Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.

User opinions about service experiences have been extensively acknowledged to play a key role in influencing the consumption decisions of other customers. The widespread adoption of internet technologies has amplified enormously the volume and the potential impact of such customer-generated content in the form of electronic word-of-mouth (eWOM). Exploring the Power of Electronic Word-of-Mouth in the Services Industry is an essential research book that explores the importance of consumer perception and the influence of word-of-mouth in the digital world. Featuring a range of topics such as data mining, online engagement, and social media, this book is ideal for academicians, researchers, IT developers, marketers, managers, media specialists, and professionals.

Interdisciplinary and multidisciplinary research is slowly yet steadily revolutionizing traditional education. However, multidisciplinary research can and will also improve the extent to which a country can protect its critical and vital assets. Applying Methods of Scientific Inquiry Into Intelligence, Security, and Counterterrorism is an essential scholarly publication that provides personnel directly working in the fields of intelligence, law enforcement, and science with the opportunity to understand the multidisciplinary nature of intelligence and science in order to improve current intelligence activities and contribute to the protection of the nation. Each chapter of the book discusses various components of science that should be applied to the intelligence arena. Featuring coverage on a range of topics including cybersecurity, economics, and political strategy, this book is ideal for law enforcement, intelligence and security practitioners, students, educators, and researchers.

Food is a necessary aspect of human life, and agriculture is crucial to any country's global economy. Because the food business is essential to both a country's economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.

Artificial intelligence has become an invaluable tool in modern society and can be utilized across fields such as healthcare, travel, education, and construction. There are numerous benefits for companies, industries, and governments when adopting this technology into their daily operations as it continues to evolve to support the needs of society. Further study on the challenges and strategies of implementation is required in order to ensure the technology is employed to its full potential. Artificial Intelligence for Societal Development and Global Well-Being considers the various uses, best practices, and success factors of artificial intelligence across fields and industries and discusses critical ways in which the technology must be developed further for the good of society. Covering a range of topics such as smart devices, artificial neural networks, and natural intelligence, this reference work is crucial for scientists, librarians, business owners, government officials, entrepreneurs, scholars, researchers, practitioners, instructors, and students.

Complex Systems and Clouds: A Self-Organization and Self-Management Perspective provides insights into the intricate world of self-organizing systems. Large scale distributed computer systems have evolved into very complex systems and are at the point where they need to borrow self-adapting organizing concepts from nature. The book explores complexity in big distributed systems and in the natural processes in physics and chemistry, building a platform for understanding how self-organization in big distributed systems can be achieved. It goes beyond the theoretical description of self-organization to present principles for designing self-organizing systems, and concludes by showing the need for a paradigm shift in the development of large-scale systems from strictly deterministic to non-deterministic and adaptive.

4 zettabytes (4 billion terabytes) of data generated in 2013, 44 zettabytes predicted for 2020 and 185 zettabytes for 2025. These figures are staggering and perfectly illustrate this new era of data deluge. Data has become a major economic and social challenge. The speed of processing of these data is the weakest link in a computer system: the storage system. It is therefore crucial to optimize this operation. During the last decade, storage systems have experienced a major revolution: the advent of flash memory. Flash Memory Integration: Performance and Energy Issues contributes to a better understanding of these revolutions. The authors offer us an insight into the integration of flash memory in computer systems, their behavior in performance and in power consumption compared to traditional storage systems. The book also presents, in their entirety, various methods for measuring the performance and energy consumption of storage systems for embedded as well as desktop/server computer systems. We are invited on a journey to the memories of the future.

Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities. Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.

This organizational history relates the role of the National Science Foundation (NSF) in the development of modern computing. Drawing upon new and existing oral histories, extensive use of NSF documents, and the experience of two of the authors as senior managers, this book describes how NSF's programmatic activities originated and evolved to become the primary source of funding for fundamental research in computing and information technologies. The book traces how NSF's support has provided facilities and education for computing usage by all scientific disciplines, aided in institution and professional community building, supported fundamental research in computer science and allied disciplines, and led the efforts to broaden participation in computing by all segments of society. Today, the research and infrastructure facilitated by NSF computing programs are significant economic drivers of American society and industry. For example, NSF supported work that led to the first widely-used web browser, Netscape; sponsored the creation of algorithms at the core of the Google search engine; facilitated the growth of the public Internet; and funded research on the scientific basis for countless other applications and technologies. NSF has advanced the development of human capital and ideas for future advances in computing and its applications. This account is the first comprehensive coverage of NSF's role in the extraordinary growth and expansion of modern computing and its use. It will appeal to historians of computing, policy makers and leaders in government and academia, and individuals interested in the history and development of computing and the NSF.

The second in the Women Securing the Future with TIPPSS series, this book provides insight and expert advice from seventeen women leaders in technology, healthcare and policy to address the challenges of Trust, Identity, Privacy, Protection, Safety and Security (TIPPSS) for connected healthcare, and the growing Internet of Medical Things (IoMT) ecosystem. The ten chapters in this book delve into trust, security and privacy risks in connected healthcare for patients, medical devices, personal and clinical data, healthcare providers and institutions, and provide practical approaches to manage and protect the data, devices, and humans. Cybersecurity, technology and legal experts discuss risks, from data and device hacks to ransomware, and propose approaches to address the challenges including new frameworks for architecting and evaluating medical device and connected hospital cybersecurity. We all need to be aware of the TIPPSS challenges in connected healthcare, and we call upon engineers, device manufacturers, system developers and healthcare providers to ensure trust and manage the risk. Featuring contributions from prominent female experts and role models in technology, cybersecurity, engineering, computer science, data science, business, healthcare, accessibility, research, law, privacy and policy, this book sets the stage to improve security and safety in our increasingly connected world.

Translation and communication between cultures can sometimes be a difficult process. Image-based assessments can offer a way for large populations to be tested on different subjects without having to create multiple testing programs. Cross-Cultural Analysis of Image-Based Assessments: Emerging Research and Opportunities is an innovative resource that offers insight into the application of visual assessments across a global and intercultural context. Highlighting applicable topics which include visual literacy, psychological assessments, assessment development, and equivalency measurements, this publication is ideal for psychologists, therapists, and researchers who would like to stay current on the most efficient way to test multi-cultural populations in various fields of knowledge.

Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends. Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods.

Advances in Computers, the latest volume in the series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

It is known that trust is of the utmost importance in human interactions, and blockchain technology establishes a new type of foundation for financial and political confidence. This new kind of trust is based on cryptographic techniques and distributed in digital networks. In an uncertain world where it is difficult to tell what is real or fake, decentralized organizational networks may prove to be particularly competitive given that this new ""distributed trust"" endows them with an unusual functional autonomy, namely guaranteeing the authenticity, confidentiality, and integrity of the processed data. Besides the direct sharing of information enabled by blockchain, transactions can now also take place with newfound trust and ways to safely manage personal data. It is important to look at these implications, particularly in sectors such as business and healthcare. Political and Economic Implications of Blockchain Technology in Business and Healthcare provides relevant theoretical frameworks on the political and economic impact of blockchain technology, which is thought to be able to redesign human interactions concerning transactions. Specifically, it will give ideas, concepts, and instruments considered relevant to advance the knowledge about ""cryptoeconomics"" and decentralized governance. The chapters will also provide several insights on business applications of this digital innovation, particularly in the healthcare sector, and will explore the ethical impact of the new ""distributed trust"" paradigm resulting from the surge of such a disruptive technology. This book is essential for students and researchers in social and life sciences, professionals and policymakers working in the fields of public and business administration, healthcare workers and researchers, academicians, and students interested in blockchain technology and the political and economic impacts in the industry.

Emerging technologies continue to affect a variety of industries, making processes more effective and efficient. However, they also impact society by promoting opportunities to encourage social change and socioeconomic advancement. Blockchain is one that is already influencing third world countries and disrupting the globe. Blockchain Technology for Global Social Change is an essential research publication that provides insight into advancements being made in blockchain and some potential applications of the technology that can improve the lives of individuals in emerging markets. This publication covers a range of topics such as digital government, health systems, and urbanization and is ideal for policymakers, academicians, researchers, sociologists, government officials, economists, and financial experts seeking current and relevant research on evolving blockchain technologies.

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting.