This book provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. Topics and features: includes perspectives from an international and interdisciplinary selection of pre-eminent authorities; presents balanced coverage of both detailed theoretical analysis and real-world applications; examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications; reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities; discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation.

This book constitutes the refereed proceedings of the 17th International Conference on Engineering Applications of Neural Networks, EANN 2016, held in Aberdeen, UK, in September 2016. The 22 revised full papers and three short papers presented together with two tutorials were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections on active learning and dynamic environments; semi-supervised modeling; classification applications; clustering applications; cyber-physical systems and cloud applications; time-series prediction; learning-algorithms.

This comprehensive textbook/reference presents a focused review of the state of the art in privacy research, encompassing a range of diverse topics. The first book of its kind designed specifically to cater to courses on privacy, this authoritative volume provides technical, legal, and ethical perspectives on privacy issues from a global selection of renowned experts. Features: examines privacy issues relating to databases, P2P networks, big data technologies, social networks, and digital information networks; describes the challenges of addressing privacy concerns in various areas; reviews topics of privacy in electronic health systems, smart grid technology, vehicular ad-hoc networks, mobile devices, location-based systems, and crowdsourcing platforms; investigates approaches for protecting privacy in cloud applications; discusses the regulation of personal information disclosure and the privacy of individuals; presents the tools and the evidence to better understand consumers' privacy behaviors.

This thesis focuses on the problem of optimizing the quality of network multimedia services. This problem spans multiple domains, from subjective perception of multimedia quality to computer networks management. The work done in this thesis approaches the problem at different levels, developing methods for modeling the subjective perception of quality based on objectively measurable parameters of the multimedia coding process as well as the transport over computer networks. The modeling of subjective perception is motivated by work done in psychophysics, while using Machine Learning techniques to map network conditions to the human perception of video services. Furthermore, the work develops models for efficient control of multimedia systems operating in dynamic networked environments with the goal of delivering optimized Quality of Experience. Overall this thesis delivers a set of methods for monitoring and optimizing the quality of multimedia services that adapt to the dynamic environment of computer networks in which they operate.

Information Systems (IS) as a discipline draws on diverse areas including, technology, organisational theory, management and social science. The field is recognized as very broad and encompassing many themes and areas. However, the development of artefacts, or information systems development (ISD), in the broadest sense, is a central concern of the discipline. Significantly, ISD impacts on the organisational and societal contexts through the use of the artefacts constructed by the development. Today, that impact also needs to be evaluated in terms of its effects on the environment. Sustainable, or "green," IT is a catch-all term used to describe the development, manufacture, management, use and disposal of ICT in a way that minimizes damage to the environment. As a result, the term has many different meanings, depending on the role assumed in the life span of the ICT artefact. The theme of the proposed work is to critically examine the whole range of issues around ISD from the perspective of sustainability. Sustainable IT is an emerging theme in academic research and industry practice in response to an individual concern for the environment and the embryonic regulatory environments being enacted globally to address the environmental impact of ICT. In this work we intend to bring together in one volume the diverse research around the development of sustainable IS.

This book examines the principles of and advances in personalized task recommendation in crowdsourcing systems, with the aim of improving their overall efficiency. It discusses the challenges faced by personalized task recommendation when crowdsourcing systems channel human workforces, knowledge, skills and perspectives beyond traditional organizational boundaries. The solutions presented help interested individuals find tasks that closely match their personal interests and capabilities in a context of ever-increasing opportunities of participating in crowdsourcing activities. In order to explore the design of mechanisms that generate task recommendations based on individual preferences, the book first lays out a conceptual framework that guides the analysis and design of crowdsourcing systems. Based on a comprehensive review of existing research, it then develops and evaluates a new kind of task recommendation service that integrates with existing systems. The resulting prototype provides a platform for both the field study and the practical implementation of task recommendation in productive environments.

Proper analysis of image and multimedia data requires efficient extraction and segmentation techniques. Among the many computational intelligence approaches, the soft computing paradigm is best equipped with several tools and techniques that incorporate intelligent concepts and principles. This book is dedicated to object extraction, image segmentation, and edge detection using soft computing techniques with extensive real-life application to image and multimedia data. The authors start with a comprehensive tutorial on the basics of brain structure and learning, and then the key soft computing techniques, including evolutionary computation, neural networks, fuzzy sets and fuzzy logic, and rough sets. They then present seven chapters that detail the application of representative techniques to complex image processing tasks such as image recognition, lighting control, target tracking, object extraction, and edge detection. These chapters follow a structured approach with detailed explanations of the problems, solutions, results, and conclusions. This is both a standalone textbook for graduates in computer science, electrical engineering, system science, and information technology, and a reference for researchers and engineers engaged with pattern recognition, image processing, and soft computing.

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient's medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more. This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter. Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

This two-volume set (LNAI 9875 and LNAI 9876) constitutes the refereed proceedings of the 8th International Conference on Collective Intelligence, ICCCI 2016, held in Halkidiki, Greece, in September 2016. The 108 full papers presented were carefully reviewed and selected from 277 submissions. The aim of this conference is to provide an internationally respected forum for scientific research in the computer-based methods of collective intelligence and their applications in (but not limited to) such fields as group decision making, consensus computing, knowledge integration, semantic web, social networks and multi-agent systems.

This book comprises a set of articles that specify the methodology of text mining, describe the creation of lexical resources in the framework of text mining and use text mining for various tasks in natural language processing (NLP). The analysis of large amounts of textual data is a prerequisite to build lexical resources such as dictionaries and ontologies and also has direct applications in automated text processing in fields such as history, healthcare and mobile applications, just to name a few. This volume gives an update in terms of the recent gains in text mining methods and reflects the most recent achievements with respect to the automatic build-up of large lexical resources. It addresses researchers that already perform text mining, and those who want to enrich their battery of methods. Selected articles can be used to support graduate-level teaching. The book is suitable for all readers that completed undergraduate studies of computational linguistics, quantitative linguistics, computer science and computational humanities. It assumes basic knowledge of computer science and corpus processing as well as of statistics.

This book constitutes the proceedings of the 14th International Workshop on Knowledge Management and Acquisition for Intelligent Systems, PKAW 2016, held in Phuket, Thailand, in August 2016. The 16 full papers and 5 short papers included in this volume were carefully reviewed and selected from 61 initial submissions. They deal with knowledge acquisition and machine learning; knowledge acquisition and natural language processing; knowledge acquisition from network and big data; and knowledge acquisition and applications.

Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.

This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the visual reasoning processes of people with the computation. This methodology affords user interaction on visual data representations that are native to the domain of the data. User interaction in visual analytics systems is critical to enabling visual data exploration. Interaction transforms people from mere viewers to active participants in the process of analyzing and understanding data. This discourse between people and data enables people to understand aspects of their data, such as structure, patterns, trends, outliers, and other properties that ultimately result in insight. Through interacting with visualizations, users engage in sensemaking, a process of developing and understanding relationships within datasets through foraging and synthesis. The book provides a description of the principles of semantic interaction, providing design guidelines for the integration of semantic interaction into visual analytics, examples of existing technologies that leverage semantic interaction, and a discussion of how to evaluate these technologies. Semantic interaction has the potential to increase the effectiveness of visual analytic technologies and opens possibilities for a fundamentally new design space for user interaction in visual analytics systems.

This book constitutes the refereed proceedings of the 15th International Conference on Systems Simulation, Asia Simulation 2015, held in Jeju, Korea, in November 2016.The 11 revised full papers presented were carefully reviewed and selected from 126 submissions. The papers are organized in topical sections on model and design; simulation and analysis.

This, the 27th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of 12 papers presented at the Big Data and Technology for Complex Urban Systems symposium, held in Kauai, HI, USA in January 2016. The papers explore the use of big data in complex urban systems in the areas of politics, society, commerce, tax, and emergency management.

In this book, the authors describe how Mind Genomics works - a revolutionary marketing method that combines the three sciences of Mathematics, Psychology, and Economics - in a masterful way. Mind Genomics helps the seller of products and services to know what people are thinking about them before one ever commits to an approach by knowing what is important to the people one is trying to influence. Mind Genomics identifies what aspects of a general topic are important to the audience, how different people in the audience will respond to different aspects of that topic, and how to pinpoint the viewpoints of different audience segments to each aspect of the topic. A careful step by step approach explains what activities ought to be taken and what scenarios must be followed while applying this method in order to find the right way to capture the hearts and minds of targeted audiences. This book explains how Mind Genomics plays a matching game with one's potential audience and various ways one can present the products and ideas resulting in a systematic approach to influencing others, backed by real data; how one can play with ideas, see patterns imposed by the mind and create new, inductive, applied sciences of the mind, measuring the world using the mind of man as the yardstick. In details it describes how everyday thought is transferred into actionable data and results. Whether one is a senior marketer for a large corporation, a professor at a university, or administrator at a hospital, one could use Mind Genomics to learn how to transform available information into actionable steps that will increase the products sales, or increase the number of interested students for a new university program, or the number of satisfied patients in the hospital with their medical conditions kept at highest levels after leaving it. Mind Genomics was first introduced by Dr. Howard Moskowitz, an alumnus of Harvard University and the father of Horizontal Segmentation - a widely accepted business model for targeted marketing and profit maximization.

New technologies have enabled us to collect massive amounts of data in many fields. However, our pace of discovering useful information and knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains a comprehensive set of data mining algorithms from various data mining fields. The book reviews theoretical rationales and procedural details of data mining algorithms, including those commonly found in the literature and those presenting considerable difficulty, using small data examples to explain and walk through the algorithms. The book covers a wide range of data mining algorithms, including those commonly found in data mining literature and those not fully covered in most of existing literature due to their considerable difficulty. The book presents a list of software packages that support the data mining algorithms, applications of the data mining algorithms with references, and exercises, along with the solutions manual and PowerPoint slides of lectures. The author takes a practical approach to data mining algorithms so that the data patterns produced can be fully interpreted. This approach enables students to understand theoretical and operational aspects of data mining algorithms and to manually execute the algorithms for a thorough understanding of the data patterns produced by them.

This book constitutes the refereed proceedings of the 6th International Conference on Well-Being in the Information Society, WIS 2016, held in Tampere, Finland, in September 2016. The 21 revised full papers presented were carefully reviewed and selected from 42 submissions. With the core topic "Building Sustainable Health Ecosystems" WIS 2016 focused on innovations and fresh ideas in the cross-section of urban living, information society and health as understood in a wide sense. The papers presented in this volume are organized along the following seven broad topics: 1. Macro level considerations of e-health and welfare, 2.Welfare issues of children, youth, young elderly and seniors, 3. Analytics issues of eHealth and welfare, 4. National/regional initiatives in eHealth and welfare, and 5. Specific topics of eHealth. The papers in these topics span qualitative and quantitative analysis, empirical surveys, case studies as well as conceptual work.

Learn SQL Server Reporting Services and become current with the 2016 edition. Develop interactive, dynamic reports that combine graphs, charts, and tabular data into attractive dashboards and reports to delight business analysts and other users of corporate data. Deliver mobile reports to anywhere and any device. Build vital knowledge of Reporting Services at a time when Microsoft's dominance in business intelligence is on the rise. Beginning SQL Server Reporting Services turns novices into skilled report developers. The book begins by explaining how to set up the development environment. It then walks you through creating your first reports using the built-in wizard. After showing what is possible, the book breaks down and explains the skills needed to create reports from scratch. And not just reports! But also dashboards with charts, graphs, and maps. Each chapter builds on knowledge gained in the previous chapters with step-by-step tutorials. Beginning SQL Server Reporting Services boosts your skills and provides you additional career options. Don't be without those options. Grab and read this book today. Build reports with and without the built-in wizard. Build interactive features such as drill-through reports. Build dashboards full of charts, graphs, and maps. Build mobile reports. What You Will Learn Set up your development environment. Organized projects and share components among reports. Create report using a wizard. Create reports from scratch, including grouping levels, parameters, and drill through features. Build interactive dashboard with graphs, charts, and maps. Deploy and manage reports for use by others in the business. Who This Book Is For Database professionals of all experience levels who have some experience in databases and want to make the leap into business intelligence reporting. The book is an excellent choice for those needing to add Reporting Services to their current list of skills, or who are looking for a skill set that is in demand for in order to break into IT.

This book offers a thorough yet easy-to-read reference guide to various aspects of cloud computing security. It begins with an introduction to the general concepts of cloud computing, followed by a discussion of security aspects that examines how cloud security differs from conventional information security and reviews cloud-specific classes of threats and attacks. A range of varying threats in cloud computing are covered, from threats of data loss and data breaches, to threats to availability and threats posed by malicious insiders. Further, the book discusses attacks launched on different levels, including attacks on the hypervisor, and on the confidentiality of data. Newer types, such as side-channel attacks and resource-freeing attacks, are also described. The work closes by providing a set of general security recommendations for the cloud.

This book reports on cutting-edge research carried out within the context of the EU-funded Dicode project, which aims at facilitating and augmenting collaboration and decision making in data-intensive and cognitively complex settings. Whenever appropriate, Dicode builds on prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze, and aggregate data from diverse, extremely large and rapidly evolving sources. The Dicode approach and services are fully explained and particular emphasis is placed on deepening insights regarding the exploitation of big data, as well as on collaboration and issues relating to sense-making support. Building on current advances, the solution developed in the Dicode project brings together the reasoning capabilities of both the machine and humans. It can be viewed as an innovative "workbench" incorporating and orchestrating a set of interoperable services that reduce the data intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and effective in their work practices.

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.

Recently, the pressure for fast processing and efficient storage of large data with complex relations increased beyond the capability of traditional databases. Typical examples include iPhone applications, computer aided design - both electrical and mechanical, biochemistry applications, and incremental compilers. Serialization, which is sometimes used in such situations is notoriously tedious and error prone. In this book, Jiri Soukup and Petr Machacek show in detail how to write programs which store their internal data automatically and transparently to disk. Together with special data structure libraries which treat relations among objects as first-class entities, and with a UML class-diagram generator, the core application code is much simplified. The benchmark chapter shows a typical example where persistent data is faster by the order of magnitude than with a traditional database, in both traversing and accessing the data. The authors explore and exploit advanced features of object-oriented languages in a depth hardly seen in print before. Yet, you as a reader need only a basic knowledge of C++, Java, C#, or Objective C. These languages are quite similar with respect to persistency, and the authors explain their differences where necessary. The book targets professional programmers working on any industry applications, it teaches you how to design your own persistent data or how to use the existing packages efficiently. Researchers in areas like language design, compiler construction, performance evaluation, and no-SQL applications will find a wealth of novel ideas and valuable implementation tips. Under http://www.codefarms.com/book, you will find a blog and other information, including a downloadable zip file with the sources of all the listings that are longer than just a few lines - ready to compile and run.

This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data. The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers. The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.

Advance Praise for Indian Mujahideen: Computational Analysis and Public Policy "This book presents a highly innovative computational approach to analyzing the strategic behavior of terrorist groups and formulating counter-terrorism policies. It would be very useful for international security analysts and policymakers." Uzi Arad, National Security Advisor to the Prime Minister of Israel and Head, Israel National Security Council (2009-2011) "An important book on a complex security problem. Issues have been analysed in depth based on quality research. Insightful and well-balanced in describing the way forward." Naresh Chandra, Indian Ambassador to the USA (1996-2001) and Cabinet Secretary (1990-1992). "An objective and clinical account of the origins, aims, extra-territorial links and modus-operandi, of a growingly dangerous terrorist organization that challenges the federal, democratic, secular and pluralistic ethos of India's polity. The authors have meticulously researched and analysed the multi-faceted challenges that the "Indian Mujahideen" poses and realistically dwelt on the ways in which these challenges could be faced and overcome." G. Parthasarathy, High Commissioner of India to Australia (1995-1998) and Pakistan (1998-2000). This book provides the first in-depth look at how advanced mathematics and modern computing technology can influence insights on analysis and policies directed at the Indian Mujahideen (IM) terrorist group. The book also summarizes how the IM group is committed to the destabilization of India by leveraging links with other terror groups such as Lashkar-e-Taiba, and through support from the Pakistani Government and Pakistan's intelligence service. Foreword by The Hon. Louis J. Freeh.