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.

News headlines about privacy invasions, discrimination, and biases discovered in the platforms of big technology companies are commonplace today, and big tech's reluctance to disclose how they operate counteracts ideals of transparency, openness, and accountability. This book is for computer science students and researchers who want to study big tech's corporate surveillance from an experimental, empirical, or quantitative point of view and thereby contribute to holding big tech accountable. As a comprehensive technical resource, it guides readers through the corporate surveillance landscape and describes in detail how corporate surveillance works, how it can be studied experimentally, and what existing studies have found. It provides a thorough foundation in the necessary research methods and tools, and introduces the current research landscape along with a wide range of open issues and challenges. The book also explains how to consider ethical issues and how to turn research results into real-world change.

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 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.

This book presents a unified collection of concepts, tools, and techniques that constitute the most important technology available today for the design and implementation of information systems. The framework adopted for this integration goal is the one offered by the relational model of data, its applica tions, and implementations in multiuser and distributed environments. The topics presented in the book include conceptual modeling of application environments using the relational model, formal properties of that model, and tools such as relational languages which go with it, techniques for the logical and physical design of relational database systems and their imple mentations. The book attempts to develop an integrated methodology for addressing all these issues on the basis of the relational approach and various research and practical developments related to that approach. This book is the only one available today that presents such an inte gration. The diversity of approaches to data models, to logical and physical database design, to database application programming, and to use and imple mentation of database systems calls for a common framework for all of them. It has become difficult to study modern database technology with out such a unified approach to a diversity of results developed during the vigorous growth of the database area in recent years, let alone to teach a course on the subject."

This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of potential applications in sensor and cognitive systems engineering.
The topics and application include Information Geometry, Differential Geometry of structured Matrix, Positive Definite Matrix, Covariance Matrix, Sensors (Electromagnetic Fields, Acoustic sensors) and Applications in Cognitive systems, in particular Data Mining."

Information Organization and Databases: Foundations of Data Organization provides recent developments of information organization technologies that have become crucial not only for data mining applications and information visualization, but also for treatment of semistructured data, spatio-temporal data and multimedia data that are not necessarily stored in conventional DBMSs. Information Organization and Databases: Foundations of Data Organization presents: semistructured data addressing XML, query languages and integrity constraints, focusing on advanced technologies for organizing web data for effective retrieval; multimedia database organization emphasizing video data organization and data structures for similarity retrieval; technologies for data mining and data warehousing; index organization and efficient query processing issues; spatial data access and indexing; organizing and retrieval of WWW and hypermedia. Information Organization and Databases: Foundations of Data Organization is a resource for database practitioners, database researchers, designers and administrators of multimedia information systems, and graduate-level students in the area of information retrieval and/or databases wishing to keep abreast of advances in the information organization technologies.

With the healthcare industry becoming increasingly more competitive, there exists a need for medical institutions to improve both the efficiency and the quality of their services. In order to do so, it is important to investigate how statistical models can be used to study health outcomes. Cases on Health Outcomes and Clinical Data Mining: Studies and Frameworks provides several case studies developed by faculty and graduates of the University of Louisville's PhD program in Applied and Industrial Mathematics. The studies in this book use non-traditional, exploratory data analysis and data mining tools to examine health outcomes, finding patterns and trends in observational data. This book is ideal for the next generation of data mining practitioners.

1. When I was asked by the editors of this book to write a foreword, I was seized by panic. Obviously, neither I am an expert in Knowledge Representation in Fuzzy Databases nor I could have been beforehand unaware that the book's contributors would be some of the most outstanding researchers in the field. However, Amparo Vila's gentle insistence gradually broke down my initial resistance, and panic then gave way to worry. Which paving stones did I have at my disposal for making an entrance to the book? After thinking about it for some time, I concluded that it would be pretentious on my part to focus on the subjects which are dealt with directly in the contributions presented, and that it would instead be better to confine myself to making some general reflections on knowledge representation given by imprecise information using fuzzy sets; reflections which have been suggested to me by some words in the following articles such as: graded notions, fuzzy objects, uncertainty, fuzzy implications, fuzzy inference, empty intersection, etc.

Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global economy, and ub- uitouscomputingandnetworkingacrosseverysectorand business, data andits deep analysis becomes a particularly important issue for enhancing the soft power of an organization, its production systems, decision-making and performance. The last ten years have seen ever-increasingapplications of data mining in business, gove- ment, social networks and the like. However, a crucial problem that prevents data mining from playing a strategic decision-support role in ICT is its usually limited decision-support power in the real world. Typical concerns include its actionability, workability, transferability, and the trustworthy, dependable, repeatable, operable and explainable capabilities of data mining algorithms, tools and outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies and techniques, which are critical issues faced by data mining, as well as the ?ndings, thoughts and lessons learned in conducting several large-scale real-world data mining bu- ness applications. The aim and objective of domain driven data mining is to study effective and ef?cient methodologies, techniques, tools, and applications that can discover and deliver actionable knowledge that can be passed on to business people for direct decision-making and action-takin

This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11-12, 2010 a workshop entitled 'Optimization and Data Analysis in Biomedical Informatics' was organized at The Fields Institute. Following this event invited contributions were gathered based on the talks presented at the workshop, and additional invited chapters were chosen from world's leading experts. In this publication, the authors share their expertise in the form of state-of-the-art research and review chapters, bringing together researchers from different disciplines and emphasizing the value of mathematical methods in the areas of clinical sciences. This work is targeted to applied mathematicians, computer scientists, industrial engineers, and clinical scientists who are interested in exploring emerging and fascinating interdisciplinary topics of research. It is designed to further stimulate and enhance fruitful collaborations between scientists from different disciplines.

TRACK 1: Innovative Applications in the Public Sector The integration of multimedia based applications and the information superhighway fundamentally concerns the creation of a communication technology to support the ac tivities of people. Communication is a profoundly social activity involving interactions among groups or individuals, common standards of exchange, and national infrastruc tures to support telecommunications activities. The contributions of the invited speakers and others in this track begin to explore the social dimension of communication within the context of integrated, information systems for the public sector. Interactions among businesses and households are described by Ralf Strauss through the development within a real community of a "wired city" with information and electronic services provided by the latest telecommunications technologies. A more specific type of interaction between teacher and student forms the basis of education. John Tiffin demonstrates how virtual classrooms can be used to augment the educational process. Carl Loeffler presents yet another perspective on interaction through the integration of A-life and agent technologies to investigate the dynamics of complex behaviors within networked simulation environments. Common standards for communication in the form of electronic documents or CSCW (Computer Supported Cooperative Work), according to Roland Traunmiiller, provide en abling technologies for a paradigm shift in the management of organizations. As pointed out by William Olle, the impact of standardization work on the future of information technology depends critically upon the interoperability of software systems."

"Introduction to Data Mining" presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

Recently, a new set of software development techniques has become available, collectively termed Aspect-Oriented Software Development (AOSD). This aims to support the modularization of systemic properties (also referred to as crosscutting concerns) and their subsequent composition with the other parts of a system.

Rashid focuses on the use of Aspect-Oriented Programming (AOP) techniques to modularize otherwise broadly scoped features in database systems, such as the evolution or the versioning model, to improve their customizability, extensibility and maintainability. He shows how the use of AOP can transform the way we develop, use and maintain database systems. He also discusses how database systems can support AOP by providing a means for the storage and retrieval of aspects.

"Aspect-Oriented Database Systems" shows the possible synergy between AOP and database systems, and is of particular interest to researchers, graduate students and software developers in database systems and applications.

This volume contains a selection of papers that focus on the state-of the-art in formal specification and verification of real-time computing systems. Preliminary versions of these papers were presented at a workshop on the foundations of real-time computing sponsored by the Office of Naval Research in October, 1990 in Washington, D. C. A companion volume by the title Foundations of Real-Time Computing: Scheduling and Resource Management complements this hook by addressing many of the recently devised techniques and approaches for scheduling tasks and managing resources in real-time systems. Together, these two texts provide a comprehensive snapshot of current insights into the process of designing and building real time computing systems on a scientific basis. The notion of real-time system has alternative interpretations, not all of which are intended usages in this collection of papers. Different communities of researchers variously use the term real-time to refer to either very fast computing, or immediate on-line data acquisition, or deadline-driven computing. This text is concerned with the formal specification and verification of computer software and systems whose correct performance is dependent on carefully orchestrated interactions with time, e. g., meeting deadlines and synchronizing with clocks. Such systems have been enabled for a rapidly increasing set of diverse end-uses by the unremitting advances in computing power per constant-dollar cost and per constant-unit-volume of space. End use applications of real-time computers span a spectrum that includes transportation systems, robotics and manufacturing, aerospace and defense, industrial process control, and telecommunications."