Spatial data mining for enhanced soil map modelling

The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

Epidemiological modelling (including economic modelling) and its role in preventive drug therapy

In contrast to curative therapies, preventive therapies are administered to largely healthy individuals over long periods. The risk-benefit and cost-benefit ratios are more likely to be unfavourable, making treatment decisions difficult. Drug trials provide insufficient information for treatment decisions, as they are conducted on highly selected populations over short durations, estimate only relative benefits of treatment and offer little information on risks and costs. Epidemiological modelling is a method of combining evidence from observational epidemiology and clinical trials to assist in clinical and health policy decision-making. It can estimate absolute benefits, risks and costs of long-term preventive strategies, and thus allow their precise targeting to individuals for whom they are safest and most cost-effective. Epidemiological modelling also allows explicit information about risks and benefits of therapy to be presented to patients, facilitating informed decision-making.

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.

Special issue: Selected papers from the sixth IFIP 2.6 working conference on visual database systems: Guest editors' introduction

While multimedia data, image data in particular, is an integral part of most websites and web documents, our quest for information so far is still restricted to text based search. To explore the World Wide Web more effectively, especially its rich repository of truly multimedia information, we are facing a number of challenging problems. Firstly, we face the ambiguous and highly subjective nature of defining image semantics and similarity. Secondly, multimedia data could come from highly diversified sources, as a result of automatic image capturing and generation processes. Finally, multimedia information exists in decentralised sources over the Web, making it difficult to use conventional content-based image retrieval (CBIR) techniques for effective and efficient search. In this special issue, we present a collection of five papers on visual and multimedia information management and retrieval topics, addressing some aspects of these challenges. These papers have been selected from the conference proceedings (Kluwer Academic Publishers, ISBN: 1-4020- 7060-8) of the Sixth IFIP 2.6 Working Conference on Visual Database Systems (VDB6), held in Brisbane, Australia, on 29–31 May 2002.

Visual biology of Hawaiian coral reef fishes. II. Colors of Hawaiian coral reef fish

The colors of 51 species of Hawaiian reef fish have been measured using a spectrometer and therefore can be described in objective terms that are not influenced by the human visual experience. In common with other known reef fish populations, the colors of Hawaiian reef fish occupy spectral positions from 300-800nm; yellow or orange with blue, yellow with black, and black with white are the most frequently combined colors; and there is no link between possession of ultraviolet (UV) reflectance and UV visual sensitivity or the potential for UV visual sensitivity. In contrast to other reef systems, blue, yellow, and orange appear more frequently in Hawaiian reef fish. Based on spectral quality of reflections from fish skin, trends in fish colors can be seen that are indicative of both visually driven selective pressures and chemical or physical constraints on the design of colors. UV-reflecting colors can function as semiprivate communication signals. White or yellow with black form highly contrasting patterns that transmit well through clear water. Labroid fishes display uniquely complex colors but lack the ability to see the UV component that is common in their pigments. Step-shaped spectral curves are usually long-wavelength colors such as yellow or red, and colors with a peak-shaped spectral curves are green, blue, violet, and UV.

Event-related FMRI analysis with maximum correlation modelling

Functional magnetic resonance imaging (FMRI) analysis methods can be quite generally divided into hypothesis-driven and data-driven approaches. The former are utilised in the majority of FMRI studies, where a specific haemodynamic response is modelled utilising knowledge of event timing during the scan, and is tested against the data using a t test or a correlation analysis. These approaches often lack the flexibility to account for variability in haemodynamic response across subjects and brain regions which is of specific interest in high-temporal resolution event-related studies. Current data-driven approaches attempt to identify components of interest in the data, but currently do not utilise any physiological information for the discrimination of these components. Here we present a hypothesis-driven approach that is an extension of Friman's maximum correlation modelling method (Neurolmage 16, 454-464, 2002) specifically focused on discriminating the temporal characteristics of event-related haemodynamic activity. Test analyses, on both simulated and real event-related FMRI data, will be presented.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Snakes and kittens in the grass: No evidence for preferential processing of fear-relevant animals in visual search

Ohman and colleagues provided evidence for preferential processing of pictures depicting fear-relevant animals by showing that pictures of snakes and spiders are found faster among pictures of fiowers and mushrooms than vice versa and that the speed of detecting fear-relevant animals was not affected by set size whereas the speed of detecting fiowers/mushrooms was. Experiment 1 replicated this finding. Experiment 2, however, found similar search advantages when pictures of cats and horses or of wolves and big cats were to be found among pictures of flowers and mushrooms. Moreover, Experiment 3, in a within subject comparison, failed to find faster identification of snakes and spiders than of cats and horses among flowers and mushrooms. The present findings seem to indicate that previous reports of preferential processing of pictures of snakes and spiders in a visual search task may reflect a processing advantage for animal pictures in general rather than fear-relevance.

Activation of visual areas during the attentional blink

When two targets are presented in rapid succession, identification of the first target is nearly perfect while identification of the second is severely impaired at shorter inter-target lags, and then gradually improves as lag increases. This second-target deficit is known as the attentional blink (AB). Numerous studies have implicated competition for access to higher-order processing mechanisms as the primary cause of the AB. However, relatively few studies have directly examined how the AB modulates activity in specific brain areas. To this end, we used fMRI to measure activation in the occipital and parietal cortices (including V1, V2, and area MT) during an AB task. Participants were presented with an initial target of oriented line segments embedded in a central stream of letter distractors. This central target was followed 100 - 700 ms later by a peripheral ‘X’ presented at one of four locations along with three ‘+’ distractors. All peripheral items were presented in the centre of a small field of moving dots. Participants made non-speeded judgments about line-segment orientation and the location of the second target at the end of a trial and to ignore all other stimuli. The results showed a robust AB characterised by a linear improvement in second-target accuracy as lag increased. This pattern of behavioural results was mirrored by changes in activation patterns across a number of visual areas indicating robust modulation of brain activity by the AB.

Numerical modelling of chemical effects of magma solidification problems in porous rocks

The solidification of intruded magma in porous rocks can result in the following two consequences: (1) the heat release due to the solidification of the interface between the rock and intruded magma and (2) the mass release of the volatile fluids in the region where the intruded magma is solidified into the rock. Traditionally, the intruded magma solidification problem is treated as a moving interface (i.e. the solidification interface between the rock and intruded magma) problem to consider these consequences in conventional numerical methods. This paper presents an alternative new approach to simulate thermal and chemical consequences/effects of magma intrusion in geological systems, which are composed of porous rocks. In the proposed new approach and algorithm, the original magma solidification problem with a moving boundary between the rock and intruded magma is transformed into a new problem without the moving boundary but with the proposed mass source and physically equivalent heat source. The major advantage in using the proposed equivalent algorithm is that a fixed mesh of finite elements with a variable integration time-step can be employed to simulate the consequences and effects of the intruded magma solidification using the conventional finite element method. The correctness and usefulness of the proposed equivalent algorithm have been demonstrated by a benchmark magma solidification problem. Copyright (c) 2005 John Wiley & Sons, Ltd.

The fMRI response of the LGN and V1 to cardinal red-green, blue-yellow, and achromatic visual stimuli

We compared the responsiveness of the LGN and the early retinotopic cortical areas to stimulation of the two cone-opponent systems (red - green and blue - yellow) and the achromatic system. This was done at two contrast levels to control for any effect of contrast. MR images were acquired on seven subjects with a 4T Bruker MedSpec scanner. The early visual cortical areas were localised by phase encoded retinotopic mapping with a volumetric analysis (Dumoulin et al, 2003 NeuroImage 18 576 - 587). We initially located the LGN in four subjects by using flickering stimuli in a separate scanning session, but subsequently identified it using the experimental stimuli. Experimental stimuli were sine-wave counterphasing rings (2 Hz, 0.5 cycle deg-1), cardinal for the selective activation of the L/M cone-opponent (RG), S cone-opponent (BY), and achromatic (Ach) systems. A region of interest analysis was performed. When presented at equivalent absolute contrasts (cone contrast = 5% - 6%), the BOLD response of the LGN is strongest to isoluminant red - green stimuli and weakest to blue - yellow stimuli, with the achromatic response falling in between. Area V1, on the other hand, responds best to both chromatic stimuli, with the achromatic response falling below. The key change from the LGN to V1 is a dramatic boost in the relative blue - yellow response, which occurred at both contrast levels used. This greatly enhanced cortical response to blue - yellow relative to the red - green and achromatic responses may be due to an increase in cell number and/or cell response between the LGN and V1. We speculate that the effect might reflect the operation of contrast constancy across colour mechanisms at the cortical level.

Modelling of species in hood fires by conditional moment closure

Carbon monoxide, the chief killer in fires, and other species are modelled for a series of enclosure fires. The conditions emulate building fires where CO is formed in the rich, turbulent, nonpremixed flame and is transported frozen to lean mixtures by the ceiling jet which is cooled by radiation and dilution. Conditional moment closure modelling is used and computational domain minimisation criteria are developed which reduce the computational cost of this method. The predictions give good agreement for CO and other species in the lean, quenched-gas stream, holding promise that this method may provide a practical means of modelling real, three-dimensional fire situations. (c) 2005 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Attentional modulation of visual cortex activity following right parietal damage in humans

Pathological inattention following parietal damage causes perceptual impairments for visual stimuli in the contralesional hemifield. Here we used functional magnetic resonance imaging (fMRI) to examine visual cortex activity in parietal patients as they performed a spatial attention task. Righthemisphere patients and healthy controls viewed counterphasing checkerboards in which coloured targets appeared briefly within the contralesional and ipsilesional hemifields. In separate fMRI runs participants focused their attention covertiy on the left or right hemifield, or on both hemifields concurrentiy. They were required to detect coloured targets that appeared briefly within the attended hemifield(s), and to withhold responses to distractor stimuli. Neural activit}' was significantly attenuated in early visual areas within the damaged hemisphere. Crucially, although attention significantiy modulated early visual activit}' within the intact (left) hemisphere, there was relatively littie modulation of activity within the affected hemisphere. Our findings suggest that parietal lesions alter early cortical responses to contralesional visual inputs.