This carefully edited and reviewed volume addresses the increasingly popular demand for seeking more clarity in the data that we are immersed in. It offers excellent examples of the intelligent ubiquitous computation, as well as recent advances in systems engineering and informatics. The content represents state-of-the-art foundations for researchers in the domain of modern computation, computer science, system engineering and networking, with many examples that are set in industrial application context. The book includes the carefully selected best contributions to APCASE 2014, the 2nd Asia-Pacific Conference on Computer Aided System Engineering, held February 10-12, 2014 in South Kuta, Bali, Indonesia. The book consists of four main parts that cover data-oriented engineering science research in a wide range of applications: computational models and knowledge discovery; communications networks and cloud computing; computer-based systems; and data-oriented and software-intensive systems.

In October 2000, the US National Institute of Standards and Technology selected the block cipher Rijndael as the Advanced Encryption Standard (AES). AES is expected to gradually replace the present Data Encryption Standard (DES) as the most widely applied data encryption technology. This book by the designers of the block cipher presents Rijndael from scratch. The underlying mathematics and the wide trail strategy as the basic design idea are explained in detail and the basics of differential and linear cryptanalysis are reworked. Subsequent chapters review all known attacks against the Rijndael structure and deal with implementation and optimization issues. Finally, other ciphers related to Rijndael are presented. This book is THE authoritative guide to the Rijndael algorithm and AES. Professionals, researchers, and students active or interested in data encryption will find it a valuable source of information and reference.

This volume directly addresses the complexities involved in data mining and the development of new algorithms, built on an underlying theory consisting of linear and non-linear dynamics, data selection, filtering, and analysis, while including analytical projection and prediction. The results derived from the analysis are then further manipulated such that a visual representation is derived with an accompanying analysis. The book brings very current methods of analysis to the forefront of the discipline, provides researchers and practitioners the mathematical underpinning of the algorithms, and the non-specialist with a visual representation such that a valid understanding of the meaning of the adaptive system can be attained with careful attention to the visual representation. The book presents, as a collection of documents, sophisticated and meaningful methods that can be immediately understood and applied to various other disciplines of research. The content is composed of chapters addressing: An application of adaptive systems methodology in the field of post-radiation treatment involving brain volume differences in children; A new adaptive system for computer-aided diagnosis of the characterization of lung nodules; A new method of multi-dimensional scaling with minimal loss of information; A description of the semantics of point spaces with an application on the analysis of terrorist attacks in Afghanistan; The description of a new family of meta-classifiers; A new method of optimal informational sorting; A general method for the unsupervised adaptive classification for learning; and the presentation of two new theories, one in target diffusion and the other in twisting theory.

This book is an essential contribution to the description of fuzziness in information systems. Usually users want to retrieve data or summarized information from a database and are interested in classifying it or building rule-based systems on it. But they are often not aware of the nature of this data and/or are unable to determine clear search criteria. The book examines theoretical and practical approaches to fuzziness in information systems based on statistical data related to territorial units. Chapter 1 discusses the theory of fuzzy sets and fuzzy logic to enable readers to understand the information presented in the book. Chapter 2 is devoted to flexible queries and includes issues like constructing fuzzy sets for query conditions, and aggregation operators for commutative and non-commutative conditions, while Chapter 3 focuses on linguistic summaries. Chapter 4 presents fuzzy logic control architecture adjusted specifically for the aims of business and governmental agencies, and shows fuzzy rules and procedures for solving inference tasks. Chapter 5 covers the fuzzification of classical relational databases with an emphasis on storing fuzzy data in classical relational databases in such a way that existing data and normal forms are not affected. This book also examines practical aspects of user-friendly interfaces for storing, updating, querying and summarizing. Lastly, Chapter 6 briefly discusses possible integration of fuzzy queries, summarization and inference related to crisp and fuzzy databases. The main target audience of the book is researchers and students working in the fields of data analysis, database design and business intelligence. As it does not go too deeply into the foundation and mathematical theory of fuzzy logic and relational algebra, it is also of interest to advanced professionals developing tailored applications based on fuzzy sets.

This book offers a comprehensive guide to implementing SAP and HANA on private, public and hybrid clouds. Cloud computing has transformed the way organizations run their IT infrastructures: the shift from legacy monolithic mainframes and UNIX platforms to cloud based infrastructures offering ubiquitous access to critical information, elastic provisioning and drastic cost savings has made cloud an essential part of every organization's business strategy. Cloud based services have evolved from simple file sharing, email and messaging utilities in the past, to the current situation, where their improved technical capabilities and SLAs make running mission-critical applications such as SAP possible. However, IT professionals must take due care when deploying SAP in a public, private or hybrid cloud environment. As a foundation for core business operations, SAP cloud deployments must satisfy stringent requirements concerning their performance, scale and security, while delivering measurable improvements in IT efficiency and cost savings. The 2nd edition of "SAP on the Cloud" continues the work of its successful predecessor released in 2013, providing updated guidance for deploying SAP in public, private and hybrid clouds. To do so, it discusses the technical requirements and considerations necessary for IT professionals to successfully implement SAP software in a cloud environment, including best-practice architectures for IaaS, PaaS and SaaS deployments. The section on SAP's in-memory database HANA has been significantly extended to cover Suite on HANA (SoH) and the different incarnations of HANA Enterprise Cloud (HEC) and Tailored Datacenter Integration (TDI). As cyber threats are a significant concern, it also explores appropriate security models for defending SAP cloud deployments against modern and sophisticated attacks. The reader will gain the insights needed to understand the respective benefits and drawbacks of various deployment models and how SAP on the cloud can be used to deliver IT efficiency and cost-savings in a secure and agile manner.

Data and knowledge play a key role in both current and future Grids. The issues concerning representation, discovery, and integration of data and knowledge in dynamic distributed environments can be addressed by exploiting features offered by Grid Technologies. Current research activities are leveraging the Grid for the provision of generic- and domain-specific solutions and services for data management and knowledge discovery. Knowledge and Data Management in Grids is the third volume of the Core Grid series and brings together scientific contributions by researchers and scientists working on storage, data, and knowledge management in Grid and Peer-to-Peer systems. This volume presents the latest Grid solutions and research results in key areas of knowledge and data management such as distributed storage management, Grid databases, Semantic Grid and Grid-aware data mining. Knowledge and Data Management in Grids is for a professional audience, composed of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.

Health information about patients is critical; currently, health records are saved in databases controlled by individual users, organizations, or large groups of organizations. As there are many malicious users, this information is not shared with other organizations due to security issues and the chance of the data being modified or tampered with. Blockchain can be used to securely exchange healthcare data, which can be accessed by organizations sharing the same network, allowing doctors/practitioners to provide better care for patients. The key properties of decentralization, such as immutability and transparency, improve healthcare interoperability. This book brings forth the prospects and research trends of Blockchain in healthcare, so that Researchers, Database professionals, Academia, and Healthcare professionals across the world can know/use the concept of Blockchain in healthcare. The book provides the fundamental and technical details of Blockchain, the applications of Blockchain in healthcare, hands-on chapters for graduate/postgraduate/doctoral students/healthcare professionals to secure healthcare data of patients, and research challenges and future work directions for researchers in healthcare.

With advances and in-depth applications of computer technologies, and the extensive applications of Web technology in various areas, databases have become the repositories of large volumes of data. It is very critical to manage data resources for effective problem solving and decision making. Collecting and presenting the latest research and development results from the leading researchers in the field of intelligent databases, ""Intelligent Databases: Technologies and Applications"" provides a single record of current research and practical applications in this field. ""Intelligent Databases: Technologies and Applications"" integrates data management in databases with intelligent data processing and analysis in artificial intelligence. This book challenges today's database technology and promotes its evolution.

Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each other's methods to facilitate knowledge discovery. Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.

Web search engines are not just indispensable tools for finding and accessing information online, but have become a defining component of the human condition and can be conceptualized as a complex behavior embedded within an individual's everyday social, cultural, political, and information-seeking activities. This book investigates Web search from the non-technical perspective, bringing together chapters that represent a range of multidisciplinary theories, models, and ideas.

This book presents real-world decision support systems, i.e., systems that have been running for some time and as such have been tested in real environments and complex situations; the cases are from various application domains and highlight the best practices in each stage of the system's life cycle, from the initial requirements analysis and design phases to the final stages of the project. Each chapter provides decision-makers with recommendations and insights into lessons learned so that failures can be avoided and successes repeated. For this reason unsuccessful cases, which at some point of their life cycle were deemed as failures for one reason or another, are also included. All decision support systems are presented in a constructive, coherent and deductive manner to enhance the learning effect. It complements the many works that focus on theoretical aspects or individual module design and development by offering 'good' and 'bad' practices when developing and using decision support systems. Combining high-quality research with real-world implementations, it is of interest to researchers and professionals in industry alike.

The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. ""Data Mining and Medical Knowledge Management: Cases and Applications"" presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.

Research in multi-agent systems offers a promising technology for problems with networks, online trading and negotiations but also social structures and communication. This is a book on agent and multi-agent technology for internet and enterprise systems. The book is a pioneer in the combination of the fields and is based on the concept of developing a platform to share ideas and presents research in technology in the field and application to real problems. The chapters range over both applications, illustrating the possible uses of agents in an enterprise domain, and design and analytic methods, needed to provide the solid foundation required for practical systems.

Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks.
The thesis on which this book is based was honored with the Top 100 Excellent Doctoral Dissertations Award from the Chinese Academy of Sciences and was nominated as the Outstanding Doctoral Dissertation by the Chinese Computer Federation.

Considered the gold-standard reference on information security, the Information Security Management Handbook provides an authoritative compilation of the fundamental knowledge, skills, techniques, and tools required of today's IT security professional. Now in its sixth edition, this 3200 page, 4 volume stand-alone reference is organized under the CISSP Common Body of Knowledge domains and has been updated yearly. Each annual update, the latest is Volume 6, reflects the changes to the CBK in response to new laws and evolving technology.

Database Concurrency Control: Methods, Performance and Analysis is a review of developments in concurrency control methods for centralized database systems, with a quick digression into distributed databases and multicomputers, the emphasis being on performance. The main goals of Database Concurrency Control: Methods, Performance and Analysis are to succinctly specify various concurrency control methods; to describe models for evaluating the relative performance of concurrency control methods; to point out problem areas in earlier performance analyses; to introduce queuing network models to evaluate the baseline performance of transaction processing systems; to provide insights into the relative performance of transaction processing systems; to illustrate the application of basic analytic methods to the performance analysis of various concurrency control methods; to review transaction models which are intended to relieve the effect of lock contention; to provide guidelines for improving the performance of transaction processing systems due to concurrency control; and to point out areas for further investigation. This monograph should be of direct interest to computer scientists doing research on concurrency control methods for high performance transaction processing systems, designers of such systems, and professionals concerned with improving (tuning) the performance of transaction processing systems.

Patrick Humphreys Department of Social Psychology London School of Economics and Political Science, Houghton Street, London WC2A 2AE. Email: P. Humphreys@lse. ac. uk This book presents a selection of contributions to the conference on Implementing Systems for Supporting Management Decisions: Concepts, Methods, and Experiences held in London in July, 1996. The conference was organized by the International Federation of Infonnation Processing's Working Group 8. 3 on Decision Support Systems and the London School of Economics and Political Science. (LSE). The Programme Committee for the Conference comprised Liam Bannon, University of Limerick; Patrick Humphreys, LSE, co-chairperson; Andrew McCosh, University of Edinburgh; Piero Migliarese, Politecnico di Milano, co chairperson; Jean-Charles Pomerol, LAFORIA, Universite Paris VI. The chairperson of the organizing committee was Dina Berkeley, LSE. The programme committee members served also as the editors of this book. Each contribution was selected by the editors after peer review and was developed by its authors specifically for inclusion in this volume. Working group 8. 3 was formally established in 1981 on the recommendation ofIFIP's Technical Committee on Information Systems (TC8). The scope of the working group covers: "Development of approaches for applying information systems technology to increase the effectiveness of decision makers in situations where the computer system can support and enhance human judgment in the perfonnance of tasks that have elements that cannot be specified in advance."

This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics.

The IT Security Governance Guidebook with Security Program Metrics provides clear and concise explanations of key issues in information protection, describing the basic structure of information protection and enterprise protection programs. Including graphics to support the information in the text, this book includes both an overview of material as well as detailed explanations of specific issues. The accompanying downloadable resources offers a collection of metrics, formed from repeatable and comparable measurement, that are designed to correspond to the enterprise security governance model provided in the text, allowing an enterprise to measure its overall information protection program.

Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.