This book constitutes the refereed proceedings of the 14th IFIP WG 2.13 International Conference on Open Source Systems, OSS 2018, held in Athens, Greece, in June 2018. The 14 revised full papers and 2 short papers presented were carefully reviewed and selected from 38 submissions. The papers cover a wide range of topics in the field of free/libre open source software (FLOSS) and are organized in the following thematic sections: organizational aspects of OSS projects, OSS projects validity, mining OSS data, OSS in public administration, OSS governance, and OSS reusability.

Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.

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.

This book presents multibiometric watermarking techniques for security of biometric data. This book also covers transform domain multibiometric watermarking techniques and their advantages and limitations. The authors have developed novel watermarking techniques with a combination of Compressive Sensing (CS) theory for the security of biometric data at the system database of the biometric system. The authors show how these techniques offer higher robustness, authenticity, better imperceptibility, increased payload capacity, and secure biometric watermarks. They show how to use the CS theory for the security of biometric watermarks before embedding into the host biometric data. The suggested methods may find potential applications in the security of biometric data at various banking applications, access control of laboratories, nuclear power stations, military base, and airports.

This PALO volume constitutes the Proceedings of the 19th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015), held in Bangkok, Thailand, November 22-25, 2015. The IES series of conference is an annual event that was initiated back in 1997 in Canberra, Australia. IES aims to bring together researchers from countries of the Asian Pacific Rim, in the fields of intelligent systems and evolutionary computation, to exchange ideas, present recent results and discuss possible collaborations. Researchers beyond Asian Pacific Rim countries are also welcome and encouraged to participate. The theme for IES 2015 is "Transforming Big Data into Knowledge and Technological Breakthroughs". The host organization for IES 2015 is the School of Information Technology (SIT), King Mongkut's University of Technology Thonburi (KMUTT), and it is technically sponsored by the International Neural Network Society (INNS). IES 2015 is collocated with three other conferences; namely, The 6th International Conference on Computational Systems-Biology and Bioinformatics 2015 (CSBio 2015), The 7th International Conference on Advances in Information Technology 2015 (IAIT 2015) and The 10th International Conference on e-Business 2015 (iNCEB 2015), as a major part of series of events to celebrate the SIT 20th anniversary and the KMUTT 55th anniversary.

Blockchain is a technology that transcends cryptocurrencies. There are other services in different sectors of the economy that can benefit from the trust and security that blockchains offer. For example, financial institutions are using blockchains for international money transfer, and in logistics, it has been used for supply chain management and tracking of goods. As more global companies and governments are experimenting and deploying blockchain solutions, it is necessary to compile knowledge on the best practices, strategies, and failures in order to create a better awareness of how blockchain could either support or add value to other services. Cross-Industry Use of Blockchain Technology and Opportunities for the Future provides emerging research highlighting the possibilities inherent in blockchain for different sectors of the economy and the added value blockchain can provide for the future of these different sectors. Featuring coverage on a broad range of topics such as data privacy, information sharing, and digital identity, this book is ideally designed for IT specialists, consultants, design engineers, cryptographers, service designers, researchers, academics, government officials, and industry professionals.

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.

This book, written by an international team of prominent authors, gathers the latest developments in mobile technologies for the acquisition, management, analysis and sharing of Volunteered Geographic Information (VGI) in the context of Earth observation. It is divided into three parts, the first of which presents case studies on the implementation of VGI for Earth observation, discusses the characteristics of volunteers' engagement in relation with their expertise and motivation, analyzes the tasks they are called upon to perform, and examines the available tools for developing VGI. In turn, the second part introduces readers to essential methods, techniques and algorithms used to develop mobile information systems based on VGI for distinct Earth observation tasks, while the last part focuses on the drawbacks and limitations of VGI with regard to the above-mentioned tasks and proposes innovative methods and techniques to help overcome them. Given its breadth of coverage, the book offers a comprehensive, practice-oriented reference guide for researchers and practitioners in the field of geo-information management.

This book puts in one place and in accessible form Richard Berk's most recent work on forecasts of re-offending by individuals already in criminal justice custody. Using machine learning statistical procedures trained on very large datasets, an explicit introduction of the relative costs of forecasting errors as the forecasts are constructed, and an emphasis on maximizing forecasting accuracy, the author shows how his decades of research on the topic improves forecasts of risk. Criminal justice risk forecasts anticipate the future behavior of specified individuals, rather than "predictive policing" for locations in time and space, which is a very different enterprise that uses different data different data analysis tools. The audience for this book includes graduate students and researchers in the social sciences, and data analysts in criminal justice agencies. Formal mathematics is used only as necessary or in concert with more intuitive explanations.

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

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.

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.

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.

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.

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.

This is the first textbook on attribute exploration, its theory, its algorithms forapplications, and some of its many possible generalizations. Attribute explorationis useful for acquiring structured knowledge through an interactive process, byasking queries to an expert. Generalizations that handle incomplete, faulty, orimprecise data are discussed, but the focus lies on knowledge extraction from areliable information source.The method is based on Formal Concept Analysis, a mathematical theory ofconcepts and concept hierarchies, and uses its expressive diagrams. The presentationis self-contained. It provides an introduction to Formal Concept Analysiswith emphasis on its ability to derive algebraic structures from qualitative data,which can be represented in meaningful and precise graphics.

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 book provides an overview of predictive methods demonstrated by open source software modeling with Rattle (R') and WEKA. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on prescriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic data types. Chapter 3 covers fundamentals time series modeling tools, and Chapter 4 provides demonstration of multiple regression modeling. Chapter 5 demonstrates regression tree modeling. Chapter 6 presents autoregressive/integrated/moving average models, as well as GARCH models. Chapter 7 covers the set of data mining tools used in classification, to include special variants support vector machines, random forests, and boosting. Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.

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 offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ideas within this very active field. With extensive introductions, formal and mathematical developments and real case studies, this book provides readers with a deeper understanding of the mutual relationships between these methods, which are clearly expressed with respect to three facets: logical, combinatorial and statistical. Using relational mathematical representation, all types of data structures can be handled in precise and unified ways which the author highlights in three stages: Clustering a set of descriptive attributes Clustering a set of objects or a set of object categories Establishing correspondence between these two dual clusterings Tools for interpreting the reasons of a given cluster or clustering are also included. Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering will be a valuable resource for students and researchers who are interested in the areas of Data Analysis, Clustering, Data Mining and Knowledge Discovery.

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.