High-performance computing (HPC) describes the use of connected computing units to perform complex tasks. It relies on parallelization techniques and algorithms to synchronize these disparate units in order to perform faster than a single processor could, alone. Used in industries from medicine and research to military and higher education, this method of computing allows for users to complete complex data-intensive tasks. This field has undergone many changes over the past decade, and will continue to grow in popularity in the coming years. Innovative Research Applications in Next-Generation High Performance Computing aims to address the future challenges, advances, and applications of HPC and related technologies. As the need for such processors increases, so does the importance of developing new ways to optimize the performance of these supercomputers. This timely publication provides comprehensive information for researchers, students in ICT, program developers, military and government organizations, and business professionals.

"What information do these data reveal?" "Is the information correct?" "How can I make the best use of the information?" The widespread use of computers and our reliance on the data generated by them have made these questions increasingly common and important. Computerized data may be in either digital or analog form and may be relevant to a wide range of applications that include medical monitoring and diagnosis, scientific research, engineering, quality control, seismology, meteorology, political and economic analysis and business and personal financial applications. The sources of the data may be databases that have been developed for specific purposes or may be of more general interest and include those that are accessible on the Internet. In addition, the data may represent either single or multiple parameters. Examining data in its initial form is often very laborious and also makes it possible to "miss the forest for the trees" by failing to notice patterns in the data that are not readily apparent. To address these problems, this monograph describes several accurate and efficient methods for displaying, reviewing and analyzing digital and analog data. The methods may be used either singly or in various combinations to maximize the value of the data to those for whom it is relevant. None of the methods requires special devices and each can be used on common platforms such as personal computers, tablets and smart phones. Also, each of the methods can be easily employed utilizing widely available off-the-shelf software. Using the methods does not require special expertise in computer science or technology, graphical design or statistical analysis. The usefulness and accuracy of all the described methods of data display, review and interpretation have been confirmed in multiple carefully performed studies using independent, objective endpoints. These studies and their results are described in the monograph. Because of their ease of use, accuracy and efficiency, the methods for displaying, reviewing and analyzing data described in this monograph can be highly useful to all who must work with computerized information and make decisions based upon it.

With the growing use of new technologies and artificial intelligence (AI) applications, intelligent systems can be used to manage large amounts of existing data in healthcare domains. Having more intelligent methods for accessing data allows medical professionals to more efficiently identify the best medical practices and more concrete solutions for diagnosing and treating a multitude of rare diseases. Intelligent Systems for Healthcare Management and Delivery provides relevant and advanced methodological, technological, and scientific approaches related to the application of sophisticated exploitation of AI, as well as providing insight into the technologies and intelligent applications that have received growing attention in recent years such as medical imaging, EMR systems, and drug development assistance. This publication fosters a scientific debate for new healthcare intelligent systems and sophisticated approaches for enhanced healthcare services and is ideally designed for medical professionals, hospital staff, rehabilitation specialists, medical educators, and researchers.

While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.

Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning. Since the first HSMM was introduced in 1980 for machine recognition of speech, three other HSMMs have been proposed, with various definitions of duration and observation distributions. Those models have different expressions, algorithms, computational complexities, and applicable areas, without explicitly interchangeable forms. Hidden Semi-Markov Models: Theory, Algorithms and Applications provides a unified and foundational approach to HSMMs, including various HSMMs (such as the explicit duration, variable transition, and residential time of HSMMs), inference and estimation algorithms, implementation methods and application instances. Learn new developments and state-of-the-art emerging topics as they relate to HSMMs, presented with examples drawn from medicine, engineering and computer science.

Text analysis tools aid in extracting meaning from digital content. As digital text becomes more and more complex, new techniques are needed to understand conceptual structure. Concept Parsing Algorithms (CPA) for Textual Analysis and Discovery: Emerging Research and Opportunities provides an innovative perspective on the application of algorithmic tools to study unstructured digital content. Highlighting pertinent topics such as semantic tools, semiotic systems, and pattern detection, this book is ideally designed for researchers, academics, students, professionals, and practitioners interested in developing a better understanding of digital text analysis.

Communities of Computing is the first book-length history of the Association for Computing Machinery (ACM), founded in 1947 and with a membership today of 100,000 worldwide. It profiles ACM's notable SIGs, active chapters, and individual members, setting ACM's history into a rich social and political context. The book's 12 core chapters are organized into three thematic sections. "Defining the Discipline" examines the 1960s and 1970s when the field of computer science was taking form at the National Science Foundation, Stanford University, and through ACM's notable efforts in education and curriculum standards. "Broadening the Profession" looks outward into the wider society as ACM engaged with social and political issues - and as members struggled with balancing a focus on scientific issues and awareness of the wider world. Chapters examine the social turbulence surrounding the Vietnam War, debates about the women's movement, efforts for computing and community education, and international issues including professionalization and the Cold War. "Expanding Research Frontiers" profiles three areas of research activity where ACM members and ACM itself shaped notable advances in computing, including computer graphics, computer security, and hypertext. Featuring insightful profiles of notable ACM leaders, such as Edmund Berkeley, George Forsythe, Jean Sammet, Peter Denning, and Kelly Gotlieb, and honest assessments of controversial episodes, the volume deals with compelling and complex issues involving ACM and computing. It is not a narrow organizational history of ACM committees and SIGS, although much information about them is given. All chapters are original works of research. Many chapters draw on archival records of ACM's headquarters, ACM SIGs, and ACM leaders. This volume makes a permanent contribution to documenting the history of ACM and understanding its central role in the history of computing.

Modern computing systems preserve all information in intricate binary codes. The evolution of systems and technologies that aid in this preservation process must be continually assessed to ensure that they are keeping up with the demands of society. Formation Methods, Models, and Hardware Implementation of Pseudorandom Number Generators: Emerging Research and Opportunities is a crucial scholarly resource that examines the current methodologies used in number generator construction, and how they pertain to the overall advancement of contemporary computer systems. Featuring coverage on relevant topics such as cellular automata theory, inhomogeneous cells, and sequence generators, this publication is ideal for software engineers, computer programmers, academicians, students, and researchers that are interested in staying abreast of innovative trends within the computer engineering field.

With the growth and advancement of business and industry, there is a growing need for the advancement of the strategies that manage these modernizations. Adaptation to advancement is essential for the success of these organizations and using the proper methods to accomplish this essential adaptation is paramount. Organizational Transformation and Managing Innovation in the Fourth Industrial Revolution provides innovative insights into the management of advancements and the implementation of strategies to accommodate these changes. The content within this publication examines social engagement, cyber-journalism, and educational innovation. It is designed for managers, consultants, academicians, researchers, and professionals, and covers topics centered on the growth of businesses and how they change alongside the economy and infrastructure.

Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in computer hardware, software, theory, design, and applications. It has also provided 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.

A variety of applications have been developed in order to engage with society. These tools have enabled computer scientists to captured large sets of unstructured data for machine learning and make the information widely available in academia. Techniques for Coding Imagery and Multimedia: Emerging Research and Opportunities is a pivotal reference source featuring the latest scholarly research on ways researchers code imagery and multimedia for research purposes, as well as describe some of the applied methods for research value. Including coverage on a wide variety of topics such as linguistic analysis, gender communication, and mass surveillance, this book is an important resource for researchers, academics, graduate students, and professionals seeking current research on best ways to globally expand multimedia research and imagery.

'Rana el Kaliouby's vision for how technology should work in parallel with empathy is bold, inspired and hopeful' Arianna Huffington, founder and CEO of Thrive Global 'This lucid and captivating book by a renowned pioneer of emotion-AI tackles one of the most pressing issues of our time: How can we ensure a future where this technology empowers rather than surveils and manipulates us?' Max Tegmark, professor of physics at Massachusetts Institute of Technology and author of Life 3.0 We are entering an empathy crisis. Most of our communication is conveyed through non-verbal cues - facial expressions, tone of voice, body language - nuances that are completely lost when we interact through our smartphones and other technology. The result is a digital universe that's emotion-blind - a society lacking in empathy. Rana el Kaliouby discovered this when she left Cairo, a newly-married, Muslim woman, to take up her place at Cambridge University to study computer science. Many thousands of miles from home, she began to develop systems to help her better connect with her family. She started to pioneer the new field of Emotional Intelligence (EI). She now runs her company, Affectiva (the industry-leader in this emerging field) that builds EI into our technology and develops systems that understand humans the way we understand one another. In a captivating memoir, Girl Decoded chronicles el Kaliouby's mission to humanise technology and what she learns about humanity along the way.

This book introduces the properties of conservative extensions of First Order Logic (FOL) to new Intensional First Order Logic (IFOL). This extension allows for intensional semantics to be used for concepts, thus affording new and more intelligent IT systems. Insofar as it is conservative, it preserves software applications and constitutes a fundamental advance relative to the current RDB databases, Big Data with NewSQL, Constraint databases, P2P systems, and Semantic Web applications. Moreover, the many-valued version of IFOL can support the AI applications based on many-valued logics.

Security video surveillance systems, such as homeland security and national defence, rely on specific mathematical algorithms in order to run effectively. It is essential for these parameters to be understood in order to design and create a successful system. Video Surveillance Techniques and Technologies presents empirical research and acquired experience on the original solutions and mathematical algorithms for motion detection and object identification problems. Emphasising a wide variety of applications of security systems, this book is an essential tool for graduate students and professionals in the field of signal and image processing applied in static/moving object detection, tracking, and identification.

The rapid advancements in telecommunications, computing hardware and software, and data encryption, and the widespread use of electronic data processing and electronic business conducted through the Internet have led to a strong increase in information security threats. The latest advances in information security have increased practical deployments and scalability across a wide range of applications to better secure and protect our information systems and the information stored, processed and transmitted. This book outlines key emerging trends in information security from the foundations and technologies in biometrics, cybersecurity, and big data security to applications in hardware and embedded systems security, computer forensics, the Internet of Things security, and network security. Information Security: Foundations, technologies and applications is a comprehensive review of cutting-edge algorithms, technologies, and applications, and provides new insights into a range of fundamentally important topics in the field. This up-to-date body of knowledge is essential reading for researchers and advanced students in information security, and for professionals in sectors where information security is required.