Machine Learning is evolving computation and its application like never before. It is now widely recognized that machine learning is playing a similar role as electricity played in modernizing the world. From simple high school science projects to large-scale radio astronomy, machine learning has revolutionized it all. However, a few of the applications stand out as transforming the world and opening up a new era. The book intends to showcase applications of machine learning that are leading us to the next generation of computing and living standards. The book portrays the application of machine learning to cutting-edge technologies that are playing a prominent role in improving the quality of life and the progress of civilization. The focus of the book is not just machine learning, but its application to specific domains that are resulting in substantial progress of civilization. It is ideal for scientists and researchers, academic and corporate libraries, students, lecturers and teachers, and practitioners and professionals.

Throughout the world, artificial intelligence is reshaping businesses, trade interfaces, economic activities, and society as a whole. In recent years, scholarly research on artificial intelligence has emerged from a variety of empirical and applied domains of knowledge. Computer scientists have developed advanced deep learning algorithms to leverage its utility in a variety of fields such as medicine, energy, travel, education, banking, and business management. Although a growing body of literature is shedding light on artificial intelligence-enabled difficulties, there is still much to be gained by applying fresh theory-driven techniques to this vital topic. Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments provides a comprehensive understanding of the business systems, platforms, procedures, and mechanisms that underpin different stakeholders' experiences with reality-enhancing technologies and their transformative application in management. The book also identifies areas in various business processes where artificial intelligence intervention would not only transform the business but would also make the business more sustainable. Covering key topics such as blockchain, business automation, and manufacturing, this reference work is ideal for computer scientists, business owners, managers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

In recent years, technological advances have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Privacy and Security Policies in Big Data is a pivotal reference source for the latest research on innovative concepts on the management of security and privacy analytics within big data. Featuring extensive coverage on relevant areas such as kinetic knowledge, cognitive analytics, and parallel computing, this publication is an ideal resource for professionals, researchers, academicians, advanced-level students, and technology developers in the field of big data.

An integral element of software engineering is model engineering. They both endeavor to minimize cost, time, and risks with quality software. As such, model engineering is a highly useful field that demands in-depth research on the most current approaches and techniques. Only by understanding the most up-to-date research can these methods reach their fullest potential. Advancements in Model-Driven Architecture in Software Engineering is an essential publication that prepares readers to exercise modeling and model transformation and covers state-of-the-art research and developments on various approaches for methodologies and platforms of model-driven architecture, applications and software development of model-driven architecture, modeling languages, and modeling tools. Highlighting a broad range of topics including cloud computing, service-oriented architectures, and modeling languages, this book is ideally designed for engineers, programmers, software designers, entrepreneurs, researchers, academicians, and students.

Computer science has emerged as a key driver of innovation in the 21st century. Yet preparing teachers to teach computer science or integrate computer science content into K-12 curricula remains an enormous challenge. Recent policy reports have suggested the need to prepare future teachers to teach computer science through pre-service teacher education programs. In order to prepare a generation of teachers who are capable of delivering computer science to students, however, the field must identify research-based examples, pedagogical strategies, and policies that can facilitate changes in teacher knowledge and practices. The purpose of this book is to provide examples that could help guide the design and delivery of effective teacher preparation on the teaching of computer science. This book identifies promising pathways, pedagogical strategies, and policies that will help teacher education faculty and preservice teachers infuse computer science content into their curricula as well as teach stand-alone computing courses. Specifically, the book focuses on pedagogical practices for developing and assessing pre-service teacher knowledge of computer science, course design models for pre-service teachers, and discussion of policies that can support the teaching of computer science. The primary audience of the book is students and faculty in educational technology, educational or cognitive psychology, learning theory, teacher education, curriculum and instruction, computer science, instructional systems, and learning sciences.

Large-scale interconnected systems have become more prominent in society due to a higher demand for sustainable development. As such, it is imperative to create effective methods and techniques to control such systems. Large-Scale Fuzzy Interconnected Control Systems Design and Analysis is an innovative source of academic research that discusses the latest approaches to control large-scale systems, and the challenges that occur when implementing them. Highlighting a critical range of topics such as system stability, system stabilization, and fuzzy rules, this book is an ideal publication for engineers, researchers, academics, graduate students, and practitioners interested in the design of large-scale interconnected systems.