1 296 kr

Läs direkt efter köp

This book constitutes the refereed proceedings of the Second International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2024, held in Virtual Event, during April 27–28, 2024.

The 38 full papers presented here were carefully reviewed and selected from 167 submissions. These papers have been categorized into the following sections: This volume encompassing a diverse array of topics at the intersection of cutting-edge technologies and practical applications. Each chapter delves into innovative approaches and solutions, providing valuable insights into contemporary challenges and opportunities in various domains. Here, we explore the realms of blockchain, data science, machine learning, artificial intelligence, and more, offering in-depth analyses and practical implementations.

Graph Neural Networks: Essentials and Use Cases

AvPethuru Raj Chelliah,Pawan Whigm. fl.

Inbunden, Engelska, 2025

1 883 kr

Skickas inom 10-15 vardagar

This book explains the technologies and tools that underpin GNNs, offering a clear and practical guide to their industrial applications and use cases. AI engineers, data scientists, and researchers in AI and graph theory will find detailed insights into the latest trends and innovations driving this dynamic field. With practical chapters demonstrating how GNNs are reshaping various industry verticals—and how they complement advances in generative, agentic, and physical AI—this book is an essential resource for understanding and leveraging their potential.The neural network paradigm has surged in popularity for its ability to uncover hidden patterns within vast datasets. This transformative technology has spurred global innovations, particularly through the evolution of deep neural networks (DNNs). Convolutional neural networks (CNNs) have revolutionized computer vision, while recurrent neural networks (RNNs) and their advanced variants have automated natural language processing tasks such as speech recognition, translation, and content generation.Traditional DNNs primarily handle Euclidean data, yet many real-world problems involve non-Euclidean data—complex relationships and interactions naturally represented as graphs. This challenge has driven the rise of graph neural networks (GNNs), an approach that extends deep learning into new domains.GNNs are powerful models designed to work with graph-structured data, where nodes represent individual data points and edges denote the relationships between them. Several variants have emerged:Graph Convolutional Networks (GCNs): These networks learn from a node’s local neighborhood by aggregating information from adjacent nodes, updating the node’s representation in the process.Graph Attentional Networks (GATs): By incorporating attention mechanisms, GATs focus on the most relevant neighbors during aggregation, enhancing model performance.Graph Recurrent Networks (GRNs): These networks combine principles from RNNs with graph structures to capture dynamic relationships within the data.GNNs are applied in a variety of advanced use cases, including node classification, link prediction, graph clustering, anomaly detection, recommendation systems, and also in natural language processing and computer vision. They help forecast traffic patterns, analyze molecular structures, verify programs, predict social influence, model electronic health records, and map brain networks.

Graph Neural Networks: Essentials and Use Cases

AvNikhitha Yathiraju,Usha Sakthivelm. fl.

E-bok

Engelska, 2025

2 359 kr

Läs direkt efter köp

This book explains the technologies and tools that underpin GNNs, offering a clear and practical guide to their industrial applications and use cases. AI engineers, data scientists, and researchers in AI and graph theory will find detailed insights into the latest trends and innovations driving this dynamic field. With practical chapters demonstrating how GNNs are reshaping various industry verticals—and how they complement advances in generative, agentic, and physical AI—this book is an essential resource for understanding and leveraging their potential.The neural network paradigm has surged in popularity for its ability to uncover hidden patterns within vast datasets. This transformative technology has spurred global innovations, particularly through the evolution of deep neural networks (DNNs). Convolutional neural networks (CNNs) have revolutionized computer vision, while recurrent neural networks (RNNs) and their advanced variants have automated natural language processing tasks such as speech recognition, translation, and content generation.Traditional DNNs primarily handle Euclidean data, yet many real-world problems involve non-Euclidean data—complex relationships and interactions naturally represented as graphs. This challenge has driven the rise of graph neural networks (GNNs), an approach that extends deep learning into new domains.GNNs are powerful models designed to work with graph-structured data, where nodes represent individual data points and edges denote the relationships between them. Several variants have emerged:Graph Convolutional Networks (GCNs): These networks learn from a node’s local neighborhood by aggregating information from adjacent nodes, updating the node’s representation in the process.Graph Attentional Networks (GATs): By incorporating attention mechanisms, GATs focus on the most relevant neighbors during aggregation, enhancing model performance.Graph Recurrent Networks (GRNs): These networks combine principles from RNNs with graph structures to capture dynamic relationships within the data.GNNs are applied in a variety of advanced use cases, including node classification, link prediction, graph clustering, anomaly detection, recommendation systems, and also in natural language processing and computer vision. They help forecast traffic patterns, analyze molecular structures, verify programs, predict social influence, model electronic health records, and map brain networks.

Nyhet

Graph Neural Networks: Essentials and Use Cases

AvPethuru Raj Chelliah,Pawan Whigm. fl.

Häftad, Engelska, 2026

1 883 kr

Skickas inom 10-15 vardagar

This book explains the technologies and tools that underpin GNNs, offering a clear and practical guide to their industrial applications and use cases. AI engineers, data scientists, and researchers in AI and graph theory will find detailed insights into the latest trends and innovations driving this dynamic field. With practical chapters demonstrating how GNNs are reshaping various industry verticals—and how they complement advances in generative, agentic, and physical AI—this book is an essential resource for understanding and leveraging their potential.The neural network paradigm has surged in popularity for its ability to uncover hidden patterns within vast datasets. This transformative technology has spurred global innovations, particularly through the evolution of deep neural networks (DNNs). Convolutional neural networks (CNNs) have revolutionized computer vision, while recurrent neural networks (RNNs) and their advanced variants have automated natural language processing tasks such as speech recognition, translation, and content generation.Traditional DNNs primarily handle Euclidean data, yet many real-world problems involve non-Euclidean data—complex relationships and interactions naturally represented as graphs. This challenge has driven the rise of graph neural networks (GNNs), an approach that extends deep learning into new domains.GNNs are powerful models designed to work with graph-structured data, where nodes represent individual data points and edges denote the relationships between them. Several variants have emerged:Graph Convolutional Networks (GCNs): These networks learn from a node’s local neighborhood by aggregating information from adjacent nodes, updating the node’s representation in the process.Graph Attentional Networks (GATs): By incorporating attention mechanisms, GATs focus on the most relevant neighbors during aggregation, enhancing model performance.Graph Recurrent Networks (GRNs): These networks combine principles from RNNs with graph structures to capture dynamic relationships within the data.GNNs are applied in a variety of advanced use cases, including node classification, link prediction, graph clustering, anomaly detection, recommendation systems, and also in natural language processing and computer vision. They help forecast traffic patterns, analyze molecular structures, verify programs, predict social influence, model electronic health records, and map brain networks.

Del 2887 - Communications in Computer and Information Science

Sustainable Development through Machine Learning, AI and IoT

Third International Conference, ICSD 2025, New Delhi, India, June 14–15, 2025, Proceedings, Part I

AvPawan Whig,Nuno Silvam. fl.

Häftad, Engelska, 2026

945 kr

Skickas inom 10-15 vardagar

This two-volume set CCIS 2887-2888 constitutes the refereed proceedings of the Third International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2025, held in New Delhi, India, during June 14-15, 2025.The 56 full papers include in these volumes were carefully reviewed and selected from 252 submissions. They provide a comprehensive overview of recent research trends and technological advancements in sustainable development enabled by machine learning, artificial intelligence, and IoT. The contributions cover a broad spectrum of application domains, including energy-efficient and intelligent systems, smart and sustainable cities, environmental monitoring and protection, agriculture and food systems, and innovative healthcare solutions.

Sustainable Development through Machine Learning, AI and IoT

Third International Conference, ICSD 2025, New Delhi, India, June 14-15, 2025, Proceedings, Part I

AvPavika Sharma,Nagender Anejam. fl.

E-bok

Engelska, 2026

1 211 kr

Läs direkt efter köp

This two-volume set CCIS 2887-2888 constitutes the refereed proceedings of the Third International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2025, held in New Delhi, India, during June 14-15, 2025.The 56 full papers include in these volumes were carefully reviewed and selected from 252 submissions. They provide a comprehensive overview of recent research trends and technological advancements in sustainable development enabled by machine learning, artificial intelligence, and IoT. The contributions cover a broad spectrum of application domains, including energy-efficient and intelligent systems, smart and sustainable cities, environmental monitoring and protection, agriculture and food systems, and innovative healthcare solutions.

Del 2888 - Communications in Computer and Information Science

Sustainable Development through Machine Learning, AI and IoT

Third International Conference, ICSD 2025, New Delhi, India, June 14–15, 2025, Proceedings, Part II

AvPawan Whig,Nuno Silvam. fl.

Häftad, Engelska, 2026

945 kr

Skickas inom 10-15 vardagar

This two-volume set CCIS 2887-2888 constitutes the refereed proceedings of the Third International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2025, held in New Delhi, India, during June 14-15, 2025.The 56 full papers include in these volumes were carefully reviewed and selected from 252 submissions. They provide a comprehensive overview of recent research trends and technological advancements in sustainable development enabled by machine learning, artificial intelligence, and IoT. The contributions cover a broad spectrum of application domains, including energy-efficient and intelligent systems, smart and sustainable cities, environmental monitoring and protection, agriculture and food systems, and innovative healthcare solutions.

Sustainable Development through Machine Learning, AI and IoT

Third International Conference, ICSD 2025, New Delhi, India, June 14-15, 2025, Proceedings, Part II

AvPavika Sharma,Nagender Anejam. fl.

E-bok

Engelska, 2026

1 211 kr

Läs direkt efter köp

This two-volume set CCIS 2887-2888 constitutes the refereed proceedings of the Third International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2025, held in New Delhi, India, during June 14-15, 2025.The 56 full papers include in these volumes were carefully reviewed and selected from 252 submissions. They provide a comprehensive overview of recent research trends and technological advancements in sustainable development enabled by machine learning, artificial intelligence, and IoT. The contributions cover a broad spectrum of application domains, including energy-efficient and intelligent systems, smart and sustainable cities, environmental monitoring and protection, agriculture and food systems, and innovative healthcare solutions.