Rohit Tanwar – författare

Information Security and Optimization maintains a practical perspective while offering theoretical explanations. The book explores concepts that are essential for academics as well as organizations. It discusses aspects of techniques and tools—definitions, usage, and analysis—that are invaluable for scholars ranging from those just beginning in the field to established experts. What are the policy standards? What are vulnerabilities and how can one patch them? How can data be transmitted securely? How can data in the cloud or cryptocurrency in the blockchain be secured? How can algorithms be optimized? These are some of the possible queries that are answered here effectively using examples from real life and case studies.

Features:

Information Security and Optimization is equally helpful for undergraduate and postgraduate students as well as for researchers working in the domain. It can be recommended as a reference or textbook for courses related to cybersecurity.

Information Security and Optimization maintains a practical perspective while offering theoretical explanations. The book explores concepts that are essential for academics as well as organizations. It discusses aspects of techniques and tools—definitions, usage, and analysis—that are invaluable for scholars ranging from those just beginning in the field to established experts. What are the policy standards? What are vulnerabilities and how can one patch them? How can data be transmitted securely? How can data in the cloud or cryptocurrency in the blockchain be secured? How can algorithms be optimized? These are some of the possible queries that are answered here effectively using examples from real life and case studies.

Features:

Information Security and Optimization is equally helpful for undergraduate and postgraduate students as well as for researchers working in the domain. It can be recommended as a reference or textbook for courses related to cybersecurity.

The volume provides a wealth of up-to-date information on developments and applications of deep learning in healthcare and medicine, providing deep insight and understanding of novel applications that address the tough questions of disease diagnosis, prevention, and immunization. The volume looks at applications of deep learning for major medical challenges such as cancer detection and identification, birth asphyxia among neonates, kidney abnormalities, white blood cell segmentation, diabetic retinopathy detection, and Covid-19 diagnosis, prevention, and immunization. The volume discusses applications of deep learning in detection, diagnosis, intensive examination and evaluation, genomic sequencing, convolutional neural networks for image recognition and processing, and more for health issues such as kidney problems, brain tumors, lung damage, and breast cancer. The authors look at ML for brain tumor segmentation, in lung CT scans, in digital X-ray devices, and for logistic and transport systems for effective delivery of healthcare.

The volume provides a wealth of up-to-date information on developments and applications of deep learning in healthcare and medicine, providing deep insight and understanding of novel applications that address the tough questions of disease diagnosis, prevention, and immunization. The volume looks at applications of deep learning for major medical challenges such as cancer detection and identification, birth asphyxia among neonates, kidney abnormalities, white blood cell segmentation, diabetic retinopathy detection, and Covid-19 diagnosis, prevention, and immunization. The volume discusses applications of deep learning in detection, diagnosis, intensive examination and evaluation, genomic sequencing, convolutional neural networks for image recognition and processing, and more for health issues such as kidney problems, brain tumors, lung damage, and breast cancer. The authors look at ML for brain tumor segmentation, in lung CT scans, in digital X-ray devices, and for logistic and transport systems for effective delivery of healthcare.

Unleashing the Art of Digital Forensics is intended to describe and explain the steps taken during a forensic examination, with the intent of making the reader aware of the constraints and considerations that apply during a forensic examination in law enforcement and in the private sector.

Key Features:

• Discusses the recent advancements in Digital Forensics and Cybersecurity

• Reviews detailed applications of Digital Forensics for real-life problems

• Addresses the challenges related to implementation of Digital Forensics and Anti-Forensic approaches

• Includes case studies that will be helpful for researchers

• Offers both quantitative and qualitative research articles, conceptual papers, review papers, etc.

• Identifies the future scope of research in the field of Digital Forensics and Cybersecurity.

This book is aimed primarily at and will be beneficial to graduates, postgraduates, and researchers in Digital Forensics and Cybersecurity.

Unleashing the Art of Digital Forensics is intended to describe and explain the steps taken during a forensic examination, with the intent of making the reader aware of the constraints and considerations that apply during a forensic examination in law enforcement and in the private sector.

Key Features:

• Discusses the recent advancements in Digital Forensics and Cybersecurity

• Reviews detailed applications of Digital Forensics for real-life problems

• Addresses the challenges related to implementation of Digital Forensics and Anti-Forensic approaches

• Includes case studies that will be helpful for researchers

• Offers both quantitative and qualitative research articles, conceptual papers, review papers, etc.

• Identifies the future scope of research in the field of Digital Forensics and Cybersecurity.

This book is aimed primarily at and will be beneficial to graduates, postgraduates, and researchers in Digital Forensics and Cybersecurity.

This book focuses on artificial intelligence (AI) and machine learning (ML) technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems. This concise reference book offers a broad overview of the most important trends and discusses how these trends and technologies are being created and employed in the applications in which they are being used.

Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies offers a broad package involving the incubation of AI and ML with various emerging technologies such as Internet of Things (IoT), healthcare, smart cities, robotics, and more. The book discusses various data collection and data transformation techniques and also maps the legal and ethical issues of data-driven e-healthcare systems while covering possible ways to resolve them. The book explores different techniques on how AI can be used to create better virtual reality experiences and deals with the techniques and possible ways to merge the power of AI and IoT to create smart home appliances.

With contributions from experts in the field, this reference book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

This book focuses on artificial intelligence (AI) and machine learning (ML) technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems. This concise reference book offers a broad overview of the most important trends and discusses how these trends and technologies are being created and employed in the applications in which they are being used.

Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies offers a broad package involving the incubation of AI and ML with various emerging technologies such as Internet of Things (IoT), healthcare, smart cities, robotics, and more. The book discusses various data collection and data transformation techniques and also maps the legal and ethical issues of data-driven e-healthcare systems while covering possible ways to resolve them. The book explores different techniques on how AI can be used to create better virtual reality experiences and deals with the techniques and possible ways to merge the power of AI and IoT to create smart home appliances.

With contributions from experts in the field, this reference book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

CyberMedics: Navigating AI and Security in the Medical Field is a comprehensive exploration of the transformative role of artificial intelligence (AI) in healthcare and the critical importance of securing medical data in an increasingly digital world. As AI technologies revolutionize diagnostics, treatment planning, and patient care, they also introduce new challenges related to data privacy, ethical considerations, and cybersecurity. This book offers a balanced perspective, providing healthcare professionals, technologists, and policymakers with the tools they need to understand and navigate the intersection of AI and security. Through detailed case studies, expert insights, and practical guidance, readers will discover how AI can be leveraged to improve patient outcomes while maintaining the highest standards of data protection.

Key topics include:

Whether you’re on the front lines of patient care, involved in healthcare IT, or shaping policy, CyberMedics: Navigating AI and Security in the Medical Field equips you with the knowledge to make informed decisions in a rapidly evolving landscape, ensuring that innovation and security go hand in hand to enhance the quality of care.

CyberMedics: Navigating AI and Security in the Medical Field is a comprehensive exploration of the transformative role of artificial intelligence (AI) in healthcare and the critical importance of securing medical data in an increasingly digital world. As AI technologies revolutionize diagnostics, treatment planning, and patient care, they also introduce new challenges related to data privacy, ethical considerations, and cybersecurity. This book offers a balanced perspective, providing healthcare professionals, technologists, and policymakers with the tools they need to understand and navigate the intersection of AI and security. Through detailed case studies, expert insights, and practical guidance, readers will discover how AI can be leveraged to improve patient outcomes while maintaining the highest standards of data protection.

Key topics include:

Whether you’re on the front lines of patient care, involved in healthcare IT, or shaping policy, CyberMedics: Navigating AI and Security in the Medical Field equips you with the knowledge to make informed decisions in a rapidly evolving landscape, ensuring that innovation and security go hand in hand to enhance the quality of care.

The book examines the integration of IoT, Blockchain, and Smart Healthcare, providing a comprehensive analysis of these advanced technologies and their impact on the healthcare industry. It offers practical examples of how Blockchain and IoT devices can be used to address real-world healthcare challenges and overcome the hurdles of implementing them in the healthcare sector.

IoT, Blockchain, and Smart Healthcare: Integration Techniques and Case Studies provides a detailed exploration of how these technologies are combined, giving readers a deep understanding of their role in revolutionizing healthcare. It explores the practical applications of Blockchain and IoT devices in solving healthcare problems and addresses the challenges of incorporating these technologies into healthcare systems. The book also provides practical guidance on implementing cutting-edge methodologies, enabling readers to apply theoretical knowledge in real-world situations effectively.

By bridging the gap between technology and healthcare, this book makes complex concepts understandable to a wide audience, including healthcare professionals, researchers, technology enthusiasts, and policymakers.

The book examines the integration of IoT, Blockchain, and Smart Healthcare, providing a comprehensive analysis of these advanced technologies and their impact on the healthcare industry. It offers practical examples of how Blockchain and IoT devices can be used to address real-world healthcare challenges and overcome the hurdles of implementing them in the healthcare sector.

IoT, Blockchain, and Smart Healthcare: Integration Techniques and Case Studies provides a detailed exploration of how these technologies are combined, giving readers a deep understanding of their role in revolutionizing healthcare. It explores the practical applications of Blockchain and IoT devices in solving healthcare problems and addresses the challenges of incorporating these technologies into healthcare systems. The book also provides practical guidance on implementing cutting-edge methodologies, enabling readers to apply theoretical knowledge in real-world situations effectively.

By bridging the gap between technology and healthcare, this book makes complex concepts understandable to a wide audience, including healthcare professionals, researchers, technology enthusiasts, and policymakers.

This book offers a complete package involving the incubation of machine learning, AI, and IoT in healthcare that is beneficial for researchers, healthcare professionals, scientists, and technologists.

The applications and challenges of machine learning and artificial intelligence in the Internet of Things (IoT) for healthcare applications are comprehensively covered in this book.

IoT generates big data of varying data quality; intelligent processing and analysis of this big data are the keys to developing smart IoT applications, thereby making space for machine learning (ML) applications. Due to its computational tools that can substitute for human intelligence in the performance of certain tasks, artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Since IoT platforms provide an interface to gather data from various devices, they can easily be deployed into AI/ML systems. The value of AI in this context is its ability to quickly mesh insights from data and automatically identify patterns and detect anomalies in the data that smart sensors and devices generate—information such as temperature, pressure, humidity, air quality, vibration, and sound—that can be really helpful to rapid diagnosis.

Audience

This book will be of interest to researchers in artificial intelligence, the Internet of Things, machine learning as well as information technologists working in the healthcare sector.

This book offers a complete package involving the incubation of machine learning, AI, and IoT in healthcare that is beneficial for researchers, healthcare professionals, scientists, and technologists.

The applications and challenges of machine learning and artificial intelligence in the Internet of Things (IoT) for healthcare applications are comprehensively covered in this book.

IoT generates big data of varying data quality; intelligent processing and analysis of this big data are the keys to developing smart IoT applications, thereby making space for machine learning (ML) applications. Due to its computational tools that can substitute for human intelligence in the performance of certain tasks, artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Since IoT platforms provide an interface to gather data from various devices, they can easily be deployed into AI/ML systems. The value of AI in this context is its ability to quickly mesh insights from data and automatically identify patterns and detect anomalies in the data that smart sensors and devices generate—information such as temperature, pressure, humidity, air quality, vibration, and sound—that can be really helpful to rapid diagnosis.

Audience

This book will be of interest to researchers in artificial intelligence, the Internet of Things, machine learning as well as information technologists working in the healthcare sector.