This book presents the state-of-the-arts application of digital watermarking in audio, speech, image, video, 3D mesh graph, text, software, natural language, ontology, network stream, relational database, XML, and hardware IPs. It also presents new and recent algorithms in digital watermarking for copyright protection and discusses future trends in the field. Today, the illegal manipulation of genuine digital objects and products represents a considerable problem in the digital world. Offering an effective solution, digital watermarking can be applied to protect intellectual property, as well as fingerprinting, enhance the security and proof-of-authentication through unsecured channels.

This book contains some selected papers from the International Conference on Extreme Learning Machine 2015, which was held in Hangzhou, China, December 15-17, 2015. This conference brought together researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

While high quality library and information services continue to thrive and strengthen economic and social development, much of the knowledge that exists on user's needs and behaviours is fundamentally based on the results of users in English-speaking, western developed countries. Information Access and Library User Needs in Developing Countries highlights the struggles that developing countries face in terms of information gaps and information-seeking user behaviour. The publication highlights ways in which users in developing countries can benefit from properly implementing LIS services. Researchers, academics, and practitioners interested in the design and delivery of information services will benefit from this collection of research.

Sequential data from Web server logs, online transaction logs, and performance measurements is collected each day. This sequential data is a valuable source of information, as it allows individuals to search for a particular value or event and also facilitates analysis of the frequency of certain events or sets of related events. Finding patterns in sequences is of utmost importance in many areas of science, engineering, and business scenarios. Pattern Discovery Using Sequence Data Mining: Applications and Studies provides a comprehensive view of sequence mining techniques and presents current research and case studies in pattern discovery in sequential data by researchers and practitioners. This research identifies industry applications introduced by various sequence mining approaches.

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.

This guide helps you protect networks from unauthorized access. It discusses counter security threats, optimum use of encryption, integrity checks, and uniqueness mechanisms.

This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.

This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, with an emphasis on exploratory and unsupervised data analysis, an area of increasing significance with the pace of growth of data vastly outpacing any chance of labeling them manually. The book looks at the underlying algorithms and technologies that facilitate the area within big data analytics, it covers their applications across domains such as smarter transportation, social media, fake news detection and enterprise search among others. This book enables readers to understand a spectrum of advances in this emerging area, and it will hopefully empower them to leverage and develop methods in multi-source data fusion and analytics with applications to a variety of scenarios. Includes advances on unsupervised, semi-supervised and supervised approaches to heterogeneous data linkage and fusion; Covers use cases of analytics over multi-view and heterogeneous data from across a variety of domains such as fake news, smarter transportation and social media, among others; Provides a high-level overview of advances in this emerging field and empowers the reader to explore novel applications and methodologies that would enrich the field.

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.

This book is for product managers, product owners, product marketing managers, VPs and Heads of Product, CEOs, and start-up founders. In short, it serves anyone interested personally or professionally in software product management. You'll learn how to plan, coordinate and execute all activities required for software product success. It enables you to find the right balance for delivering customer value and long-term product success. The book offers a comprehensive introduction for beginners as well as proven practices and a novel, holistic approach for experienced product managers. It provides much-needed clarity regarding the numerous tasks and responsibilities involved in the professional and successful management of software products. Readers can use this book as a reference book if they are interested in or have the urgent need to improve one of the following software product management dimensions: Product Viability, Product Development, Go-to-Market / Product Marketing, Software Demonstrations and Training, The Market / Your Customers, or Organizational Maturity. The book helps product people to maximize their impact and effectiveness. Whether you're a seasoned practitioner, new to software product management, or just want to learn more about the best-of-all disciplines and advance your skills, this book introduces a novel and "business" tested approach to structure and orchestrate the vital dimensions of software product management. You will learn how to create focus and alignment on the things that matter for product success. The book describes a holistic framework to keep the details that matter for product success in balance, taking into consideration the limiting factors, strategies and responsibilities that determine the overall product yield potential. It explains how to leverage and adapt the framework with regard to aspects like product viability, product development, product marketing and software demonstrations and training, as well as more general aspects like markets, customers and organizational maturity. The book focuses on the unique challenges of software product managers or any related roles, whether you are a founder of a small to mid-sized software company or working in the complex ecosystems of large software enterprises or corporate IT departments.

The use of game theoretic techniques is playing an increasingly important role in the network design domain. Understanding the background, concepts, and principles in using game theory approaches is necessary for engineers in network design. Game Theory Applications in Network Design provides the basic idea of game theory and the fundamental understanding of game theoretic interactions among network entities. The material in this book also covers recent advances and open issues, offering game theoretic solutions for specific network design issues. This publication will benefit students, educators, research strategists, scientists, researchers, and engineers in the field of network design.

Many techniques, algorithms, protocols and tools have been developed in the different aspects of cyber-security, namely, authentication, access control, availability, integrity, privacy, confidentiality and non-repudiation as they apply to both networks and systems. ""Web Services Security and E-Business"" focuses on architectures and protocols, while bringing together the understanding of security problems related to the protocols and applications of the Internet, and the contemporary solutions to these problems. ""Web Services Security and E-Business"" provides insight into uncovering the security risks of dynamically-created content, and how proper content management can greatly improve the overall security. It also studies the security lifecycle and how to respond to an attack, as well as the problems of site hijacking and phishing.

The widespread use of XML in business and scientific databases has prompted the development of methodologies, techniques, and systems for effectively managing and analyzing XML data. This has increasingly attracted the attention of different research communities, including database, information retrieval, pattern recognition, and machine learning, from which several proposals have been offered to address problems in XML data management and knowledge discovery. XML Data Mining: Models, Methods, and Applications aims to collect knowledge from experts of database, information retrieval, machine learning, and knowledge management communities in developing models, methods, and systems for XML data mining. This book addresses key issues and challenges in XML data mining, offering insights into the various existing solutions and best practices for modeling, processing, analyzing XML data, and for evaluating performance of XML data mining algorithms and systems.

The aim of cryptography is to design primitives and protocols that withstand adversarial behavior. Information theoretic cryptography, how-so-ever desirable, is extremely restrictive and most non-trivial cryptographic tasks are known to be information theoretically impossible. In order to realize sophisticated cryptographic primitives, we forgo information theoretic security and assume limitations on what can be efficiently computed. In other words we attempt to build secure systems conditioned on some computational intractability assumption such as factoring, discrete log, decisional Diffie-Hellman, learning with errors, and many more. In this work, based on the 2013 ACM Doctoral Dissertation Award-winning thesis, we put forth new plausible lattice-based constructions with properties that approximate the sought after multilinear maps. The multilinear analog of the decision Diffie-Hellman problem appears to be hard in our construction, and this allows for their use in cryptography. These constructions open doors to providing solutions to a number of important open problems.

The book provides a thorough treatment of set functions, games and capacities as well as integrals with respect to capacities and games, in a mathematical rigorous presentation and in view of application to decision making. After a short chapter introducing some required basic knowledge (linear programming, polyhedra, ordered sets) and notation, the first part of the book consists of three long chapters developing the mathematical aspects. This part is not related to a particular application field and, by its neutral mathematical style, is useful to the widest audience. It gathers many results and notions which are scattered in the literature of various domains (game theory, decision, combinatorial optimization and operations research). The second part consists of three chapters, applying the previous notions in decision making and modelling: decision under uncertainty, decision with multiple criteria, possibility theory and Dempster-Shafer theory.

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.

The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

This book presents the data privacy protection which has been extensively applied in our current era of big data. However, research into big data privacy is still in its infancy. Given the fact that existing protection methods can result in low data utility and unbalanced trade-offs, personalized privacy protection has become a rapidly expanding research topic.In this book, the authors explore emerging threats and existing privacy protection methods, and discuss in detail both the advantages and disadvantages of personalized privacy protection. Traditional methods, such as differential privacy and cryptography, are discussed using a comparative and intersectional approach, and are contrasted with emerging methods like federated learning and generative adversarial nets. The advances discussed cover various applications, e.g. cyber-physical systems, social networks, and location-based services. Given its scope, the book is of interest to scientists, policy-makers, researchers, and postgraduates alike.

This book introduces Meaningful Purposive Interaction Analysis (MPIA) theory, which combines social network analysis (SNA) with latent semantic analysis (LSA) to help create and analyse a meaningful learning landscape from the digital traces left by a learning community in the co-construction of knowledge. The hybrid algorithm is implemented in the statistical programming language and environment R, introducing packages which capture - through matrix algebra - elements of learners' work with more knowledgeable others and resourceful content artefacts. The book provides comprehensive package-by-package application examples, and code samples that guide the reader through the MPIA model to show how the MPIA landscape can be constructed and the learner's journey mapped and analysed. This building block application will allow the reader to progress to using and building analytics to guide students and support decision-making in learning.

This book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis techniques. Each chapter offers a summary of the field and a sample analysis. Also covered are telehealth infrastructure, healthcare information association rules, methods for mass spectrometry imaging, environmental biodiversity, and the global nonlinear fitness function for protein structures. Diseases are addressed in chapters on functional annotation of lncRNAs in human disease, metabolomics characterization of human diseases, disease risk factors using SNP data and Bayesian methods, and imaging informatics for diagnostic imaging marker selection. With the exploding accumulation of Electronic Health Records (EHRs), there is an urgent need for computer-aided analysis of heterogeneous biomedical datasets. Biomedical data is notorious for its diversified scales, dimensions, and volumes, and requires interdisciplinary technologies for visual illustration and digital characterization. Various computer programs and servers have been developed for these purposes by both theoreticians and engineers. This book is an essential reference for investigating the tools available for analyzing heterogeneous biomedical data. It is designed for professionals, researchers, and practitioners in biomedical engineering, diagnostics, medical electronics, and related industries.

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.