Achyut Shankar – författare

Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way. The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today.The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.

Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way. The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today.The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.

Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way.

The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today.

The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.

Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way.

The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today.

The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.

In the past decades, cyber-physical systems (CPSs) have been widely applied to fields such as smart grids, environment monitoring, aerospace, smart transportation, and industrial automation. Great strides have been made in CPSs to improve the computing mechanism, communication, and quality of service by applying optimization algorithms. Currently, these efforts are integrated with the applications of machine learning (ML) and artificial intelligence (AI). To maintain system reliability and stability, CPSs such as smart grids face numerous challenges, including large-scale Internet-of-Things (IoT) device adaptation, ever-increasing demands of electrical energy, and the rise of a wide range of security threats. These challenges bring forth the need to find sustainable and advanced solutions to guarantee reliable and secure operations in these systems.The goal of this book is to foster transformative, multidisciplinary, and novel approaches that ensure CPS security by taking into consideration the unique security challenges present in the environment. This book attracts contributions in all aspects pertaining to this multidisciplinary paradigm, which includes the development and implementation of Smart CPS, Supervisory Control and Data Acquisition (SCADA) systems, CPS for Industry 4.0, CPS architecture for IoT applications, and CPS forensics.This book:Discusses concepts including wireless sensor networks (WSNs), CPSs, and the IoT in a comprehensive manner.Covers routing protocols in sensor networks, attacks, and vulnerabilities in WSNs, the Internet of Cyber-Physical Things, and CPSs for industrial applications.Highlights technological advances, practical solutions, emerging trends, and prototypes related to privacy in CPSs and the IoT.Presents a pathway and architecture for proactive security schemes in CPSs to counter vulnerabilities, including phishing attacks, malware injection, internal stealing of data, and hacking.Discusses the most recent research and development on the enabling technologies for IoT-based CPSs.Owing to the scope and diversity of topics covered, the book will be of interest not only to researchers and theorists but also to professionals, material developers, technology specialists, and methodologists dealing with the multifarious aspects of data privacy and security enhancement in CPSs. The book will provide these professionals an overview of CPS security and privacy design, as well as enlighten them to promising solutions to research problems such as cyberattacks in CPS, risk identification and management in CPS, ML-based trust computational models for CPSs, nature-inspired algorithms for CPSs, and distributed consensus algorithms for event detection in CPSs. The secondary target audience of this book includes legal practitioners, hackers, cyber law policymakers, cyber forensic analysts, and global security consortiums who may use it to further their research exposure to pertinent topics in cybersecurity.

In the past decades, cyber-physical systems (CPSs) have been widely applied to fields such as smart grids, environment monitoring, aerospace, smart transportation, and industrial automation. Great strides have been made in CPSs to improve the computing mechanism, communication, and quality of service by applying optimization algorithms. Currently, these efforts are integrated with the applications of machine learning (ML) and artificial intelligence (AI). To maintain system reliability and stability, CPSs such as smart grids face numerous challenges, including large-scale Internet-of-Things (IoT) device adaptation, ever-increasing demands of electrical energy, and the rise of a wide range of security threats. These challenges bring forth the need to find sustainable and advanced solutions to guarantee reliable and secure operations in these systems.The goal of this book is to foster transformative, multidisciplinary, and novel approaches that ensure CPS security by taking into consideration the unique security challenges present in the environment. This book attracts contributions in all aspects pertaining to this multidisciplinary paradigm, which includes the development and implementation of Smart CPS, Supervisory Control and Data Acquisition (SCADA) systems, CPS for Industry 4.0, CPS architecture for IoT applications, and CPS forensics.This book:Discusses concepts including wireless sensor networks (WSNs), CPSs, and the IoT in a comprehensive manner.Covers routing protocols in sensor networks, attacks, and vulnerabilities in WSNs, the Internet of Cyber-Physical Things, and CPSs for industrial applications.Highlights technological advances, practical solutions, emerging trends, and prototypes related to privacy in CPSs and the IoT.Presents a pathway and architecture for proactive security schemes in CPSs to counter vulnerabilities, including phishing attacks, malware injection, internal stealing of data, and hacking.Discusses the most recent research and development on the enabling technologies for IoT-based CPSs.Owing to the scope and diversity of topics covered, the book will be of interest not only to researchers and theorists but also to professionals, material developers, technology specialists, and methodologists dealing with the multifarious aspects of data privacy and security enhancement in CPSs. The book will provide these professionals an overview of CPS security and privacy design, as well as enlighten them to promising solutions to research problems such as cyberattacks in CPS, risk identification and management in CPS, ML-based trust computational models for CPSs, nature-inspired algorithms for CPSs, and distributed consensus algorithms for event detection in CPSs. The secondary target audience of this book includes legal practitioners, hackers, cyber law policymakers, cyber forensic analysts, and global security consortiums who may use it to further their research exposure to pertinent topics in cybersecurity.

This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and engages in a discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems, which are important in intelligent wireless communications.Features:• Discusses machine learning-based network management strategy in wireless systems, and machine learning-inspired big data analytics frameworks for wireless network applications.• Presents high-speed communication systems, deep learning for wireless networks, security aspects in wireless networks, and decision-making for wireless networks.• Highlights the importance of using deep reinforcement learning in intelligent wireless networks and deep reinforcement learning-based mobile data offloading frameworks.• Covers novel network architectures for distributed edge learning, and privacy issues in distributed edge learning.• Illustrates experimentation and deep learning-based simulations in networking systems, deep learning-based communication frameworks for multiuser detection and sparse channel estimation.The book is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

In the past decades, cyber-physical systems (CPSs) have been widely applied to fields such as smart grids, environment monitoring, aerospace, smart transportation, and industrial automation. Great strides have been made in CPSs to improve the computing mechanism, communication, and quality of service by applying optimization algorithms. Currently, these efforts are integrated with the applications of machine learning (ML) and artificial intelligence (AI). To maintain system reliability and stability, CPSs such as smart grids face numerous challenges, including large-scale Internet-of-Things (IoT) device adaptation, ever-increasing demands of electrical energy, and the rise of a wide range of security threats. These challenges bring forth the need to find sustainable and advanced solutions to guarantee reliable and secure operations in these systems.The goal of this book is to foster transformative, multidisciplinary, and novel approaches that ensure CPS security by taking into consideration the unique security challenges present in the environment. This book attracts contributions in all aspects pertaining to this multidisciplinary paradigm, which includes the development and implementation of Smart CPS, Supervisory Control and Data Acquisition (SCADA) systems, CPS for Industry 4.0, CPS architecture for IoT applications, and CPS forensics.This book: Discusses concepts including wireless sensor networks (WSNs), CPSs, and the IoT in a comprehensive manner. Covers routing protocols in sensor networks, attacks, and vulnerabilities in WSNs, the Internet of Cyber-Physical Things, and CPSs for industrial applications. Highlights technological advances, practical solutions, emerging trends, and prototypes related to privacy in CPSs and the IoT. Presents a pathway and architecture for proactive security schemes in CPSs to counter vulnerabilities, including phishing attacks, malware injection, internal stealing of data, and hacking. Discusses the most recent research and development on the enabling technologies for IoT-based CPSs. Owing to the scope and diversity of topics covered, the book will be of interest not only to researchers and theorists but also to professionals, material developers, technology specialists, and methodologists dealing with the multifarious aspects of data privacy and security enhancement in CPSs. The book will provide these professionals an overview of CPS security and privacy design, as well as enlighten them to promising solutions to research problems such as cyberattacks in CPS, risk identification and management in CPS, ML-based trust computational models for CPSs, nature-inspired algorithms for CPSs, and distributed consensus algorithms for event detection in CPSs. The secondary target audience of this book includes legal practitioners, hackers, cyber law policymakers, cyber forensic analysts, and global security consortiums who may use it to further their research exposure to pertinent topics in cybersecurity.

In the past decades, cyber-physical systems (CPSs) have been widely applied to fields such as smart grids, environment monitoring, aerospace, smart transportation, and industrial automation. Great strides have been made in CPSs to improve the computing mechanism, communication, and quality of service by applying optimization algorithms. Currently, these efforts are integrated with the applications of machine learning (ML) and artificial intelligence (AI). To maintain system reliability and stability, CPSs such as smart grids face numerous challenges, including large-scale Internet-of-Things (IoT) device adaptation, ever-increasing demands of electrical energy, and the rise of a wide range of security threats. These challenges bring forth the need to find sustainable and advanced solutions to guarantee reliable and secure operations in these systems.The goal of this book is to foster transformative, multidisciplinary, and novel approaches that ensure CPS security by taking into consideration the unique security challenges present in the environment. This book attracts contributions in all aspects pertaining to this multidisciplinary paradigm, which includes the development and implementation of Smart CPS, Supervisory Control and Data Acquisition (SCADA) systems, CPS for Industry 4.0, CPS architecture for IoT applications, and CPS forensics.This book: Discusses concepts including wireless sensor networks (WSNs), CPSs, and the IoT in a comprehensive manner. Covers routing protocols in sensor networks, attacks, and vulnerabilities in WSNs, the Internet of Cyber-Physical Things, and CPSs for industrial applications. Highlights technological advances, practical solutions, emerging trends, and prototypes related to privacy in CPSs and the IoT. Presents a pathway and architecture for proactive security schemes in CPSs to counter vulnerabilities, including phishing attacks, malware injection, internal stealing of data, and hacking. Discusses the most recent research and development on the enabling technologies for IoT-based CPSs. Owing to the scope and diversity of topics covered, the book will be of interest not only to researchers and theorists but also to professionals, material developers, technology specialists, and methodologists dealing with the multifarious aspects of data privacy and security enhancement in CPSs. The book will provide these professionals an overview of CPS security and privacy design, as well as enlighten them to promising solutions to research problems such as cyberattacks in CPS, risk identification and management in CPS, ML-based trust computational models for CPSs, nature-inspired algorithms for CPSs, and distributed consensus algorithms for event detection in CPSs. The secondary target audience of this book includes legal practitioners, hackers, cyber law policymakers, cyber forensic analysts, and global security consortiums who may use it to further their research exposure to pertinent topics in cybersecurity.

This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and engages in a discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems, which are important in intelligent wireless communications.Features:* Discusses machine learning-based network management strategy in wireless systems, and machine learning-inspired big data analytics frameworks for wireless network applications.* Presents high-speed communication systems, deep learning for wireless networks, security aspects in wireless networks, and decision-making for wireless networks.* Highlights the importance of using deep reinforcement learning in intelligent wireless networks and deep reinforcement learning-based mobile data offloading frameworks.* Covers novel network architectures for distributed edge learning, and privacy issues in distributed edge learning.* Illustrates experimentation and deep learning-based simulations in networking systems, deep learning-based communication frameworks for multiuser detection and sparse channel estimation.The book is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and engages in a discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems, which are important in intelligent wireless communications.Features:* Discusses machine learning-based network management strategy in wireless systems, and machine learning-inspired big data analytics frameworks for wireless network applications.* Presents high-speed communication systems, deep learning for wireless networks, security aspects in wireless networks, and decision-making for wireless networks.* Highlights the importance of using deep reinforcement learning in intelligent wireless networks and deep reinforcement learning-based mobile data offloading frameworks.* Covers novel network architectures for distributed edge learning, and privacy issues in distributed edge learning.* Illustrates experimentation and deep learning-based simulations in networking systems, deep learning-based communication frameworks for multiuser detection and sparse channel estimation.The book is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

This book introduces new and innovative science and technology research and development toward supporting sustainable economic development and protecting the environment. It explores how emergent and eco-technologies are reshaping major sectors toward sustainability goals at global level. Addressing new studies, industrial case studies, numerous disciplinary research, this book gives insights of research in topics like green material, renewable energy, smart city, AI driven environmental monitoring, the circular economy, the sustainable agriculture, the water conservation, and green movement. Advanced results in these areas are very important because of the challenges which include climate change, loss of resources, and over-exploitation of industries. This book connects technology, policy, science, and history to demonstrate how these costs, trade-offs can be transformed into opportunities for innovative solutions and growth with lesser the impacts of natural disasters while strengthening the economy success. This book describes scalable practices, disruptive new approaches, and case studies that show the reader how to adopt sustainable practices for ecological balance and with economic success. This book addresses how digitization, smart system like AI, IoT, blockchain can support sustainable governance with sustainable utilization of resources. This book also covers awareness and opportunities for educational reform needed to produce an environmentally aware and sustainable society. Some of the challenges covered by this book are the risk of dispersed innovation activities, the absence of integration between sustainable and engineering practices, and most notably, the restricted spread of eco-technology in industrial systems. The objective of the book is to bridge these gaps by providing an integrated perspective and evidence-based case study solutions. The proposed book is useful to academicians, engineers, environmental scientists, policy makers, graduate and postgraduate students, and all those readers who want sustainable solutions for innovation and green technology prospective.