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This year marks the third edition of EuroSSC. It builds on the success of the past editions, held in Enschede, The Netherlands in 2006, and in Kendal, UK in 2007. On behalf of the Organizing Committee, we would like to welcome you to EuroSSC 2008, in Zurich, Switerland. This volume contains the invited papers and technical peer-reviewed papers selected for presentation at the conference. At EuroSSC we aim to explore technologies, algorithms, architectures, p- tocols, and user aspects underlying context-aware smart surroundings, coop- ating intelligent objects, and their applications. Since its inception, EuroSSC has taken a complementary technology-driven and user-driven view to discuss these aspects. It is one of the particularities of EuroSSC, and the 2008 edition made no exception. In addition we emphasized aspects related to quality of c- text and context-aware feedback by actuator systems. This re?ects the growing importance that context processing in uncertain environments and sensor and actuator networks take in ambient intelligence environments. We received 70 paper submissions. They originate from 30 countries of - rope, the Middle East and Africa (66%), Asia (22%), North America (9%), and South America (3%). These numbers re?ect the European origins of EuroSSC, but also show that EuroSSC is a recognized and attractive platform for parti- pants from all regions of the world.
This volume explores how context has been and can be used in computing to model human behaviors, actions and communications as well as to manage data and knowledge. It addresses context management and exploitation of context for sharing experience across domains. The book serves as a user-centric guide for readers wishing to develop context-based applications, as well as an intellectual reference on the concept of context. It provides a broad yet deep treatment of context in computing and related areas that depend heavily on computing. The coverage is broad because of its cross-disciplinary nature but treats topics at a sufficient depth to permit a reader to implement context in his/her computational endeavors. The volume addresses how context can be integrated in software and systems and how it can be used in a computing environment. Furthermore, the use of context to represent the human dimension, individually as well as collectively is explained. Contributions also include descriptions of how context has been represented in formal as well as non-formal, structured approaches. The last section describes several human behavior representation paradigms based on the concept of context as its central representational element. The depth and breadth of this content is certain to provide useful as well as intellectually enriching information to readers of diverse backgrounds who have an interest in or are intrigued by using context to assist in their representation of the real world.
Data Quality provides an exposé of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.
This book constitutes the proceedings of the 10th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2017, held in Paris, France, in June 2017. The 26 full papers and 15 short papers presented were carefully reviewed and selected from 88 submissions. The papers feature research in a wide range of disciplines related to issues of context and contextual knowledge and discuss commonalities across and differences between the disciplines' approaches to the study of context. They are organized in the following topical sections: context in representation; context modeling of human activities; context in communication; context awareness; and various specific topics.
This book is open access under a CC BY 4.0 license. This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.All contributions are based on papers submitted in connection with ABIDA (Assessing Big Data), an interdisciplinary research project exploring the societal aspects of big data and funded by the German Federal Ministry of Education and Research.This volume was produced as a part of the ABIDA project (Assessing Big Data, 01IS15016A-F). ABIDA is a four-year collaborative project funded by the Federal Ministry of Education and Research. However the views and opinions expressed in this book reflect only the authors’ point of view and not necessarily those of all members of the ABIDA project or the Federal Ministry of Education and Research.
This proceedings volume brings together some 189 peer-reviewed papers presented at the International Conference on Information Technology and Computer Application Engineering, held 27-28 August 2013, in Hong Kong, China. Specific topics under consideration include Control, Robotics, and Automation, Information Technology, Intelligent Computing and Telecommunication, Computer Science and Engineering, Computer Education and Application and other related topics. This book provides readers a state-of-the-art survey of recent innovations and research worldwide in Information Technology and Computer Application Engineering, in so-doing furthering the development and growth of these research fields, strengthening international academic cooperation and communication, and promoting the fruitful exchange of research ideas. This volume will be of interest to professionals and academics alike, serving as a broad overview of the latest advances in the dynamic field of Information Technology and Computer Application Engineering.
This groundbreaking work examines teacher quality, work norms, and professional learning opportunities, using data from 15 countries. The authors compare and contrast the United States with two high-achieving countries--Japan and Australia--that have implemented very different approaches to improving teacher quality. Drawing on both large international data sets and ethnographic and small-scale studies, the book addresses critical questions: (2) How do teacher quality and teacher recruitment and hiring policies in the United States differ from those in other countries?; (2) How do the working conditions of U.S. teachers differ from those of teachers in other countries?; (3) How do U.S. teachers' opportunities for professional learning differ from those of teachers in other countries?; (4) How do the characteristics of the national teaching force influence student achievement?; And (5) What U.S. policies offer promise for improving teacher quality?
Quality accreditation in higher education institutions (HEIs) is currently a buzzword. The need to maintain high-quality education standards is a critical requirement for HEIs to remain competitive in the market and for government and regulatory bodies to ensure the quality standards of programs offered. From being an implicit requirement that is internally addressed, quality assurance activities become an explicit requirement that is regularly audited and appraised by national and international accreditation agencies. HEIs are voluntarily integrating quality management systems (QMS), institutional and program-specific, in response to the political and competitive environment in which it exists. Through its higher education department or by creating non-profitable accreditation bodies, many governments have implemented a quality framework for licensing HEIs and invigilates its adherence based on which accreditation statuses are granted for HEIs. Global Perspectives on Quality Assurance and Accreditation in Higher Education Institutions provides a comprehensive framework for HEIs to address quality assurance and quality accreditation requirements and serves as a practical tool to develop and deploy well-defined quality management systems in higher education. The book focuses on the critical aspects of quality assurance; the need to develop a concise and agile vision, mission, values, and graduate attributes; and to develop a system that effectively aligns the various activities of the HEI to the attainment of the strategic priorities listed in the institutional plans. The chapters each cover the various facets of the quality assurance framework and accreditation agencies' requirements with practical examples of each. This book is useful for HEI administrators, quality assurance specialists in HEIs, heads of academic departments, internal auditors, external auditors, and other practitioners of quality, along with stakeholders, researchers, academicians, and students interested in quality assurance and accreditation in higher education.
The Institute of Medicine (IOM) Committee on Quality Measures for the Healthy People Leading Health Indicators was charged by the Office of the Assistant Secretary for Health to identify measures of quality for the 12 Leading Health Indicator (LHI) topics and 26 Leading Health Indicators in Healthy People 2020 (HP2020), the current version of the Department of Health and Human Services (HHS) 10-year agenda for improving the nation's health. The scope of work for this project is to use the nine aims for improvement of quality in public health (population-centered, equitable, proactive, health promoting, risk reducing, vigilant, transparent, effective, and efficient) as a framework to identify quality measures for the Healthy People Leading Health Indicators (LHIs). The committee reviewed existing literature on the 12 LHI topics and the 26 Leading Health Indicators. Quality measures for the LHIs that are aligned with the nine aims for improvement of quality in public health will be identified. When appropriate, alignments with the six Priority Areas for Improvement of Quality in Public Health will be noted in the Committee's report. Toward Quality Measures for Population Health and the Leading Health Indicators also address data reporting and analytical capacities that must be available to capture the measures and for demonstrating the value of the measures to improving population health. Toward Quality Measures for Population Health and the Leading Health Indicators provides recommendations for how the measures can be used across sectors of the public health and health care systems. The six priority areas (also known as drivers) are population health metrics and information technology; evidence-based practices, research, and evaluation; systems thinking; sustainability and stewardship; policy; and workforce and education.
This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity, insufficient resolution, contradictory, fake and/or redundant. Sources may provide unverified reports obtained from other sources resulting in correlations and biases. The success of the fusion processing depends on how well knowledge produced by the processing chain represents reality, which in turn depends on how adequate data are, how good and adequate are the models used, and how accurate, appropriate or applicable prior and contextual knowledge is. By offering contributions by leading experts, this book provides an unparalleled understanding of the problem of information quality in information fusion and decision-making for researchers and professionals in the field.