Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Bioinformatics for characterisation of allergens, allergenicity and allergic crossreactivity

Allergies are a major cause of chronic ill health in industrialised countries with the incidence of reported cases steadily increasing. This Research Focus details how bioinformatics is transforming the field of allergy through providing databases for management of allergen data, algorithms for characterisation of allergic crossreactivity, structural motifs and B- and T-cell epitopes, tools for prediction of allergenicity and techniques for genomic and proteomic analysis of allergens.

Multiresolution spatial databases: Making web-based spatial applications faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

The determinants of default risk in Brazil

We formulated a general unrestricted model of the Brazilian Emerging Markets Bond Index Plus (EMBI+) spreads, a proxy for the country`s default risk. Employing algorithms that perform automated model selection, we found that macroeconomic fundamentals, such as current account deficit ratio to gross domestic product, public deficit ratio to gross domestic product and imports over foreign exchange reserves, can explain a great part of the variation in EMBI+ spreads. There is also robust evidence of systematic contagion from Argentina and Mexico and that the variance of the spread also affects its mean.