Sudesh Yadav – författare

Quaternion-Sparse Image Processing: Advances in Multispectral Processing brings together the technologies, research, and managerial applications of quaternion-sparse based complex algebra in image processing. The book covers the entire range of complicated tasks performed on color images, including denoising, reconstruction, classification, hallucination, feature extraction, dimension reduction, and regularization. It provides easy understanding and smooth adaptability of basic and advanced concepts for graduate students, researchers, doctors, academics, and practitioners.Uncovers the innovative features of complex algebra, specifically the quaternion-sparse concept in image processing and how it can help in improving the computational efficiency of image processingDeals with the most common quaternion convolution neural network, quaternion wavelet, and sparse representation-based techniques in multispectral image processingFocuses on how evolution in algebraic concepts, i.e., quaternion and sparse, help in improving accuracy and efficiency of various color image restoration, reconstruction, and recognitionIllustrates how important features are extracted and complete information is stored in extracted features to help and process tasks in an easy and computationally efficient way

Quaternion-Sparse Image Processing: Advances in Multispectral Processing brings together the technologies, research, and managerial applications of quaternion-sparse based complex algebra in image processing. The book covers the entire range of complicated tasks performed on color images, including denoising, reconstruction, classification, hallucination, feature extraction, dimension reduction, and regularization. It provides easy understanding and smooth adaptability of basic and advanced concepts for graduate students, researchers, doctors, academics, and practitioners.- Uncovers the innovative features of complex algebra, specifically the quaternion-sparse concept in image processing and how it can help in improving the computational efficiency of image processing- Deals with the most common quaternion convolution neural network, quaternion wavelet, and sparse representation-based techniques in multispectral image processing- Focuses on how evolution in algebraic concepts, i.e., quaternion and sparse, help in improving accuracy and efficiency of various color image restoration, reconstruction, and recognition- Illustrates how important features are extracted and complete information is stored in extracted features to help and process tasks in an easy and computationally efficient way

ADVANCES IN FUZZY-BASED INTERNET OF MEDICAL THINGS (IOMT) This book explores the latest trends, transitions, and advancements of the Internet of Medical Things whose integration through cloud-hosted software applications adds required intelligence from tools such as medical instruments, scanners, and appliances, enabling fuzzy logic to help medical professionals establish linguistic concepts in deciding diagnosis and prognosis. The main goal of the book is to strengthen medical professionals and caregivers by providing methods for achieving fuzzy logic-based health diagnosis and medication. The health condition and various physical parameters of humans, such as heartbeat rate, sugar level, blood pressure, temperature, and oxygen quality, are captured through a host of multifaceted sensors. Additionally, remote health monitoring, medication, and management are being facilitated through a host of ingestible sensors, 5G communication, networked embedded systems, AI models running on cloud servers and edge devices, etc. Furthermore, chronic disease management is another vital domain getting increased attention. The distinct advancements in the fuzzy logic field are useful in various advanced medical care functionalities and facilities. The readers will discover: new and innovative features of health care by using fuzzy logic that raises economic efficiency at macro and micro levels;expounds on fuzzy logic techniques used in medical science;describes the evolution of the fuzzy logic paradigm and how it helps physicians decide on diagnosis and prognosis;uncovers how trust management is dealt with between patients and medical officials to help advance the fuzzy logic field;provides case studies, various technology advancements, and practical aspects on the impacts and challenges of fuzzy-based Internet of Medical Things.Audience The book will be read and used by researchers in artificial intelligence, fuzzy logic, medical professionals, caregivers, health administrators, and policymakers.

ADVANCES IN FUZZY-BASED INTERNET OF MEDICAL THINGS (IOMT)

This book explores the latest trends, transitions, and advancements of the Internet of Medical Things whose integration through cloud-hosted software applications adds required intelligence from tools such as medical instruments, scanners, and appliances, enabling fuzzy logic to help medical professionals establish linguistic concepts in deciding diagnosis and prognosis.

The main goal of the book is to strengthen medical professionals and caregivers by providing methods for achieving fuzzy logic-based health diagnosis and medication. The health condition and various physical parameters of humans, such as heartbeat rate, sugar level, blood pressure, temperature, and oxygen quality, are captured through a host of multifaceted sensors. Additionally, remote health monitoring, medication, and management are being facilitated through a host of ingestible sensors, 5G communication, networked embedded systems, AI models running on cloud servers and edge devices, etc. Furthermore, chronic disease management is another vital domain getting increased attention. The distinct advancements in the fuzzy logic field are useful in various advanced medical care functionalities and facilities.

The readers will discover:

new and innovative features of health care by using fuzzy logic that raises economic efficiency at macro and micro levels; expounds on fuzzy logic techniques used in medical science; describes the evolution of the fuzzy logic paradigm and how it helps physicians decide on diagnosis and prognosis; uncovers how trust management is dealt with between patients and medical officials to help advance the fuzzy logic field; provides case studies, various technology advancements, and practical aspects on the impacts and challenges of fuzzy-based Internet of Medical Things.

Audience

The book will be read and used by researchers in artificial intelligence, fuzzy logic, medical professionals, caregivers, health administrators, and policymakers.

ADVANCES IN FUZZY-BASED INTERNET OF MEDICAL THINGS (IOMT)

This book explores the latest trends, transitions, and advancements of the Internet of Medical Things whose integration through cloud-hosted software applications adds required intelligence from tools such as medical instruments, scanners, and appliances, enabling fuzzy logic to help medical professionals establish linguistic concepts in deciding diagnosis and prognosis.

The main goal of the book is to strengthen medical professionals and caregivers by providing methods for achieving fuzzy logic-based health diagnosis and medication. The health condition and various physical parameters of humans, such as heartbeat rate, sugar level, blood pressure, temperature, and oxygen quality, are captured through a host of multifaceted sensors. Additionally, remote health monitoring, medication, and management are being facilitated through a host of ingestible sensors, 5G communication, networked embedded systems, AI models running on cloud servers and edge devices, etc. Furthermore, chronic disease management is another vital domain getting increased attention. The distinct advancements in the fuzzy logic field are useful in various advanced medical care functionalities and facilities.

The readers will discover:

new and innovative features of health care by using fuzzy logic that raises economic efficiency at macro and micro levels; expounds on fuzzy logic techniques used in medical science; describes the evolution of the fuzzy logic paradigm and how it helps physicians decide on diagnosis and prognosis; uncovers how trust management is dealt with between patients and medical officials to help advance the fuzzy logic field; provides case studies, various technology advancements, and practical aspects on the impacts and challenges of fuzzy-based Internet of Medical Things.

Audience

The book will be read and used by researchers in artificial intelligence, fuzzy logic, medical professionals, caregivers, health administrators, and policymakers.

Explores the future of transportation and provides a comprehensive guide to leveraging cutting-edge digital technologies and AI-powered platforms for creating smart, energy-efficient, and sustainable urban transportation systems.As urbanization accelerates globally, transportation has become a major contributor to environmental degradation and climate change. Rising greenhouse gas (GHG) emissions—including carbon dioxide (CO2), methane, ozone, nitrous oxide, and chlorofluorocarbons—pose a serious threat to air quality and environmental sustainability. To counteract these challenges, nations advocate smart, eco-friendly urban mobility solutions. This book presents the latest advancements and transformative trends in urban transportation, emphasizing emerging digital technologies that foster sustainability. The integration of artificial intelligence, 5G and 6G, cybersecurity, the Internet of Things, blockchain, edge computing, and cloud-native infrastructures enhances intelligent and energy-efficient transportation systems. Experts and environmental advocates champion innovative software platforms and solutions essential for modernizing mobility. This book examines the foundational technologies driving this transformation and explores AI-powered platforms and management solutions shaping the future of urban transportation, making it an essential resource for beginners and seasoned professionals alike. Uncovers the innovative features of artificial intelligence in urban transportation, illustrating how integrated platforms enhance operational efficiency and sustainability at both macro and micro levels;Delves into the most common AI techniques and algorithms used in modern urban mobility systems;Focuses on how the evolution of AI paradigms supports real-time decision-making, transforming urban transportation planning and management;Examines the integration of trust management and advanced cybersecurity measures within AI-powered transportation systems;Provides a collection of case studies and detailed analyses of AI-based integrated platforms, offering theoretical perspectives and practical examples of technological advancements and their challenges.

Explores the future of transportation and provides a comprehensive guide to leveraging cutting-edge digital technologies and AI-powered platforms for creating smart, energy-efficient, and sustainable urban transportation systems. As urbanization accelerates globally, transportation has become a major contributor to environmental degradation and climate change. Rising greenhouse gas (GHG) emissions including carbon dioxide (CO2), methane, ozone, nitrous oxide, and chlorofluorocarbons pose a serious threat to air quality and environmental sustainability. To counteract these challenges, nations advocate smart, eco-friendly urban mobility solutions. This book presents the latest advancements and transformative trends in urban transportation, emphasizing emerging digital technologies that foster sustainability. The integration of artificial intelligence, 5G and 6G, cybersecurity, the Internet of Things, blockchain, edge computing, and cloud-native infrastructures enhances intelligent and energy-efficient transportation systems. Experts and environmental advocates champion innovative software platforms and solutions essential for modernizing mobility. This book examines the foundational technologies driving this transformation and explores AI-powered platforms and management solutions shaping the future of urban transportation, making it an essential resource for beginners and seasoned professionals alike. Uncovers the innovative features of artificial intelligence in urban transportation, illustrating how integrated platforms enhance operational efficiency and sustainability at both macro and micro levels; Delves into the most common AI techniques and algorithms used in modern urban mobility systems; Focuses on how the evolution of AI paradigms supports real-time decision-making, transforming urban transportation planning and management; Examines the integration of trust management and advanced cybersecurity measures within AI-powered transportation systems; Provides a collection of case studies and detailed analyses of AI-based integrated platforms, offering theoretical perspectives and practical examples of technological advancements and their challenges.

Explores the future of transportation and provides a comprehensive guide to leveraging cutting-edge digital technologies and AI-powered platforms for creating smart, energy-efficient, and sustainable urban transportation systems. As urbanization accelerates globally, transportation has become a major contributor to environmental degradation and climate change. Rising greenhouse gas (GHG) emissions including carbon dioxide (CO2), methane, ozone, nitrous oxide, and chlorofluorocarbons pose a serious threat to air quality and environmental sustainability. To counteract these challenges, nations advocate smart, eco-friendly urban mobility solutions. This book presents the latest advancements and transformative trends in urban transportation, emphasizing emerging digital technologies that foster sustainability. The integration of artificial intelligence, 5G and 6G, cybersecurity, the Internet of Things, blockchain, edge computing, and cloud-native infrastructures enhances intelligent and energy-efficient transportation systems. Experts and environmental advocates champion innovative software platforms and solutions essential for modernizing mobility. This book examines the foundational technologies driving this transformation and explores AI-powered platforms and management solutions shaping the future of urban transportation, making it an essential resource for beginners and seasoned professionals alike. Uncovers the innovative features of artificial intelligence in urban transportation, illustrating how integrated platforms enhance operational efficiency and sustainability at both macro and micro levels; Delves into the most common AI techniques and algorithms used in modern urban mobility systems; Focuses on how the evolution of AI paradigms supports real-time decision-making, transforming urban transportation planning and management; Examines the integration of trust management and advanced cybersecurity measures within AI-powered transportation systems; Provides a collection of case studies and detailed analyses of AI-based integrated platforms, offering theoretical perspectives and practical examples of technological advancements and their challenges.

Move to the forefront of psychiatric technology with a deep dive into the latest advancements in clinical natural language processing, providing the data-driven precision needed to scale mental health resources effectively. Mental health is one of the most significant public health concerns facing healthcare professionals today. The World Health Organization estimates that every year, 700,000 individuals die by suicide worldwide. With more people experiencing heightened anxiety and mental health pressure, health services are unable to keep up with demand. To deal with ever-increasing mental health problems worldwide, natural language processing proves a vital resource to medical practitioners. This book offers a comprehensive exploration of recent behavior-based natural language processing developments for mental health. It delves into methodologies and aspects of mathematical analysis, covering approaches such as behavioral signal processing in speech and language, speech analysis, clinical natural language processing, and rule-based chatbot approaches. By providing comprehensive coverage, the book equips readers with a deep understanding of the field to keep them abreast of the latest advancements. Readers will find the volume: Explores new and innovative ideas of natural language processing in mental healthcare;Introduces various speech-processing techniques, behavioral detection techniques, and social media detection;Presents various mathematical approaches to the cognitive analysis of mental illness;Uncovers the impact and challenges of using various behavioral NLP techniques.Audience Mental health specialists, academics, AI engineers and data scientists, IT professionals, and business executives exploring significant advancements in digital technologies and how next-generation innovations can enable cognitive and behavioral natural language processing in mental health.

Move to the forefront of psychiatric technology with a deep dive into the latest advancements in clinical natural language processing, providing the data-driven precision needed to scale mental health resources effectively. Mental health is one of the most significant public health concerns facing healthcare professionals today. The World Health Organization estimates that every year, 700,000 individuals die by suicide worldwide. With more people experiencing heightened anxiety and mental health pressure, health services are unable to keep up with demand. To deal with ever-increasing mental health problems worldwide, natural language processing proves a vital resource to medical practitioners. This book offers a comprehensive exploration of recent behavior-based natural language processing developments for mental health. It delves into methodologies and aspects of mathematical analysis, covering approaches such as behavioral signal processing in speech and language, speech analysis, clinical natural language processing, and rule-based chatbot approaches. By providing comprehensive coverage, the book equips readers with a deep understanding of the field to keep them abreast of the latest advancements. Readers will find the volume: Explores new and innovative ideas of natural language processing in mental healthcare; Introduces various speech-processing techniques, behavioral detection techniques, and social media detection; Presents various mathematical approaches to the cognitive analysis of mental illness; Uncovers the impact and challenges of using various behavioral NLP techniques. Audience Mental health specialists, academics, AI engineers and data scientists, IT professionals, and business executives exploring significant advancements in digital technologies and how next-generation innovations can enable cognitive and behavioral natural language processing in mental health.

Move to the forefront of psychiatric technology with a deep dive into the latest advancements in clinical natural language processing, providing the data-driven precision needed to scale mental health resources effectively. Mental health is one of the most significant public health concerns facing healthcare professionals today. The World Health Organization estimates that every year, 700,000 individuals die by suicide worldwide. With more people experiencing heightened anxiety and mental health pressure, health services are unable to keep up with demand. To deal with ever-increasing mental health problems worldwide, natural language processing proves a vital resource to medical practitioners. This book offers a comprehensive exploration of recent behavior-based natural language processing developments for mental health. It delves into methodologies and aspects of mathematical analysis, covering approaches such as behavioral signal processing in speech and language, speech analysis, clinical natural language processing, and rule-based chatbot approaches. By providing comprehensive coverage, the book equips readers with a deep understanding of the field to keep them abreast of the latest advancements. Readers will find the volume: Explores new and innovative ideas of natural language processing in mental healthcare; Introduces various speech-processing techniques, behavioral detection techniques, and social media detection; Presents various mathematical approaches to the cognitive analysis of mental illness; Uncovers the impact and challenges of using various behavioral NLP techniques. Audience Mental health specialists, academics, AI engineers and data scientists, IT professionals, and business executives exploring significant advancements in digital technologies and how next-generation innovations can enable cognitive and behavioral natural language processing in mental health.