This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms - the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.

Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world's leading data fusion researchers and academicians, this authoritative book: Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors Describes new materials and achievements in optimal fusion and multisensor filters Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.

Routing of VLSI chips is an important, time consuming, and difficult problem. The difficulty of the problem is attributed to the large number of often conflicting factors that affect the routing quality. Traditional techniques have approached routing by ignoring some of these factors and imposing unnecessary constraints in order to make routing tractable. In addition to the imposition of these restrictions, which simplify the problems to a degree but at the same time reduce the routing quality, traditional approaches use brute force. They often transform the problem into mathematical or graph problems and completely ignore the specific knowledge about the routing task that can greatly help the solution. This thesis overcomes some of the above problems and presents a system that performs routing close to what human designers do. In other words it heavily capitalizes on the knowledge of human expertise in this area, it does not impose unnecessary constraints, it considers all the different factors that affect the routing quality, and most importantly it allows constant user interaction throughout the routing process. To achieve the above, this thesis presents background about some representative techniques for routing and summarizes their characteristics. It then studies in detail the different factors (such as minimum area, number of vias, wire length, etc.) that affect the routing quality, and the different criteria (such as vertical/horizontal constraint graph, merging, minimal rectilinear Steiner tree, etc.) that can be used to optimize these factors.

Organizational cognition concerns the processes which provide agents and organizations with the ability to learn, make decisions, and solve problems. ""Organizational and Technological Implications of Cognitive Machines: Designing Future Information Management Systems"" presents new challenges and perspectives to the understanding of the participation of cognitive machines in organizations. Containing extensive research by an international collaboration of experts, this book addresses the possible implications of cognitive machines for current and future organizations.

This volume presents selected contributions from the "Advanced Research Workshop on Explosives Detection" hosted by the Department of Information Engineering of the University of Florence, Italy in 2018. The main goal of the workshop was to find out how Science for Peace and Security projects in the field of Explosives Detection contribute to the development and/or refinement of scientific and technical knowledge and competencies. The findings of the workshop, presented in the last section of the book, determine future actions and direction of the SPS Programme in the field of explosives detection and management.The NATO Science for Peace and Security (SPS) Programme, promotes dialogue and practical cooperation between NATO member states and partner nations based on scientific research, technological innovation and knowledge exchange. Several initiatives were launched in the field of explosive detection and clearance, as part of NATO's enhanced role in the international fight against terrorism. Experts and scientists from NATO members and partner countries have been brought together in multi-year projects, within the framework of the SPS Programme, to cooperate in the scientific research in explosive detection field, developing new technologies and methods to be implemented in order to detect explosive substances in different contexts.

This volume surveys recent research on autonomous sensor networks from the perspective of enabling technologies that support medical, environmental and military applications.

State of the art, as well as emerging concepts in wireless sensor networks, body area networks and ambient assisted living introduce the reader to the field, while subsequent chapters deal in depth with established and related technologies, which render their implementation possible. These range from smart textiles and printed electronic devices to implanted devices and specialized packaging, including the most relevant technological features.

The last four chapters are devoted to customization, implementation difficulties and outlook for these technologies in specific applications.

This volume represents an advanced, comprehensive state-of-the-art survey of the field of rational agency as it stands today. It covers the philosophical foundations of rational agency, logical and decision-theoretic approaches to rational agency, multi-agent aspects of rational agency and a number of approaches to programming rational agents. It will be of interest to researchers in logic, mainstream computer science, the philosophy of rational action and agency, and economics.

How do organizations become created? Entrepreneurship scholars have debated this question for decades, but only recently have they been able to gain insights into the non-linear dynamics that lead to organizational emergence, through the use of the complexity sciences. Written for social science researchers, Generative Emergence summarizes these literatures, including the first comprehensive review of each of the 15 complexity science disciplines. In doing so, the book makes a bold proposal for a discipline of Emergence, and explores one of its proposed fields, namely Generative Emergence. The book begins with a detailed summary of its underlying science, dissipative structures theory, and rigorously maps the processes of order creation discovered by that science to identify a 5-phase model of order creation in entrepreneurial ventures. The second half of the book presents the findings from an experimental study that tested the model in four fast-growth ventures through a year-long, week-by-week longitudinal analysis of their processes, based on over 750 interviews and 1000 hours of on-site observation. These data, combined with reports from over a dozen other studies, confirm the dynamics of the 5-phase model in multiple contexts. By way of conclusion, the book explores how the model of Generative Emergence could be applied to enact emergence within and across organizations.

Within the framework of so-called second generation expert systems [62] knowledge modeling is one of the most important aspects. On the one hand, knowledge acquisition is no longer seen as a knowledge transfer process, rather it is now considered as model construction process which is typically a cyclic and error prone process. On the other hand, the distinction between knowledge and symbol level descriptions [166] resulted in various proposals for conceptual knowledge models describing knowledge in an implementation independent way. One of the most prominent examples of such a conceptual model is the KADS model of expertise which is characterized by its clear distinction of different know ledge types and by the usage of specific modeling primitives to describe these different knowledge types [185]. The semi formal KADS expertise model entails all the advantages and disadvantages which have been identified for semi-formal system models e.g. in the software engineering community.

eMaintenance: Essential Electronic Tools for Efficiency enables the reader to improve efficiency of operations, maintenance staff, infrastructure managers and system integrators, by accessing a real time computerized system from data to decision. In recent years, the exciting possibilities of eMaintenance have become increasingly recognized as a source of productivity improvement in industry. The seamless linking of systems and equipment to control centres for real time reconfiguring is improving efficiency, reliability, and sustainability in a variety of settings. The book provides an introduction to collecting and processing data from machinery, explains the methods of overcoming the challenges of data collection and processing, and presents tools for data driven condition monitoring and decision making. This is a groundbreaking handbook for those interested in the possibilities of running a plant as a smart asset.

Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.

A fundamental assumption of work in artificial intelligence and machine learning is that knowledge is expressed in a computer with the help of knowledge representations. Since the proper choice of such representations is a difficult task that fundamentally affects the capabilities of a system, the problem of automatic representation change is an important topic in current research. Concept Formation and Knowledge Revision focuses on representation change as a concept formation task, regarding concepts as the elementary representational vocabulary from which further statements are constructed. Taking an interdisciplinary approach from psychological foundations to computer implementations, the book draws on existing psychological results about the nature of human concepts and concept formation to determine the scope of concept formation phenomena, and to identify potential components of computational concept formation models. The central idea of this work is that computational concept formation can usefully be understood as a process that is triggered in a demand-driven fashion by the representational needs of the learning system, and identify the knowledge revision activities of a system as a particular context for such a process. The book presents a detailed analysis of the revision problem for first-order clausal theories, and develops a set of postulates that any such operation should satisfy. It shows how a minimum theory revision operator can be realized by using exception sets, and that this operator is indeed maximally general. The book then shows that concept formation can be triggered from within the knowledge revision process whenever the existing representation does not permit the plausible reformulation of an exception set, demonstrating the usefulness of the approach both theoretically and empirically within the learning knowledge acquisition system MOBAL. In using a first-order representation, this book is part of the rapidly developing field of Inductive Logic Programming (ILP). By integrating the computational issues with psychological and fundamental discussions of concept formation phenomena, the book will be of interest to readers both theoretically and psychologically inclined. From the foreword by Katharina Morik: The ideal to combine the three sources of artificial intelligence research has almost never been reached. Such a combined and integrated research requires the researcher to master different ways of thinking, different work styles, different sets of literature, and different research procedures. It requires capabilities in software engineering for the application part, in theoretical computer science for the theory part, and in psychology for the cognitive part. The most important capability for artificial intelligence is to keep the integrative view and to create a true original work that goes beyond the collection of pieces from different fields. This book achieves such an integrative view of concept formation and knowledge revision by presenting the way from psychological investigations that indicate that concepts are theories and point at the important role of a demand for learning. to an implemented system which supports users in their tasks when working with a knowledge base and its theoretical foundation. '

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.

In professional practice, many designers collect and maintain personal notes as guidelines about experiences and insights for handling technical problems and design situations. An intelligent personal assistant (IPA) can act as a database for these notes, making the entire design process more efficient. Based on real industrial procedures, this book contains practical examples for professionals and students interested in real implementations of knowledge based systems in engineering. It integrates two major ideas: a computer system integrating computer design tools and a computer system fulfilling the role of an intelligent personal assistant. This user-friendly approach to the main ideas, concepts and techniques shows how an IPA can serve as a significant and fruitful knowledge based technique in engineering design.

In this book, Haridimos Tsoukas, one of the most imaginative organization theorists of our time, examines the nature of knowledge in organizations, and how individuals and scholars approach the concept of knowledge. Tsoukas firstly looks at organizational knowledge and its embessedness in social contexts and forms of life. He shows that knowledge is not just a collection of free floating representations of the world to be used at will, but an activity constitute of the world. On the one hand, the organization as an institutionalized system does produce regularities that can be captured via propositional forms of knowledge. On the other, the organization as practice as a lifeworld, or as an open-ended system produce stories, values, and shared traditions which can only be captured by narrative forms of knowledge. Secondly, Tsoukas looks at the issue of how individuals deal with the notion of complexity in organizations: Our inability to reduce the behavior of complex organizations to their constituent parts. Drawing on concepts such as discourse, narrativity, and reflexivity, he adopts a hermeneutical approach to the issue. Finally, Tsoukas examines the concept of meta-knowledge, and how we know what we know. Arguing that the underlying representationalist epistemology of much of mainstream management causes many problems, he advocates adopting a more discursive approach. He describes what such an epistemology might be, and illustrates it with examples from organization studies and strategic management. An ideal introduction to the thinking of a leading organizational theorist, this book will be essential reading for academics, researchers, and students of Knowledge Management, Organization Studies, Management Studies, Business Strategy and Applied Epistemology.

In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings.

Multisensor Data Fusion, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world's leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field.

New to the Second Edition-

- Applications in electromagnetic systems and chemical and biological sensors

- Army command and combat identification techniques

- Techniques for automated reasoning

- Advances in Kalman filtering

- Fusion in a network centric environment

- Service-oriented architecture concepts

- Intelligent agents for improved decision making

- Commercial off-the-shelf (COTS) software tools

From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.

The three-volume set IFIP AICT 368-370 constitutes the refereed post-conference proceedings of the 5th IFIP TC 5, SIG 5.1 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2011, held in Beijing, China, in October 2011. The 189 revised papers presented were carefully selected from numerous submissions. They cover a wide range of interesting theories and applications of information technology in agriculture, including simulation models and decision-support systems for agricultural production, agricultural product quality testing, traceability and e-commerce technology, the application of information and communication technology in agriculture, and universal information service technology and service systems development in rural areas. The 68 papers included in the second volume focus on GIS, GPS, RS, and precision farming.

Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed.
This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs.
*Authors are well-recognized experts in the field who have applied the techniques to real-world problems
* Presents the core ideas of KR&R in a simple straight forward approach, independent of the quirks of research systems
*Offers the first true synthesis of the field in over a decade

With the collapse of high-profile companies such as Enron and Tyco, worldwide anti-globalization protests, and recent revelations of questionable behavior by financial groups and auditors, corporate behavior has become the highest priority topic for businesspeople, investors, politicians and the public. Yet despite the critical importance of maintaining public and shareholder trust, most corporations make very little formal effort to actively manage the activities that can put their reputation, share price, and customer base at risk. Most corporations officially embrace the concept of Corporate Social Responsibility; but giving money away to local communities or worthy causes will not prevent an ethical disaster.
The problem is not social irresponsibility; the problem is a lack of knowledge about what is taking place in the company or at its subcontractor sites. What companies need to be thinking about is not a theoretical construct around Corporate Social Responsibility, or how they can spin public opinion by charitable actions. They need to be thinking about how they can create a practical knowledge and risk management framework in their company that allows them to avoid costly and reputation-damaging behavior in the first place.
Ultimately, this comes down to knowledge management. Whether violations of human rights, employment law, or environmental standards - or simply accounting shenanigans - invariably the reason that these activities are not anticipated and avoided is simply that executives and board members do not realize what is happening in the organization, and what the likely implications of actions will be. And the larger the organization, the more extensive thatlack of knowledge.
The good news is that developing a strategic approach to corporate integrity is neither exceptionally expensive nor particularly difficult. The problem is that companies that are already using sophisticated information technology and knowledge management tools for gathering internal and external information have focused those systems and practices almost exclusively on operational issues and increasing productivity. But these same knowledge management techniques - built around emerging ethical guidelines being developed by international standards groups - can be used by companies to create an effective global policy for building and maintaining corporate integrity. This means applying knowledge management techniques in three important areas:
* First, they need to mobilize key employee knowledge and the vast amount of information available on potentially sensitive issues in a way that allows key decision-makers to "sense and respond" quickly and correctly to developing risks.
* Second, it means creating objective, scenario-based guidelines for ethical behavior, communicating those guidelines using knowledge management techniques among key organizational leaders, and providing a workable system of incentives for managers to surface potentially dangerous issues.
* Third, companies need to adopt emerging guidelines such as AA1000 that provide for ethical procedures and performance indicators that enable companies to audit and monitor their own behavior, and also to provide shareholders and the buying public with an objective report on the company's ethical performance. Much like ISO 9000, Six Sigma and other performance and productivity and practicestandards of the 1990s, these new global ethics standards will inevitably become a baseline by which investors and customers judge a company's potential for future growth and stability. High marks on auditable ethical performance set against these guidelines will become an important way for companies to differentiate themselves from their competition in the future.
Developing a workable program for corporate ethics will be one of the most important issues of this decade, and will be "the next big thing" for large organizations. A drive toward standardized reporting of corporate ethics practices was coming anyway; the recent public corporate disasters will only encourage corporate executive teams to scramble to demonstrate to customers and shareholders that their organization takes these issues seriously.
This book, therefore, will be a primer for business people and business students worldwide who will shortly be tasked with devising or participating in those types of corporate integrity initiatives, and will explain how knowledge management is indispensable as a tool for helping corporations to manage their risk and integrity policies. Through a mixture of leading practice case studies and a clear framework, it will show how a corporation can begin to combine leading practices in risk and knowledge management with emerging international guidelines in order to develop and manage a program of corporate integrity.
* The first book to show how knowledge management and corporate integrity intersect
* Shows executives how to develop a strategic approach to corporate integrity in this post-Enron age
* Neef, an expert on knowledge management, explains how a company canre-engineer existing knowledge management systems to build and maintain an effective corporate integrity program

Since its inception, fuzzy logic has attracted an incredible amount of interest, and this interest continues to grow at an exponential rate. As such, scientists, researchers, educators and practitioners of fuzzy logic continue to expand on the applicability of what and how fuzzy can be utilised in the real-world. In this book, the authors present key application areas where fuzzy has had significant success. The chapters cover a plethora of application domains, proving credence to the versatility and robustness of a fuzzy approach. A better understanding of fuzzy will ultimately allow for a better appreciation of fuzzy. This book provides the reader with a varied range of examples to illustrate what fuzzy logic can be capable of and how it can be applied. The text will be ideal for individuals new to the notion of fuzzy, as well as for early career academics who wish to further expand on their knowledge of fuzzy applications. The book is also suitable as a supporting text for advanced undergraduate and graduate-level modules on fuzzy logic, soft computing, and applications of AI.

The book is the complete introduction and applications guide to this new technology. This book introduces the reader to features and gives an overview of geometric modeling techniques, discusses the conceptual development of features as modeling entities, illustrates the use of features for a variety of engineering design applications, and develops a set of broad functional requirements and addresses high level design issues.

Including contributions from leading experts in the field, this book covers applications and developments of heuristic search methods for solving complex optimization problems. The book covers various local search strategies including genetic algorithms, simulated annealing, tabu search and hybrids thereof. These methods have proved extraordinarily successful by solving some of the most difficult, real-world problems. At the interface between Artificial Intelligence and Operational Research, research in this exciting area is progressing apace spurred on by the needs of industry and commerce. The introductory chapter provides a clear overview of the basic techniques and useful pointers to further reading and to current research. The second section of the book covers some of the most recent and exciting developments of the basic techniques, with suggestions not only for extending and improving these but also for hybridizing and incorporating automatic adaption. The third section contains a number of case studies, surveys and comparative studies which span a wide range of application areas ranging from the classic Steiner tree problem to more practical problems arising in telecommunications and data analysis. The coverage of the latest research and the illustrative case studies will ensure that the book is invaluable for researchers and professionals with an interest in heuristic search methods.

The Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia.
The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.

The Intelligent Transportation System (ITS) Program is a cooperative effort by government, private industry, and academia to apply advanced technology to the task of resolving the problems of surface transportation. The objective is to improve travel efficiency and mobility, enhance safety, conserve energy, provide economic benefits, and protect the environment. The current demand for mobility has exceeded the available capacity of the roadway system. Because the highway system cannot be expanded, except in minor ways, the available capacity must be used more efficiently to handle the increased demand.
ITS applies advanced information processing, communication, sensing, and computer control technologies to the problems of surface transportation. Considerable research and development efforts will be required to produce these new technologies and to convert technologies developed in the defense and space programs to solve surface transportation problems.
ITS has been subdivided into six interlocking technology areas. This book addresses human factors concerns for four of these areas:
*" Advanced Traveler Information Systems" are a variety of systems that provide real time, in-vehicle information to drivers regarding navigation and route guidance, motorist services, roadway signing, and hazard warnings.
*" Advanced Vehicle Control Systems" refer to systems that aid drivers in controlling their vehicle particularly in emergency situations and ultimately taking over some or all of the driving tasks.
*" Commercial Vehicle Operations" address the application of ITS technologies to the special needs of commercial roadway vehicles including automated vehicle identification, location, weigh-in-motion, clearance sensing, and record keeping.
*" Advanced Traffic Management Systems" monitor, control and manage traffic on streets and highways to reduce congestion using vehicle route diversion, automated signal timing, changeable message signs, and priority control systems.
Two technical areas are not specifically addressed in individual chapters, but many aspects of them are covered in associated chapters:
*" Advanced Rural Transportation Systems" include systems that apply ITS technologies to the special needs of rural systems and include emergency notification and response, vehicle location, and traveler information.
*" Advanced Public Transportation Systems" enhance the effectiveness, attractiveness and economics of public transportation and include fleet management, automated fare collection, and real-time information systems.