The present volume gathers together the talks presented at the second colloquim on the Future Professional Communication in Astronomy (FPCA II), held at Harvard University (Cambridge, MA) on 13-14 April 2010. This meeting provided a forum for editors, publishers, scientists, librarians and officers of learned societies to discuss the future of the field. The program included talks from leading researchers and practitioners and drew a crowd of approximately 50 attendees from 10 countries. These proceedings contain contributions from invited and contributed talks from leaders in the field, touching on a number of topics. Among them: - The role of disciplinary repositories such as ADS and arXiv in astronomy and the physical sciences; - Current status and future of Open Access Publishing models and their impact on astronomy and astrophysics publishing; - Emerging trends in scientific article publishing: semantic annotations, multimedia content, links to data products hosted by astrophysics archives; - Novel approaches to the evaluation of facilities and projects based on bibliometric indicators; - Impact of Government mandates, Privacy laws, and Intellectual Property Rights on the evolving digital publishing environment in astronomy; - Communicating astronomy to the public: the experience of the International Year of Astronomy 2009.

Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications.

Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data.

Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.

This book presents the proceedings of the Working Conference on the societal and organizational implications for information systems of social inclusion. The contributed papers explore technology design and use in organizations, and consider the processes that engender social exclusion along with the issues that derive from it. The conference, sponsored by the International Federation for Information Processing Working Group 8.2, was held in Limerick, Ireland, in July, 2006.

The development of Operations Research (OR) requires constant improvements, such as the integration of research results with business applications and innovative educational practice. The full deployment and commercial exploitation of goods and services generally need the construction of strong synergies between educational institutions and businesses. The IO2015 -XVII Congress of APDIO aims at strengthening the knowledge triangle in education, research and innovation, in order to maximize the contribution of OR for sustainable growth, the promoting of a knowledge-based economy, and the smart use of finite resources. The IO2015-XVII Congress of APDIO is a privileged meeting point for the promotion and dissemination of OR and related disciplines, through the exchange of ideas among teachers, researchers, students , and professionals with different background, but all sharing a common desire that is the development of OR.

This book includes extended versions of selected works presented at the 52nd Annual Convention of Computer Society of India (CSI 2017), held at Science City, Kolkata on 19-21 January 2018. It features a collection of chapters focusing on recent trends in computational intelligence, covering topics such as ANN, neuro-fuzzy based clustering, edge detection, data mining, mobile cloud computing, intelligent scheduling, processing and authentication. It also discusses societal applications of these methods. As such it is useful for students, researchers and industry professionals working in the area of computational intelligence.

Linking Government Data provides a practical approach to addressing common information management issues. The approaches taken are based on international standards of the World Wide Web Consortium. Linking Government Data gives both the costs and benefits of using linked data techniques with government data; describes how agencies can fulfill their missions with less cost; and recommends how intra-agency culture must change to allow public presentation of linked data. Case studies from early adopters of linked data approaches in international governments are presented in the last section of the book. Linking Government Data is designed as a professional book for those working in Semantic Web research and standards development, and for early adopters of Semantic Web standards and techniques. Enterprise architects, project managers and application developers in commercial, not-for-profit and government organizations concerned with scalability, flexibility and robustness of information management systems will also find this book valuable. Students focused on computer science and business management will also find value in this book.

Motivation for the Book This book aims to describe a comprehensive methodology for service-oriented inf- mation systems planning, considered in particular, in eGovernment initiatives. The methodology is based on the research results produced by the Italian project "eG- ernment for Mediterranean Countries (eG4M)," granted by the Italian Ministry of University and Research from 2005 to 2008. The concept of service is at the center of the book. The methodology is focused on quality of services as a key factor for eGovernment initiatives. Since its grou- ing is in a project whose goal has been to develop a methodology for eGove- ment in Mediterranean countries it is called eG4M. Furthermore, eG4M aims at encompassing the relationships existing between ICT technologies and social c- texts of service provision, organizational issues, and juridical framework, looking at ICT technologies more as a means than an end. eG4M satis es a real need of constituencies and stakeholders involved in eGovernment projects, con rmed in the eG4M experimentations and in previous preliminary experiences in the Italian P- lic Administrations. A structured process is needed that provides a clear perspective on the different facets that eGovernment initiatives usually have to challenge and disciplines the complex set of decisions to be taken. The available approaches to eGovernment usually provide only one perspective to public managers and local authorities on the domain of intervention, either te- nological, organizational, legal, economic, or social.

This book presents a review of traditional context-aware computing research, identifies its limitations in developing social context-aware pervasive systems, and introduces a new technology framework to address these limitations. Thus, this book provides a good reference for developments in context-aware computing and pervasive social computing. It examines the emerging area of pervasive social computing, which is a novel collective paradigm derived from pervasive computing, social media, social networking, social signal processing and multimodal human-computer interaction. This book offers a novel approach to model, represent, reason about and manage different types of social context. It shows how users' social context information can be acquired from different online social networks such as Facebook, LinkedIn, Twitter and Google Calendar. It further presents the use of social context information in developing innovative smart mobile applications to assist users in their daily life. The mix of both theoretical and applied research results makes this book attractive to a variety of readers from both academia and industry. This book provides a new platform for implementing different types of socially-aware mobile applications. The platform hides the complexity of managing social context, and thus provides essential support to application developers for the development of socially-aware applications. The book contains detailed descriptions of how the underlying platform has been implemented using available technologies such as ontology and rule engines, and how this platform can be used to develop socially-aware mobile applications using two exemplar applications. The book also presents evaluations of the proposed platform and applications using real-world data from Facebook, LinkedIn and Twitter. Therefore, this book is a syndication of scientific research with practical industrial applications, making it useful to researchers as well as to software engineers.

Information Processing and Security Systems is a collection of forty papers that were originally presented at an international multi-conference on Advanced Computer Systems (ACS) and Computer Information Systems and Industrial Management Applications (CISIM) held in Elk, Poland. This volume describes the latest developments in advanced computer systems and their applications within artificial intelligence, biometrics and information technology security. The volume also includes contributions on computational methods, algorithms and applications, computational science, education and industrial management applications.

This book proposes a novel approach to classification, discusses its myriad advantages, and outlines how such an approach to classification can best be pursued. It encourages a collaborative effort toward the detailed development of such a classification. This book is motivated by the increased importance of interdisciplinary scholarship in the academy, and the widely perceived shortcomings of existing knowledge organization schemes in serving interdisciplinary scholarship. It is designed for scholars of classification research, knowledge organization, the digital environment, and interdisciplinarity itself. The approach recommended blends a general classification with domain-specific classification practices. The book reaches a set of very strong conclusions: -Existing classification systems serve interdisciplinary research and teaching poorly. -A novel approach to classification, grounded in the phenomena studied rather than disciplines, would serve interdisciplinary scholarship much better. It would also have advantages for disciplinary scholarship. The productivity of scholarship would thus be increased. -This novel approach is entirely feasible. Various concerns that might be raised can each be addressed. The broad outlines of what a new classification would look like are developed. -This new approach might serve as a complement to or a substitute for existing classification systems. -Domain analysis can and should be employed in the pursuit of a general classification. This will be particularly important with respect to interdisciplinary domains. -Though the impetus for this novel approach comes from interdisciplinarity, it is also better suited to the needs of the Semantic Web, and a digital environment more generally. Though the primary focus of the book is on classification systems, most chapters also address how the analysis could be extended to thesauri and ontologies. The possibility of a universal thesaurus is explored. The classification proposed has many of the advantages sought in ontologies for the Semantic Web. The book is therefore of interest to scholars working in these areas as well.

Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.

DATA ENGINEERING: Mining, Information, and Intelligence describes applied research aimed at the task of collecting data and distilling useful information from that data. Most of the work presented emanates from research completed through collaborations between Acxiom Corporation and its academic research partners under the aegis of the Acxiom Laboratory for Applied Research (ALAR). Chapters are roughly ordered to follow the logical sequence of the transformation of data from raw input data streams to refined information. Four discrete sections cover Data Integration and Information Quality; Grid Computing; Data Mining; and Visualization. Additionally, there are exercises at the end of each chapter. The primary audience for this book is the broad base of anyone interested in data engineering, whether from academia, market research firms, or business-intelligence companies. The volume is ideally suited for researchers, practitioners, and postgraduate students alike. With its focus on problems arising from industry rather than a basic research perspective, combined with its intelligent organization, extensive references, and subject and author indices, it can serve the academic, research, and industrial audiences.

Artificial Intelligence and Security in Computing Systems is a peer-reviewed conference volume focusing on three areas of practice and research progress in information technologies:

-Methods of Artificial Intelligence presents methods and algorithms which are the basis for applications of artificial intelligence environments.
-Multiagent Systems include laboratory research on multiagent intelligent systems as well as upon their applications in transportation and information systems.
-Computer Security and Safety presents techniques and algorithms which will be of great interest to practitioners. In general, they focus on new cryptographic algorithms (including a symmetric key encryption scheme, hash functions, secret generation and sharing schemes, and secure data storage), a formal language for policy access control description and its implementation, and risk management methods (used for continuous analysis both in distributed network and software development projects).

Noisy data appears very naturally in applications where the authentication is based on physical identifiers, such as human beings, or physical structures, such as physical unclonable functions. This book examines how the presence of noise has an impact on information security, describes how it can be dealt with and possibly used to generate an advantage over traditional approaches, and provides a self-contained overview of the techniques and applications of security based on noisy data.

Security with Noisy Data thoroughly covers the theory of authentication based on noisy data and shows it in practice as a key tool for preventing counterfeiting. Part I discusses security primitives that allow noisy inputs, and Part II focuses on the practical applications of the methods discussed in the first part.

Key features:

a [ Contains algorithms to derive secure keys from noisy data, in particular from physical unclonable functions and biometrics - as well as the theory proving that those algorithms are secure

a [ Offers practical implementations of algorithms, including techniques that give insight into system security

a [ Includes an overview and detailed description of new applications made possible by using these new algorithms

a [ Discusses recent theoretical as well as application-oriented developments in the field, combining noisy data with cryptography

a [ Describes the foundations of the subject in a clear, accessible and reader-friendly style

a [ Presents the principles of key establishment and multiparty computation over noisy channels

a [ Provides a detailed overview of the building blocks of cryptography for noisy data and explains how these techniquescan be applied, (for example as anti-counterfeiting and key storage)

a [ Introduces privacy protected biometric systems, analyzes the theoretical and practical properties of PUFs and discusses PUF based systems

a [ Addresses biometrics and physical unclonable functions extensively

This comprehensive introduction offers an excellent foundation to graduate students and researchers entering the field, and will also benefit professionals needing to expand their knowledge. Readers will gain a well-rounded and broad understanding of the topic through the insight it provides into both theory and practice.

Pim Tuyls is a Principal Scientist at Philips Research and a Visiting Professor at the COSIC Department of the Katholieke Universiteit of Leuven, Dr Boris Skoric and Dr Tom Kevenaar are research scientists at Philips Research Laboratories, Eindhoven.

This book features selected contributions in the areas of modeling, simulation, and optimization. The contributors discusses requirements in problem solving for modeling, simulation, and optimization. Modeling, simulation, and optimization have increased in demand in exponential ways and how potential solutions might be reached. They describe how new technologies in computing and engineering have reduced the dimension of data coverage worldwide, and how recent inventions in information and communication technology (ICT) have inched towards reducing the gaps and coverage of domains globally. The chapters cover how the digging of information in a large data and soft-computing techniques have contributed to a strength in prediction and analysis, for decision making in computer science, technology, management, social computing, green computing, and telecom. The book provides an insightful reference to the researchers in the fields of engineering and computer science. Researchers, academics, and professionals will benefit from this volume. Features selected expanded papers in modeling, simulation, and optimization from COMPSE 2016; Includes research into soft computing and its application in engineering and technology; Presents contributions from global experts in academia and industry in modeling, simulation, and optimization.

The Internet of Things (IoT) is the next big challenge for the research community. The IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is considered a key part of the IoT. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects. This book presents a concrete, solid and logically ordered work on congestion control for 6LoWPAN networks as a step toward successful implementation of the IoT and supporting the IoT application requirements. The book addresses the congestion control issue in 6LoWPAN networks and presents a comprehensive literature review on congestion control for WSNs and 6LoWPAN networks. An extensive congestion analysis and assessment for 6LoWPAN networks is explored through analytical modelling, simulations and real experiments. A number of congestion control mechanisms and algorithms are proposed to mitigate and solve the congestion problem in 6LoWPAN networks by using and utilizing the non-cooperative game theory, multi-attribute decision making and network utility maximization framework. The proposed algorithms are aware of node priorities and application priorities to support the IoT application requirements and improve network performance in terms of throughput, end-to-end delay, energy consumption, number of lost packets and weighted fairness index.

This book discusses challenges and solutions for the required information processing and management within the context of multi-disciplinary engineering of production systems. The authors consider methods, architectures, and technologies applicable in use cases according to the viewpoints of product engineering and production system engineering, and regarding the triangle of (1) product to be produced by a (2) production process executed on (3) a production system resource. With this book industrial production systems engineering researchers will get a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in future research and development activities. Engineers and managers from engineering domains will be able to get a better understanding of the benefits and limitations of applicable methods, architectures, and technologies for selected use cases. IT researchers will be enabled to identify research issues related to the development of new methods, architectures, and technologies for multi-disciplinary engineering, pushing forward the current state of the art.

This book constitutes the thoroughly refereed post conference proceedings of the 6th IFIP WG 9.2, 9.6/11.7, 11.4, 11.6/PrimeLife International Summer School, held in Helsingborg, Sweden, in August 2010. The 27 revised papers were carefully selected from numerous submissions during two rounds of reviewing. They are organized in topical sections on terminology, privacy metrics, ethical, social, and legal aspects, data protection and identity management, eID cards and eID interoperability, emerging technologies, privacy for eGovernment and AAL applications, social networks and privacy, privacy policies, and usable privacy.

Market Basket Analysis (MBA) provides the ability to continually monitor the affinities of a business and can help an organization achieve a key competitive advantage. Time Variant data enables data warehouses to directly associate events in the past with the participants in each individual event. In the past however, the use of these powerful tools in tandem led to performance degradation and resulted in unactionable and even damaging information. Data Warehouse Designs: Achieving ROI with Market Basket Analysis and Time Variance presents an innovative, soup-to-nuts approach that successfully combines what was previously incompatible, without degradation, and uses the relational architecture already in place. Built around two main chapters, Market Basket Solution Definition and Time Variant Solution Definition, it provides a tangible how-to design that can be used to facilitate MBA within the context of a data warehouse. Presents a solution for creating home-grown MBA data marts Includes database design solutions in the context of Oracle, DB2, SQL Server, and Teradata relational database management systems (RDBMS) Explains how to extract, transform, and load data used in MBA and Time Variant solutions The book uses standard RDBMS platforms, proven database structures, standard SQL and hardware, and software and practices already accepted and used in the data warehousing community to fill the gaps left by most conceptual discussions of MBA. It employs a form and language intended for a data warehousing audience to explain the practicality of how data is delivered, stored, and viewed. Offering a comprehensive explanation of the applications that provide, store, and use MBA data, Data Warehouse Designs provides you with the language and concepts needed to require and receive information that is relevant and actionable.

This book includes 23 papers dealing with the impact of modern information and communication technologies that support a wide variety of communities: local communities, virtual communities, and communities of practice, such as knowledge communities and scientific communities. The volume is the result of the second multidisciplinary "Communities and Technologies Conference," a major event in this emerging research field. The various chapters discuss how communities are affected by technologies, and how understanding of the way that communities function can be used in improving information systems design. This state of the art overview will be of interest to computer and information scientists, social scientists and practitioners alike.

The technique of data fusion has been used extensively in information retrieval due to the complexity and diversity of tasks involved such as web and social networks, legal, enterprise, and many others. This book presents both a theoretical and empirical approach to data fusion. Several typical data fusion algorithms are discussed, analyzed and evaluated. A reader will find answers to the following questions, among others:

What are the key factors that affect the performance of data fusion algorithms significantly?

What conditions are favorable to data fusion algorithms?

CombSum and CombMNZ, which one is better? and why?

What is the rationale of using the linear combination method?

How can the best fusion option be found under any given circumstances?"

There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

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This book presents fundamental new techniques for understanding and processing geospatial data. These "spatial gems" articulate and highlight insightful ideas that often remain unstated in graduate textbooks, and which are not the focus of research papers. They teach us how to do something useful with spatial data, in the form of algorithms, code, or equations. Unlike a research paper, Spatial Gems, Volume 1 does not focus on "Look what we have done!" but rather shows "Look what YOU can do!" With contributions from researchers at the forefront of the field, this volume occupies a unique position in the literature by serving graduate students, professional researchers, professors, and computer developers in the field alike.

Blockchain Technology Solutions for the Security of IoT-Based Healthcare Systems explores the various benefits and challenges associated with the integration of blockchain with IoT healthcare systems, focusing on designing cognitive-embedded data technologies to aid better decision-making, processing and analysis of large amounts of data collected through IoT. This book series targets the adaptation of decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures, as well as big data and Internet of Things (IoT) problems can be handled in practice. Current Internet of Things (IoT) based healthcare systems are incapable of sharing data between platforms in an efficient manner and holding them securely at the logical and physical level. To this end, blockchain technology guarantees a fully autonomous and secure ecosystem by exploiting the combined advantages of smart contracts and global consensus. However, incorporating blockchain technology in IoT healthcare systems is not easy. Centralized networks in their current capacity will be incapable to meet the data storage demands of the incoming surge of IoT based healthcare wearables.