Bhabani Shankar Prasad Mishra – författare

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real-life case studies, illustrative examples and video demonstrations. The book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions, providing guidance on best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc.

In each section, different machine learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition and surveillance.

Covers different machine intelligence concepts, algorithms and applications in the field of cybersecurity, e-health monitoring, secure cloud computing and secure IOT based operations Explores advanced approaches to improve recognition performance of biometric systems with the use of recent machine intelligence techniques Introduces detection or segmentation techniques to detect biometric characteristics from the background in the input sample

This book is intended to provide a systematic overview of so-called smart techniques, such as nature-inspired algorithms, machine learning and metaheuristics. Despite their ubiquitous presence and widespread application to different scientific problems, such as searching, optimization and /or classification, a systematic study is missing in the current literature. Here, the editors collected a set of chapters on key topics, paying attention to provide an equal balance of theory and practice, and to outline similarities between the different techniques and applications. All in all, the book provides an unified view on the field on intelligent methods, with their current perspective and future challenges.

This book discusses harnessing the real power of cloud computing in optimization problems, presenting state-of-the-art computing paradigms, advances in applications, and challenges concerning both the theories and applications of cloud computing in optimization with a focus on diverse fields like the Internet of Things, fog-assisted cloud computing, and big data. In real life, many problems – ranging from social science to engineering sciences – can be identified as complex optimization problems. Very often these are intractable, and as a result researchers from industry as well as the academic community are concentrating their efforts on developing methods of addressing them. Further, the cloud computing paradigm plays a vital role in many areas of interest, like resource allocation, scheduling, energy management, virtualization, and security, and these areas are intertwined with many optimization problems. Using illustrations and figures, this book offers students and researchers a clear overview of the concepts and practices of cloud computing and its use in numerous complex optimization problems.

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems.

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems.

Rather than focusing on a single aspect of software engineering, this book provides a systematic overview of recent techniques, including requirement gathering in the form of story points in agile software, and bio-inspired techniques for estimating the effort, cost, and time required for software development.

Rather than focusing on a single aspect of software engineering, this book provides a systematic overview of recent techniques, including requirement gathering in the form of story points in agile software, and bio-inspired techniques for estimating the effort, cost, and time required for software development.

This book discusses harnessing the real power of cloud computing in optimization problems, presenting state-of-the-art computing paradigms, advances in applications, and challenges concerning both the theories and applications of cloud computing in optimization with a focus on diverse fields like the Internet of Things, fog-assisted cloud computing, and big data. In real life, many problems – ranging from social science to engineering sciences – can be identified as complex optimization problems. Very often these are intractable, and as a result researchers from industry as well as the academic community are concentrating their efforts on developing methods of addressing them. Further, the cloud computing paradigm plays a vital role in many areas of interest, like resource allocation, scheduling, energy management, virtualization, and security, and these areas are intertwined with many optimization problems. Using illustrations and figures, this book offers students and researchers a clear overview of the concepts and practices of cloud computing and its use in numerous complex optimization problems.

This book discusses applications of computational intelligence in sensor networks. Advances in sensor technology and computer networks have enabled sensor networks to evolve from small systems of large sensors to large nets of miniature sensors, from wired communications to wireless communications, and from static to dynamic network topology.

This book discusses applications of computational intelligence in sensor networks. Advances in sensor technology and computer networks have enabled sensor networks to evolve from small systems of large sensors to large nets of miniature sensors, from wired communications to wireless communications, and from static to dynamic network topology.

This book examines the nature, extent and implications of rapid strides digitalization has made in India since the turn of the millennium.  These have been examined not merely in the sphere of information and communication technology (ICT) but its multifarious applications spreading across almost all aspects of production, services and institutions which have profound repercussions for the transformation of the society and economy at the micro, meso and macro levels. With contributions from both ICT scholars and social scientists, this book presents diverse scenarios and unravels challenges faced in the process of technical applications, access by the users of these disruptive technologies (automation, e-commerce, big data analytics & algorithms, artificial intelligence, cloud computing, etc.) which, unlike heavy machines (embodied technology), mostly defy physical space, pace of mobility and inoperability between technologies.  Chapters in this volume address challenges and possibilities in establishing and operating intricate engineering infrastructure, technical and societal constraints encountered in broad-basing digitalization across layers of educational and social skills conducive to difficult geographies.  Issues dealt within this book include farming, healthcare, education, food processing, e-commerce, labour, rural community development, open source data and information democracy. The chapters also reflect upon implications on local economy and society, of the very global nature of these seamless technologies where inter-operability remains the quintessential advantage of digitalization whether promoted or spearheaded through the state, private sector or global capital.  The book critiques policy inadequacies and suggests plausible policy approaches to reduce the adverse impacts of fast digitalization and broad-base potential benefits across space and levels of socio-economic development of regions and society.  This bookwould be of interest to scholars, practitioners, technocrats, industry analysts, policy makers and civil society agencies.

This book examines the nature, extent and implications of rapid strides digitalization has made in India since the turn of the millennium.  These have been examined not merely in the sphere of information and communication technology (ICT) but its multifarious applications spreading across almost all aspects of production, services and institutions which have profound repercussions for the transformation of the society and economy at the micro, meso and macro levels. With contributions from both ICT scholars and social scientists, this book presents diverse scenarios and unravels challenges faced in the process of technical applications, access by the users of these disruptive technologies (automation, e-commerce, big data analytics & algorithms, artificial intelligence, cloud computing, etc.) which, unlike heavy machines (embodied technology), mostly defy physical space, pace of mobility and inoperability between technologies.  Chapters in this volume address challenges and possibilities in establishing and operating intricate engineering infrastructure, technical and societal constraints encountered in broad-basing digitalization across layers of educational and social skills conducive to difficult geographies.  Issues dealt within this book include farming, healthcare, education, food processing, e-commerce, labour, rural community development, open source data and information democracy. The chapters also reflect upon implications on local economy and society, of the very global nature of these seamless technologies where inter-operability remains the quintessential advantage of digitalization whether promoted or spearheaded through the state, private sector or global capital.  The book critiques policy inadequacies and suggests plausible policy approaches to reduce the adverse impacts of fast digitalization and broad-base potential benefits across space and levels of socio-economic development of regions and society.  This bookwould be of interest to scholars, practitioners, technocrats, industry analysts, policy makers and civil society agencies.

Some of the areas covered include control of linear and nonlinear systems, intelligent systems, stochastic control, knowledge-based systems applications, fault diagnosis and tolerant control, and real-time control applications.

Some of the areas covered include control of linear and nonlinear systems, intelligent systems, stochastic control, knowledge-based systems applications, fault diagnosis and tolerant control, and real-time control applications.

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies.

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies.

This book includes best-selected, high-quality research papers presented at Second International Conference on Biologically Inspired Techniques in Many Criteria Decision Making (BITMDM 2021) organized by Department of Information & Communication Technology, Fakir Mohan University, Balasore, Odisha, India, during December 20-21, 2021.