Globalisation, security and international order after 11 September

This article advances the discussion of the contentious question of links between global inequalities of power and violent responses, focussing on globalisation and non-inclusive forms of governance. Drawing on international political economy, the article criticises the nationstate-centrism in much political discourse, suggesting that both authority and security need to be reconsidered - to account for less plausible national borders and controls. It suggests that human security (including issues of development and equality) ought to replace national security as the primary focus of public policy. It draws attention to the intractability of difference, insisting that the terrorism of 2001 has complex transnational antecedents. Realist approaches to international order have become part of a problem to be overcome through further intellectual debate.

Fetal echocardiography: are we getting it right?

Objective To determine the diagnostic accuracy of prenatal fetal echocardiography. Methods The study was a retrospective chart review of 190 consecutive patients over a 3-year period from November 1998 to February 2002 of all women referred to the Maternal Fetal Medicine unit, Mater Mothers Hospital, for fetal echocardiography. The prenatal diagnosis was compared with the postnatal diagnosis made by postnatal echocardiography, surgical findings or post-mortem. The accuracy of prenatal diagnosis was described on a predetermined 4-point scale. Results Of the 89 patients, for whom complete diagnostic follow-up was available, there was complete agreement between the prenatal and postnatal diagnosis in 63 cases, minor discrepancies in 25 cases and major disagreement in 1 case. Conclusions In experienced hands, fetal echocardiography is accurate and allows medical staff and patients information in order manage a pregnancy appropriately. Copyright (C) 2004 John Wiley Sons, Ltd.

A First Order Predicate Logic Formulation of the 3D Reconstruction Problem and its Solution Space

This paper defines the 3D reconstruction problem as the process of reconstructing a 3D scene from numerous 2D visual images of that scene. It is well known that this problem is ill-posed, and numerous constraints and assumptions are used in 3D reconstruction algorithms in order to reduce the solution space. Unfortunately, most constraints only work in a certain range of situations and often constraints are built into the most fundamental methods (e.g. Area Based Matching assumes that all the pixels in the window belong to the same object). This paper presents a novel formulation of the 3D reconstruction problem, using a voxel framework and first order logic equations, which does not contain any additional constraints or assumptions. Solving this formulation for a set of input images gives all the possible solutions for that set, rather than picking a solution that is deemed most likely. Using this formulation, this paper studies the problem of uniqueness in 3D reconstruction and how the solution space changes for different configurations of input images. It is found that it is not possible to guarantee a unique solution, no matter how many images are taken of the scene, their orientation or even how much color variation is in the scene itself. Results of using the formulation to reconstruct a few small voxel spaces are also presented. They show that the number of solutions is extremely large for even very small voxel spaces (5 x 5 voxel space gives 10 to 10(7) solutions). This shows the need for constraints to reduce the solution space to a reasonable size. Finally, it is noted that because of the discrete nature of the formulation, the solution space size can be easily calculated, making the formulation a useful tool to numerically evaluate the usefulness of any constraints that are added.

Concept-based document readability in domain specific information retrieval

Domain specific information retrieval has become in demand. Not only domain experts, but also average non-expert users are interested in searching domain specific (e.g., medical and health) information from online resources. However, a typical problem to average users is that the search results are always a mixture of documents with different levels of readability. Non-expert users may want to see documents with higher readability on the top of the list. Consequently the search results need to be re-ranked in a descending order of readability. It is often not practical for domain experts to manually label the readability of documents for large databases. Computational models of readability needs to be investigated. However, traditional readability formulas are designed for general purpose text and insufficient to deal with technical materials for domain specific information retrieval. More advanced algorithms such as textual coherence model are computationally expensive for re-ranking a large number of retrieved documents. In this paper, we propose an effective and computationally tractable concept-based model of text readability. In addition to textual genres of a document, our model also takes into account domain specific knowledge, i.e., how the domain-specific concepts contained in the document affect the document’s readability. Three major readability formulas are proposed and applied to health and medical information retrieval. Experimental results show that our proposed readability formulas lead to remarkable improvements in terms of correlation with users’ readability ratings over four traditional readability measures.