This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data as more and more types of crowd sourcing spatial data are used in GIScience, such as movement trajectories, cellular phone calls, and social networks. In order to effectively manage these massive data collections, new methods and algorithms are called for. The book highlights state-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for graduate students, researchers and practitioners in the field of GIScience.

This book provides an overview of current Intellectual Property (IP) based System-on-Chip (SoC) design methodology and highlights how security of IP can be compromised at various stages in the overall SoC design-fabrication-deployment cycle. Readers will gain a comprehensive understanding of the security vulnerabilities of different types of IPs. This book would enable readers to overcome these vulnerabilities through an efficient combination of proactive countermeasures and design-for-security solutions, as well as a wide variety of IP security and trust assessment and validation techniques. This book serves as a single-source of reference for system designers and practitioners for designing secure, reliable and trustworthy SoCs.

This book constitutes the refereed proceedings of the 27th IFIP TC 11 International Information Security Conference, SEC 2012, held in Heraklion, Crete, Greece, in June 2012. The 42 revised full papers presented together with 11 short papers were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on attacks and malicious code, security architectures, system security, access control, database security, privacy attitudes and properties, social networks and social engineering, applied cryptography, anonymity and trust, usable security, security and trust models, security economics, and authentication and delegation.

Multiprocessing: Trade-Offs in Computation and Communication presents an in-depth analysis of several commonly observed regular and irregular computations for multiprocessor systems. This book includes techniques which enable researchers and application developers to quantitatively determine the effects of algorithm data dependencies on execution time, on communication requirements, on processor utilization and on the speedups possible. Starting with simple, two-dimensional, diamond-shaped directed acyclic graphs, the analysis is extended to more complex and higher dimensional directed acyclic graphs. The analysis allows for the quantification of the computation and communication costs and their interdependencies. The practical significance of these results on the performance of various data distribution schemes is clearly explained. Using these results, the performance of the parallel computations are formulated in an architecture independent fashion. These formulations allow for the parameterization of the architecture specitific entities such as the computation and communication rates. This type of parameterized performance analysis can be used at compile time or at run-time so as to achieve the most optimal distribution of the computations. The material in Multiprocessing: Trade-Offs in Computation and Communication connects theory with practice, so that the inherent performance limitations in many computations can be understood, and practical methods can be devised that would assist in the development of software for scalable high performance systems.

This book reports on cutting-edge technologies that have been fostering sustainable development in a variety of fields, including built and natural environments, structures, energy, advanced mechanical technologies as well as electronics and communication technologies. It reports on the applications of Geographic Information Systems (GIS), Internet-of-Things, predictive maintenance, as well as modeling and control techniques to reduce the environmental impacts of buildings, enhance their environmental contribution and positively impact the social equity. The different chapters, selected on the basis of their timeliness and relevance for an audience of engineers and professionals, describe the major trends in the field of sustainable engineering research, providing them with a snapshot of current issues together with important technical information for their daily work, as well as an interesting source of new ideas for their future research. The works included in this book were selected among the contributions to the BUE ACE1, the first event, held in Cairo, Egypt, on 8-9 November 2016, of a series of Annual Conferences & Exhibitions (ACE) organized by the British University in Egypt (BUE).

Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.

Biometrics such as fingerprint, face, gait, iris, voice and signature, recognizes one's identity using his/her physiological or behavioral characteristics. Among these biometric signs, fingerprint has been researched the longest period of time, and shows the most promising future in real-world applications. However, because of the complex distortions among the different impressions of the same finger, fingerprint recognition is still a challenging problem.

Computational Algorithms for Fingerprint Recognition presents an entire range of novel computational algorithms for fingerprint recognition. These include feature extraction, indexing, matching, classification, and performance prediction/validation methods, which have been compared with state-of-art algorithms and found to be effective and efficient on real-world data. All the algorithms have been evaluated on NIST-4 database from National Institute of Standards and Technology (NIST). Specific algorithms addressed include:
-Learned template based minutiae extraction algorithm,
-Triplets of minutiae based fingerprint indexing algorithm,
-Genetic algorithm based fingerprint matching algorithm,
-Genetic programming based feature learning algorithm for fingerprint classification,
-Comparison of classification and indexing based approaches for identification,
-Fundamental fingerprint matching performance prediction analysis and its validation.

Computational Algorithms for Fingerprint Recognition 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.

As a new generation of technologies, frameworks, concepts and practices for information systems emerge, practitioners, academicians, and researchers are in need of a source where they can go to educate themselves on the latest innovations in this area. ""Semantic Web Information Systems: State-of-the-Art Applications"" establishes value-added knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government. ""Semantic Web Information Systems: State-of-the-Art Applications"" covers new semantic Web-enabled tools for the citizen, learner, organization, and business. Real-world applications toward the development of the knowledge society and semantic Web issues, challenges and implications in each of the IS research streams are included as viable sources for this challenging subject.

"Incomplete Information System and Rough Set Theory: Models and Attribute Reductions" covers theoretical study of generalizations of rough set model in various incomplete information systems. It discusses not only the regular attributes but also the criteria in the incomplete information systems. Based on different types of rough set models, the book presents the practical approaches to compute several reducts in terms of these models. The book is intended for researchers and postgraduate students in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, and granular computing.

Dr. Xibei Yang is a lecturer at the School of Computer Science and Engineering, Jiangsu University of Science and Technology, China; Jingyu Yang is a professor at the School of Computer Science, Nanjing University of Science and Technology, China.

"Date on Database: Writings 2000 2006" captures some of the freshest thinking from widely known and respected relational database pioneer C. J. Date . Known for his tenacious defense of relational theory in its purest form, Date tackles many topics that are important to database professionals, including the difference between model and implementation, data integrity, data redundancy, deviations in SQL from the relational model, and much more.

Date clearly and patiently explains where many of todays products and practices go wrong, and illustrates some of the trouble you can get into if you don't carefully think through your use of current database technology. In almost every field of endeavor, the writings of the founders and early leaders have had a profound effect. And now is your chance to read Date while his material is fresh and the field is still young. You'll want to read this book because it: Provides C. J. Date's freshest thinking on relational theory versus current products in the field Features a tribute to E. F. Codd, founder of the relational database field Clearly explains how the unwary practitioner can avoid problems with current relational database technology Offers novel insights into classic issues like redundancy and database design

Cellular Automata Transforms describes a new approach to using the dynamical system, popularly known as cellular automata (CA), as a tool for conducting transforms on data. Cellular automata have generated a great deal of interest since the early 1960s when John Conway created the Game of Life'. This book takes a more serious look at CA by describing methods by which information building blocks, called basis functions (or bases), can be generated from the evolving states. These information blocks can then be used to construct any data. A typical dynamical system such as CA tend to involve an infinite possibilities of rules that define the inherent elements, neighborhood size, shape, number of states, and modes of association, etc. To be able to build these building blocks an elegant method had to be developed to address a large subset of these rules. A new formula, which allows for the definition a large subset of possible rules, is described in the book. The robustness of this formula allows searching of the CA rule space in order to develop applications for multimedia compression, data encryption and process modeling. Cellular Automata Transforms is divided into two parts. In Part I the fundamentals of cellular automata, including the history and traditional applications are outlined. The challenges faced in using CA to solve practical problems are described. The basic theory behind Cellular Automata Transforms (CAT) is developed in this part of the book. Techniques by which the evolving states of a cellular automaton can be converted into information building blocks are taught. The methods (including fast convolutions) by which forward and inverse transforms of any data can beachieved are also presented. Part II contains a description of applications of CAT. Chapter 4 describes digital image compression, audio compression and synthetic audio generation, three approaches for compressing video data. Chapter 5 contains both symmetric and public-key implementation of CAT encryption. Possible methods of attack are also outlined. Chapter 6 looks at process modeling by solving differential and integral equations. Examples are drawn from physics and fluid dynamics.

This unique text/reference describes an exciting and novel approach to supercomputing in the DataFlow paradigm. The major advantages and applications of this approach are clearly described, and a detailed explanation of the programming model is provided using simple yet effective examples. The work is developed from a series of lecture courses taught by the authors in more than 40 universities across more than 20 countries, and from research carried out by Maxeler Technologies, Inc. Topics and features: presents a thorough introduction to DataFlow supercomputing for big data problems; reviews the latest research on the DataFlow architecture and its applications; introduces a new method for the rapid handling of real-world challenges involving large datasets; provides a case study on the use of the new approach to accelerate the Cooley-Tukey algorithm on a DataFlow machine; includes a step-by-step guide to the web-based integrated development environment WebIDE.

This book constitutes the Proceedings of the IFIP Working Conference PRO COMET'98, held 8-12 June 1998 at Shelter Island, N.Y. The conference is organized by the t'wo IFIP TC 2 Working Groups 2.2 Formal Description of Programming Concepts and 2.3 Programming Methodology. WG2.2 and WG2.3 have been organizing these conferences every four years for over twenty years. The aim of such Working Conferences organized by IFIP Working Groups is to bring together leading scientists in a given area of computer science. Participation is by invitation only. As a result, these conferences distinguish themselves from other meetings by extensive and competent technical discus sions. PROCOMET stands for Programming Concepts and Methods, indicating that the area of discussion for the conference is the formal description of pro gramming concepts and methods, their tool support, and their applications. At PROCOMET working conferences, papers are presented from this whole area, reflecting the interest of the individuals in WG2.2 and WG2.3."

Fuzzy Database Modeling with XML aims to provide a single record of current research and practical applications in the fuzzy databases. This volume is the outgrowth of research the author has conducted in recent years. Fuzzy Database Modeling with XML introduces state-of-the-art information to the database research, while at the same time serving the information technology professional faced with a non-traditional application that defeats conventional approaches.

The research on fuzzy conceptual models and fuzzy object-oriented databases is receiving increasing attention, in addition to fuzzy relational database models. With rapid advances in network and internet techniques as well, the databases have been applied under the environment of distributed information systems. It is essential in this case to integrate multiple fuzzy database systems. Since databases are commonly employed to store and manipulate XML data, additional requirements are necessary to model fuzzy information with XML. Secondly, this book maps fuzzy XML model to the fuzzy databases. Very few efforts at investigating these issues have thus far occurred.

Fuzzy Database Modeling with XML is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.

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.

Data mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign, looking for patterns in financial transactions to discover illegal activities or analyzing genome sequences. From this perspective, it was just a matter of time for the discipline to reach the important area of computer security. Applications Of Data Mining In Computer Security presents a collection of research efforts on the use of data mining in computer security.

Applications Of Data Mining In Computer Security concentrates heavily on the use of data mining in the area of intrusion detection. The reason for this is twofold. First, the volume of data dealing with both network and host activity is so large that it makes it an ideal candidate for using data mining techniques. Second, intrusion detection is an extremely critical activity. This book also addresses the application of data mining to computer forensics. This is a crucial area that seeks to address the needs of law enforcement in analyzing the digital evidence.