The amount of data shared and stored on the web and other document repositories is steadily on the rise. Unfortunately, this growth increases inefficiencies and difficulties when trying to find the most relevant and up-to-date information due to unstructured data. Advanced Metaheuristic Methods in Big Data Retrieval and Analytics examines metaheuristic techniques as an important alternative model for solving complex problems that are not treatable by deterministic methods. Recent studies suggest that IR and biomimicry can be used together for several application problems in big data and internet of things, especially when conventional methods would be too expensive or difficult to implement. Featuring coverage on a broad range of topics such as ontology, plagiarism detection, and machine learning, this book is ideally designed for engineers, graduate students, IT professionals, and academicians seeking an overview of new trends in information retrieval in big data.

Video Data Management and Information Retrieval combines the two important areas of research within computer technology and presents them in comprehensive, easy to understand manner. Video Data Management and Information Retrieval is ideal for graduates and under-graduates, as well as researchers working in either video data management or information retrieval. It takes an in depth look at many relevant topics within both video data management and information retrieval. In addition to dissecting those issues, the book also provides a ""big picture"" view of each topic. This shows the relevance of each issue and how those areas affect every one today.

"Advanced SQL:1999 - Understanding Object-Relational and Other Advanced Features" is the practitioner's handbook to the standard's advanced features. It is not a re-presentation of the standard, but rather an authoritative, in-depth guide to its practical application. Like its companion, "SQL:1999 - Understanding Relational Language Components," which explained the standard's basic features, this book will show you how to make your applications both effective and standard-compliant.

This handy reference has a modular format so you can explore specific topics with ease. It is equally useful to those upgrading from earlier versions of SQL and those with no previous experience. Written by the standard's distinguished editor, "Advanced SQL:1999" will complete your knowledge and support your skills like no other book can.
* Focuses entirely on the issues that matter to programmers who are connecting applications to databases.
* Details SQL:1999's object facilities, including structured user-defined types, typed tables, user-defined routines, and routine invocation.
* Examines facilities new to SQL, including those relating to on-line analytical processing (OLAP), management of external data (SQL/MED), and Java support.
* Covers the ongoing development of XML support.
* Includes appendices that cover the SQL:1999 annexes, a SQL:1999 example using UDTs, status codes, and useful information on the standardization process.

Reengineering: An Objectoriented Model for Data, Knowledge and System Reengineering (S.M. Huang et al.). Uturn Methodology: A Database Reengineering Methodology Based on the Entity -Structure- Relationship Data Model (I.K. Jeong, D.K. Baik). The Management Perspective of Database Reengineering (C. Yau). Reengineering VSAM, IMS, and DL/1 Applications into Relational Databases (R. England). Reengineering Library Data: The Long Way from ADABAS to NIMARC (D. Aebi, R. Largo). Reverse Engineering in a Client'Server Environment Case Studies on Relational Database Design (B. Siu, J. Fong). Eliminating the Impedance Mismatch between Relational Systems and Objectoriented Programming Languages (J. Chen, Q. Huang). Generalization without Reorganization in a Simple Objectoriented DBMS (T. Beldjilali). Interoperability: Semantic Query Transformation: An Approach to Achieve Semantic Interoperability in Heterogeneous Application Domains (N. Bolloju). On Interoperability Verification and Testing of Objectoriented Databases (T.Y. Kuo, T.Y. Cheung). An Objectoriented Approach to Query Interoperability (J. Zhan, W.S. Luk). Building Parameterized Canonical Representations to Achieve Interoperability among Heterogeneous Databases (Y. Chang, L. Raschid). Flexible Transaction Management in an Interoperable Database Environment (W. Yu, F. Eliassen). A Pilot Survey of Database Reengineering for Data Interoperability (I.S.Y. Kwan). Designing Client-Server Applications for Enterprise Database Connectivity (C. Moffatt). Handling Terabyte Databases on Open Systems (T. Banham). Integration: Schema Integration Methodology including Structural Conflict Resolution and Checking Similarity (G. Suzuki, M. Yamamuro). Extensional Issues in Schema Integration (M. GarciaSolaco et al.). Towards Intelligent Integration of Heterogeneous Information Sources (S.B. Navathe, M.J. Donahoo). A Business ProcessDriven Multidatabase Integration Methodology (R.M. Muhlerger, M.E. Orlowska). A Database Integration System and an Example of Its Application (A.E. James). DEE: A Data Exchange Environment (G.N. Benadjaoud, B.T. David). Database Replica Management Strategies in Multidatabase Systems with Mobile Hosts (M. Faiz, A. Zaslavsky). Providing Multidatabase Access: An Association Approach (P. Missier et al.). Index.

As the world has entered the era of big data, there is a need to give a semantic perspective to the data to find unseen patterns, derive meaningful information, and make intelligent decisions. This 2-volume handbook set is a unique, comprehensive, and complete presentation of the current progress and future potential explorations in the field of data science and related topics. Handbook of Data Science with Semantic Technologies provides a roadmap for a new trend and future development of data science with semantic technologies. The first volume serves as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for both academic researchers and industry professionals. The second volume provides a roadmap for the deployment of semantic technologies in the field of data science that enables users to create intelligence through these technologies by exploring the opportunities while eradicating the current and future challenges. The set explores the optimal use of these technologies to provide the maximum benefit to the user under one comprehensive source. This set consisting of two separate volumes can be utilized independently or together as an invaluable resource for students, scholars, researchers, professionals, and practitioners in the field.

Advanced Topics in Database Research is a series of books in the fields of database, software engineering, and systems analysis and design. They feature the latest research ideas and topics on how to enhance current database systems, improve information storage, refine existing database models, and develop advanced applications. Advanced Topics in Database Research, Volume 4 is a part of this series. Advanced Topics in Database Research, Volume 4 is enriched with authors who have submitted their best works for inclusion in this scholarly book. Advanced Topics in Database Research, Volume 4 is a useful reference and a valuable collection for both researchers and practitioners.

Seeking to define a new approach to data management at the enterprise level, this work takes the reader beyond information management to information control, where the methods of data capture and manipulation supersede data quantity. Using the metadata approach ensures long-term, universal control of all data characteristics and improves the effectiveness of IT as a corporate function by minimizing the potential for errors, and improving communication and understanding between IT and other disciplines. By describing how to establish metadata management within an organization, this volume provides examples of data structure architectures, and reviews issues associated with metadata management in relation to the Internet and data warehousing. It offers to help the reader to control the factors that make data useable throughout an organization and manage data so that it becomes a valuable corporate asset. The book examines real-world business departments that can benefit from this approach and ways in which sets of metadata can be both autonomous and overlapping.

This book explains the fundamentals of control theory for Internet of Things (IoT) systems and smart grids and its applications. It discusses the challenges imposed by large-scale systems, and describes the current and future trends and challenges in decision-making for IoT in detail, showing the ongoing industrial and academic research in the field of smart grid domain applications. It presents step-by-step design guidelines for the modeling, design, customisation and calibration of IoT systems applied to smart grids, in which the challenges increase with each system's increasing complexity. It also provides solutions and detailed examples to demonstrate how to use the techniques to overcome these challenges, as well as other problems related to decision-making for successful implementation. Further, it anaylses the features of decision-making, such as low-complexity and fault-tolerance, and uses open-source and publicly available software tools to show readers how they can design, implement and customise their own system control instantiations. This book is a valuable resource for power engineers and researchers, as it addresses the analysis and design of flexible decision-making mechanisms for smart grids. It is also of interest to students on courses related to control of large-scale systems, since it covers the use of state-of-the-art technology with examples and solutions in every chapter. And last but not least, it offers practical advice for professionals working with smart grids.

This provides a comprehensive overview of the key principles of security concerns surrounding the upcoming Internet of Things (IoT), and introduces readers to the protocols adopted in the IoT. It also analyses the vulnerabilities, attacks and defense mechanisms, highlighting the security issues in the context of big data. Lastly, trust management approaches and ubiquitous learning applications are examined in detail. As such, the book sets the stage for developing and securing IoT applications both today and in the future.

This invaluable reference offers the most comprehensive introduction available to the concepts of multisensor data fusion. It introduces key algorithms, provides advice on their utilization, and raises issues associated with their implementation. With a diverse set of mathematical and heuristic techniques for combining data from multiple sources, the book shows how to implement a data fusion system, describes the process for algorithm selection, functional architectures and requirements for ancillary software, and illustrates man-machine interface requirements an database issues.

This thesis presents an experimental study of quantum memory based on cold atomic ensembles and discusses photonic entanglement. It mainly focuses on experimental research on storing orbital angular momentum, and introduces readers to methods for storing a single photon carried by an image or an entanglement of spatial modes. The thesis also discusses the storage of photonic entanglement using the Raman scheme as a step toward implementing high-bandwidth quantum memory. The storage of photonic entanglement is central to achieving long-distance quantum communication based on quantum repeaters and scalable linear optical quantum computation. Addressing this key issue, the findings presented in the thesis are very promising with regard to future high-speed and high-capacity quantum communications.

This book reports on a novel concept of mechanism transitions for the design of highly scalable and adaptive publish/subscribe systems. First, it introduces relevant mechanisms for location-based filtering and locality-aware dissemination of events based on a thorough review of the state-of-the-art. This is followed by a detailed description of the design of a transition-enabled publish/subscribe system that enables seamless switching between mechanisms during runtime. Lastly, the proposed concepts are evaluated within the challenging context of location-based mobile applications. The book assesses in depth the performance and cost of transition execution, highlighting the impact of the proposed state transfer mechanism and the potential of coexisting transition-enabled mechanisms.

The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors introduce the many different tools and developing approaches in Big Data for historical and humanistic scholarship, show how to use them, what to be wary of, and discuss the kinds of questions and new perspectives this new macroscopic perspective opens up. Authored 'live' online with ongoing feedback from the wider digital history community, Exploring Big Historical Data breaks new ground and sets the direction for the conversation into the future. It represents the current state-of-the-art thinking in the field and exemplifies the way that digital work can enhance public engagement in the humanities.Exploring Big Historical Data should be the go-to resource for undergraduate and graduate students confronted by a vast corpus of data, and researchers encountering these methods for the first time. It will also offer a helping hand to the interested individual seeking to make sense of genealogical data or digitized newspapers, and even the local historical society who are trying to see the value in digitizing their holdings.The companion website to Exploring Big Historical Data can be found at www.themacroscope.org/. On this site you will find code, a discussion forum, essays, and datafiles that accompany this book.

The history and future of geographic information (GI) in the context of big data creates new avenues of concern over its organization, access and use. In this book the authors explore both the background and present challenges facing the preservation of GI, focusing on the roles of librarians, archivists, data scientists, and other information professionals in the creation of GI records for its organization, access, and use.

Integrative Document and Content Management: Strategies for Exploiting Enterprise Knowledge blends theory and practice to provide practical knowledge and guidelines to enterprises wishing to understand the importance of managing documents to their operations along with presentation of document content to facilitate business planning and operations support. This book gives extensive pointers to those who propose to embark upon the implementation of integrated document management systems and to embrace Web content management within a life cycle framework covering document creation to Web publication.

Graphs are a powerful tool for representing and understanding objects and their relationships in various application domains. The growing popularity of graph databases has generated data management problems that include finding efficient techniques for compressing large graph databases and suitable techniques for visualizing, browsing, and navigating large graph databases. Graph Data Management: Techniques and Applications is a central reference source for different data management techniques for graph data structures and their application. This book discusses graphs for modeling complex structured and schemaless data from the Semantic Web, social networks, protein networks, chemical compounds, and multimedia databases and offers essential research for academics working in the interdisciplinary domains of databases, data mining, and multimedia technology.

Conceptual modeling has always been one of the main issues in information systems engineering as it aims to describe the general knowledge of the system at an abstract level that facilitates user understanding and software development. This collection of selected papers provides a comprehensive and extremely readable overview of what conceptual modeling is and perspectives on making it more and more relevant in our society. It covers topics like modeling the human genome, blockchain technology, model-driven software development, data integration, and wiki-like repositories and demonstrates the general applicability of conceptual modeling to various problems in diverse domains. Overall, this book is a source of inspiration for everybody in academia working on the vision of creating a strong, fruitful and creative community of conceptual modelers. With this book the editors and authors want to honor Prof. Antoni Olive for his enormous and ongoing contributions to the conceptual modeling discipline. It was presented to him on the occasion of his keynote at ER 2017 in Valencia, a conference that he has contributed to and supported for over 20 years. Thank you very much to Antoni for so many years of cooperation and friendship.

In this book, contributors provide insights into the latest developments of Edge Computing/Mobile Edge Computing, specifically in terms of communication protocols and related applications and architectures. The book provides help to Edge service providers, Edge service consumers, and Edge service developers interested in getting the latest knowledge in the area. The book includes relevant Edge Computing topics such as applications; architecture; services; inter-operability; data analytics; deployment and service; resource management; simulation and modeling; and security and privacy. Targeted readers include those from varying disciplines who are interested in designing and deploying Edge Computing. Features the latest research related to Edge Computing, from a variety of perspectives; Tackles Edge Computing in academia and industry, featuring a variety of new and innovative operational ideas; Provides a strong foundation for researchers to advance further in the Edge Computing domain.

Transactions are a concept related to the logical database as seen from the perspective of database application programmers: a transaction is a sequence of database actions that is to be executed as an atomic unit of work. The processing of transactions on databases is a well- established area with many of its foundations having already been laid in the late 1970s and early 1980s. The unique feature of this textbook is that it bridges the gap between the theory of transactions on the logical database and the implementation of the related actions on the underlying physical database. The authors relate the logical database, which is composed of a dynamically changing set of data items with unique keys, and the underlying physical database with a set of fixed-size data and index pages on disk. Their treatment of transaction processing builds on the "do-redo-undo" recovery paradigm, and all methods and algorithms presented are carefully designed to be compatible with this paradigm as well as with write-ahead logging, steal-and-no-force buffering, and fine-grained concurrency control. Chapters 1 to 6 address the basics needed to fully appreciate transaction processing on a centralized database system within the context of our transaction model, covering topics like ACID properties, database integrity, buffering, rollbacks, isolation, and the interplay of logical locks and physical latches. Chapters 7 and 8 present advanced features including deadlock-free algorithms for reading, inserting and deleting tuples, while the remaining chapters cover additional advanced topics extending on the preceding foundational chapters, including multi-granular locking, bulk actions, versioning, distributed updates, and write-intensive transactions. This book is primarily intended as a text for advanced undergraduate or graduate courses on database management in general or transaction processing in particular.

This invaluable text/reference investigates the state of the art in approaches to building, monitoring, managing, and governing smart cities. A particular focus is placed on the distributed computing environments within the infrastructure of such cities, including issues of device connectivity, communication, security, and interoperability. A selection of experts of international repute offer their perspectives on current trends and best practices, and their suggestions for future developments, together with case studies supporting the vision of smart cities based on the Internet of Things (IoT). Topics and features: examines the various methodologies relating to next-level urbanization, including approaches to security and privacy relating to social and legal aspects; describes a recursive and layered approach to modeling large-scale resource management systems for self-sustainable cities; proposes a novel architecture for hybrid vehicular wireless sensor networks, and a pricing mechanism for the management of natural resources; discusses the challenges and potential solutions to building smart city surveillance systems, applying knowledge-based governance, and adopting electric vehicles; covers topics on intelligent distributed systems, IoT, fog computing paradigms, big data management and analytics, and smart grids; reviews issues of sustainability in the design of smart cities and healthcare services, illustrated by case studies taken from cities in Japan, India, and Brazil. This illuminating volume offers a comprehensive reference for researchers investigating smart cities and the IoT, students interested in the distributed computing technologies used by smart living systems, and practitioners wishing to adopt the latest security and connectivity techniques in smart city environments.

Currently, Internet and virtual reality communication is essentially audio-visual. The next important breakthrough of the Internet will be the communication and sharing of smell and taste experiences digitally. Audio-visual stimuli are frequency based, and they can be easily digitized and actuated. On the other hand, taste and smell stimuli are based on chemical molecules, therefore, they are not easy to digitize or actuate. To solve this problem, we are required to discover new digital actuation technologies for taste and smell. The authors of this book have experimented on developing digital actuation devices for several years. This book will provide a complete overview of the importance of digitizing taste and smell, prior works, proposed technologies by the authors, other state of the art research, advantages and limitations of the proposed methods, and future applications. We expect digital taste and smell technologies will revolutionize the field of multisensory augmented reality and open up new interaction possibilities in different disciplines such as Human Computer Interaction, Communication, and Augmented and Virtual Reality.

This book presents a comprehensive introduction to Integrated Business Planning (IBP), building on practitioner's experience and showcasing the value gains when moving from disconnected planning to IBP. It also proposes a road map for the transformation of planning, including technological initiatives, business priorities and organizational processes, and demonstrates how to motivate different IBP stakeholders to work together, when and how to connect strategic (to be understood as long term SC&O), tactical and operational planning and how to leverage functional and data integration features of SAP IBP. Real-world business-process use cases help to show the practical implications of implementing SAP IBP. Furthermore the book explores new capabilities, talent acquisition and retention, career development leadership, IBP Center of Expertise. A discussion of how disruptive technology trends like big data, Internet of Things, machine learning and artificial intelligence can influence IBP now and in the near future rounds out the book.

This book reports on the latest advances and applications of chaotic systems. It consists of 25 contributed chapters by experts who are specialized in the various topics addressed in this book. The chapters cover a broad range of topics of chaotic systems such as chaos, hyperchaos, jerk systems, hyperjerk systems, conservative and dissipative systems, circulant chaotic systems, multi-scroll chaotic systems, finance chaotic system, highly chaotic systems, chaos control, chaos synchronization, circuit realization and applications of chaos theory in secure communications, mobile robot, memristors, cellular neural networks, etc. Special importance was given to chapters offering practical solutions, modeling and novel control methods for the recent research problems in chaos theory. This book will serve as a reference book for graduate students and researchers with a basic knowledge of chaos theory and control systems. The resulting design procedures on the chaotic systems are emphasized using MATLAB software.

During the last few years, software evolution research has explored new domains such as the study of socio-technical aspects and collaboration between different individuals contributing to a software system, the use of search-based techniques and meta-heuristics, the mining of unstructured software repositories, the evolution of software requirements, and the dynamic adaptation of software systems at runtime. Also more and more attention is being paid to the evolution of collections of inter-related and inter-dependent software projects, be it in the form of web systems, software product families, software ecosystems or systems of systems.

With this book, the editors present insightful contributions on these and other domains currently being intensively explored, written by renowned researchers in the respective fields of software evolution. Each chapter presents the state of the art in a particular topic, as well as the current research, available tool support and remaining challenges. The book is complemented by a glossary of important terms used in the community, a reference list of nearly 1,000 papers and books and tips on additional resources that may be useful to the reader (reference books, journals, standards and major scientific events in the domain of software evolution and datasets).This book is intended for all those interested in software engineering, and more particularly, software maintenance and evolution. Researchers and software practitioners alike will find in the contributed chapters an overview of the most recent findings, covering a broad spectrum of software evolution topics. In addition, it can also serve as the basis of graduate or postgraduate courses on e.g., software evolution, requirements engineering, model-driven software development or social informatics.

This book presents the latest developments regarding a detailed mobile agent-enabled anomaly detection and verification system for resource constrained sensor networks; a number of algorithms on multi-aspect anomaly detection in sensor networks; several algorithms on mobile agent transmission optimization in resource constrained sensor networks; an algorithm on mobile agent-enabled in situ verification of anomalous sensor nodes; a detailed Petri Net-based formal modeling and analysis of the proposed system, and an algorithm on fuzzy logic-based cross-layer anomaly detection and mobile agent transmission optimization. As such, it offers a comprehensive text for interested readers from academia and industry alike.