This book constitutes the refereed post-conference proceedings of the 10th IFIP WG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2016, held in Dongying, China, in October 2016. The 55 revised papers presented were carefully reviewed and selected from 128 submissions. They cover a wide range of interesting theories and applications of information technology in agriculture, including intelligent sensing, cloud computing, key technologies of the Internet of Things, precision agriculture, animal husbandry information technology, including Internet + modern animal husbandry, livestock big data platform and cloud computing applications, intelligent breeding equipment, precision production models, water product networking and big data , including fishery IoT, intelligent aquaculture facilities, and big data applications.

The successful implementation and deployment of Enterprise Resource Planning hinges on an organization's understanding of the complex and challenging issues involved in the process. And, the further development of information and communication technologies are presenting more challenges to organizations. ERP & Data Warehousing in Organizations: Issues and Challenges attempts to provide the most recent research and findings concerning these issues, in order to provide practical assessments and suggestions for managers in the process of developing such systems.

Data science has been playing a vital role in almost all major fields. Many researchers are interested in the development of IT applications, which are user-driven with a focus on issues. This can be addressed using data science. User-driven research and data science have gained much attention from many private, public, and government organizations and research institutions. The Handbook of Research on Designing User Interfaces With a Data Science Approach promotes the inclusion of more diversified users for user-centered designs of applications across domains and analyzes user data with a data science approach for effective and user-friendly user interface designs. It introduces the foundations of advanced topics of human-computer interaction, particularly with user-centered designs and techniques. Covering topics such as artificial neural networks, natural dialog systems, and machine learning, this book is an essential resource for faculty, research scholars, industry professionals, students of higher education, mathematicians, data scientists, interaction designers, visual designers, software engineers, user experience researchers, accessibility engineers, cognitive system engineers, academicians, and libraries.

With the proliferation of Software-as-a-Service (SaaS) offerings, it is becoming increasingly important for individual SaaS providers to operate their services at a low cost. This book investigates SaaS from the perspective of the provider and shows how operational costs can be reduced by using "multi tenancy," a technique for consolidating a large number of customers onto a small number of servers. Specifically, the book addresses multi tenancy on the database level, focusing on in-memory column databases, which are the backbone of many important new enterprise applications. For efficiently implementing multi tenancy in a farm of databases, two fundamental challenges must be addressed, (i) workload modeling and (ii) data placement. The first involves estimating the (shared) resource consumption for multi tenancy on a single in-memory database server. The second consists in assigning tenants to servers in a way that minimizes the number of required servers (and thus costs) based on the assumed workload model. This step also entails replicating tenants for performance and high availability. This book presents novel solutions to both problems.

This book presents a unified framework, based on specialized evolutionary algorithms, for the global induction of various types of classification and regression trees from data. The resulting univariate or oblique trees are significantly smaller than those produced by standard top-down methods, an aspect that is critical for the interpretation of mined patterns by domain analysts. The approach presented here is extremely flexible and can easily be adapted to specific data mining applications, e.g. cost-sensitive model trees for financial data or multi-test trees for gene expression data. The global induction can be efficiently applied to large-scale data without the need for extraordinary resources. With a simple GPU-based acceleration, datasets composed of millions of instances can be mined in minutes. In the event that the size of the datasets makes the fastest memory computing impossible, the Spark-based implementation on computer clusters, which offers impressive fault tolerance and scalability potential, can be applied.

The purpose of this book is to review the recent advances in E-health technologies and applications. In particular, the book investigates the recent advancements in physical design of medical devices, signal processing and emergent wireless technologies for E-health. In a second part, novel security and privacy solutions for IoT-based E-health applications are presented. The last part of the book is focused on applications, data mining and data analytics for E-health using artificial intelligence and cloud infrastructure. E-health has been an evolving concept since its inception, due to the numerous technologies that can be adapted to offer new innovative and efficient E-health applications. Recently, with the tremendous advancement of wireless technologies, sensors and wearable devices and software technologies, new opportunities have arisen and transformed the E-health field. Moreover, with the expansion of the Internet of Things, and the huge amount of data that connected E-health devices and applications are generating, it is also mandatory to address new challenges related to the data management, applications management and their security. Through this book, readers will be introduced to all these concepts. This book is intended for all practitioners (industrial and academic) interested in widening their knowledge in wireless communications and embedded technologies applied to E-health, cloud computing, artificial intelligence and big data for E-health applications and security issues in E-health.

This book discusses the challenges in the convergence of technologies as the Internet of Things (IoT) evolves. These include sensing, computing, information processing, networking, and controlling intelligent technologies. The contributors first provide a survey of various assessment and evaluation approaches available for successful convergence. They then go on to cover several operational ideas to apply. The contributors then discuss the challenges involved bridging gaps in computation and the communication process, hidden networks, intelligent decision making, human-to-machine perception and large-scale IoT environments. The contributors aim to provide the reader an overview of trends in IoT in terms of performability and traffic modeling and efforts that can be spent in assessing the graceful degradation in IoT paradigms. Provides a survey of IoT assessment and evaluation approaches; Covers new and innovative operational ideas that apply to the IoT industry and the industries it affects; Includes chapters from researchers and industry leaders in IoT from around the world.

This book documents the creation of the Bichitra Online Tagore Variorum, a publicly accessible database of Rabindranath Tagore's complete works in Bengali and English totaling some 140,000 pages of primary material. Chapters cover innovative aspects of the site, all replicable in other projects: a hyperbibliography; a search engine and hyperconcordance working across the database; and a unique collation program comparing variant texts at three levels. There are also chapters on the special problems of processing manuscripts, and on planning the website. Early chapters take readers through the history of the project, an overview of Tagore's works, and the Bengali writing system with the challenges of adapting it to electronic form. The name Bichitra, meaning "various" in Bengali, alludes both to the great variety of Tagore's works and to their various stages of composition. Beyond their literary excellence, they are notable for their sheer quantity, the number of variant forms of a great many items, and their afterlife in translation, often the poet's own. Seldom if ever has the same writer revised his material and recast it across genres on such a scale. Tagore won the Nobel Prize in 1913. By its value-added presentation of this range of material, Bichitra can be a model for future databases covering an author's complete works or other major corpus of texts. It offers vastly expanded access to Tagore's writings, and enables new kinds of research including computational text analysis. The "book of the website" shows in technical and human terms how researchers with interests in art, literature and technology can collaborate on cultural informatics projects.

This book introduces new logic primitives for electronic design automation tools. The author approaches fundamental EDA problems from a different, unconventional perspective, in order to demonstrate the key role of rethinking EDA solutions in overcoming technological limitations of present and future technologies. The author discusses techniques that improve the efficiency of logic representation, manipulation and optimization tasks by taking advantage of majority and biconditional logic primitives. Readers will be enabled to accelerate formal methods by studying core properties of logic circuits and developing new frameworks for logic reasoning engines.

This book provides an overview of the research work on data privacy and privacy enhancing technologies carried by the participants of the ARES project. ARES (Advanced Research in Privacy an Security, CSD2007-00004) has been one of the most important research projects funded by the Spanish Government in the fields of computer security and privacy. It is part of the now extinct CONSOLIDER INGENIO 2010 program, a highly competitive program which aimed to advance knowledge and open new research lines among top Spanish research groups. The project started in 2007 and will finish this 2014. Composed by 6 research groups from 6 different institutions, it has gathered an important number of researchers during its lifetime. Among the work produced by the ARES project, one specific work package has been related to privacy. This books gathers works produced by members of the project related to data privacy and privacy enhancing technologies. The presented works not only summarize important research carried in the project but also serve as an overview of the state of the art in current research on data privacy and privacy enhancing technologies.

This book presents the state-of-the-art in various aspects of analysis and mining of online social networks. Within the broader context of online social networks, it focuses on important and upcoming topics of social network analysis and mining such as the latest in sentiment trends research and a variety of techniques for community detection and analysis. The book collects chapters that are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2015), which was held in Paris, France in August 2015. All papers have been peer reviewed and checked carefully for overlap with the literature. The book will appeal to students and researchers in social network analysis/mining and machine learning.

This book presents the basics of search engines and their components. It introduces, for the first time, the concept of Cellular Automata in Web technology and discusses the prerequisites of Cellular Automata. In today's world, searching data from the World Wide Web is a common phenomenon for virtually everyone. It is also a fact that searching the tremendous amount of data from the Internet is a mammoth task - and handling the data after retrieval is even more challenging. In this context, it is important to understand the need for space efficiency in data storage. Though Cellular Automata has been utilized earlier in many fields, in this book the authors experiment with employing its strong mathematical model to address some critical issues in the field of Web Mining.

"Data Warehousing in the Age of the Big Data "will help you and your organization make the most of unstructured data with your existing data warehouse.

As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data-ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory.

Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse.
Learn how to leverage Big Data by effectively integrating it into your data warehouse. Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

The book reports on advanced theories and methods in two related engineering fields: electrical and electronic engineering, and communications engineering and computing. It highlights areas of global and growing importance, such as renewable energy, power systems, mobile communications, security and the Internet of Things (IoT). The contributions cover a number of current research issues, including smart grids, photovoltaic systems, wireless power transfer, signal processing, 4G and 5G technologies, IoT applications, mobile cloud computing and many more. Based on the proceedings of the first International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM 2016), held in Voila Bagatelle, Mauritius from November 25 to 27, 2016, the book provides graduate students, researchers and professionals with a snapshot of the state-of-the-art and a source of new ideas for future research and collaborations.

The objective of this book is to contribute to the development of the intelligent information and database systems with the essentials of current knowledge, experience and know-how. The book contains a selection of 40 chapters based on original research presented as posters during the 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016) held on 14-16 March 2016 in Da Nang, Vietnam. The papers to some extent reflect the achievements of scientific teams from 17 countries in five continents. The volume is divided into six parts: (a) Computational Intelligence in Data Mining and Machine Learning, (b) Ontologies, Social Networks and Recommendation Systems, (c) Web Services, Cloud Computing, Security and Intelligent Internet Systems, (d) Knowledge Management and Language Processing, (e) Image, Video, Motion Analysis and Recognition, and (f) Advanced Computing Applications and Technologies. The book is an excellent resource for researchers, those working in artificial intelligence, multimedia, networks and big data technologies, as well as for students interested in computer science and other related fields.

With the increasing advances in hardware technology for data collection, and advances in software technology (databases) for data organization, computer scientists have increasingly participated in the latest advancements of the outlier analysis field. Computer scientists, specifically, approach this field based on their practical experiences in managing large amounts of data, and with far fewer assumptions- the data can be of any type, structured or unstructured, and may be extremely large. Outlier Analysis is a comprehensive exposition, as understood by data mining experts, statisticians and computer scientists. The book has been organized carefully, and emphasis was placed on simplifying the content, so that students and practitioners can also benefit. Chapters will typically cover one of three areas: methods and techniques commonly used in outlier analysis, such as linear methods, proximity-based methods, subspace methods, and supervised methods; data domains, such as, text, categorical, mixed-attribute, time-series, streaming, discrete sequence, spatial and network data; and key applications of these methods as applied to diverse domains such as credit card fraud detection, intrusion detection, medical diagnosis, earth science, web log analytics, and social network analysis are covered.

The main objectives of this book are to expose key aspects that have a relevance when dealing with open data viewed from different perspectives and to provide appealing examples of how open data is implemented worldwide. The concept of open data as we know it today is the result of many different initiatives, both of a legislative and non-legislative nature, and promoted by a wide range of actors. Numerous regulatory antecedents to foster the concept of open data and embed it in national and international policy agendas have been undertaken on both sides of the Atlantic, as well as at a supranational level. The book highlights a number of the efforts made to promote open data in Europe, Asia and the United States. In addition to new insights, practical guidance and multiple disciplinary perspectives on open data, the book also addresses the transformation of current developments towards open data, which may be referred to as the democratisation of data. This book will support open data practitioners as well as open data scholars in their endeavours to promote open data implementation and research. Bastiaan van Loenen is associate professor and director of the Knowledge Centre Open Data at the Faculty of Architecture and The Built Environment of Delft University of Technology in the Netherlands, as is Glenn Vancauwenberghe, who is a post-doctoral researcher, and Joep Crompvoets is a professor at the Public Governance Institute of the KU Leuven in Belgium.

This book provides a critical examination of how the choice of what to believe is represented in the standard model of belief change. In particular the use of possible worlds and infinite remainders as objects of choice is critically examined. Descriptors are introduced as a versatile tool for expressing the success conditions of belief change, addressing both local and global descriptor revision. The book presents dynamic descriptors such as Ramsey descriptors that convey how an agent's beliefs tend to be changed in response to different inputs. It also explores sentential revision and demonstrates how local and global operations of revision by a sentence can be derived as a special case of descriptor revision. Lastly, the book examines revocation, a generalization of contraction in which a specified sentence is removed in a process that may possibly also involve the addition of some new information to the belief set.

This volume contains nineteen research papers belonging to the areas of computational statistics, data mining, and their applications. Those papers, all written specifically for this volume, are their authors' contributions to honour and celebrate Professor Jacek Koronacki on the occcasion of his 70th birthday. The book's related and often interconnected topics, represent Jacek Koronacki's research interests and their evolution. They also clearly indicate how close the areas of computational statistics and data mining are.

This book examines the methodological foundations of the Big Data-driven world, formulates its concept within the frameworks of modern control methods and theories, and approaches the peculiarities of Control Technologies as a specific sphere of the Big Data-driven world, distinguished in the modern Digital Economy. The book studies the genesis of mathematical and information methods' transition from data analysis & processing to knowledge discovery and predictive analytics in the 21st century. In addition, it analyzes the conditions of development and implementation of Big Data analysis approaches in investigative activities and determines the role and meaning of global networks as platforms for the establishment of legislation and regulations in the Big Data-driven world. The book examines that world through the prism of Legislation Issues, substantiate the scientific and methodological approaches to studying modern mechanisms of terrorism and extremism counteraction in the conditions of new challenges of dissemination and accessibility of socially dangerous information. Systematization of successful experience of the Big Data solutions implementation in the different countries and analyze causal connections of the Digital Economy formation from the positions of new technological challenges is performed. The book's target audience includes scientists, students, PhD and Master students who conduct scientific research on the topic of Big Data not only in the field of IT& data science, but also in connection with legislative regulation aspects of the modern information society. It also includes practitioners and experts, as well as state authorities and representatives of international organizations interested in creating mechanisms for implementing Digital Economy projects in the Big Data-driven world.

This volume complies a set of Data Mining techniques and new applications in real biomedical scenarios. Chapters focus on innovative data mining techniques, biomedical datasets and streams analysis, and real applications. Written in the highly successful Methods in Molecular Biology series format, chapters are thought to show to Medical Doctors and Engineers the new trends and techniques that are being applied to Clinical Medicine with the arrival of new Information and Communication technologies Authoritative and practical, Data Mining in Clinical Medicine seeks to aid scientists with new approaches and trends in the field.

This book provides recent results of game theory for networking applications. The contributors address the major opportunities and challenges in applying traditional game theory as well as intelligent game theory to the understanding and designing of modern network systems, with emphasis on both new analytical techniques and novel application scenarios. After an overview of game theory for networks, the book narrows in on game theory in communications, game theory in wireless networks, and game theory applications. The book features contributions from researchers and professionals around the world. Presents a variety of perspectives on game theory for networking applications; Shows how game theory can apply to the study of data traffic, new generation networks, and smartgrid; Includes recent results of applied game theory for networks, providing some technical progresses in GAMENETS.

This book highlights technical advances in knowledge management and their applications across a diverse range of domains. It explores the applications of knowledge computing methodologies in image processing, pattern recognition, health care and industrial contexts. The chapters also examine the knowledge engineering process involved in information management. Given its interdisciplinary nature, the book covers methods for identifying and acquiring valid, potentially useful knowledge sources. The ideas presented in the respective chapters illustrate how to effectively apply the perspectives of knowledge computing in specialized domains.

This book offers practical advice on managing enterprise modeling (EM) projects and facilitating participatory EM sessions. Modeling activities often involve groups of people, and models are created in a participatory way. Ensuring that this is done efficiently requires dedicated individuals who know how to organize modeling projects and sessions, how to manage discussions during these sessions, and what aspects influence the success and efficiency of modeling in practice. The book also includes a summary of the theoretical background to EM, although participatory modeling can also be used in conjunction with other methods that are not made for EM, such as those made for goal-oriented requirements engineering and information systems analysis. The first four chapters present an overview of enterprise modeling from various viewpoints (including methods, processes and organizational challenges), providing a background for those that need to refresh their basic knowledge. The next six chapters form the core of the book and detail the roles and competences needed in an EM project, typical stakeholder behaviors and how to handle them, tools and methods for managing participatory modeling and facilitation, and how to train modeling experts for these social aspects of modeling. Lastly, a concluding chapter presents a summary and an outlook on current research in participatory EM. This book is intended for anybody who wants to learn more about how to facilitate participatory modeling in practice and how to set up and carry out EM projects. It does not require any in-depth knowledge about specific EM methods and tools, and can be used by students and lecturers for courses on participatory modeling, and by practitioners wanting to extend their knowledge of social and organizational topics to become an experienced facilitator and EM project manager.

This edited volume presents a collection of lessons learned with, and research conducted on, OpenStreetMap, the goal being to promote the project's integration. The respective chapters address a) state-of-the-art and cutting-edge approaches to data quality analysis in OpenStreetMap, b) investigations on understanding OpenStreetMap contributors and the nature of their contributions, c) identifying patterns of contributions and contributors, d) applications of OpenStreetMap in different domains, e) mining value-added knowledge and information from OpenStreetMap, f) limitations in the analysis OpenStreetMap data, and g) integrating OpenStreetMap with commercial and non-commercial datasets. The book offers an ideal opportunity to present and disseminate a number of cutting-edge developments and applications in the field of geography, spatial statistics, GIS, social science, and cartography.