Legal Theory, Sources of Law and the Semantic Web is an attempt to construct an integrated conceptual framework for the application-neutral and problem-neutral representation of sources of law using Semantic Web technology and concepts, and some technically straightforward extensions to Semantic Web technology based on established practices found in fielded applications. To construct this framework, the author disentangled some problems that are often mixed up in legal theory and – in extension – legal knowledge representation. The purpose of this framework is to provide a theoretical background for the creation of reusable and maintainable knowledge components representing knowledge of sources of law on the Semantic Web. These components should form a basis for the development for computer applications supporting straightforward, routine decision making problems using traditional methods. This book aims to be a work of ontology: an account of relevant aspects of the knowledge domain of law from the perspective of a legal knowledge engineer interested in sources of law. One cannot however say that the result of this work is an ontology: this book presents a mix of design principles, design patterns for knowledge representation in OWL DL and ontology fragments.

This book constitutes the refereed proceedings of the 12th Asian Computing Science Conference, ASIAN 2007, held in Doha, Qatar, in December 2007. Covering all current aspects of computer and network security, the papers are organized in topical sections on program security, computer security, access control, protocols, intrusion detection, network security, and safe execution.

The unusual format of a series of discussions among a logician, a computer scientist, a philosopher and some researchers from other disciplines encourages the reader to develop his own point of view. --Book Jacket.

For more than 20 years, Network World has been the premier provider of information, intelligence and insight for network and IT executives responsible for the digital nervous systems of large organizations. Readers are responsible for designing, implementing and managing the voice, data and video systems their companies use to support everything from business critical applications to employee collaboration and electronic commerce.

This books describes a number of techniques that have been developed to facilitate Semantic Network Analysis. It describes techniques to automatically extract networks using co-occurrence, grammatical analysis, and sentiment analysis using machine learning. Additionally, it describes techniques to represent the extracted semantic networks and background knowledge about the actors and issues in the network, using Semantic Web techniques to deal with multiple issue categorisations and political roles and functions that shift over time. It shows how this combined network of message content and background knowledge can be queried and visualized to make it easy to answer a variety of research questions. Finally, this book describes the AmCAT infrastructure and iNet coding program for that have been developed to facilitate managing large automatic and manual content analysis projects.

This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.