Brunel University London

About: Brunel University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Context (language use) & Large Hadron Collider. The organization has 10918 authors who have published 29515 publications receiving 893330 citations. The organization is also known as: Brunel & University of Brunel.

visualising semantic spaces and author co-citation networks in digital libraries

Abstract: This paper describes the development and application of visualisation techniques for users to access and explore information in a digital library effectively and intuitively. Salient semantic structures and citation patterns are extracted from several collections of documents, including the ACM SIGCHI Conference Proceedings (1995–1997) and ACM Hypertext Conference Proceedings (1987–1998), using Latent Semantic Indexing and Pathfinder Network Scaling. The unique spatial metaphor leads to a natural combination of search and navigation within the same semantic space in a 3-dimensional virtual world. Author co-citation patterns are visualised through a number of author co-citation maps in attempts to reveal the structure of the hypertext, including an overall co-citation map of 367 authors and three periodical maps. These maps highlight predominant research areas in the field. This approach provides a means for transcending the boundaries of collections of documents and visualising more profound patterns in terms of semantic structures and co-citation networks.

The Visible Human Project : Informatic Bodies and Posthuman Medicine

Abstract: The Visible Human Project is a critical investigation of the spectacular, three-dimensional recordings of real human bodies - dissected, photographed and converted into visual data files - made by the US National Library of Medicine in Baltimore. Catherine Waldby uses new ideas from cultural studies, science studies and social studies of the computer to situate the Visible Human Project in its historical and cultural context, and to consider the meanings such an object has within a computerised culture. In this fascinating and important book, Catherine Waldby explores how advances in medical technologies have changed the way we view and study the human body, and places the VHP within the history of technologies such as the X-ray and CT-scan, which allow us to view the human interior. Bringing together medical conceptions of the human body with theories of visual culture from Foucault to Donna Haraway, Waldby links the VHP to a range of other biomedical projects, such as the Human Genome Project and cloning, which approach living bodies as data sources. She argues that the VHP is an example of the increasingly blurred distinction between 'living' and 'dead' human bodies, as the bodies it uses are digitally preserved as a resource for living bodies, and considers how computer-based biotechnologies affect both medical and non-medical meanings of the body's life and death, its location and its limits.

The Field Guide to Understanding Human Error

Abstract: The Field Guide to Understanding Human Error, by Sidney Dekker, Ashgate Publishing, Aldershot, Hampshire, UK, 2006, pp. 236, £20.00, paperback (ISBN 0 7546 4826 5), £55.00, hardback (ISBN 0 7546 48...

Stable Matching-Based Selection in Evolutionary Multiobjective Optimization

Abstract: Multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem into a set of scalar optimization subproblems and optimizes them in a collaborative manner. Subproblems and solutions are two sets of agents that naturally exist in MOEA/D. The selection of promising solutions for subproblems can be regarded as a matching between subproblems and solutions. Stable matching, proposed in economics, can effectively resolve conflicts of interests among selfish agents in the market. In this paper, we advocate the use of a simple and effective stable matching (STM) model to coordinate the selection process in MOEA/D. In this model, subproblem agents can express their preferences over the solution agents, and vice versa. The stable outcome produced by the STM model matches each subproblem with one single solution, and it tradeoffs convergence and diversity of the evolutionary search. Comprehensive experiments have shown the effectiveness and competitiveness of our MOEA/D algorithm with the STM model. We have also demonstrated that user-preference information can be readily used in our proposed algorithm to find a region that decision makers are interested in.