The Semantic Web has been around for some years with recent advances in mature technologies and applications. Lately, its development has been demonstrated in its contribution to businesses through the enhancement of e-commerce. Semantic Web for Business: Cases and Applications delivers real-life cases that illustrate the benefits of Semantic Web technologies as applied to e-business and e-commerce scenarios. Covering topics such as business integration, organizational knowledge management, and Semantic Web services, this book provides academic research libraries with a comprehensive reference to the commercial capabilities of Semantic Web technologies, as well as practical applications for the benefit of IT professionals, business executives, consultants, and students.

This volume presents the first part of the proceedings of the Mediterranean Conference on Information & Communication Technologies (MedICT 2015), which was held at Saidia, Morocco during 7-9 May, 2015. MedICT provides an excellent international forum to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development. The conference has also a special focus on enabling technologies for societal challenges, and seeks to address multidisciplinary challenges in Information & Communication Technologies such as health, demographic change, wellbeing, security and sustainability issues. The proceedings publish high quality papers which are closely related to the various theories, as well as emerging and practical applications of particular interest to the ICT community. This first volume provides a compact yet broad view of recent developments in devices, technologies and processing, and covers recent research areas in the field including Microwave Devices and Printed Antennas, Advances in Optical and RF Devices and Applications, Signal Processing and Information Theory, Wireless and Optical Technologies and Techniques, Computer Vision, Optimization and Modeling in Wireless Communication Systems, Modeling, Identification and Biomedical Signal Processing, Photovoltaic Cell & Systems, RF Devices and Antennas for Wireless Applications, RFID, Ad Hoc and Networks Issues.

Information systems belong to the most complex artifacts built in today's society. Developing, maintaining, and using an information system raises a large number of difficult problems, ranging from purely technical to organizational and social. ""Information Systems Engineering"" presents the most current research on existing and emergent trends on conceptual modeling and information systems engineering, bridging the gap between research and practice by providing a much-needed reference point on the design of software systems that evolve seamlessly to adapt to rapidly changing business and organizational practices.

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.

Managers today are experiencing an increased focus on emergent collaborative technologies designed to enable virtual organization users to share resources and accomplish complex tasks better. Grid Technology for Maximizing Collaborative Decision Management and Support: Advancing Effective Virtual Organizations provides a state-of-the-art collection of opportunities and applicable practices of grid technology to sustain competitive advantage. Offering a collection of international research studies by leading experts, this book describes how grid technology can be applied to serve the purpose within interconnected organizations in an effective and efficient collaborative setting.

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 addresses major challenges faced by farmers and the technological solutions based on Internet of Things (IoT). A major challenge in agriculture is cultivating and supplying high-quality produce at the best. Currently, around 50% of global farm produce never reaches the end consumer due to wastage and suboptimal prices. The book presents solutions that reduce the transport costs, improve the predictability of prices based on data analytics and the current market conditions, and reduce the number of middle steps and agents between the farmer and the end consumer. It discusses the design of an IoT-based monitoring system to analyze crop environments and a method to improve the efficiency of decision-making by analyzing harvest statistics. Further, it explores climate-smart methods, known as smart agriculture, that have been adopted by a number of Indian farmers.

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.

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 presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.

Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guide CompTIA Data+ Study Guide: Exam DA0-001 delivers easily accessible and actionable instruction for achieving data analysis competencies required for the job and on the CompTIA Data+ certification exam. You'll learn to collect, analyze, and report on various types of commonly used data, transforming raw data into usable information for stakeholders and decision makers. With comprehensive coverage of data concepts and environments, data mining, data analysis, visualization, and data governance, quality, and controls, this Study Guide offers: All the information necessary to succeed on the exam for a widely accepted, entry-level credential that unlocks lucrative new data analytics and data science career opportunities 100% coverage of objectives for the NEW CompTIA Data+ exam Access to the Sybex online learning resources, with review questions, full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms Ideal for anyone seeking a new career in data analysis, to improve their current data science skills, or hoping to achieve the coveted CompTIA Data+ certification credential, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst.

This book intersects the distributed ledger technology (DLT) community with the international security community. Given the increasing application of blockchain technology in the fields of business and international development, there is a growing body of study on other use cases. For instance, can blockchain have a significant role in preserving and improving international security? This book explores this question in the context of preventing the proliferation of some of the most dangerous materials in the world-items that if not secured can lend to the development of weapons of mass destruction. It considers how blockchain can increase efficiencies in the global trade of nuclear and chemical materials and technology, thereby increasing assurances related to compliance with international nonproliferation and disarmament treaties.

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.

This book provides the first extensive survey of block ciphers following the Lai-Massey design paradigm. After the introduction, with historical remarks, the author structures the book into a chapter on the description of the PES, IDEA and other related ciphers, followed by a chapter on cryptanalysis of these ciphers, and another chapter on new cipher designs. The appendices include surveys of cryptographic substitution boxes and of MDS codes. This comprehensive treatment can serve as a reference source for researchers, students and practitioners.

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 introduces research presented at the "International Conference on Artificial Intelligence: Advances and Applications-2019 (ICAIAA 2019)," a two-day conference and workshop bringing together leading academicians, researchers as well as students to share their experiences and findings on all aspects of engineering applications of artificial intelligence. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business and security. It also includes research in core concepts of computer networks, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, SDN and NFV. As such it is a valuable resource for students, academics and practitioners in industry working on AI applications.

This volume presents the second part of the proceedings of the Mediterranean Conference on Information & Communication Technologies (MedICT 2015), which was held at Saidia, Morocco during 7-9 May, 2015. MedICT provides an excellent international forum to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development. The conference has also a special focus on enabling technologies for societal challenges, and seeks to address multidisciplinary challenges in Information & Communication Technologies such as health, demographic change, wellbeing, security and sustainability issues. The proceedings publish high quality papers which are closely related to the various theories, as well as emerging and practical applications of particular interest to the ICT community. This second volume provides a compact yet broad view of recent developments in Data, Systems, Services and Education, and covers recent research areas in the field including Control Systems, Software Engineering, Data Mining and Big Data, ICT for Education and Support Activities, Networking, Cloud Computing and Security, ICT Based Services and Applications, Mobile Agent Systems, Software Engineering, Data Mining and Big Data, Online Experimentation & Artificial Intelligence in Education, Networking, Cloud Computing and Security, ICT Based Education and Services ICT Challenges and Applications, Advances in ICT Modeling and Design ICT Developments.

This uniquely accessible book helps readers use CABology to solve real-world business problems and drive real competitive advantage. It provides reliable, concise information on the real benefits, usage and operationalization aspects of utilizing the "Trio Wave" of cloud, analytic and big data. Anyone who thinks that the game changing technology is slow paced needs to think again. This book opens readers' eyes to the fact that the dynamics of global technology and business are changing. Moreover, it argues that businesses must transform themselves in alignment with the Trio Wave if they want to survive and excel in the future. CABology focuses on the art and science of optimizing the business goals to deliver true value and benefits to the customer through cloud, analytic and big data. It offers business of all sizes a structured and comprehensive way of discovering the real benefits, usage and operationalization aspects of utilizing the Trio Wave.

This book provides an overview of the problems involved in engineering scalable, elastic, and cost-efficient cloud computing services and describes the CloudScale method - a description of rescuing tools and the required steps to exploit these tools. It allows readers to analyze the scalability problem in detail and identify scalability anti-patterns and bottlenecks within an application. With the CloudScale method, software architects can analyze both existing and planned IT services. The method allows readers to answer questions like: * With an increasing number of users, can my service still deliver acceptable quality of service? * What if each user uses the service more intensively? Can my service still handle it with acceptable quality of service? * What if the number of users suddenly increases? Will my service still be able to handle it? * Will my service be cost-efficient? First the book addresses the importance of scalability, elasticity, and cost-efficiency as vital quality-related attributes of modern cloud computing applications. Following a brief overview of CloudScale, cloud computing applications are then introduced in detail and the aspects that need to be captured in models of such applications are discussed. In CloudScale, these aspects are captured in instances of the ScaleDL modeling language. Subsequently, the book describes the forward engineering part of CloudScale, which is applicable when developing a new service. It also outlines the reverse and reengineering parts of CloudScale, which come into play when an existing (legacy) service is modified. Lastly, the book directly focuses on the needs of both business-oriented and technical managers by providing guidance on all steps of implementing CloudScale as well as making decisions during that implementation. The demonstrators and reference projects described serve as a valuable starting point for learning from experience. This book is meant for all stakeholders interested in delivering scalable, elastic, and cost-efficient cloud computing applications: managers, product owners, software architects and developers alike. With this book, they can both see the overall picture as well as dive into issues of particular interest.

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.

This two-volume set of IFIP AICT 617 and 618 constitutes the refereed proceedings of the IFIP WG 8.6 International Working Conference "Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation" on Transfer and Diffusion of IT, TDIT 2020, held in Tiruchirappalli, India, in December 2020.The 86 revised full papers and 36 short papers presented were carefully reviewed and selected from 224 submissions. The papers focus on the re-imagination of diffusion and adoption of emerging technologies. They are organized in the following parts: Part I: artificial intelligence and autonomous systems; big data and analytics; blockchain; diffusion and adoption technology; emerging technologies in e-Governance; emerging technologies in consumer decision making and choice; fin-tech applications; healthcare information technology; and Internet of Things Part II: information technology and disaster management; adoption of mobile and platform-based applications; smart cities and digital government; social media; and diffusion of information technology and systems

This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments. This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.

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 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.

This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.