Metaheuristics Algorithms for Medical Applications: Methods and Applications provides readers with the most complete reference for developing Metaheuristics techniques with Machine Learning for solving biomedical problems. The book is organized to present a stepwise progression beginning with the basics of Metaheuristics, leading into methods and practices, and concluding with advanced topics. The first section of the book presents the fundamental concepts of Metaheuristics and Machine Learning, and also provides a comprehensive taxonomic view of Metaheuristics methods according to a variety of criteria such as data type, scope, method, and so forth. The second section of the book explains how to apply Metaheuristics techniques for solving large-scale biomedical problems, including analysis and validation under different strategies. The final portion of the book focuses on advanced topics in Metaheuristics in four different applications. Readers will discover a variety of new methods, approaches, and techniques, as well as a wide range of applications demonstrating key concepts in Metaheuristics for biomedical science. The book provides a leading-edge resource for researchers in a variety of scientific fields who are interested in metaheuristics, including mathematics, biomedical engineering, computer science, biological sciences, and clinicians in medical practice. Introduces a new set of Metaheuristics techniques for biomedical applications Presents basic concepts of Metaheuristics, methods and practices, followed by advanced topics and applications Provides researchers, practitioners, and project stakeholders with a complete guide for understanding and applying metaheuristics and machine learning techniques in their projects and solutions
Multi-Criteria Decision-Making for Renewable Energy: Methods, Applications, and Challenges brings together the latest fuzzy and soft computing methods, models, and algorithms as applied to the field of renewable energy and supported by specific application examples and case studies. The book begins by approaching renewable energy sources, challenges and factors that affect their development, as well as green renewable energy sites and the utilization of fuzzy multi-criteria decision-making (MCDM) techniques in these broad contexts, as well as utilization in addressing the various environmental, economic, and social barriers to ensuring the sustainability of energy resources. Detailed chapters focus on the application of multi-criteria decision-making methods for planning, modeling and prioritization in specific areas of renewable energy, including solar energy, wind farms, solar-powered hydrogen production plants, biofuel production, energy storage, hydropower, and marine energy. Finally, future opportunities and research directions are explored. Provides a set of multi-criteria techniques to address challenges across renewable energy Reviews and analyzes the current state-of-the-art and identifies future opportunities and directions Offers clear examples, case studies and practical applications of the described concepts
In the era of the Internet of Things and with the explosive worldwide growth of electronic data volume, and associated need of processing, analysis, and storage of such a humongous amount of data, it has now become mandatory to exploit the power of massively parallel architecture for fast computation. Cloud computing provides a cheap source of such a computing framework for a large volume of data for real-time applications. It is, therefore, not surprising to see that cloud computing has become a buzzword in the computing fraternity over the last decade. Applications of Cloud Computing: Approaches and Practices lays a good foundation for the core concepts and principles of cloud computing applications, walking the reader through the fundamental ideas with expert ease. The book progresses on the topics in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into the applications of it. It is a valuable source of knowledge for researchers, engineers, practitioners, and graduate and doctoral students working in the field of cloud computing. It will also be useful for faculty members of graduate schools and universities.
This book provides a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of dynamic wireless sensor networks (WSNs) for intelligent and smart applications in a variety of environments. It presents the most central concepts associated with Dynamic Wireless Sensor Networks applications, and discusses issues surrounding Wireless Sensor Network Structures for complex and mobile-based applications. The book subsequently discusses several topics related to energy management in dynamic WSNs, and reviews the steps involved in building a secure and trusted data transmission model using the WSN applications of intelligent environments. Lastly, it discusses the applications of WSNs in live data systems such as SCADA systems. Readers will discover a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of WSNs for intelligent real-life applications. In addition, the book presents original research on the application of a dynamic WSN to solve the problem of energy consumption in a secure WSN during the process of data aggregation and transmission. Written by respected experts in the field, the book will stimulate further efforts in the application of the intelligent WSNs model, helping to solve the problem of data processing in a limited resource WSN-based environment.
This book offers an essential guide to Wireless Sensor Networks, IoT Security, Image Processing, Secure Information Systems, and Data Encryption. In addition, it introduces students and aspiring practitioners to the subject of destination marketing in a structured manner. It is chiefly intended for researcher students in the areas of Wireless Sensor Networks and Secure Data Communication (including image encryption, and intrusion detection systems), academics at universities and colleges, IT professionals, policymakers and legislators. Given its content, the book can be used as a reference text for both undergraduate and graduate studies, in courses on Wireless Sensor Networks, Secure Image Processing, and Data Encryption applications. The book is written in plain and easy-to-follow language and explains each main concept the first time it appears, helping readers with no prior background in the field. As such, it is a “must-read” guide to the subject matter.
This book contains high-quality research articles and reviews that promote research and reflect the most recent advances in intelligent wavelet based techniques for advanced multimedia applications as well as other emerging areas. In recent time, wavelet transforms have become useful in many signal, image and video processing applications, especially for multimedia security and surveillance. A few applications of wavelets in security and surveillance are watermarking, fusion, steganography, object detection, tracking, motion recognition and intention recognition, etc. Wavelets are well capable of analyzing signal, image and video at different resolution levels, popularly known as multiresolution analysis. The multiresolution analysis is advantageous in multimedia security and surveillance applications. It provides flexibility in selection of different resolution levels that leads to better accuracy. Furthermore, recently sparse representation has become an advancement to analyze wavelet coefficients. It is observed that wavelet transforms possess the invariance property which makes them suitable for many vision applications. This book provides a concise overview of the current state of the art and disseminates some of the novel and exciting ideas and techniques. In addition, it is also helpful for the senior undergraduate and graduate students, researcher, academicians, IT professional and providers, citizens, customers as well as policy makers working in this area as well as other emerging applications demanding state-of-the-art wavelet based multimedia applications.
This book provides a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of dynamic wireless sensor networks (WSNs) for intelligent and smart applications in a variety of environments. It presents the most central concepts associated with Dynamic Wireless Sensor Networks applications, and discusses issues surrounding Wireless Sensor Network Structures for complex and mobile-based applications. The book subsequently discusses several topics related to energy management in dynamic WSNs, and reviews the steps involved in building a secure and trusted data transmission model using the WSN applications of intelligent environments. Lastly, it discusses the applications of WSNs in live data systems such as SCADA systems. Readers will discover a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of WSNs for intelligent real-life applications. In addition, the book presents original research on the application of a dynamic WSN to solve the problem of energy consumption in a secure WSN during the process of data aggregation and transmission. Written by respected experts in the field, the book will stimulate further efforts in the application of the intelligent WSNs model, helping to solve the problem of data processing in a limited resource WSN-based environment.
In the era of the Internet of Things and with the explosive worldwide growth of electronic data volume, and associated need of processing, analysis, and storage of such a humongous amount of data, it has now become mandatory to exploit the power of massively parallel architecture for fast computation. Cloud computing provides a cheap source of such a computing framework for a large volume of data for real-time applications. It is, therefore, not surprising to see that cloud computing has become a buzzword in the computing fraternity over the last decade. Applications of Cloud Computing: Approaches and Practices lays a good foundation for the core concepts and principles of cloud computing applications, walking the reader through the fundamental ideas with expert ease. The book progresses on the topics in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into the applications of it. It is a valuable source of knowledge for researchers, engineers, practitioners, and graduate and doctoral students working in the field of cloud computing. It will also be useful for faculty members of graduate schools and universities.
Metaheuristics Algorithms for Medical Applications: Methods and Applications provides readers with the most complete reference for developing Metaheuristics techniques with Machine Learning for solving biomedical problems. The book is organized to present a stepwise progression beginning with the basics of Metaheuristics, leading into methods and practices, and concluding with advanced topics. The first section of the book presents the fundamental concepts of Metaheuristics and Machine Learning, and also provides a comprehensive taxonomic view of Metaheuristics methods according to a variety of criteria such as data type, scope, method, and so forth. The second section of the book explains how to apply Metaheuristics techniques for solving large-scale biomedical problems, including analysis and validation under different strategies. The final portion of the book focuses on advanced topics in Metaheuristics in four different applications. Readers will discover a variety of new methods, approaches, and techniques, as well as a wide range of applications demonstrating key concepts in Metaheuristics for biomedical science. The book provides a leading-edge resource for researchers in a variety of scientific fields who are interested in metaheuristics, including mathematics, biomedical engineering, computer science, biological sciences, and clinicians in medical practice. Introduces a new set of Metaheuristics techniques for biomedical applications Presents basic concepts of Metaheuristics, methods and practices, followed by advanced topics and applications Provides researchers, practitioners, and project stakeholders with a complete guide for understanding and applying metaheuristics and machine learning techniques in their projects and solutions
Multi-Criteria Decision-Making for Renewable Energy: Methods, Applications, and Challenges brings together the latest fuzzy and soft computing methods, models, and algorithms as applied to the field of renewable energy and supported by specific application examples and case studies. The book begins by approaching renewable energy sources, challenges and factors that affect their development, as well as green renewable energy sites and the utilization of fuzzy multi-criteria decision-making (MCDM) techniques in these broad contexts, as well as utilization in addressing the various environmental, economic, and social barriers to ensuring the sustainability of energy resources. Detailed chapters focus on the application of multi-criteria decision-making methods for planning, modeling and prioritization in specific areas of renewable energy, including solar energy, wind farms, solar-powered hydrogen production plants, biofuel production, energy storage, hydropower, and marine energy. Finally, future opportunities and research directions are explored. Provides a set of multi-criteria techniques to address challenges across renewable energy Reviews and analyzes the current state-of-the-art and identifies future opportunities and directions Offers clear examples, case studies and practical applications of the described concepts
This book offers an essential guide to Wireless Sensor Networks, IoT Security, Image Processing, Secure Information Systems, and Data Encryption. In addition, it introduces students and aspiring practitioners to the subject of destination marketing in a structured manner. It is chiefly intended for researcher students in the areas of Wireless Sensor Networks and Secure Data Communication (including image encryption, and intrusion detection systems), academics at universities and colleges, IT professionals, policymakers and legislators. Given its content, the book can be used as a reference text for both undergraduate and graduate studies, in courses on Wireless Sensor Networks, Secure Image Processing, and Data Encryption applications. The book is written in plain and easy-to-follow language and explains each main concept the first time it appears, helping readers with no prior background in the field. As such, it is a “must-read” guide to the subject matter.
This book covers various, leading-edge deep learning technologies. The author discusses new applications of deep learning and gives insight into the integration of deep learning with various application domains, such as autonomous driving, augmented reality, AIOT, 5G and beyond.
This book contains high-quality research articles and reviews that promote research and reflect the most recent advances in intelligent wavelet based techniques for advanced multimedia applications as well as other emerging areas. In recent time, wavelet transforms have become useful in many signal, image and video processing applications, especially for multimedia security and surveillance. A few applications of wavelets in security and surveillance are watermarking, fusion, steganography, object detection, tracking, motion recognition and intention recognition, etc. Wavelets are well capable of analyzing signal, image and video at different resolution levels, popularly known as multiresolution analysis. The multiresolution analysis is advantageous in multimedia security and surveillance applications. It provides flexibility in selection of different resolution levels that leads to better accuracy. Furthermore, recently sparse representation has become an advancement to analyze wavelet coefficients. It is observed that wavelet transforms possess the invariance property which makes them suitable for many vision applications. This book provides a concise overview of the current state of the art and disseminates some of the novel and exciting ideas and techniques. In addition, it is also helpful for the senior undergraduate and graduate students, researcher, academicians, IT professional and providers, citizens, customers as well as policy makers working in this area as well as other emerging applications demanding state-of-the-art wavelet based multimedia applications.
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