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ICANN, the International Conference on Artificial Neural Networks, is the official conference series of the European Neural Network Society which started in Helsinki in 1991. Since then ICANN has taken place in Brighton, Amsterdam, Sorrento, Paris, Bochum and Lausanne, and has become Europe's major meeting in the field of neural networks. This book contains the proceedings of ICANN 98, held 2-4 September 1998 in Skovde, Sweden. Of 340 submissions to ICANN 98, 180 were accepted for publication and presentation at the conference. In addition, this book contains seven invited papers presented at the conference. A conference of this size is obviously not organized by three individuals alone. We therefore would like to thank the following people and organizations for supporting ICANN 98 in one way or another: • the European Neural Network Society and the Swedish Neural Network Society for their active support in the organization of this conference, • the Programme Committee and all reviewers for the hard and timely work that was required to produce more than 900 reviews during April 1998, • the Steering Committee which met in Skovde in May 1998 for the final selection of papers and the preparation of the conference program, • the other Module Chairs: Bengt Asker (Industry and Research), Harald Brandt (Applications), Anders Lansner (Computational Neuroscience and Brain Theory), Thorsteinn Rognvaldsson (Theory), Noel Sharkey (co chair Autonomous Robotics and Adaptive Behavior), Bertil Svensson (Hardware and Implementations), • the conference secretary, Leila Khammari, and the rest of the
This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.
This book presents state of the art theoretical and empirical research on the ubiquitous internet: its everyday users and its economic stakeholders. The book offers a 360-degree media analysis of the contemporary terrain of the internet by examining both user and industry perspectives and their relation to one another. Contributors consider user practices in terms of internet at your fingertips—the abundance, free flow, and interconnectivity of data. They then consider industry’s use of user data and standards in commodification and value-creation.
This book is written to promote academic strategic management and envision future innovations for academic library resources, services and instructions in the digital age. It provides academic executives, consultants, instructors, IT specialists, librarians, LIS students, managers, trainers and other professionals with the latest information for developing trends of emerging technologies applied to student-centred and service-oriented academic learning environments. This book explores various fields where key emerging technologies may have great implications on academic library information technologies, academic library management, academic library information services, and academic library internal operations. - Reflects most recent emerging technologies which might impact on library administrations, resources, services and instructions - Draws a clear roadmap how and where to monitor emerging technologies which began to emerge under academic library environments - Provides practical and realistic suggestions and solutions how to utilize emerging technologies in academic learning environments
The Internet Corporation for Assigned Names and Numbers (ICANN), founded in 1998, is a not-for-profit public-benefit corporation established to ensure a stable and secure global Internet. As the custodian of the Domain Name System (DNS), one of its key responsibilities is the introduction and promotion of competition in Internet-related markets, an aim which ICANN has tried to achieve through the delegation of generic top-level domains (gTLDs). This book investigates how successful ICANN has been in achieving this goal. Over the years, ICANN has been required to decide on a substantial number of complaints from applicants for gTLDs related to capture, arbitrariness, discrimination, and unwarranted restriction of competition. This book is the first detailed study of complaints related to ICANN decisions that have been brought using ICANN's Independent Review Process (IRP). The authors - preeminent expert practitioners in international litigation and arbitration related to Internet governance - take a close look at how ICANN has handled the major issues raised and how ICANN has shaped its own accountability mechanisms. The book also weighs the influence of external accountability on ICANN’s decision-making process and considers the implications of third-party decisions (such as IRP decisions) for the ongoing development of the Internet. This authoritative analysis covers: • the regulatory framework governing ICANN and the introduction of new gTLDs in a historic perspective; • ICANN’s accountability framework; • all the IRP cases that have been decided to date, with an in-depth analysis of those cases that have become reference decisions in the latest application round; and • the 2016 amendments to ICANN’s articles of incorporation and bylaws, concentrating on the problems that remain unresolved. This work is a welcome addition to the debate on how to address the shortcomings in ICANN’s accountability in the interests of the global Internet community. The authors make concrete proposals and recommendations, suggesting changes to ICANN’s regulatory framework in the light of the lessons learned and with a view to preventing similar problems arising in a next round of gTLD applications. This book has the potential to become the Green Book for fundamental changes to ICANN’s accountability framework.
Topics in Nonlinear Dynamics, Volume 1: Proceedings of the 31st IMAC, A Conference and Exposition on Structural Dynamics, 2013, the first volume of seven from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Nonlinear Oscillations Nonlinearities ... In Practice Nonlinear System Identification: Methods Nonlinear System Identification: Friction & Contact Nonlinear Modal Analysis Nonlinear Modeling & Simulation Nonlinear Vibration Absorbers Constructive Utilization of Nonlinearity
Proceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention MechaProceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention Mechanisms, held 23-28 October 2000 in Vietri sul Mare, Italy.nisms, held 23-28 October 2000 in Vietri sul Mare, Italy. The book covers a number of broad themes relevant to visual attention, ranging from computer vision to psychology and physiology of vision. The main theme of the book is the attention processes of vision systems and it aims to point out the analogies and the divergences of biological vision with the frameworks introduced by computer scientists in artificial vision.
Support vector machines (SVMs), were originally formulated for two-class classification problems, and have been accepted as a powerful tool for developing pattern classification and function approximations systems. This book provides a unique perspective of the state of the art in SVMs by taking the only approach that focuses on classification rather than covering the theoretical aspects. The book clarifies the characteristics of two-class SVMs through their extensive analysis, presents various useful architectures for multiclass classification and function approximation problems, and discusses kernel methods for improving generalization ability of conventional neural networks and fuzzy systems. Ample illustrations, examples and computer experiments are included to help readers understand the new ideas and their usefulness. This book supplies a comprehensive resource for the use of SVMs in pattern classification and will be invaluable reading for researchers, developers & students in academia and industry.
The field of biologically inspired computation has coexisted with mainstream computing since the 1930s, and the pioneers in this area include Warren McCulloch, Walter Pitts, Robert Rosen, Otto Schmitt, Alan Turing, John von Neumann and Norbert Wiener. Ideas arising out of studies of biology have permeated algorithmics, automata theory, artificial intelligence, graphics, information systems and software design. Within this context, the biomolecular, cellular and tissue levels of biological organisation have had a considerable inspirational impact on the development of computational ideas. Such innovations include neural computing, systolic arrays, genetic and immune algorithms, cellular automata, artificial tissues, DNA computing and protein memories. With the rapid growth in biological knowledge there remains a vast source of ideas yet to be tapped. This includes developments associated with biomolecular, genomic, enzymic, metabolic, signalling and developmental systems and the various impacts on distributed, adaptive, hybrid and emergent computation. This multidisciplinary book brings together a collection of chapters by biologists, computer scientists, engineers and mathematicians who were drawn together to examine the ways in which the interdisciplinary displacement of concepts and ideas could develop new insights into emerging computing paradigms. Funded by the UK Engineering and Physical Sciences Research Council (EPSRC), the CytoCom Network formally met on five occasions to examine and discuss common issues in biology and computing that could be exploited to develop emerging models of computation.
The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative community of interna tional researchers. A number of extensions and modifications have been developed during the last two decades. The reason is surely not that the original algorithm was imperfect or inad equate. It is rather the universal applicability and easy handling of the SOM. Com pared to many other network paradigms, only a few parameters need to be arranged and thus also for a beginner the network leads to useful and reliable results. Never theless there is scope for improvements and sophisticated new developments as this book impressively demonstrates. The number of published applications utilizing the SOM appears to be unending. As the title of this book indicates, the reader will benefit from some of the latest the oretical developments and will become acquainted with a number of challenging real-world applications. Our aim in producing this book has been to provide an up to-date treatment of the field of self-organizing neural networks, which will be ac cessible to researchers, practitioners and graduated students from diverse disciplines in academics and industry. We are very grateful to the father of the SOMs, Professor Teuvo Kohonen for sup porting this book and contributing the first chapter.