Nature-Inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM) covers several areas that include bioinspired techniques and optimization approaches for system dependability. The book addresses the issue of integration and interaction of the bioinspired techniques in system dependability computing so that intelligent decisions, design, and architectures can be supported. It brings together these emerging areas under the umbrella of bio- and nature-inspired computational intelligence. The primary audience of this book includes experts and developers who want to deepen their understanding of bioinspired computing in basic theory, algorithms, and applications. The book is also intended to be used as a textbook for masters and doctoral students who want to enhance their knowledge and understanding of the role of bioinspired techniques in system dependability.

Continuous improvements in digitized practices have created opportunities for businesses to develop more streamlined processes. This not only leads to higher success in day-to-day production, but it increases the overall success of businesses. Always-On Enterprise Information Systems for Modern Organizations is a critical scholarly resource that examines how EIS implementations support business processes and facilitate this in today's e-business environment. Featuring coverage on a broad range of topics such as customer relations management, supply chain management, and business intelligence, this book is geared towards professionals, researchers, managers, consultants, and university students interested in emerging developments for business process management.

Multi-Paradigm Modelling for Cyber-Physical Systems explores modeling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modeling techniques related to different disciplines, as well as a common background knowledge. This book will serve as a reference for anyone starting in the field of CPS who needs a solid foundation of modeling, including a comprehensive introduction to existing techniques and a clear explanation of their advantages and limitations. This book is aimed at both researchers and practitioners who are interested in various modeling paradigms across computer science and engineering.

Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants.

The Feature-Driven Method for Structural Optimization details a novel structural optimization method within a CAD framework, integrating structural optimization and feature-based design. The book presents cutting-edge research on advanced structures and introduces the feature-driven structural optimization method by regarding engineering features as basic design primitives. Consequently, it presents a method that allows structural optimization and feature design to be done simultaneously so that feature attributes are preserved throughout the design process. The book illustrates and supports the effectiveness of the method described, showing potential applications through numerical modeling techniques and programming. This volume presents a high-performance optimization method adapted to engineering structures-a novel perspective that will help engineers in the computation, modeling and design of advanced structures.

Complexity and Complex Thermoeconomic Systems describes the properties of complexity and complex thermo-economic systems as the consequence of formulations, definitions, tools, solutions and results consistent with the best performance of a system. Applying to complex systems contemporary advanced techniques, such as static optimization, optimal control, and neural networks, this book treats the systems theory as a science of general laws for functional integrities. It also provides a platform for the discussion of various definitions of complexity, complex hierarchical structures, self-organization examples, special references, and historical issues. This book is a valuable reference for scientists, engineers and graduated students in chemical, mechanical, and environmental engineering, as well as those in physics, ecology and biology, helping them better understand the complex thermodynamic systems and enhance their technical skills in research.

Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis.

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.

Growing Your Career with Social Media presents social media tools, current trends and professional development strategies to help busy librarians remain up-to-date. This title offers advice from librarians on how to use social media for career development and continuing education. Advice is based on accumulated experience from professionals who have incorporated social media into their professional lives. The book includes interviews and suggests ways librarians can use social media as a tool for self-promotion. It includes tables of social media tools and their potential uses, and also provides resources, lists, organizations and information on librarians currently active in social media.

Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, development and management of intelligent systems, neural networks and related machine learning techniques for speech signal processing.

Handbook of Metaheuristic Algorithms: From Fundamental Theories to Advanced Applications provides a brief introduction to metaheuristic algorithms from the ground up, including basic ideas and advanced solutions. Although readers may be able to find source code for some metaheuristic algorithms on the Internet, the coding styles and explanations are generally quite different, and thus requiring expanded knowledge between theory and implementation. This book can also help students and researchers construct an integrated perspective of metaheuristic and unsupervised algorithms for artificial intelligence research in computer science and applied engineering domains. Metaheuristic algorithms can be considered the epitome of unsupervised learning algorithms for the optimization of engineering and artificial intelligence problems, including simulated annealing (SA), tabu search (TS), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), differential evolution (DE), and others. Distinct from most supervised learning algorithms that need labeled data to learn and construct determination models, metaheuristic algorithms inherit characteristics of unsupervised learning algorithms used for solving complex engineering optimization problems without labeled data, just like self-learning, to find solutions to complex problems.

Transportation Policy and Economic Regulation: Essays in Honor of Theodore Keeler addresses a number of today's important transportation policy issues, exploring a variety of transportation modes, and examining the policy implications of a number of alternatives. Theodore Keeler had a distinguished career in transportation economics, helping to shape regulatory policies concerning the transportation industries and assessing the appropriateness of various policies. A distinguishing feature of his work is that it always had policy implications. As a tribute to Theodore Keeler, this book examines transportation policy issues across a variety of transportation industries, including aviation, railroads, highways, motor carrier transport, automobiles, urban transit, and ocean shipping. The book evaluates the economic impact and effectiveness of various policies, employing empirical analyses and new estimation techniques, such as Bayesian analysis. The book is designed for transportation professionals and researchers, as well as transportation economics students, providing an in-depth analysis of some of today's important transportation policy issues. Policy changes established in the last 35-40 years have introduced profound changes in the business environment of the transportation industry. Past policy changes promoted the free market's role in setting prices and determining service availability. While 21st century policy has focused on a variety of other issues, such as safety, road and air congestion, productivity growth, labor relations and exhaust emission, many still promote the role of competition. In addition to examining various transportation policy issues in the U.S., the book explores some approaches to dealing with transportation issues in different parts of the world. Contemporary transportation policy debates have broadened from their initial focus of primarily examining the merits of reforming economic regulations at national levels, to now examining a variety of issues such as alternative methods of social regulation (such as safety regulation and emission controls), new approaches to changing economic regulations, the potential for reforming international regulations, and the appropriate role for government in transportation.

Application Performance Management (APM) in the Digital Enterprise enables IT professionals to be more successful in managing their company's applications. It explores the fundamentals of application management, examines how the latest technological trends impact application management, and provides best practices for responding to these changes. The recent surge in the use of containers as a way to simplify management and deploy applications has created new challenges, and the convergence of containerization, cloud, mobile, virtualization, analytics, and automation is reshaping the requirements for application management. This book serves as a guide for understanding these dramatic changes and how they impact the management of applications, showing how to create a management strategy, define the underlying processes and standards, and how to select the appropriate tools to enable management processes.

Building the Agile Enterprise with Capabilities, Collaborations and Values, Second Edition covers advances that make technology more powerful and pervasive while, at the same time, improving alignment of technology with business. Using numerous examples, illustrations, and case studies, Fred Cummins, an industry expert, author and former fellow with EDS and Hewlett Packard, updates his first edition incorporating the following industry developments: The ubiquitous use of the Internet along with intelligent, mobile devices, which have enabled everyone and everything to be connected anytime, anywhere The emergence of a "business architecture" discipline that has driven improvements in business design and transformation practices The development of CMMN (Case Management Model and Notation) that will provide automation to support the collaboration of knowledge workers and managers The development of VDML (Value Delivery Modeling Language) that supports modeling of business design from a management perspective The importance of "big data" management and analysis as a new source of insight into evolution of the business and the ecosystem How the architecture of the agile enterprise and business modeling change enterprise governance, management and innovation Building the Agile Enterprise with Capabilities, Collaborations and Values, Second Edition is a must have reference for business leaders, CTOs; business architects, information systems architects and business process modeling professionals who wish to close the gap between strategic planning and business operations as well as the gap between business and IT and enhance the creation and delivery of business value.

Enterprise Level Security 2: Advanced Topics in an Uncertain World follows on from the authors' first book on Enterprise Level Security (ELS), which covered the basic concepts of ELS and the discoveries made during the first eight years of its development. This book follows on from this to give a discussion of advanced topics and solutions, derived from 16 years of research, pilots, and operational trials in putting an enterprise system together. The chapters cover specific advanced topics derived from painful mistakes and numerous revisions of processes. This book covers many of the topics omitted from the first book including multi-factor authentication, cloud key management, enterprise change management, entity veracity, homomorphic computing, device management, mobile ad hoc, big data, mediation, and several other topics. The ELS model of enterprise security is endorsed by the Secretary of the Air Force for Air Force computing systems and is a candidate for DoD systems under the Joint Information Environment Program. The book is intended for enterprise IT architecture developers, application developers, and IT security professionals. This is a unique approach to end-to-end security and fills a niche in the market.

With recent advances in IT in areas such as AI and IoT, collaboration systems such as business chat, cloud services, conferencing systems, and unified communications are rapidly becoming widely used as new IT applications in global corporations' strategic activities. Through in-depth longitudinal studies of global corporations, the book presents a new theoretical framework and implications for IT-enabled dynamic capabilities using collaboration systems from the perspective of micro strategy theory and organization theory. The content of the book is based on longitudinal analyses that employ various qualitative research methods including ethnography, participant observation, action research and in-depth case studies of global corporations in Europe, the United States and Asia that actively use collaboration systems. It presents a new concept of micro dynamism whereby dynamic "IT-enabled knowledge communities" such as "IT-enabled communities of practice" and "IT-enabled strategic communities" create "IT-enabled dynamic capabilities" through the integration of four research streams - an information systems view, micro strategy view, micro organization view and knowledge-based view. The book demonstrates that collaboration systems create, maintain and develop "IT-enabled knowledge communities" within companies and are strategic IT applications for enhancing the competitiveness of companies in the ongoing creation of new innovation and the realization of sustainable growth in a 21st century knowledge-based society. This book is primarily written for academics, researchers and graduate students, but will also offer practical implications for business leaders and managers. Its use is anticipated not only in business and management schools, graduate schools and university education environments around the world but also in the broad business environment including management and leadership development training.

Computational Finance Using C and C#: Derivatives and Valuation, Second Edition provides derivatives pricing information for equity derivatives, interest rate derivatives, foreign exchange derivatives, and credit derivatives. By providing free access to code from a variety of computer languages, such as Visual Basic/Excel, C++, C, and C#, it gives readers stand-alone examples that they can explore before delving into creating their own applications. It is written for readers with backgrounds in basic calculus, linear algebra, and probability. Strong on mathematical theory, this second edition helps empower readers to solve their own problems. *Features new programming problems, examples, and exercises for each chapter. *Includes freely-accessible source code in languages such as C, C++, VBA, C#, and Excel.. *Includes a new chapter on the history of finance which also covers the 2008 credit crisis and the use of mortgage backed securities, CDSs and CDOs. *Emphasizes mathematical theory.

The ability to preserve electronic evidence is critical to presenting a solid case for civil litigation, as well as in criminal and regulatory investigations. Preserving Electronic Evidence for Trial provides everyone connected with digital forensics investigation and litigation with a clear and practical hands-on guide to the best practices in preserving electronic evidence. Corporate management personnel (legal & IT) and outside counsel need reliable processes for the litigation hold - identifying, locating, and preserving electronic evidence. Preserving Electronic Evidence for Trial provides the road map, showing you how to organize the digital evidence team before the crisis, not in the middle of litigation. This practice handbook by an internationally known digital forensics expert and an experienced litigator focuses on what corporate and litigation counsel as well as IT managers and forensic consultants need to know to communicate effectively about electronic evidence. You will find tips on how all your team members can get up to speed on each other's areas of specialization before a crisis arises. The result is a plan to effectively identify and pre-train the critical electronic-evidence team members. You will be ready to lead the team to success when a triggering event indicates that litigation is likely, by knowing what to ask in coordinating effectively with litigation counsel and forensic consultants throughout the litigation progress. Your team can also be ready for action in various business strategies, such as merger evaluation and non-litigation conflict resolution.

With this practical guide, you'll learn how to understand the needs of external customers without requirements elicitation or sign-offs, the difference between customer and business value, and why you need to create both. You'll discover how to respond to changes in the market and the actions of competitors. You'll understand how to develop new products, launch them into the market, and how to deliver business outcomes through the maturity and eventual retirement of your product.

Applied Computing in Medicine and Health is a comprehensive presentation of on-going investigations into current applied computing challenges and advances, with a focus on a particular class of applications, primarily artificial intelligence methods and techniques in medicine and health. Applied computing is the use of practical computer science knowledge to enable use of the latest technology and techniques in a variety of different fields ranging from business to scientific research. One of the most important and relevant areas in applied computing is the use of artificial intelligence (AI) in health and medicine. Artificial intelligence in health and medicine (AIHM) is assuming the challenge of creating and distributing tools that can support medical doctors and specialists in new endeavors. The material included covers a wide variety of interdisciplinary perspectives concerning the theory and practice of applied computing in medicine, human biology, and health care. Particular attention is given to AI-based clinical decision-making, medical knowledge engineering, knowledge-based systems in medical education and research, intelligent medical information systems, intelligent databases, intelligent devices and instruments, medical AI tools, reasoning and metareasoning in medicine, and methodological, philosophical, ethical, and intelligent medical data analysis.

Nearly every large corporation and governmental agency is taking a fresh look at their current enterprise-scale business intelligence (BI) and data warehousing implementations at the dawn of the "Big Data Era"...and most see a critical need to revitalize their current capabilities. Whether they find the frustrating and business-impeding continuation of a long-standing "silos of data" problem, or an over-reliance on static production reports at the expense of predictive analytics and other true business intelligence capabilities, or a lack of progress in achieving the long-sought-after enterprise-wide "single version of the truth" - or all of the above - IT Directors, strategists, and architects find that they need to go back to the drawing board and produce a brand new BI/data warehousing roadmap to help move their enterprises from their current state to one where the promises of emerging technologies and a generation's worth of best practices can finally deliver high-impact, architecturally evolvable enterprise-scale business intelligence and data warehousing. Author Alan Simon, whose BI and data warehousing experience dates back to the late 1970s and who has personally delivered or led more than thirty enterprise-wide BI/data warehousing roadmap engagements since the mid-1990s, details a comprehensive step-by-step approach to building a best practices-driven, multi-year roadmap in the quest for architecturally evolvable BI and data warehousing at the enterprise scale. Simon addresses the triad of technology, work processes, and organizational/human factors considerations in a manner that blends the visionary and the pragmatic.