This book presents and discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a renaissance in interest in neural networks, with applications including image and speech processing, data analytics, robotics, healthcare monitoring, and IoT solutions. Efficient implementation of neural networks to support complex deep learning-based applications is a complex challenge for embedded and mobile computing platforms with limited computational/storage resources and a tight power budget. Even for cloud-scale systems it is critical to select the right hardware configuration based on the neural network complexity and system constraints in order to increase power- and performance-efficiency. Hardware Architectures for Deep Learning provides an overview of this new field, from principles to applications, for researchers, postgraduate students and engineers who work on learning-based services and hardware platforms.

Between adolescence and adulthood, individuals begin to explore themselves mentally and emotionally in an attempt to figure out who they are and where they fit in society. Social technologies in the modern age have ushered in an era where these evolving adolescents must circumvent the negative pressures of online influences while also still trying to learn how to be utterly independent. Recent Advances in Digital Media Impacts on Identity, Sexuality, and Relationships is a collection of critical reference materials that provides imperative research on identity exploration in emerging adults and examines how digital media is used to help explore and develop one's identity. While highlighting topics such as mobile addiction, online intimacy, and cyber aggression, this publication explores a crucial developmental period in the human lifespan and how digital media hinders (or helps) maturing adults navigate life. This book is ideally designed for therapists, psychologists, sociologists, psychiatrists, researchers, educators, academicians, and professionals.

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools. This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data. Drawing upon years of practical experience, and using numerous examples and use cases, Jules Berman discusses the principles, methods, and tools that must be studied and mastered to achieve data simplification, open source tools, free utilities and snippets of code that can be reused and repurposed to simplify data, natural language processing and machine translation as a tool to simplify data, and data summarization and visualization and the role they play in making data useful for the end user.

The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided.

Trusted Platform Modules (TPMs) are small, inexpensive chips which provide a limited set of security functions. They are most commonly found as a motherboard component on laptops and desktops aimed at the corporate or government markets, but can also be found on many consumer-grade machines and servers, or purchased as independent components. Their role is to serve as a Root of Trust - a highly trusted component from which we can bootstrap trust in other parts of a system. TPMs are most useful for three kinds of tasks: remotely identifying a machine, or machine authentication; providing hardware protection of secrets, or data protection; and providing verifiable evidence about a machine's state, or attestation. This book describes the primary uses for TPMs, and practical considerations such as when TPMs can and should be used, when they shouldn't be, what advantages they provide, and how to actually make use of them, with use cases and worked examples of how to implement these use cases on a real system. Topics covered include when to use a TPM; TPM concepts and functionality; programming introduction; provisioning: getting the TPM ready to use; first steps: TPM keys; machine authentication; data protection; attestation; other TPM features; software and specifications; and troubleshooting. Appendices contain basic cryptographic concepts; command equivalence and requirements charts; and complete code samples.

Cloud computing is rapidly expanding in its applications and capabilities through various parts of society. Utilizing different types of virtualization technologies can push this branch of computing to even greater heights. Design and Use of Virtualization Technology in Cloud Computing is a crucial resource that provides in-depth discussions on the background of virtualization, and the ways it can help shape the future of cloud computing technologies. Highlighting relevant topics including grid computing, mobile computing, open source virtualization, and virtualization in education, this scholarly reference source is ideal for computer engineers, academicians, students, and researchers that are interested in learning more about how to infuse current cloud computing technologies with virtualization advancements.

In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: "Introduction and Background on Control Theory", "Adaptive Control and Neuroscience", "Adaptive Learning Algorithms", "Cyber-Physical Systems and Cooperative Control", "Applications". The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists. This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems. * Collection of chapters from several well-known professors and researchers that will showcase their recent work * Presents different state-of-the-art control approaches and theory for complex systems * Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams * Real system examples and figures throughout, make ideas concrete

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.

Advances in Computers carries on a tradition of excellence, presenting detailed coverage of innovations in computer hardware, software, theory, design, and applications. The book provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles typically allow. The articles included in this book will become standard references, with lasting value in this rapidly expanding field.

Intelligent systems and related designs have become important instruments leading to profound innovations in automated control and interaction with computers and machines. Such systems depend upon established methods and tools for solving complex learning and decision-making problems under uncertain and continuously varying conditions. Intelligent Applications for Heterogeneous System Modeling and Design examines the latest developments in intelligent system engineering being used across industries with an emphasis on transportation, aviation, and medicine. Focusing on the latest trends in artificial intelligence, systems design and testing, and related topic areas, this publication is designed for use by engineers, IT specialists, academicians, and graduate-level students.

The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science. Artificial Intelligence Methods and Applications in Computer Engineering illuminates how today's computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.

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.

This book explores 10 unique facets of Internet health and safety, including physical safety, information security, and the responsible use of technology, offering takeaways from interviews with experts in the field and suggestions for proactively improving users' Internet safety. The Internet has become for many people—especially students and young adults—an essential and intrinsic part of their lives. It makes information available to be shared worldwide, at any time; enables learning about any topic; and allows for instantaneous communication. And it provides endless entertainment as well. But the benefits of online access are accompanied by serious potential risks. This book covers the key elements of Internet health and safety, including physical safety, information security, and the responsible use of technology. It begins with an introductory essay that gives readers the necessary conceptual framework, and then explains specific topics such as cyberbullying, file sharing, online predators, Internet fraud, and obscene and offensive content. The book also answers readers' questions in a "Q & A" section with a subject expert and includes a directory of resources that provides additional information and serves as a gateway to further study.

Even though terrorism poses an increasing threat to multinational companies, corporate leaders can thwart attacks by learning to navigate the complexities of foreign governments, social unrest, and cultural dissonance. Multinational corporations are on the front lines of terrorism and cyberattacks—two of the world's biggest threats to global security. How can corporate leaders mitigate their organizations' risks and develop an infrastructure that detects and deters a security menace before it happens? This timely reference lays out essential political context and historical background to help executives identify contemporary threats and understand the interconnections between threat dynamics in an increasingly dangerous international environment. This compelling work is organized into seven chapters. The beginning chapters profile the specific risks for multinational companies and detail which global—and regional—factors might propagate violence targeted at American-based businesses. Next, two historical case studies on terrorist assaults at Tigantourine and Mombasa illustrate how counterterrorism can successfully thwart potential attacks against business targets. The final part describes industrial espionage and criminal activity and then outlines a corporate counterterror blueprint to combat the prospect of terrorism, providing specific recommendations for preventative measures.