] > Stream Data Management Nauman Chaudhry, Kevin Shaw and Mahdi Abdelguerfi Springer 2005 ISBN 0-387-24393-3 Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management. Fundamentals of Mobile and Pervasive Computing Frank Adelstein, Sandeep Gupta, Golden G. Richard III, and Loren Schwiebert McGraw-Hill 2004 ISBN 0-071-41237-9 Mobile computing is characterized and driven by portable, lightweight hardware, wireless communication, and innovations in application and system software. Pervasive computing uses small, battery-powered, wireless computing and sensing devices embedded in our environment to provide contextual information to new types of applications. The trends driving the associated technologies to get smaller, more powerful, and more portable are likely to continue for the foreseeable future and this volume is the first to provide a balanced treatment of current technology, future vision, and fundamental issues in mobile and pervasive computing. Conceptually, the book is organized into four parts: Part One, which comprises the first four chapters, covers issues related to mobile and pervasive computing applications. This includes not only disseminating the data and caching it, but also routing and location management to determine where to send the data in the first place. Context aware computing is the final chapter in Part One. Part Two, which comprises chapters five to seven, focuses on middleware, the layer that bridges mobile computing applications to the underlying systems that support this mobility. Middleware topics include agents and service discovery protocols. Part Three, which comprises chapters eight to eleven, covers an important enabling networking technology for pervasive computing: ad-hoc and wireless sensor networks. Ad-hoc networks form when needed, on-the-fly, without central management or infrastructure. Wireless sensors record some type of data, such as temperature and humidity, and form an ad-hoc network to efficiently disseminate these readings. Part Three discusses the applications, problems, approaches, and protocols for wireless sensor networking. Part Four, which comprises chapters twelve to seventeen, covers security in wireless environments. After describing common security problems, these chapters present how security is handled in personal, local, metropolitan, and wide area networks, as well as current research work and future trends. Machine Learning and Statistical Modeling Approaches to Image Retrieval Yixin Chen, Jia Li, and James Z. Wang Kluwer Academic Press 2004 ISBN 1-4020-8034-4 In the early 1990s, the establishment of the Internet brought forth a revolutionary viewpoint of information storage, distribution, and processing: the World Wide Web is becoming an enormous and expanding distributed digital library. Along with the development of the Web, image indexing and retrieval have grown into research areas sharing a vision of intelligent agents: computer programs capable of making "meaningful interpretations" of images based on automatically extracted imagery features. Far beyond Web searching, image indexing and retrieval can potentially be applied to many other areas, including biomedicine, space science, biometric identification, digital libraries, the military, education, commerce, culture, and entertainment. Although much research effort has been put into image indexing and retrieval, we are still very far from having computer programs with even a modest level of human intelligence. Decades of research have shown that designing a generic computer algorithm for object recognition, scene understanding, and automatically translating the content of images to linguistic terms is a highly challenging task. However, a series of successes have been achieved in recognizing a relatively small set of objects or concepts within specific domains, based on learning and statistical modeling techniques. This motivates many researchers to use recently-developed machine learning and statistical modeling methods for image indexing and retrieval. Some results are quite promising. The topics of this book reflect our personal biases and experiences of machine learning and statistical modeling based image indexing and retrieval. A significant portion of the book is built upon material from articles we have written, our unpublished reports, and talks we have presented at several conferences and workshops. In particular, the book presents five different techniques of integrating machine learning and statistical modeling into image indexing and retrieval systems: an similarity measure defined over region-based image features; an image clustering and retrieval scheme based on dynamic graph partitioning; an image categorization method based on the information of regions contained in the images; modeling semantic concepts of photographic images by stochastic processes; and the characterization of ancient paintings using a mixture of stochastic models. The first two techniques are within the scope of image retrieval. The remaining three techniques are closely related to automatic linguistic image indexing. The book will be of value to faculty seeking a textbook that covers some of the most recent advances in the areas of automated image indexing, retrieval, and annotation. Researchers and graduate students interested in exploring state-of-the-art research in the related areas will find in-depth treatments of the covered topics. Mining Spatio-Temporal Information Systems Roy Ladner, Kevin Shaw, Mahdi Abdelguerfi Kluwer Academic Publishers 2001 ISBN 1-4020-7170-1 We are facing a rapidly growing capability to collect more and more data regarding our environment. With that, we must have the ability to extract more insightful knowledge about the environmental processes at work on the earth. Spatio-Temporal Information Systems (STIS) will especially prove beneficial in producing useful knowledge about changes in our world from these ever burgeoning collections of environment data. STIS provide the ability to store, analyze and represent the dynamic properties of the environment, that is, geographic information in space and time. An STIS, for example, can produce a weather map, but more importantly, it can present a user with information in map or report form indicating how precipitation progresses in space over time to affect a watershed. Other uses include forestry and even electrical systems management. Forestry experts using an STIS are able to examine the rates of movements of forest fires, how they evolve over time, and their impact on forest growth over long periods of time. A large electrical network system manager uses an STIS to track the failures and repairs of electrical transformers. Use of an STIS in this case allows the reconstruction of the status of the network at any given past time. Mining Spatio-Temporal Information Systems, an edited volume is composed of chapters from leading experts in the field of Spatial-Temporal Information Systems and addresses the many issues in support of modeling, creation, querying, visualizing and mining. Mining Spatio-Temporal Information Systems is intended to bring together a coherent body of recent knowledge relating to STIS data modeling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the latest techniques for the practical design of STIS, essential for complex query processing. Mining Spatio-Temporal Information Systems is structured to meet the needs of practitioners and researchers in industry and graduate-level students in Computer Science. Service and Device Discovery Protocols and Programming Dr. Golden G. Richard III McGraw-Hill Professional Publishing 2002 ISBN 0071379592 Service and Device Discovery is a complete survey of the state-of-the-art in an emerging field. Client/server architectures may not be new, but the world has changed around them. Increasingly complex networked environments and the proliferation of mobile devices create many instances where highly dynamic client/service behavior is the norm and not the exception. Service discovery protocols enable "plug and play" architectures, where services may be introduced into a network and removed at will, without configuration hassles. In addition, service discovery is an important step toward eliminating manually installed drivers, relying instead on standard interfaces to put devices in touch. This book covers four key protocols - Jini, SLP (Service Location Protocol), UPnP (Universal Plug and Play) and Bluetooth SDP. An Introduction to Programming and Object Oriented Design, Using Java 1.5 (second edition) Jaime Niņo and Frederick A. Hosch John Wiley and Sons, Inc. 2005 ISBN 0-471-48167-X Nino and Hosch's second edition of this innovative text teaches your students how to design applications with objects from the very beginning. They'll first experiment with simple software systems to identify objects, their properties, and their behavior; they are then introduced to the life-cycle of design-specify-implement-test for classes. Object testing is introduced early and emphasized in the rest of the book. Use of interfaces and inheritance is presented early as tools to model with abstraction. Other topics included are lists, arrays, sorting and searching, exceptions, recursion and graphical interfaces. Along the way, they'll gain strong problem-solving and programming skills that they'll be able to use as they progress to more advanced courses. Also, structured lab exercises familiarize students with objects and other concepts such as class and state from the start. Completely revised and updated, the second edition features the DrJava programming environment for development and interactive exercises, places further emphasis on testing, and includes new Java 5.0 features such as boxed/unboxed data, enumeration classes, and generic classes and methods. The class java.util.Scanner is used for simple input, and a chapter on stream i/o has been added. 3D Synthetic Environment Reconstruction Mahdi Abdelguerfi Kluwer Academic Publishers 2001 ISBN 0-7923-7321-9 3D Synthetic Environment Reconstruction contains seven invited chapters from leading experts in the field, bringing together a coherent body of recent knowledge relating 3D geospatial data collection, design issues, and techniques used in synthetic environments design, implementation and interoperability. In particular, this book describes new techniques for the generation of Synthetic Environments with increased resolution and rich attribution, both essential for accurate modeling and simulation. This book also deals with interoperability of models and simulations, which is necessary for facilitating the reuse of modeling and simulation components. 3D Synthetic Environment Reconstruction is an excellent reference for researchers and practitioners in the field. Parallel Database Techniques Mahdi Abdelguerfi and Kam-Fai Wong IEEE Computer Society Press 1998 ISBN 0-8186-8398-8 This book reviews the latest techniques in parallel relational databases. Emphasizing techniques for achieving high performance in parallel database systems, the text is structured according to the overall architecture of a parallel database system. It presents state of the art methods that can be adopted in the design of parallel database software and hardware execution environments. These techniques lead to high-performance parallel database implementation. Introduction to Software Design and Development with Ada David Rudd West Publishing 1995 ISBN 0-314-02829-3 An introduction to problem-solving concepts, and the design, development, writing, and testing of software using the Ada programming language. Emerging Trends in Database and Knowledge-Base Machines Mahdi Abdelguerfi and Simon Lavington IEEE Computer Society Press 1995 ISBN 0-8186-6552-1 This book, containing 13 original papers, surveys the latest trends in performance enhancing architectures for smart information systems. The machines featured are designed to support information systems ranging from relational databases to semantic networks and other artificial intelligence paradigms. Many of the illustrated projects contain architectural ideas that support higher-level requirements and are based on semantics-free hardware designs. Data Types and Data Structures Johannes J. Martin Prentice-Hall International 1986 ISBN 0-13-195983-2 Abstract data types and their implementation.