Space support in databases poses new challenges in every part of a database management system & the capability of spatial support in the physical layer is considered very important. This has led to the design of spatial access methods to enable the effective & efficient management of spatial objects.

R-trees have a simplicity of structure & together with their resemblance to the B-tree, allow developers to incorporate them easily into existing database management systems for the support of spatial query processing.

This book provides an extensive survey of the R-tree evolution, studying the applicability of the structure & its variations to efficient query processing, accurate proposed cost models, & implementation issues like concurrency control and parallelism. Written for database researchers, designers & programmers as well as graduate students, this comprehensive monograph will be a welcome addition to the field.

Since the early eighties IFIP/Sec has been an important rendezvous for Information Technology researchers and specialists involved in all aspects of IT security. The explosive growth of the Web is now faced with the formidable challenge of providing trusted information. IFIP/Sec'01 is the first of this decade (and century) and it will be devoted to "Trusted Information - the New Decade Challenge" This proceedings are divided in eleven parts related to the conference program. Session are dedicated to technologies: Security Protocols, Smart Card, Network Security and Intrusion Detection, Trusted Platforms. Others sessions are devoted to application like eSociety, TTP Management and PKI, Secure Workflow Environment, Secure Group Communications, and on the deployment of applications: Risk Management, Security Policies andTrusted System Design and Management. The year 2001 is a double anniversary. First, fifteen years ago, the first IFIP/Sec was held in France (IFIP/Sec'86, Monte-Carlo) and 2001 is also the anniversary of smart card technology. Smart cards emerged some twenty years ago as an innovation and have now become pervasive information devices used for highly distributed secure applications. These cards let millions of people carry a highly secure device that can represent them on a variety of networks. To conclude, we hope that the rich "menu" of conference papers for this IFIP/Sec conference will provide valuable insights and encourage specialists to pursue their work in trusted information.

In the past five years, the field of electrostatic discharge (ESD) control has under gone some notable changes. Industry standards have multiplied, though not all of these, in our view, are realistic and meaningful. Increasing importance has been ascribed to the Charged Device Model (CDM) versus the Human Body Model (HBM) as a cause of device damage and, presumably, premature (latent) failure. Packaging materials have significantly evolved. Air ionization techniques have improved, and usage has grown. Finally, and importantly, the government has ceased imposing MIL-STD-1686 on all new contracts, leaving companies on their own to formulate an ESD-control policy and write implementing documents. All these changes are dealt with in five new chapters and ten new reprinted papers added to this revised edition of ESD from A to Z. Also, the original chapters have been augmented with new material such as more troubleshooting examples in Chapter 8 and a 20-question multiple-choice test for certifying operators in Chapter 9. More than ever, the book seeks to provide advice, guidance, and practical ex amples, not just a jumble of facts and generalizations. For instance, the added tailored versions of the model specifications for ESD-safe handling and packaging are actually in use at medium-sized corporations and could serve as patterns for many readers."

Lattices are geometric objects that can be pictorially described as the set of intersection points of an infinite, regular n-dimensional grid. De spite their apparent simplicity, lattices hide a rich combinatorial struc ture, which has attracted the attention of great mathematicians over the last two centuries. Not surprisingly, lattices have found numerous ap plications in mathematics and computer science, ranging from number theory and Diophantine approximation, to combinatorial optimization and cryptography. The study of lattices, specifically from a computational point of view, was marked by two major breakthroughs: the development of the LLL lattice reduction algorithm by Lenstra, Lenstra and Lovasz in the early 80's, and Ajtai's discovery of a connection between the worst-case and average-case hardness of certain lattice problems in the late 90's. The LLL algorithm, despite the relatively poor quality of the solution it gives in the worst case, allowed to devise polynomial time solutions to many classical problems in computer science. These include, solving integer programs in a fixed number of variables, factoring polynomials over the rationals, breaking knapsack based cryptosystems, and finding solutions to many other Diophantine and cryptanalysis problems."

This doctoral thesis reports on an innovative data repository offering adaptive metadata management to maximise information sharing and comprehension in multidisciplinary and geographically distributed collaborations. It approaches metadata as a fluid, loosely structured and dynamical process rather than a fixed product, and describes the development of a novel data management platform based on a schemaless JSON data model, which represents the first fully JSON-based metadata repository designed for the biomedical sciences. Results obtained in various application scenarios (e.g. integrated biobanking, functional genomics and computational neuroscience) and corresponding performance tests are reported on in detail. Last but not least, the book offers a systematic overview of data platforms commonly used in the biomedical sciences, together with a fresh perspective on the role of and tools for data sharing and heterogeneous data integration in contemporary biomedical research.

In System-on-Chip Architectures and Implementations for Private-Key Data Encryption, new generic silicon architectures for the DES and Rijndael symmetric key encryption algorithms are presented. The generic architectures can be utilised to rapidly and effortlessly generate system-on-chip cores, which support numerous application requirements, most importantly, different modes of operation and encryption and decryption capabilities. In addition, efficient silicon SHA-1, SHA-2 and HMAC hash algorithm architectures are described. A single-chip Internet Protocol Security (IPSec) architecture is also presented that comprises a generic Rijndael design and a highly efficient HMAC-SHA-1 implementation.

In the opinion of the authors, highly efficient hardware implementations of cryptographic algorithms are provided in this book. However, these are not hard-fast solutions. The aim of the book is to provide an excellent guide to the design and development process involved in the translation from encryption algorithm to silicon chip implementation.

Advice involves recommendations on what to think; through thought, on what to choose; and via choices, on how to act. Advice is information that moves by communication, from advisors to the recipient of advice. Ivan Jureta offers a general way to analyze advice. The analysis applies regardless of what the advice is about and from whom it comes or to whom it needs to be given, and it concentrates on the production and consumption of advice independent of the field of application. It is made up of two intertwined parts, a conceptual analysis and an analysis of the rationale of advice. He premises that giving advice is a design problem and he treats advice as an artifact designed and used to influence decisions. What is unusual is the theoretical backdrop against which the author's discussions are set: ontology engineering, conceptual analysis, and artificial intelligence. While classical decision theory would be expected to play a key role, this is not the case here for one principal reason: the difficulty of having relevant numerical, quantitative estimates of probability and utility in most practical situations. Instead conceptual models and mathematical logic are the author's tools of choice. The book is primarily intended for graduate students and researchers of management science. They are offered a general method of analysis that applies to giving and receiving advice when the decision problems are not well structured, and when there is imprecise, unclear, incomplete, or conflicting qualitative information.

There is a broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Data pre-processing is an essential step in the knowledge discovery process for real-world applications. This book compiles contributions from many leading and active researchers in this growing field and paints a picture of the state-of-the-art techniques that can boost the capabilities of many existing data mining tools. The objective of this collection is to increase the awareness of the data mining community about research into feature extraction, construction and selection, which are currently conducted mainly in isolation. This book is part of an endeavor to produce a contemporary overview of modern solutions, to create synergy among these seemingly different branches, and to pave the way for developing meta-systems and novel approaches. The book can be used by researchers and graduate students in machine learning, data mining, and knowledge discovery, who wish to understand techniques of feature extraction, construction and selection for data pre-processing and to solve large size, real-world problems. The book can also serve as a reference work for those who are conducting research into feature extraction, construction and selection, and are ready to meet the exciting challenges ahead of us.

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.

This 2nd edition has been completely revised and updated, with additional new chapters. It presents state-of-the-art research in this area and focuses on key topics such as: visualization of semantic and structural information and metadata in the context of the emerging Semantic Web; Ontology-based Information Visualization and the use of graphically represented ontologies; Semantic Visualizations using Topic Maps and graph techniques; Recommender systems for filtering and recommending on the Semantic Web; SVG and X3D as new XML-based languages for 2D and 3D visualisations; methods used to construct and visualize high quality metadata and ontologies; and navigating and exploring XML documents using interactive multimedia interfaces. The design of visual interfaces for e-commerce and information retrieval is currently a challenging area of practical web development.

This book addresses the privacy issue of On-Line Analytic Processing (OLAP) systems. OLAP systems usually need to meet two conflicting goals. First, the sensitive data stored in underlying data warehouses must be kept secret. Second, analytical queries about the data must be allowed for decision support purposes. The main challenge is that sensitive data can be inferred from answers to seemingly innocent aggregations of the data. This volume reviews a series of methods that can precisely answer data cube-style OLAP, regarding sensitive data while provably preventing adversaries from inferring data.

Web Intelligence is a new direction for scientific research and development that explores the fundamental roles as well as practical impacts of artificial intelligence and advanced information technology for the next generation of Web-empowered systems, services, and environments. Web Intelligence is regarded as the key research field for the development of the Wisdom Web (including the Semantic Web). As the first book devoted to Web Intelligence, this coherently written multi-author monograph provides a thorough introduction and a systematic overview of this new field. It presents both the current state of research and development as well as application aspects. The book will be a valuable and lasting source of reference for researchers and developers interested in Web Intelligence. Students and developers will additionally appreciate the numerous illustrations and examples.

The term Web Intelligence is de?ned as a new line of scienti?c research and development, whichisusedtoexplorethefundamentalrolesandpractical- pactofArti?cialIntelligence togetherwithadvancedInformationTechnology and its e?ect on the future generations of Web-empowered products. These include systems, services, amongst other activities, all of which are carried out by the Web Intelligence Consortium (http: //wi-consortium.org/). Web Intelligence was ?rst coined in the late 1999's. From that time, many new algorithms, methods and techniques were developedand used extracting both knowledge and wisdom from the data originating from the Web. A number of initiatives have been adopted by the world communities in this areaofstudy.Theseincludebooks, conferenceseries, andjournals.Thislatest book encomposes a variaty of up to date state of the art approaches in Web Intelligence. Furthermore, it hightlights successful applications in this area of research within a practical context. The present book aims to introduce a selection of research applications in the area of Web Intelligence. We have selected a number of researchers around the world, all of which are experts in their respective research areas. Each chapter focuses on a speci?c topic in the ?eld of Web Intelligence. Furthermorethe bookconsistsofa numberofinnovativeproposalswhichwill contribute to the development of web science and technology for the lo- term future, rendering this collective work a valuable piece of knowledge. It was a great honour to have collaborated with this team of very talented experts. We also wish to express our grattitude to those who reviewed this book o?ering their constructive feedbacks.

In this fully updated second edition of the highly acclaimed Managing Gigabytes, authors Witten, Moffat, and Bell continue to provide unparalleled coverage of state-of-the-art techniques for compressing and indexing data. Whatever your field, if you work with large quantities of information, this book is essential reading--an authoritative theoretical resource and a practical guide to meeting the toughest storage and access challenges. It covers the latest developments in compression and indexing and their application on the Web and in digital libraries. It also details dozens of powerful techniques supported by mg, the authors' own system for compressing, storing, and retrieving text, images, and textual images. mg's source code is freely available on the Web.
* Up-to-date coverage of new text compression algorithms such as block sorting, approximate arithmetic coding, and fat Huffman coding
* New sections on content-based index compression and distributed querying, with 2 new data structures for fast indexing
* New coverage of image coding, including descriptions of de facto standards in use on the Web (GIF and PNG), information on CALIC, the new proposed JPEG Lossless standard, and JBIG2
* New information on the Internet and WWW, digital libraries, web search engines, and agent-based retrieval
* Accompanied by a public domain system called MG which is a fully worked-out operational example of the advanced techniques developed and explained in the book
* New appendix on an existing digital library system that uses the MG software

This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and the Semantic Web. The author shows how components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing methodology.

The massive quantity of data, information, and knowledge available in digital form on the web or within the organizational knowledge base requires a more effective way to control it. The Semantic Web and its growing complexity demands a resource for the understanding of proper tools for management.""Semantic Knowledge Management: An Ontology-Based Framework"" addresses the Semantic Web from an operative point of view using theoretical approaches, methodologies, and software applications as innovative solutions to true knowledge management. This advanced title provides readers with critical steps and tools for developing a semantic based knowledge management system.

Genetic Programming Theory and Practice explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The material contained in this contributed volume was developed from a workshop at the University of Michigan's Center for the Study of Complex Systems where an international group of genetic programming theorists and practitioners met to examine how GP theory informs practice and how GP practice impacts GP theory. The contributions cover the full spectrum of this relationship and are written by leading GP theorists from major universities, as well as active practitioners from leading industries and businesses. Chapters include such topics as John Koza's development of human-competitive electronic circuit designs; David Goldberg's application of "competent GA" methodology to GP; Jason Daida's discovery of a new set of factors underlying the dynamics of GP starting from applied research; and Stephen Freeland's essay on the lessons of biology for GP and the potential impact of GP on evolutionary theory.

This book focuses on three interdependent challenges related to managing transitions toward sustainable development, namely (a) mapping sustainability for global knowledge e-networking, (b) extending the value chain of knowledge and e-networking, and (c) engaging in explorations of new methods and venues for further developing knowledge and e-networking. While each of these challenges constitutes fundamentally different types of endeavors, they are highly interconnected. Jointly, they contribute to our expansion of knowledge and its applications in support of transitions toward sustainable development.

The central theme of this book revolves around ways of transcending barriers that impede the use of knowledge and knowledge networking in transitions toward sustainability. In order to transcend these barriers, we examine the potential contributions of innovations in information technologies as well as computation and representation of attendant complexities. A related theme addresses new ways of managing information and systematic observation for the purpose of enhancing the value of knowledge. Finally, this book shows applications of new methodologies and related findings that would contribute to our understanding of sustainablity issues that have not yet been explored. In many ways, this is a book of theory and of practice; and it is one of methods as well as policy and performance.

This book elaborates the science and engineering basis for energy-efficient driving in conventional and autonomous cars. After covering the physics of energy-efficient motion in conventional, hybrid, and electric powertrains, the book chiefly focuses on the energy-saving potential of connected and automated vehicles. It reveals how being connected to other vehicles and the infrastructure enables the anticipation of upcoming driving-relevant factors, e.g. hills, curves, slow traffic, state of traffic signals, and movements of nearby vehicles. In turn, automation allows vehicles to adjust their motion more precisely in anticipation of upcoming events, and to save energy. Lastly, the energy-efficient motion of connected and automated vehicles could have a harmonizing effect on mixed traffic, leading to additional energy savings for neighboring vehicles. Building on classical methods of powertrain modeling, optimization, and optimal control, the book further develops the theory of energy-efficient driving. In addition, it presents numerous theoretical and applied case studies that highlight the real-world implications of the theory developed. The book is chiefly intended for undergraduate and graduate engineering students and industry practitioners with a background in mechanical, electrical, or automotive engineering, computer science or robotics.

Everyday more than half of American adult internet users read or write email messages at least once. The prevalence of email has significantly impacted the working world, functioning as a great asset on many levels, yet at times, a costly liability. In an effort to improve various aspects of work-related communication, this work applies sophisticated machine learning techniques to a large body of email data. Several effective models are proposed that can aid with the prioritization of incoming messages, help with coordination of shared tasks, improve tracking of deadlines, and prevent disastrous information leaks. Carvalho presents many data-driven techniques that can positively impact work-related email communication and offers robust models that may be successfully applied to future machine learning tasks.

Knowledge in its pure state is tacit in nature-difficult to formalize and communicate-but can be converted into codified form and shared through both social interactions and the use of IT-based applications and systems. Even though there seems to be considerable synergies between the resulting huge data and the convertible knowledge, there is still a debate on how the increasing amount of data captured by corporations could improve decision making and foster innovation through effective knowledge-sharing practices. Big Data and Knowledge Sharing in Virtual Organizations provides innovative insights into the influence of big data analytics and artificial intelligence and the tools, methods, and techniques for knowledge-sharing processes in virtual organizations. The content within this publication examines cloud computing, machine learning, and knowledge sharing. It is designed for government officials and organizations, policymakers, academicians, researchers, technology developers, and students.

Despite the growing interest in Real-Time Database Systems, there is no single book that acts as a reference to academics, professionals, and practitioners who wish to understand the issues involved in the design and development of RTDBS. Real-Time Database Systems: Issues and Applications fulfills this need. This book presents the spectrum of issues that may arise in various real-time database applications, the available solutions and technologies that may be used to address these issues, and the open problems that need to be tackled in the future. With rapid advances in this area, several concepts have been proposed without a widely accepted consensus on their definitions and implications. To address this need, the first chapter is an introduction to the key RTDBS concepts and definitions, which is followed by a survey of the state of the art in RTDBS research and practice. The remainder of the book consists of four sections: models and paradigms, applications and benchmarks, scheduling and concurrency control, and experimental systems. The chapters in each section are contributed by experts in the respective areas. Real-Time Database Systems: Issues and Applications is primarily intended for practicing engineers and researchers working in the growing area of real-time database systems. For practitioners, the book will provide a much needed bridge for technology transfer and continued education. For researchers, this book will provide a comprehensive reference for well-established results. This book can also be used in a senior or graduate level course on real-time systems, real-time database systems, and database systems or closely related courses.

Computer access is the only way to retrieve up-to-date sequences and this book shows researchers puzzled by the maze of URLs, sites, and searches how to use internet technology to find and analyze genetic data. The book describes the different types of databases, how to use a specific database to find a sequence that you need, and how to analyze the data to compare it with your own work.
The content also covers sequence phenotype, mutation, and genetic linkage databases; simple repetitive DNA sequences; gene feature identification; and prediction of structure and function of proteins from sequence information. This book will be invaluable to those starting a career in life sciences research as well as to established researchers wishing to make full use of available resources.
Key Features
* Describes a wide range of databases: DNA, RNA, protein, pathways, and gene expression
* Enables readers to access the information they need from databases on the web
* Includes a directory of URLs for easy reference
* Invaluable for those starting a career in life sciences research and also for established researchers wishing to make full use of available resources.

This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain a review of recent cross-disciplinary approaches in cloud environments and multi-agent systems, and important formulations of data intensive problems in distributed computational environments together with the presentation of new agent-based tools to handle those problems and Big Data in general. This volume can serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary work in the areas of data intensive computing and Big Data systems using emergent large-scale distributed computing paradigms. It will also allow newcomers to grasp key concepts and potential solutions on advanced topics of theory, models, technologies, system architectures and implementation of applications in Multi-Agent systems and data intensive computing.

Clustering is an important unsupervised classification technique where data points are grouped such that points that are similar in some sense belong to the same cluster. Cluster analysis is a complex problem as a variety of similarity and dissimilarity measures exist in the literature. This is the first book focused on clustering with a particular emphasis on symmetry-based measures of similarity and metaheuristic approaches. The aim is to find a suitable grouping of the input data set so that some criteria are optimized, and using this the authors frame the clustering problem as an optimization one where the objectives to be optimized may represent different characteristics such as compactness, symmetrical compactness, separation between clusters, or connectivity within a cluster. They explain the techniques in detail and outline many detailed applications in data mining, remote sensing and brain imaging, gene expression data analysis, and face detection. The book will be useful to graduate students and researchers in computer science, electrical engineering, system science, and information technology, both as a text and as a reference book. It will also be useful to researchers and practitioners in industry working on pattern recognition, data mining, soft computing, metaheuristics, bioinformatics, remote sensing, and brain imaging.