Emerging scientific and industrial applications in today's world require significant computing power. Modern software tools are available for such platforms but are relatively complex and require the use of innovative programming models. One promising area in modern software design is the development, analysis, and implementation of algorithms and adaptive methods. These advancements in programming are promising but lack relevant research and understanding. Formal and Adaptive Methods for Automation of Parallel Programs Construction: Emerging Research and Opportunities is an essential reference source that solves the problem of the development of efficient models, methods, and tools for parallel programming automation based on the algebra of algorithms, term rewriting, and auto-tuning paradigms. The results of this book will help to further develop and improve existing research on design, synthesis, and optimization of sequential and parallel algorithms and programs. Featuring research on topics such as auto-tuning methods, graphics processing, and algorithmic language, this book is ideally designed for mathematicians, software engineers, data scientists, researchers, academicians, and students seeking coverage on developing tools for automated design and parallel programs.

In the implementation of smart cities, sensors and actuators that produce and consume enormous amounts of data in a variety of formats and ontologies will be incorporated into the system as a whole. The data produced by the participating devices need to be adequately categorized and connected to reduce duplication and conflicts. Newer edge computing techniques are needed to manage enormous amounts of data quickly and avoid overloading the cloud infrastructure. Cyber-Physical System Solutions for Smart Cities considers the most recent developments in several crucial software services and cyber infrastructures that are important to smart cities. Covering key topics such as artificial intelligence, smart data, big data, and computer science, this premier reference source is ideal for industry professionals, government officials, policymakers, scholars, researchers, academicians, instructors, and students.

Nowadays it is impossible to imagine a business without technology as most industries are becoming ""smarter"" and more tech-driven, ranging from small individual tech initiatives to complete business models with intertwined supply chains and ""platform""-based business models. New ways of working, such as agile and DevOps, have been introduced, leading to new risks. These risks come in the form of new challenges for teams working together in a distributed manner, privacy concerns, human autonomy, and cybersecurity concerns. Technology is now integrated into the business discipline and is here to stay leading to the need for a thorough understanding of how to address these risks and all the potential problems that could arise. With the advent of organized crime, such as hacks and denial-of-service attacks, all kinds of malicious actors are infiltrating the digital society in new and unique ways. Systems with poor design, implementation, and configurations are easily taken advantage of. When it comes to integrating business and technology, there needs to be approaches for assuring security against risks that can threaten both businesses and their digital platforms. Strategic Approaches to Digital Platform Security Assurance offers comprehensive design science research approaches to extensively examine risks in digital platforms and offer pragmatic solutions to these concerns and challenges. This book addresses significant problems when transforming an organization embracing API-based platform models, the use of DevOps teams, and issues in technological architectures. Each section will examine the status quo for business technologies, the current challenges, and core success factors and approaches that have been used. This book is ideal for security analysts, software engineers, computer engineers, executives, managers, IT consultants, business professionals, researchers, academicians, and students who want to gain insight and deeper knowledge of security in digital platforms and gain insight into the most important success factors and approaches utilized by businesses.

The COVID-19 pandemic caused educational institutions to close for the safety of students and staff and to aid in prevention measures around the world to slow the spread of the outbreak. Closures of schools and the interruption of education affected billions of enrolled students of all ages, leading to nearly the entire student population to be impacted by these measures. Consequently, this changed the educational landscape. Emergency remote education (ERE) was put into practice to ensure the continuity of education and caused the need to reinterpret pedagogical approaches. The crisis revealed flaws within our education systems and exemplified how unprepared schools were for the educational crisis both in K-12 and higher education contexts. These shortcomings require further research on education and emerging pedagogies for the future. The Handbook of Research on Emerging Pedagogies for the Future of Education: Trauma-Informed, Care, and Pandemic Pedagogy evaluates the interruption of education, reports best-practices, identifies the strengths and weaknesses of educational systems, and provides a base for emerging pedagogies. The book provides an overview of education in the new normal by distilling lessons learned and extracting the knowledge and experience gained through the COVID-19 global crisis to better envision the emerging pedagogies for the future of education. The chapters cover various subjects that include mathematics, English, science, and medical education, and span all schooling levels from preschool to higher education. The target audience of this book will be composed of professionals, researchers, instructional designers, decision-makers, institutions, and most importantly, main-actors from the educational landscape interested in interpreting the emerging pedagogies and future of education due to the pandemic.

Most technologies have been harnessed to enable educators to conduct their business remotely. However, the social context of technology as a mediating factor needs to be examined to address the perceptions of barriers to learning due to the lack of social interaction between a teacher and a learner in such a setting. Developing Technology Mediation in Learning Environments is an essential reference source that widens the scene of STEM education with an all-encompassing approach to technology-mediated learning, establishing a context for technology as a mediating factor in education. Featuring research on topics such as distance education, digital storytelling, and mobile learning, this book is ideally designed for teachers, IT consultants, educational software developers, researchers, administrators, and professionals seeking coverage on developing digital skills and professional knowledge using technology.

A practical, user-friendly handbook for understanding and protecting our personal data and digital privacy. Our Data, Ourselves addresses a common and crucial question: What can we as private individuals do to protect our personal information in a digital world? In this practical handbook, legal expert Jacqueline D. Lipton guides readers through important issues involving technology, data collection, and digital privacy as they apply to our daily lives. Our Data, Ourselves covers a broad range of everyday privacy concerns with easily digestible, accessible overviews and real-world examples. Lipton explores the ways we can protect our personal data and monitor its use by corporations, the government, and others. She also explains our rights regarding sensitive personal data like health insurance records and credit scores, as well as what information retailers can legally gather, and how. Who actually owns our personal information? Can an employer legally access personal emails? What privacy rights do we have on social media? Answering these questions and more, Our Data, Ourselves provides a strategic approach to assuming control over, and ultimately protecting, our personal information.

Infrastructure Computer Vision delves into this field of computer science that works on enabling computers to see, identify, process images and provide appropriate output in the same way that human vision does. However, implementing these advanced information and sensing technologies is difficult for many engineers. This book provides civil engineers with the technical detail of this advanced technology and how to apply it to their individual projects.

Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like “Wizard of Oz” prototyping and “Thinking aloud” protocols. Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains.

As the progression of the internet continues, society is finding easier, quicker ways of simplifying their needs with the use of technology. With the growth of lightweight devices, such as smart phones and wearable devices, highly configured hardware is in heightened demand in order to process the large amounts of raw data that are acquired. Connecting these devices to fog computing can reduce bandwidth and latency for data transmission when associated with centralized cloud solutions and uses machine learning algorithms to handle large amounts of raw data. The risks that accompany this advancing technology, however, have yet to be explored. Architecture and Security Issues in Fog Computing Applications is a pivotal reference source that provides vital research on the architectural complications of fog processing and focuses on security and privacy issues in intelligent fog applications. While highlighting topics such as machine learning, cyber-physical systems, and security applications, this publication explores the architecture of intelligent fog applications enabled with machine learning. This book is ideally designed for IT specialists, software developers, security analysts, software engineers, academicians, students, and researchers seeking current research on network security and wireless systems.

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In this book, the authors focus on efficient ways to program instrumentation and automation systems using LabVIEW (TM), a system design platform and development environment commonly used for data acquisition, instrument control, and industrial automation on a variety of operating systems. Starting with the concepts of data flow and concurrent programming, the authors go on to address the development of state machines, event programming and consumer producer systems. Chapters cover the following topics: Introduction to LabVIEW (TM), debugging tools, structures, SubVIs, structures - LabVIEW (TM) features, organizing front panel and block diagram, using software resources, using hardware resources, implementing test machines with a basic architecture, controlling the user interface, error handling, responding to the user interactions, the ATM review project, communication between loops at different rates, preventing race conditions, advanced use of software resources, and real-time programming. This book helps undergraduate and graduate students learn how to identify the most suitable design patterns depending on the application, and how to implement them in conjunction with data acquisition and instrumentation control systems. It is also a helpful resource for engineers and scientists who want to implement binary files to record data, control the user interface and implement efficient ways of programming.

By specializing in a vertical market, companies can better understand their customers and bring more insight to clients in order to become an integral part of their businesses. This approach requires dedicated tools, which is where artificial intelligence (AI) and machine learning (ML) will play a major role. By adopting AI software and services, businesses can create predictive strategies, enhance their capabilities, better interact with customers, and streamline their business processes. This edited book explores novel concepts and cutting-edge research and developments towards designing these fully automated advanced digital systems. Fostered by technological advances in artificial intelligence and machine learning, such systems potentially have a wide range of applications in robotics, human computing, sensing and networking. The chapters focus on models and theoretical approaches to guarantee automation in large multi-scale implementations of AI and ML systems; protocol designs to ensure AI systems meet key requirements for future services such as latency; and optimisation algorithms to leverage the trusted distributed and efficient complex architectures. The book is of interest to researchers, scientists, and engineers working in the fields of ICTs, networking, AI, ML, signal processing, HCI, robotics and sensing. It could also be used as supplementary material for courses on AI, machine and deep learning, ICTs, networking signal processing, robotics and sensing.