Pramod Singh Rathore – författare

This new volume looks at the electrifying world of blockchain technology and how it has been revolutionizing the Internet of Things and cyber-physical systems. Aimed primarily at business users and developers who are considering blockchain-based projects, the volume provides a comprehensive introduction to the theoretical and practical aspects of blockchain technology. It presents a selection of chapters on topics that cover new information on blockchain and bitcoin security, IoT security threats and attacks, privacy issues, fault-tolerance mechanisms, and more. Some major software packages are discussed, and it also addresses the legal issues currently affecting the field. The information presented here is relevant to current and future problems relating to blockchain technology and will provide the tools to build efficient decentralized applications.

Blockchain technology and the IoT can profoundly change how the world—and businesses—work, and this book provides a window into the current world of blockchain. No longer limited to just Bitcoin, blockchain technology has spread into many sectors and into a significant number of different technologies.

This new volume looks at the electrifying world of blockchain technology and how it has been revolutionizing the Internet of Things and cyber-physical systems. Aimed primarily at business users and developers who are considering blockchain-based projects, the volume provides a comprehensive introduction to the theoretical and practical aspects of blockchain technology. It presents a selection of chapters on topics that cover new information on blockchain and bitcoin security, IoT security threats and attacks, privacy issues, fault-tolerance mechanisms, and more. Some major software packages are discussed, and it also addresses the legal issues currently affecting the field. The information presented here is relevant to current and future problems relating to blockchain technology and will provide the tools to build efficient decentralized applications.

Blockchain technology and the IoT can profoundly change how the world—and businesses—work, and this book provides a window into the current world of blockchain. No longer limited to just Bitcoin, blockchain technology has spread into many sectors and into a significant number of different technologies.

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them.

Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector.

The features of this book include:

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them.

Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector.

The features of this book include:

In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity.

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges.

This book is useful for research scholars and students involved in critical condition analysis and computation models.

In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity.

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges.

This book is useful for research scholars and students involved in critical condition analysis and computation models.

The purpose of this book is first to study MATLAB programming concepts, then the basic concepts of modeling and simulation analysis, particularly focus on digital communication simulation. The book will cover the topics practically to describe network routing simulation using MATLAB tool. It will cover the dimensions'' like Wireless network and WSN simulation using MATLAB, then depict the modeling and simulation of vehicles power network in detail along with considering different case studies.

Key features of the book include:

The purpose of this book is first to study MATLAB programming concepts, then the basic concepts of modeling and simulation analysis, particularly focus on digital communication simulation. The book will cover the topics practically to describe network routing simulation using MATLAB tool. It will cover the dimensions'' like Wireless network and WSN simulation using MATLAB, then depict the modeling and simulation of vehicles power network in detail along with considering different case studies.

Key features of the book include:

The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named "Industry 5.0" or "Industrial Internet of Things." The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive.

The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named "Industry 5.0" or "Industrial Internet of Things." The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive.

Written and edited by a team of experts in the field, this outstanding new volume offers solutions to the problems of security, outlining the concepts behind allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts.

Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to artificial intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalized security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and data mining and several other computing technologies to deploy such a system in an effective manner.

This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice.

This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library.

This groundbreaking new volume: