Relational databases hold data, right? They indeed do, but to think of a database as nothing more than a container for data is to miss out on the profound power that underlies relational technology. Use the expressive power of mathematics to precisely specify designs and business rules. Communicate effectively about design using the universal language of mathematics. Develop and write complex SQL statements with confidence. Avoid pitfalls and problems from common relational bugaboos such as null values and duplicate rows. The math that you learn in this book will put you above the level of understanding of most database professionals today. You'll better understand the technology and be able to apply it more effectively. You'll avoid data anomalies like redundancy and inconsistency. Understanding what's in this book will take your mastery of relational technology to heights you may not have thought possible.

This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures. This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.

The area of similarity searching is a very hot topic for both research and c- mercial applications. Current data processing applications use data with c- siderably less structure and much less precise queries than traditional database systems. Examples are multimedia data like images or videos that offer query by example search, product catalogs that provide users with preference based search, scientific data records from observations or experimental analyses such as biochemical and medical data, or XML documents that come from hetero- neous data sources on the Web or in intranets and thus does not exhibit a global schema. Such data can neither be ordered in a canonical manner nor meani- fully searched by precise database queries that would return exact matches. This novel situation is what has given rise to similarity searching, also - ferred to as content based or similarity retrieval. The most general approach to similarity search, still allowing construction of index structures, is modeled in metric space. In this book. Prof. Zezula and his co authors provide the first monograph on this topic, describing its theoretical background as well as the practical search tools of this innovative technology.

E-commerce systems involve a complex interaction between Web Based Internet related software, application software and databases. It is clear that the success of e-commerce systems is going to be dependent not only on the technology of these systems but also on the quality of the underlying databases and supporting processes. Whilst databases have achieved considerable success in the wider marketplace, the main research effort has been on tools and techniques for high volume but based on relatively simplistic record management. The modern advanced e-commerce systems require a paradigm shift to allow the meaningful representation and manipulation of complex business information on the Web and Internet. This requires the development of new methodologies, environments and tools to allow one to easily understand the underlying structure to facilitate access, manipulation and modification of such information. An essential characteristic to gain understanding and interoperability is a clearly defined semantics for e-commerce systems and databases.
The focus of this volume is therefore on those issues of e-commerce systems that involve the semantics of the information represented, stored and manipulated by these systems. This not only includes methodologies for application domain modeling, formal representations of e-commerce aspects of knowledge, the role of semantics, Internet based transmission and display of data, etc. but also issues in user interfacing and process modeling, architectures that better enable integrity, consistency, interoperation reuse of components, or reports on prototypes illustrating new aspects of such systems from a semantically relevant viewpoint.
Semantic Issues in e-Commerce Systems comprises the proceedings of the Ninth Working Conference on Database Semantics, which was sponsored by the International Federation for Information Processing (IFIP) and held in Hong Kong in April 2001.
This volume will be essential for researchers and practitioners working in the areas of database management, information retrieval and data mining, and user interfaces, as applied to e-commerce.

Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.

Just like the industrial society of the last century depended on natural resources, today s society depends on information and its exchange.

Semantic Web technologies address the problem of information complexity by providing advanced support for representing and processing distributed information, while peer-to-peer technologies address issues of system complexity by allowing flexible and decentralized information storage and processing. Systems that are based on Semantic Web and peer-to-peer technologies promise to combine the advantages of the two mechanisms. A peer-to-peer style architecture for the Semantic Web will avoid both physical and semantic bottlenecks that limit information and knowledge exchange.

Staab and Stuckenschmidt structured the selected contributions into four parts: Part I, "Data Storage and Access," prepares the semantic foundation, i.e. data modelling and querying in a flexible and yet scalable manner. These foundations allow for dealing with the organization of information at the individual peers. Part II, "Querying the Network," considers the routing of queries, as well as continuous queries and personalized queries under the conditions of the permanently changing topological structure of a peer-to-peer network. Part III, "Semantic Integration," deals with the mapping of heterogeneous data representations. Finally Part IV, "Methodology and Systems," reports experiences from case studies and sample applications.

The overall result is a state-of-the-art description of the potential of Semantic Web and peer-to-peer technologies for information sharing and knowledge management when applied jointly. It serves researchers in academia and industry as an excellent and lasting reference and source of inspiration.

Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. The thirteen chapters cover: Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Graphs, Strings, Discrete Fourier Transform, Parallel Computation.

Key features:

* Complicated concepts are expressed clearly in a single page with minimal notation and without the "clutter" of the syntax of a particular programming language; algorithms are presented with self-explanatory "pseudo-code."

* Chapters 1-4 focus on elementary concepts, the exposition unfolding at a slower pace. Sample exercises with solutions are provided. Sections that may be skipped for an introductory course are starred. Requires only some basic mathematics background and some computer programming experience.

* Chapters 5-13 progress at a faster pace. The material is suitable for undergraduates or first-year graduates who need only review Chapters 1-4.

* Chapters 1-4. This book may be used for a one-semester introductory course (based on Chapters 1-4 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a one-semester advanced course that starts at Chapter 5. A yearlong course may be based on the entire book.

* Sorting, often perceived as rather technical, is not treated as a separate chapter, but is used in many examples (including bubble sort, merge sort, tree sort, heap sort, quick sort, and several parallel algorithms). Also, lower bounds on sorting by comparisons are included with thepresentation of heaps in the context of lower bounds for comparison-based structures.

* Chapter 13 on parallel models of computation is something of a mini-book itself, and a good way to end a course. Although it is not clear what parallel architectures will prevail in the future, the idea is to further teach fundamental concepts in the design of algorithms by exploring classic models of parallel computation, including the PRAM, generic PRAM simulation, HC/CCC/Butterfly, the mesh, and parallel hardware area-time tradeoffs (with many examples).

Apart from classroom use, this book serves as a good reference on the subject of data structures and algorithms. Its page-at-a-time format makes it easy to review material that the reader has studied in the past.

Data Mining introduces in clear and simple ways how to use existing data mining methods to obtain effective solutions for a variety of management and engineering design problems. Data Mining is organised into two parts: the first provides a focused introduction to data mining and the second goes into greater depth on subjects such as customer analysis. It covers almost all managerial activities of a company, including: * supply chain design, * product development, * manufacturing system design, * product quality control, and * preservation of privacy. Incorporating recent developments of data mining that have made it possible to deal with management and engineering design problems with greater efficiency and efficacy, Data Mining presents a number of state-of-the-art topics. It will be an informative source of information for researchers, but will also be a useful reference work for industrial and managerial practitioners.

Responsive Computer Systems: Steps Towards Fault-Tolerant Real-Time Systems provides an extensive treatment of the most important issues in the design of modern Responsive Computer Systems. It lays the groundwork for a more comprehensive model that allows critical design issues to be treated in ways that more traditional disciplines of computer research have inhibited. It breaks important ground in the development of a fruitful, modern perspective on computer systems as they are currently developing and as they may be expected to develop over the next decade. Audience: An interesting and important road map to some of the most important emerging issues in computing, suitable as a secondary text for graduate level courses on responsive computer systems and as a reference for industrial practitioners.

Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics is written to introduce basic concepts, advanced research techniques, and practical solutions of data warehousing and data mining for hosting large data sets and EDA. This book is unique because it is one of the few in the forefront that attempts to bridge statistics and information theory through a concept of patterns.
Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.

This book contains the papers presented and discussed at the conference that was held in May/June 1997, in Philadelphia, Pennsylvania, USA, and that was sponsored by Working Group 8.2 of the International Federation for Information Processing. IFIP established 8.2 as a group concerned with the interaction of information systems and the organization. Information Systems and Qualitative Research is essential reading for professionals and students working in information systems in a business environment, such as systems analysts, developers and designers, data administrators, and senior executives in all business areas that use information technology, as well as consultants in the fields of information systems, management, and quality management.

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. 'Biomedical Big Data' refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.

This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The aim of the book as to provide an overview of the state-of- the art in this novel and - citing research area. Of special interest are the recent methods for constraint-based mining of global models for prediction and clustering, the uni?cation of pattern mining approaches through constraint programming, the clari?cation of the re- tionship between mining local patterns and global models, and the proposed in- grative frameworks and approaches for inducive databases. On the application side, applications to practically relevant problems from bioinformatics are presented. Inductive databases (IDBs) represent a database view on data mining and kno- edge discovery. IDBs contain not only data, but also generalizations (patterns and models) valid in the data. In an IDB, ordinary queries can be used to access and - nipulate data, while inductive queries can be used to generate (mine), manipulate, and apply patterns and models. In the IDB framework, patterns and models become "?rst-class citizens" and KDD becomes an extended querying process in which both the data and the patterns/models that hold in the data are queried.

Researchers have come to rely on this thesaurus to locate precise terms from the controlled vocabulary used to index the ERIC database. This, the first print edition in more than 5 years, contains a total of 10,773 vocabulary terms with 206 descriptors and 210 use references that are new to this edition. A popular and widely used reference tool for sets of education-related terms established and updated by ERIC lexicographers to assist searchers in defining, narrowing, and broadening their search strategies. The Introduction to the "Thesaurus" contains helpful information about ERIC indexing rules, deleted and invalid descriptors, and useful parts of the descriptor entry, such as the date the term was added and the number of times it has been used.

This monograph on Security in Computing Systems: Challenges, Approaches and Solutions aims at introducing, surveying and assessing the fundamentals of se- rity with respect to computing. Here, "computing" refers to all activities which individuals or groups directly or indirectly perform by means of computing s- tems, i. e. , by means of computers and networks of them built on telecommuni- tion. We all are such individuals, whether enthusiastic or just bowed to the inevitable. So, as part of the ''information society'', we are challenged to maintain our values, to pursue our goals and to enforce our interests, by consciously desi- ing a ''global information infrastructure'' on a large scale as well as by approp- ately configuring our personal computers on a small scale. As a result, we hope to achieve secure computing: Roughly speaking, computer-assisted activities of in- viduals and computer-mediated cooperation between individuals should happen as required by each party involved, and nothing else which might be harmful to any party should occur. The notion of security circumscribes many aspects, ranging from human qua- ties to technical enforcement. First of all, in considering the explicit security requirements of users, administrators and other persons concerned, we hope that usually all persons will follow the stated rules, but we also have to face the pos- bility that some persons might deviate from the wanted behavior, whether ac- dently or maliciously.

Access control is a method of allowing and disallowing certain operations on a computer or network system. This book details access control mechanisms that are emerging with the latest Internet programming technologies. It provides a thorough introduction to the foundations of programming systems security as well as the theory behind access control models. The author explores all models employed and describes how they work.

Real-Time Systems in Mechatronic Applications brings together in one place important contributions and up-to-date research results in this fast moving area. Real-Time Systems in Mechatronic Applications serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

With the explosive growth of Multimedia Applications, the ability to index/retrieve multimedia objects in an efficient way is challenging to both researchers and practitioners. A major data type stored and managed by these applications is the representation of two dimensional (2D) objects. Objects contain many features (e.g., color, texture, and shape) that have meaningful semantics. From those features, shape is an important feature that conforms with the way human beings interpret and interact with the real world objects. The shape representation of objects can therefore be used for their indexing, retrieval and as similarity measure. The object databases can be queried and searched for different purposes. For example, a CAD application for manufacturing industrial parts might intend to reduce the cost of building new industrial parts by searching for reusable existing parts in a database. Regarding an alternative trademark registry application, one might need to ensure that a new registered trademark is sufficiently distinctive from the existing marks by searching the database. Therefore, one of the important functionalities required by all these applications is the capability to find objects in a database that match a given object.
Traditional books on computer vision and informational retrieval are too general, and they do not provide advanced or specific information regarding shape analysis and recognition. Shape Analysis and Retrieval of Multimedia Objects provides a comprehensive survey of the most advanced and powerful shape retrieval techniques used in practice today. In addition, this monograph addresses key methodological issues for evaluation of the shape retrieval methods.
Shape Analysis and Retrieval of Multimedia Objects is designed to meet the needs of practitioners and researchers in industry, and graduate-level students in Computer Science.

This book is the first work that systematically describes the procedure of data mining and knowledge discovery on Bioinformatics databases by using the state-of-the-art hierarchical feature selection algorithms. The novelties of this book are three-fold. To begin with, this book discusses the hierarchical feature selection in depth, which is generally a novel research area in Data Mining/Machine Learning. Seven different state-of-the-art hierarchical feature selection algorithms are discussed and evaluated by working with four types of interpretable classification algorithms (i.e. three types of Bayesian network classification algorithms and the k-nearest neighbours classification algorithm). Moreover, this book discusses the application of those hierarchical feature selection algorithms on the well-known Gene Ontology database, where the entries (terms) are hierarchically structured. Gene Ontology database that unifies the representations of gene and gene products annotation provides the resource for mining valuable knowledge about certain biological research topics, such as the Biology of Ageing. Furthermore, this book discusses the mined biological patterns by the hierarchical feature selection algorithms relevant to the ageing-associated genes. Those patterns reveal the potential ageing-associated factors that inspire future research directions for the Biology of Ageing research.

This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16-18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it's in sight, it isn't quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all "small data" issues that soon create "big data" troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.

RSA is a public-key cryptographic system, and is the most famous and widely-used cryptographic system in today's digital world. Cryptanalytic Attacks on RSA, a professional book, covers almost all known cryptanalytic attacks and defenses of the RSA cryptographic system and its variants. Since RSA depends heavily on computational complexity theory and number theory, background information on complexity theory and number theory is presented first, followed by an account of the RSA cryptographic system and its variants.

This book is also suitable as a secondary text for advanced-level students in computer science and mathematics.

The book provides a comprehensive investigation of the performance and problems of the TCP/IP protocol stack, when data is transmitted over GSM, GPRS and UMTS. It gives an introduction to the protocols used for Internet access today, and also the Wireless Application Protocol (WAP). The basics of GSM, GPRS and UMTS are given, which are necessary for understanding the main topic, TCP performance over GSM, GPRS and UMTS. We describe at length the problems that TCP has when operating over a mobile radio link, and what has been proposed to remedy these problems. We derive the optimum TCP packet length for maximum data throughput on wireless networks, analytically and by simulation. Results on the throughput and various other parameters of TCP over mobile networks are given. This book gives valuable advice to network operators and application programmers to maximize data throughput, and which protocols, transmission modes, and coding schemes to use and which to avoid.

On various examples ranging from geosciences to environmental sciences, this book explains how to generate an adequate description of uncertainty, how to justify semiheuristic algorithms for processing uncertainty, and how to make these algorithms more computationally efficient. It explains in what sense the existing approach to uncertainty as a combination of random and systematic components is only an approximation, presents a more adequate three-component model with an additional periodic error component, and explains how uncertainty propagation techniques can be extended to this model. The book provides a justification for a practically efficient heuristic technique (based on fuzzy decision-making). It explains how the computational complexity of uncertainty processing can be reduced. The book also shows how to take into account that in real life, the information about uncertainty is often only partially known, and, on several practical examples, explains how to extract the missing information about uncertainty from the available data.

Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video Video understanding deals with understanding of video understanding. sequences, e.g., recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvi ous overlap with computer vision. The main goal of computer graphics is to generate and animate realistic looking images, and videos. Re searchers in computer graphics are increasingly employing techniques from computer vision to generate the synthetic imagery. A good exam pIe of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is derived from real images using computer vision techniques. Here the shift is from synthesis to analy sis followed by synthesis. Image processing has always overlapped with computer vision because they both inherently work directly with images."

Document Computing: Technologies for Managing Electronic Document Collections discusses the important aspects of document computing and recommends technologies and techniques for document management, with an emphasis on the processes that are appropriate when computers are used to create, access, and publish documents. This book includes descriptions of the nature of documents, their components and structure, and how they can be represented; examines how documents are used and controlled; explores the issues and factors affecting design and implementation of a document management strategy; and gives a detailed case study. The analysis and recommendations are grounded in the findings of the latest research. Document Computing: Technologies for Managing Electronic Document Collections brings together concepts, research, and practice from diverse areas including document computing, information retrieval, librarianship, records management, and business process re-engineering. It will be of value to anyone working in these areas, whether as a researcher, a developer, or a user. Document Computing: Technologies for Managing Electronic Document Collections can be used for graduate classes in document computing and related fields, by developers and integrators of document management systems and document management applications, and by anyone wishing to understand the processes of document management.