910 resultados para Probabilistic interpretation
Resumo:
The aims of the study were to test the hypotheses that some symptoms of starvation/severe dietary restraint are interpreted by patients with eating disorders in terms or control. Sixty-nine women satisfying the Diagnostic and Statistical Manual of Mental Disorders - IV edition (DSM-IV) criteria for a clinical eating disorder and 107 controls participated in the Study. All the participants completed an ambiguous scenarios paradigm, the Eating Disorder Lamination Questionnaire (EDE-Q) and the Beck Depression Inventory (BDI). Significantly more eating disorder patients than non clinical participants interpreted the starvation/dietary restraint symptoms of hunger, heightened satiety, and dizziness in terms of control. The data give further Support to the recent cognitive-behavioural theory of eating disorders suggesting that eating disorder patients interpret some starvation/dietary restraint symptoms in terms of control.
Resumo:
Interpretation biases towards threat play a prominent role in cognitive theories of anxiety, and have been identified amongst highly anxious adults and children. Little is known, however, about the development of these cognitive biases although family processes have been implicated. The current study investigated the nature of threat interpretation of anxious children and their mothers through (i) comparison of a clinic and non-clinic population, (ii) analysis of individual differences; and (ill) pre- and post-treatment comparisons. Participants were 27 children with a primary anxiety disorder and 33 children from a non-clinic population and their mothers. Children and mothers completed self-report measures of anxiety and indicated their most likely interpretation of ambiguous scenarios. Clinic and non-clinical groups differed significantly on measures of threat interpretation. Furthermore, mothers' and children's threat interpretation correlated significantly. Following treatment for child anxiety, both children and their mothers reported a reduction in threat interpretation. (c) 2005 Elsevier Ltd. All rights reserved.
Resumo:
Objectives: To examine doctors' (Experiment 1) and doctors' and lay people's (Experiment 2) interpretations of two sets of recommended verbal labels for conveying information about side effects incidence rates. Method: Both studies used a controlled empirical methodology in which participants were presented with a hypothetical, but realistic, scenario involving a prescribed medication that was said to be associated with either mild or severe side effects. The probability of each side effect was described using one of the five descriptors advocated by the European Union (Experiment 1) or one of the six descriptors advocated in Calman's risk scale (Experiment 2), and study participants were required to estimate (numerically) the probability of each side effect occurring. Key findings: Experiment 1 showed that the doctors significantly overestimated the risk of side effects occurring when interpreting the five EU descriptors, compared with the assigned probability ranges. Experiment 2 showed that both groups significantly overestimated risk when given the six Calman descriptors, although the degree of overestimation was not as great for the doctors as for the lay people. Conclusion: On the basis of our findings, we argue that we are still a long way from achieving a standardised language of risk for use by both professionals and the general public, although there might be more potential for use of standardised terms among professionals. In the meantime, the EU and other regulatory bodies and health professionals should be very cautious about advocating the use of particular verbal labels for describing medication side effects.
Resumo:
In this paper, we evaluate the Probabilistic Occupancy Map (POM) pedestrian detection algorithm on the PETS 2009 benchmark dataset. POM is a multi-camera generative detection method, which estimates ground plane occupancy from multiple background subtraction views. Occupancy probabilities are iteratively estimated by fitting a synthetic model of the background subtraction to the binary foreground motion. Furthermore, we test the integration of this algorithm into a larger framework designed for understanding human activities in real environments. We demonstrate accurate detection and localization on the PETS dataset, despite suboptimal calibration and foreground motion segmentation input.
Resumo:
We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak learners, which operate on image intensity discriminative features that are defined on small patches and are fast to compute. A database that is designed to simulate digitized occluding contours of textured objects in natural images is used to train the weak learners. The trained classifier score is then used to obtain a probabilistic model for the presence of texture transitions, which can readily be used for line search texture boundary detection in the direction normal to an initial boundary estimate. This method is fast and therefore suitable for real-time and interactive applications. It works as a robust estimator, which requires a ribbon-like search region and can handle complex texture structures without requiring a large number of observations. We demonstrate results both in the context of interactive 2D delineation and of fast 3D tracking and compare its performance with other existing methods for line search boundary detection.
Resumo:
A new probabilistic neural network (PNN) learning algorithm based on forward constrained selection (PNN-FCS) is proposed. An incremental learning scheme is adopted such that at each step, new neurons, one for each class, are selected from the training samples arid the weights of the neurons are estimated so as to minimize the overall misclassification error rate. In this manner, only the most significant training samples are used as the neurons. It is shown by simulation that the resultant networks of PNN-FCS have good classification performance compared to other types of classifiers, but much smaller model sizes than conventional PNN.
Resumo:
Based on the idea of an important cluster, a new multi-level probabilistic neural network (MLPNN) is introduced. The MLPNN uses an incremental constructive approach, i.e. it grows level by level. The construction algorithm of the MLPNN is proposed such that the classification accuracy monotonically increases to ensure that the classification accuracy of the MLPNN is higher than or equal to that of the traditional PNN. Numerical examples are included to demonstrate the effectiveness of proposed new approach.
Resumo:
The diagnosis of thalassaemia in archaeological populations has long been hindered by a lack of pathogonomic features, and the non-specific nature of cribra orbitalia and porotic hyperostosis. In fact, clinical research has highlighted more specific diagnostic criteria for thalassaemia major and intermedia based on changes to the thorax (‘rib-within-a-rib’ and costal osteomas). A recent re-examination of 364 child skeletons from Romano-British Poundbury Camp, Dorset revealed children with general ‘wasting’ of the bones and three children who demonstrated a variety of severe lesions (e.g. zygomatic bone and rib hypertrophy, porotic hyperostosis, rib lesions, osteopenia and pitted diaphyseal shafts) that are inconsistent with dietary deficiency alone, and more consistent with a diagnosis of genetic anaemia. Two of these children displayed rib lesions typical of those seen in modern cases of thalassaemia. The children of Poundbury Camp represent the first cases of genetic anaemia identified in a British archaeological population. As thalassaemia is a condition strongly linked to Mediterranean communities, the presence of this condition in a child from England, found within a mausoleum, suggests that they were born to wealthy immigrant parents living in this small Roman settlement in Dorset. This paper explores the diagnostic criteria for genetic anaemia in the archaeological literature and what its presence in ancient populations can contribute to our knowledge of past human migration.
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Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally.
Resumo:
The effects of nano-scale and micro-scale zerovalent iron (nZVI and mZVI) particles on general (dehydrogenase and hydrolase) and specific (ammonia oxidation potential, AOP) activities mediated by the microbial community in an uncontaminated soil were examined. nZVI (diameter 12.5 nm; 10 mg gÿ1 soil)apparently inhibited AOP and nZVI and mZVI apparently stimulated dehydrogenase activity but had minimal influence on hydrolase activity. Sterile experiments revealed that the apparent inhibition of AOP could not be interpreted as such due to the confounding action of the particles, whereas, the nZVIenhanced dehydrogenase activity could represent the genuine response of a stimulated microbial population or an artifact of ZVI reactivity. Overall, there was no evidence for negative effects of nZVI or mZVI on the processes studied. When examining the impact of redox active particles such as ZVI on microbial oxidation–reduction reactions, potential confounding effects of the test particles on assay conditions should be considered.
Resumo:
DFT and TD-DFT calculations (ADF program) were performed in order to analyze the electronic structure of the [M-3(CO)(12)] clusters (M = Ru, Os) and interpret their electronic spectra. The highest occupied molecular orbitals are M-M bonding (sigma) involving different M-M bonds, both for Ru and Os. They participate in low-energy excitation processes and their depopulation should weaken M-M bonds in general. While the LUMO is M-NI and M-CO anti-bonding (sigma*), the next, higher-lying empty orbitals have a main contribution from CO (pi*) and either a small (Ru) or an almost negligible one (Os) from the metal atoms. The main difference between the two clusters comes from the different nature of these low-energy unoccupied orbitals that have a larger metal contribution in the case of ruthenium. The photochemical reactivity of the two clusters is reexamined and compared to earlier interpretations.