Ashish Mishra – författare

This book provides insights into contemporary issues and challenges in soft computing applications and techniques in healthcare. It will be a useful guide to identify, categorise and assess the role of different soft computing techniques for disease, diagnosis and prediction due to technological advancements.

The book explores applications in soft computing and covers empirical properties of artificial neural network (ANN), evolutionary computing, fuzzy logic and statistical techniques. It presents basic and advanced concepts to help beginners and industry professionals get up to speed on the latest developments in soft computing and healthcare systems. It incorporates the latest methodologies and challenges facing soft computing, examines descriptive, predictive and social network techniques and discusses analytics tools and their role in providing effective solutions for science and technology.

The primary users for the book include researchers, academicians, postgraduate students, specialists and practitioners.

Dr. Ashish Mishra is a professor in the Department of Computer Science and Engineering, Gyan Ganga Institute of Technology and Sciences, Jabalpur, Madhya Pradesh, India. He has contributed in organising the INSPIRE Science Internship Camp. He is a member of the Institute of Electrical and Electronics Engineers and is a life member of the Computer Society of India. His research interests include the Internet of Things, data mining, cloud computing, image processing and knowledge-based systems. He holds nine patents in Intellectual Property, India. He has authored four books in the areas of data mining, image processing and LaTex.

Dr. G. Suseendran is an assistant professor, Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. His research interests include ad-hoc networks, the Internet of Things, data mining, cloud computing, image processing, knowledge-based systems, and Web information exploration. He has published more than 75 research papers in various international journals such as Science Citation Index, Springer Book Chapter, Scopus, IEEE Access and UGC-referred journals.

Prof. Trung-Nghia Phung is an associate professor and Head of Academic Affairs, Thai Nguyen University of Information and Communication Technology (ICTU). He has published more than 60 research papers. His main research interest lies in the field of speech, audio, and biomedical signal processing. He serves as a technical committee program member, track chair, session chair, and reviewer of many international conferences and journals. He was a co-Chair of the International Conference on Advances in Information and Communication Technology 2016 (ICTA 2016) and a Session Chair of the 4th International Conference on Information System Design and Intelligent Applications (INDIA 2017).

This book provides insights into contemporary issues and challenges in soft computing applications and techniques in healthcare. It will be a useful guide to identify, categorise and assess the role of different soft computing techniques for disease, diagnosis and prediction due to technological advancements.

The book explores applications in soft computing and covers empirical properties of artificial neural network (ANN), evolutionary computing, fuzzy logic and statistical techniques. It presents basic and advanced concepts to help beginners and industry professionals get up to speed on the latest developments in soft computing and healthcare systems. It incorporates the latest methodologies and challenges facing soft computing, examines descriptive, predictive and social network techniques and discusses analytics tools and their role in providing effective solutions for science and technology.

The primary users for the book include researchers, academicians, postgraduate students, specialists and practitioners.

Dr. Ashish Mishra is a professor in the Department of Computer Science and Engineering, Gyan Ganga Institute of Technology and Sciences, Jabalpur, Madhya Pradesh, India. He has contributed in organising the INSPIRE Science Internship Camp. He is a member of the Institute of Electrical and Electronics Engineers and is a life member of the Computer Society of India. His research interests include the Internet of Things, data mining, cloud computing, image processing and knowledge-based systems. He holds nine patents in Intellectual Property, India. He has authored four books in the areas of data mining, image processing and LaTex.

Dr. G. Suseendran is an assistant professor, Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. His research interests include ad-hoc networks, the Internet of Things, data mining, cloud computing, image processing, knowledge-based systems, and Web information exploration. He has published more than 75 research papers in various international journals such as Science Citation Index, Springer Book Chapter, Scopus, IEEE Access and UGC-referred journals.

Prof. Trung-Nghia Phung is an associate professor and Head of Academic Affairs, Thai Nguyen University of Information and Communication Technology (ICTU). He has published more than 60 research papers. His main research interest lies in the field of speech, audio, and biomedical signal processing. He serves as a technical committee program member, track chair, session chair, and reviewer of many international conferences and journals. He was a co-Chair of the International Conference on Advances in Information and Communication Technology 2016 (ICTA 2016) and a Session Chair of the 4th International Conference on Information System Design and Intelligent Applications (INDIA 2017).

This book provides insights into contemporary issues and challenges in multi-criteria decision models. It is a useful guide for identifying, understanding and categorising multi-criteria decision models, and ultimately implementing the analysis for effective decision-making.

The use of multi-criteria decision models in software reliability engineering is a relatively new field of study, and this book collects all the latest methodologies, tools and techniques in one single volume. It covers model selection, assessment, resource allocation, release management, up-grade planning, open-source systems, bug tracking system management and defect prediction.

Multi-Criteria Decision Models in Software Reliability: Methods and Applications will cater to researchers, academicians, post-graduate students, software developers, software reliability engineers and IT managers.

This book provides insights into contemporary issues and challenges in multi-criteria decision models. It is a useful guide for identifying, understanding and categorising multi-criteria decision models, and ultimately implementing the analysis for effective decision-making.

The use of multi-criteria decision models in software reliability engineering is a relatively new field of study, and this book collects all the latest methodologies, tools and techniques in one single volume. It covers model selection, assessment, resource allocation, release management, up-grade planning, open-source systems, bug tracking system management and defect prediction.

Multi-Criteria Decision Models in Software Reliability: Methods and Applications will cater to researchers, academicians, post-graduate students, software developers, software reliability engineers and IT managers.

A unique book explaining how perception, location, communication, cognition, computation, networking, propulsion, integration of federated Internet of Robotic Things (IoRT) and digital platforms are important components of new-generation IoRT applications through continuous, real-time interaction with the world.

The 16 chapters in this book discuss new architectures, networking paradigms, trustworthy structures, and platforms for the integration of applications across various business and industrial domains that are needed for the emergence of intelligent things (static or mobile) in collaborative autonomous fleets. These new apps speed up the progress of paradigms of autonomous system design and the proliferation of the Internet of Robotic Things (IoRT). Collaborative robotic things can communicate with other things in the IoRT, learn independently, interact securely with the world, people, and other things, and acquire characteristics that make them self-maintaining, self-aware, self-healing, and fail-safe operational. Due to the ubiquitous nature of collaborative robotic things, the IoRT, which binds together the sensors and the objects of robotic things, is gaining popularity. Therefore, the information contained in this book will provide readers with a better understanding of this interdisciplinary field.

Audience

Researchers in various fields including computer science, IoT, artificial intelligence, machine learning, and big data analytics.

A unique book explaining how perception, location, communication, cognition, computation, networking, propulsion, integration of federated Internet of Robotic Things (IoRT) and digital platforms are important components of new-generation IoRT applications through continuous, real-time interaction with the world.

The 16 chapters in this book discuss new architectures, networking paradigms, trustworthy structures, and platforms for the integration of applications across various business and industrial domains that are needed for the emergence of intelligent things (static or mobile) in collaborative autonomous fleets. These new apps speed up the progress of paradigms of autonomous system design and the proliferation of the Internet of Robotic Things (IoRT). Collaborative robotic things can communicate with other things in the IoRT, learn independently, interact securely with the world, people, and other things, and acquire characteristics that make them self-maintaining, self-aware, self-healing, and fail-safe operational. Due to the ubiquitous nature of collaborative robotic things, the IoRT, which binds together the sensors and the objects of robotic things, is gaining popularity. Therefore, the information contained in this book will provide readers with a better understanding of this interdisciplinary field.

Audience

Researchers in various fields including computer science, IoT, artificial intelligence, machine learning, and big data analytics.