Like electricity and water, data and computing power are necessary commodities in the modern-day economy. A model for the effective regulation and provisioning of computational services will follow a similar paradigm as the existent model for traditional utilities. Emerging Research Surrounding Power Consumption and Performance Issues in Utility Computing explores methods of treating computing resources and materials as a standard utility, charging customers based on their usage and promoting competition among service providers. Including both benefits and hindrances, as well as theoretical concepts and practical considerations, this book provides an in-depth discussion of the utility computing paradigm for computer engineers, service providers, consumers, and academics in the field of computer science. This book includes emerging research on subjects including, but not limited to, Graphical Processing Unit (GPU) architectures, green computing, VMware, and device manufacturing techniques.

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.

The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult, traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce, bio- formatics, computer security, Web intelligence, intelligent learning database systems, ?nance, marketing, healthcare, telecommunications, andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However, the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exc

This book discusses the advancements in artificial intelligent techniques used in the well-being of human healthcare. It details the techniques used in collection, storage and analysis of data and their usage in different healthcare solutions. It also discusses the techniques of predictive analysis in early diagnosis of critical diseases. The edited book is divided into four parts - part A discusses introduction to artificial intelligence and machine learning in healthcare; part B highlights different analytical techniques used in healthcare; part C provides various security and privacy mechanisms used in healthcare; and finally, part D exemplifies different tools used in visualization and data analytics.

Computer software and technologies are advancing at an amazing rate. The accessibility of these software sources allows for a wider power among common users as well as rapid advancement in program development and operating information. Free and Open Source Software in Modern Data Science and Business Intelligence: Emerging Research and Opportunities is a critical scholarly resource that examines the differences between the two types of software, integral in the FOSS movement, and their effect on the distribution and use of software. Featuring coverage on a wide range of topics, such as FOSS Ecology, graph mining, and project tasks, this book is geared towards academicians, researchers, and students interested in current research on the growing importance of FOSS and its expanding reach in IT infrastructure.

With the immense growth of information, the prevalence of ubiquitously connected smart devices is rapidly increasing. Providing platforms that support computation, storage, and networking services between end devices is an essential aspect of an expanding digital society. The Rise of Fog Computing in the Digital Era provides innovative insights into the present generation of computing devices, as well as new approaches to computational platforms through fog computing. The content within this publication presents concepts and theories on data analytics, management systems, networking architectures, and many more. It is a vital reference source for IT professionals, computer programmers, software developers, computer engineers, researchers, and upper-level students seeking topics centered on the challenges and benefits of fog computing in mobile environments.

The book discusses Society 5.0 which fills the gap between cyber and physical space by providing a balanced environment between economic and social needs. The book is divided into two parts; part A focuses on various concepts related to Society 5.0 such as cyber space, physical space, information management and digital transformation. Part B discusses various integrated fields in Society 5.0, such as super-smart healthcare system, super-smart hospitality system, smart building, and transport management system. It also illustrates the concepts of big data, real-time analytics for smart Society 5.0 with an insight of real-time case studies.

This book discusses the advancements in artificial intelligent techniques used in the well-being of human healthcare. It details the techniques used in collection, storage and analysis of data and their usage in different healthcare solutions. It also discusses the techniques of predictive analysis in early diagnosis of critical diseases. The edited book is divided into four parts - part A discusses introduction to artificial intelligence and machine learning in healthcare; part B highlights different analytical techniques used in healthcare; part C provides various security and privacy mechanisms used in healthcare; and finally, part D exemplifies different tools used in visualization and data analytics.

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.

The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult, traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce, bio- formatics, computer security, Web intelligence, intelligent learning database systems, ?nance, marketing, healthcare, telecommunications, andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However, the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exc

This textbook tackles the matter of contemporary learners' needs, and introduces modern learning, teaching, and assessment methods. It provides a deeper understanding of these methods so that the students and teachers can create teaching and learning opportunities for themselves and others. It explores the meaning of 'pedagogy', why it is essential, and how pedagogy has evolved to take 21st-century skills and learning into account. This textbook showcases various modern learning, teaching, and assessment methods for contemporary learners in an increasingly digital environment. Each chapter presents insights and case studies that show how such modern methods can be applied to classrooms, and how they can support the existing curriculum. It shows students, educators, and researchers alike how to effectively make sense of and use modern learning, teaching, and assessment methods in everyday practice.

With the immense growth of information, the prevalence of ubiquitously connected smart devices is rapidly increasing. Providing platforms that support computation, storage, and networking services between end devices is an essential aspect of an expanding digital society. The Rise of Fog Computing in the Digital Era provides innovative insights into the present generation of computing devices, as well as new approaches to computational platforms through fog computing. The content within this publication presents concepts and theories on data analytics, management systems, networking architectures, and many more. It is a vital reference source for IT professionals, computer programmers, software developers, computer engineers, researchers, and upper-level students seeking topics centered on the challenges and benefits of fog computing in mobile environments.