Min Chen – författare

Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty.In Advances in Info-Metrics, Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah bring together a group of thirty experts to expand the study of info-metrics across the sciences and demonstrate how to solve problems using this interdisciplinary framework. Building on the theoretical underpinnings of info-metrics, the volume sheds new light on statistical inference, information, and general problem solving. The book explores the basis of information-theoretic inference and its mathematical and philosophical foundations. It emphasizes the interrelationship between information and inference and includes explanations of model building, theory creation, estimation, prediction, and decision making. Each of the nineteen chapters provides the necessary tools for using the info-metrics framework to solve a problem. The collection covers recent developments in the field, as well as many new cross-disciplinary case studies and examples. Designed to be accessible for researchers, graduate students, and practitioners across disciplines, this book provides a clear, hands-on experience for readers interested in solving problems when presented with incomplete and imperfect information.

This book explores Information theory (IT) tools, which have become state of the art to solve and understand better many of the problems in visualization. This book covers all relevant literature up to date. It is the first book solely devoted to this subject, written by leading experts in the field.

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologiesThe main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming.Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologiesCovers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programsOffers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologiesFully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learningFeatures a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOTBig-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization.

Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. • Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation,• Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets,• Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications,• Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms.Scientific Visualization will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics, and those interested in knowing more about the visualization process.

Min Chen, Arie E. Kaufman and Roni Yage/ Volume graphics is concerned with graphics scenes defined in volume data types, where a model is specified by a mass of points instead of a collection of surfaces. The underlying mathematical definition of such a model is a set of scalar fields, which define the geometrical and physical properties of every point in three­ dimensional space. As true 3D representations, volume data types possess more descriptive power than surface data types, and are morphologically closer to many high-level modelling schemes in traditional surface graphics such as parametric surfaces, implicit surfaces and volume sweeping. The past decade has witnessed significant advances in volume visualisation, driven mainly by applications such as medical imaging and scientific computation. The work in this field has produced a number of volume rendering methods that enable 3D information in a volumetric dataset to be selectively rendered into 2D images. With modern computer hardware, such a process can easily be performed on an ordinary workstation. More importantly, volume-based rendering offers a consistent solution to the primary deficiencies of the traditional surface-based rendering, which include its inability to encapsulate the internal description of a model, and the difficulties in rendering amorphous phenomena. The emergence of volume-based techniques has not only broadened the extent of graphics applications, but also brought computer graphics closer to other scientific and engineering disciplines, including image processing, computer vision, finite element analysis and rapid prototyping.

Asian Management Systems is the only text on the market that specifically addresses the Asian style of management in a comparative, country context. The text examines the four main management systems in the East Asian region: Japanese, mainland Chinese, Overseas Chinese and Korean, and compares and contrasts the management styles within Asia and with the western world. Through a comparative analysis of organizational structures, competitive strategies and cultural influences, the workings of each system are made clear. Practical guidelines make this book a vital guide for international executives and students alike. The new edition has been updated and covers the Tiger economies before and since the crash. It also looks at the rise of Islam as a force in Asian business and examines China’s new role as a quasi-capitalist economic system within a communist political system. This is the core text for all students of Asian business and for all academics with a lively interest in international business.

Traditional Chinese medicine (TCM), with a history of thousands of years, is the crystallization of the ancient Chinese people's experience in their struggle against diseases. It is also an integral part of their splendid culture. Under the influence and direction of classic Chinese philosophies, it has undergone long-term medical practice and infiltrated into, as well as absorbed from, other subjects at that time, thus gradually evolving into a unique medical theoretical system that contributed significantly to the health care of the Chinese people and the prosperity of the Chinese nation. This 7-volume set comprehensively covers the main components of TCM, such as Basic Theory, Diagnosis, Prescription, Chinese Materia Medica, Tui Na, Acupuncture and Moxibustion.

Traditional Chinese medicine (TCM), with a history of thousands of years, is the crystallization of the ancient Chinese people's experience in their struggle against diseases. It is also an integral part of their splendid culture. Under the influence and direction of classic Chinese philosophies, it has undergone long-term medical practice and infiltrated into, as well as absorbed from, other subjects at that time, thus gradually evolving into a unique medical theoretical system that contributed significantly to the health care of the Chinese people and the prosperity of the Chinese nation. This 7-volume set comprehensively covers the main components of TCM, such as Basic Theory, Diagnosis, Prescription, Chinese Materia Medica, Tui Na, Acupuncture and Moxibustion.

This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization.Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.

This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization.Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.

This book designates Visualization Psychology as an interdisciplinary subject. The field of visualization is a rich playground for discovering new knowledge in both visualization and psychology.

This book designates Visualization Psychology as an interdisciplinary subject. The field of visualization is a rich playground for discovering new knowledge in both visualization and psychology.

This book constitutes the thoroughly refereed post conference proceedings of the 4th International Conference on Cloud Computing, Cloud Comp 2013, held in Wuhan, China, in October 2013. The 28 revised full papers were carefully reviewed and selected from numerous submissions and cover topics such as mobile cloud computing, services, applications, IoT on cloud, architectures and big data, cloud-assisted pervasive computing and services, management and virtualization for cloud, cloud security.

This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis.

This book constitutes the proceedings of the 9th International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, TridentCom 2014, held in Guangzhou, China, in May 2014. The 49 revised full papers presented were carefully selected out of 149 submissions. The conference consisted of 6 symposia covering topics such as testbed virtualization, Internet of Things, vehicular networks, SDN, NDN, large-scale testbed federation, mobile networks, wireless networks.

This book constitutes the thoroughly refereed post conference proceedings of the 5th International Conference on Cloud Computing, CloudComp 2014, held in Guilin, China, in October 2014.The 25 revised full papers were carefully reviewed and selected from 72 submissions and cover topics such as mobile cloud computing, services, applications, IoT on cloud, architectures and big data, cloud-assisted pervasive computing and services, management and virtualization for cloud, cloud security.

This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and provides an overview of the potential solutions to major problems.The authors introduce the problem of per-flow size measurement for big network data and present a fast and scalable counter architecture, called Counter Tree, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range. Unlike traditional approaches to cardinality estimation problems that allocate a separated data structure (called estimator) for each flow, this book takes a different design path by viewing all the flows together as a whole: each flow is allocated with a virtual estimator, and these virtual estimators share a common memory space. A framework of virtual estimators is designed to apply the idea of sharing to an array of cardinality estimation solutions, achieving far better memory efficiency than the best existing work. To conclude, the authors discuss persistent spread estimation in high-speed networks. They offer a compact data structure called multi-virtual bitmap, which can estimate the cardinality of the intersection of an arbitrary number of sets. Using multi-virtual bitmaps, an implementation that can deliver high estimation accuracy under a very tight memory space is presented. The results of these experiments will surprise both professionals in the field and advanced-level students interested in the topic. By providing both an overview and the results of specific experiments, this book is useful for those new to online traffic measurement and experts on the topic.

This SpringerBrief introduces key techniques for 5G wireless networks. The authors cover the development of wireless networks that led to 5G, and how 5G mobile communication technology (5G) can no longer be defined by a single business model or a typical technical characteristic. The discussed networks functions and services include Network Foundation Virtualization (N-FV), Cloud Radio Access Networks (Cloud-RAN), and Mobile Cloud Networking (MCN). The benefits of cloud platforms are examined, as are definable networking and green wireless networking. Other related and representative projects on 5G are mobile and wireless communications enablers for the Twenty-Twenty Information Society, Multi-hop Cellular Networks, Network Function as-a-Service over Virtualized Infrastructures, iJOIN, and Nuage Virtualized Services Platform. Major applications of 5G range from RAN sharing and Multi-Operator Core Networks to mobile convergence. Enhancing the user experience by providing smart and customized services, 5G will support the explosive growth of big data, mobile internet, digital media, and system efficiency.  This SpringerBrief is designed for professionals, researchers, and academics working in networks or system applications. Advanced-level students of computer science or computer engineering will also find the content valuable.

This book introduces applications of RFID on the Internet of things, under the emerging technologies for tag search, anonymous RFID authentication, and identification of networked tags. A new technique called filtering vector (a compact data structure that encodes tag IDs) is proposed to enable tag filtration, meeting the stringent delay requirements for real-world applications. Based on filtering vectors, a novel iterative tag search protocol is designed, which progressively improves the accuracy of search result and reduces the time of each iteration by using the information learned from the previous iterations. Moreover, the protocol is extended to work under noisy channel.The authors also make a fundamental shift from the traditional design paradigm for anonymous RFID authentication by following an asymmetry design principle that pushes most complexity to the readers while leaving the tags as simple as possible. A novel technique is developed to dynamically generate random tokens on demand for authentication. The token-based authentication protocol only requires O(1) communication overhead and online computation overhead per authentication for both readers and tags.Finally, the authors investigate the problem of networked-tag identification. The traditional contention-based protocol design will incur too much energy overhead in multihop tag systems, and a reader-coordinated design that significantly serializes tag transmissions performs much better. In addition, a solution based on serial numbers is proposed to achieve load balancing, thereby reducing the worst-case energy cost among the tags.Designed for researchers and professionals, this SpringerBrief will interest individuals who work in efficiency, security, and privacy. Advanced-level students focused on network design will also benefit from the content.

This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and provides an overview of the potential solutions to major problems.The authors introduce the problem of per-flow size measurement for big network data and present a fast and scalable counter architecture, called Counter Tree, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range. Unlike traditional approaches to cardinality estimation problems that allocate a separated data structure (called estimator) for each flow, this book takes a different design path by viewing all the flows together as a whole: each flow is allocated with a virtual estimator, and these virtual estimators share a common memory space. A framework of virtual estimators is designed to apply the idea of sharing to an array of cardinality estimation solutions, achieving far better memory efficiency than the best existing work. To conclude, the authors discuss persistent spread estimation in high-speed networks. They offer a compact data structure called multi-virtual bitmap, which can estimate the cardinality of the intersection of an arbitrary number of sets. Using multi-virtual bitmaps, an implementation that can deliver high estimation accuracy under a very tight memory space is presented. The results of these experiments will surprise both professionals in the field and advanced-level students interested in the topic. By providing both an overview and the results of specific experiments, this book is useful for those new to online traffic measurement and experts on the topic.

This book introduces applications of RFID on the Internet of things, under the emerging technologies for tag search, anonymous RFID authentication, and identification of networked tags.

This volume contains an overview of research into computer graphics/visualization and high performance computing, currently two of the foremost technologies in the computing domain. Among the topics covered in the work are: the impact of the development of high performance computing on computer graphics and visualization; the current use of high perfomance computing architecture and software tools in computer graphics and visualization; the role of parallelism in computer graphics; and the identification of potential applications for high performance computing in computer graphics and visualization.

This book constitutes the thoroughly refereed post-conference proceedings of the First International Joint Conference on Green Communication and Networking (GreeNets 2011), held in Colmar, France, on October 5-7, 2011. The 16 revised full papers presented were carefully selected and reviewed from numerous submissions and explain the scope and challenges of designing, building, and deploying GreeNets. In this regard, the conference aims to establish a forum to bring together research professionals from diverse fields including green mobile networks, system architectures, networking & communication protocols, applications, test-bed and prototype, traffic balance and energy-efficient cooperation transmission, system and application issues related to GreenNets.

The two volume sets LNCS 8033 and 8034 constitutes the refereed proceedings of the 9th International Symposium on Visual Computing, ISVC 2013, held in Rethymnon, Crete, Greece, in July 2013. The 63 revised full papers and 35 poster papers presented together with 32 special track papers were carefully reviewed and selected from more than 220 submissions. The papers are organized in topical sections: Part I (LNCS 8033) comprises computational bioimaging; computer graphics; motion, tracking and recognition; segmentation; visualization; 3D mapping, modeling and surface reconstruction; feature extraction, matching and recognition; sparse methods for computer vision, graphics and medical imaging; and face processing and recognition. Part II (LNCS 8034) comprises topics such as visualization; visual computing with multimodal data streams; visual computing in digital cultural heritage; intelligent environments: algorithms and applications; applications and virtual reality.

The two volume sets LNCS 8033 and 8034 constitutes the refereed proceedings of the 9th International Symposium on Visual Computing, ISVC 2013, held in Rethymnon, Crete, Greece, in July 2013. The 63 revised full papers and 35 poster papers presented together with 32 special track papers were carefully reviewed and selected from more than 220 submissions. The papers are organized in topical sections: Part I (LNCS 8033) comprises computational bioimaging; computer graphics; motion, tracking and recognition; segmentation; visualization; 3D mapping, modeling and surface reconstruction; feature extraction, matching and recognition; sparse methods for computer vision, graphics and medical imaging; face processing and recognition. Part II (LNCS 8034) comprises topics such as visualization; visual computing with multimodal data streams; visual computing in digital cultural heritage; intelligent environments: algorithms and applications; applications; virtual reality.

This book blends the principles of cloud computing theory and discussion of emerging technologies in cloud broker systems, enabling users to realise the potential of an integrated broker system for scientific applications and the Internet of Things (IoT).Due to dynamic situations in user demand and cloud resource status, scalability has become crucial in the execution of complex scientific applications. Therefore, data analysts and computer scientists must grasp workflow management issues in order to better understand the characteristics of cloud resources, allocate these resources more efficiently and make critical decisions intelligently. Thus, this book addresses these issues through discussion of some novel approaches and engineering issues in cloud broker systems and cloudlets for workflow scheduling. This book closes the gaps between cloud programmers and scientific applications designers, describing the fundamentals of cloud broker system technology and the state-of-the-art applications in implementation and performance evaluation.The books gives details of scheduling structures and processes, providing guidance and inspiration for users including cloud programmers, application designers and decision makers with involvement in cloud resource management.

This book blends the principles of cloud computing theory and discussion of emerging technologies in cloud broker systems, enabling users to realise the potential of an integrated broker system for scientific applications and the Internet of Things (IoT).Due to dynamic situations in user demand and cloud resource status, scalability has become crucial in the execution of complex scientific applications. Therefore, data analysts and computer scientists must grasp workflow management issues in order to better understand the characteristics of cloud resources, allocate these resources more efficiently and make critical decisions intelligently. Thus, this book addresses these issues through discussion of some novel approaches and engineering issues in cloud broker systems and cloudlets for workflow scheduling. This book closes the gaps between cloud programmers and scientific applications designers, describing the fundamentals of cloud broker system technology and the state-of-the-art applications in implementation and performance evaluation.The books gives details of scheduling structures and processes, providing guidance and inspiration for users including cloud programmers, application designers and decision makers with involvement in cloud resource management.

This is the first book offering an in-depth and comprehensive IoT network simulation, supported by OPNET tool. This book addresses various versions of Internet of Things (IoT), including human-centric IoT, green IoT, Narrow band IoT, Smart IoT, IoT-Cloud integration.