E. Golden Julie – författare

Handbook of Research on Blockchain Technology presents the latest information on the adaptation and implementation of Blockchain technologies in real world business, scientific, healthcare and biomedical applications. The book's editors present the rapid advancements in existing business models by applying Blockchain techniques. Novel architectural solutions in the deployment of Blockchain comprise the core aspects of this book. Several use cases with IoT, biomedical engineering, and smart cities are also incorporated. As Blockchain is a relatively new technology that exploits decentralized networks and is used in many sectors for reliable, cost-effective and rapid business transactions, this book is a welcomed addition on existing knowledge.

Financial services, retail, insurance, logistics, supply chain, public sectors and biomedical industries are now investing in Blockchain research and technologies for their business growth. Blockchain prevents double spending in financial transactions without the need of a trusted authority or central server. It is a decentralized ledger platform that facilitates verifiable transactions between parties in a secure and smart way.

This book presents a detailed exploration of adaption and implementation, as well as a 360-degree view spectrum of blockchain technologies in real-world business applications. Blockchain is gaining momentum in all sectors. This book offers a collection of protocol standards, issues, security improvements, applicability, features, and types of cryptocurrency in processing and through 5G technology.

The book covers the evolution of blockchain from fundamental theories to present forms. It offers diversified business applications with usable case studies and provides successful implementations in cloud/edge computing, smart city, and IoT. The book emphasizes the advances and cutting-edge technologies along with the different tools and platforms.

The primary audience for this book includes industry experts, researchers, graduates and under graduates, practitioners, and business managers who are engaged in blockchain and IoT-related technologies.

This book presents a detailed exploration of adaption and implementation, as well as a 360-degree view spectrum of blockchain technologies in real-world business applications. Blockchain is gaining momentum in all sectors. This book offers a collection of protocol standards, issues, security improvements, applicability, features, and types of cryptocurrency in processing and through 5G technology.

The book covers the evolution of blockchain from fundamental theories to present forms. It offers diversified business applications with usable case studies and provides successful implementations in cloud/edge computing, smart city, and IoT. The book emphasizes the advances and cutting-edge technologies along with the different tools and platforms.

The primary audience for this book includes industry experts, researchers, graduates and under graduates, practitioners, and business managers who are engaged in blockchain and IoT-related technologies.

This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease.

This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat patients more effectively.

Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. This volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc.

Key features:

Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.

This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease.

This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat patients more effectively.

Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. This volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc.

Key features:

Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.

Blockchain provides an environment where technologies converge to provide numerous benefits. However, there are still many problems ahead, and changes are required at all levels - technology, algorithms, and human-computer interaction for widespread acceptance of blockchain intelligence systems. This book reviews blockchain technology and the current developments in research and business applications. It explores the real-time applications and issues that will bring the synergy needed to materialize the goal of blockchain intelligence.

Researchers in various fields such as Blockchain, Data Analysis, IoT, Data Science, Crypto currencies will find this book useful. Students and professionals working on Blockchain in artificial intelligence, IoT, Healthcare, Robotics, Soft computing, and Data science will also benefit from this. It offers a realistic and thorough introduction that supports programmers, students and researchers in other disciplines. The book comprises chapters dealing with various issues, to provide readers with greater readability, versatility and adaptability.

Blockchain provides an environment where technologies converge to provide numerous benefits. However, there are still many problems ahead, and changes are required at all levels - technology, algorithms, and human-computer interaction for widespread acceptance of blockchain intelligence systems. This book reviews blockchain technology and the current developments in research and business applications. It explores the real-time applications and issues that will bring the synergy needed to materialize the goal of blockchain intelligence.

Researchers in various fields such as Blockchain, Data Analysis, IoT, Data Science, Crypto currencies will find this book useful. Students and professionals working on Blockchain in artificial intelligence, IoT, Healthcare, Robotics, Soft computing, and Data science will also benefit from this. It offers a realistic and thorough introduction that supports programmers, students and researchers in other disciplines. The book comprises chapters dealing with various issues, to provide readers with greater readability, versatility and adaptability.

This breakthrough edited volume highlights the security, privacy, artificial intelligence, and practical approaches needed by engineers and scientists in all fields of science and technology. It highlights the current research, which is intended to advance not only mathematics but all areas of science, research, and development, and where these disciplines intersect. As the book is focused on emerging concepts in machine learning and artificial intelligence algorithmic approaches and soft computing techniques, it is an invaluable tool for researchers, academicians, data scientists, and technology developers.

The newest and most comprehensive volume in the area of mathematical methods for use in real-time engineering, this groundbreaking new work is a must-have for any engineer or scientist’s library. Also useful as a textbook for the student, it is a valuable contribution to the advancement of the science, both a working handbook for the new hire or student, and a reference for the veteran engineer.

This breakthrough edited volume highlights the security, privacy, artificial intelligence, and practical approaches needed by engineers and scientists in all fields of science and technology. It highlights the current research, which is intended to advance not only mathematics but all areas of science, research, and development, and where these disciplines intersect. As the book is focused on emerging concepts in machine learning and artificial intelligence algorithmic approaches and soft computing techniques, it is an invaluable tool for researchers, academicians, data scientists, and technology developers.

The newest and most comprehensive volume in the area of mathematical methods for use in real-time engineering, this groundbreaking new work is a must-have for any engineer or scientist’s library. Also useful as a textbook for the student, it is a valuable contribution to the advancement of the science, both a working handbook for the new hire or student, and a reference for the veteran engineer.

This book provides a comprehensive exploration of computational intelligence techniques and their applications, offering valuable insights into advanced information processing, machine learning concepts, and their impact on agile manufacturing systems.

Computational Intelligence presents a new concept for advanced information processing. Computational Intelligence (CI) is the principle, architecture, implementation, and growth of machine learning concepts that are physiologically and semantically inspired. Computational Intelligence methods aim to develop an approach to evaluating and creating flexible processing of human information, such as sensing, understanding, learning, recognizing, and thinking. The Artificial Neural Network simulates the human nervous system’s physiological characteristics and has been implemented numerically for non-linear mapping. Fuzzy Logic Systems simulate the human brain’s psychological characteristics and have been used for linguistic translation through membership functions and bioinformatics. The Genetic Algorithm simulates computer evolution and has been applied to solve problems with optimization algorithms for improvements in diagnostic and treatment technologies for various diseases. To expand the agility and learning capacity of manufacturing systems, these methods play essential roles. This book will express the computer vision techniques that make manufacturing systems more flexible, efficient, robust, adaptive, and productive by examining many applications and research into computational intelligence techniques concerning the main problems in design, making plans, and manufacturing goods in agile manufacturing systems.

This book provides a comprehensive exploration of computational intelligence techniques and their applications, offering valuable insights into advanced information processing, machine learning concepts, and their impact on agile manufacturing systems.

Computational Intelligence presents a new concept for advanced information processing. Computational Intelligence (CI) is the principle, architecture, implementation, and growth of machine learning concepts that are physiologically and semantically inspired. Computational Intelligence methods aim to develop an approach to evaluating and creating flexible processing of human information, such as sensing, understanding, learning, recognizing, and thinking. The Artificial Neural Network simulates the human nervous system’s physiological characteristics and has been implemented numerically for non-linear mapping. Fuzzy Logic Systems simulate the human brain’s psychological characteristics and have been used for linguistic translation through membership functions and bioinformatics. The Genetic Algorithm simulates computer evolution and has been applied to solve problems with optimization algorithms for improvements in diagnostic and treatment technologies for various diseases. To expand the agility and learning capacity of manufacturing systems, these methods play essential roles. This book will express the computer vision techniques that make manufacturing systems more flexible, efficient, robust, adaptive, and productive by examining many applications and research into computational intelligence techniques concerning the main problems in design, making plans, and manufacturing goods in agile manufacturing systems.