769 resultados para 380305 Knowledge Representation and Machine Learning
Resumo:
Recruiting safe, volunteer blood donors requires understanding motivations for donating and knowledge and attitudes about HIV. We surveyed 1,600 persons presenting for blood donation at a large blood bank in Sao Paulo, Brazil using a self-administered, structured questionnaire, and classified motivations into three domains as well as categorizing persons by HIV test-seeking behavior. Motivations, in descending order, and their significant associations were: ""altruism``: female gender, volunteer donor and repeat donor status; ""direct appeal``: female gender, repeat donor status and age 21-50 years; ""selfinterest``: male gender, age under 20 years, first-time donor status and lower education. HIV test-seekers were more likely to give incorrect answers regarding HIV risk behavior and blood donation and the ability of antibody testing to detect recent HIV infections. Altruism is the main motivator for blood donation in Brazil; other motivators were associated with specific demographic subgroups. HIV test-seeking might be reduced by educational interventions.
Resumo:
After providing some brief background on Dendrolagus species in Australia, two consecutive surveys of Brisbane’s residents are used to assess public knowledge of tree-kangaroos and the stated degree of support for their conservation in Australia. The responses of participants in Survey I are based on their pre-survey knowledge of wildlife. The same additional set of participants completed Survey II after being provided with information on all the wildlife species mentioned in Survey I. Changes in the attitudes of respondents and their degree of support for the protection and conservation of Australia’s tree-kangaroos are measured, including changes in their contingent valuations and stated willingness to provide financial support for such conservation. Reasons for wanting to protect tree-kangaroos are specified and analyzed. Furthermore, changes that occur in the relative importance of these reasons with increased knowledge are also examined. Support for the conservation of tree-kangaroos is found to increase with the additional knowledge supplied. Furthermore, support for the conservation of Australia’s less well-known tropical mammals is shown to increase relative to better known mammals (icons) present in temperate areas, such as koalas and red kangaroos with this increased knowledge. Possible implications of the results for government conservation policies in Australia are examined.
Resumo:
Motivated by application of twisted current algebra in description of the entropy of Ads(3) black hole, we investigate the simplest twisted current algebra sl(3, c)(k)((2)). Free field representation of the twisted algebra, and the corresponding twisted Sugawara energy-momentum tensor are obtained by using three (beta, gamma) pairs and two scalar fields. Primary fields and two screening currents of the first kind are presented. (C) 2001 Published by Elsevier Science B.V.
Resumo:
Evaluative learning theory states that affective learning, the acquisition of likes and dislikes, is qualitatively different from relational learning, the learning of predictive relationships among stimuli. Three experiments tested the prediction derived from evaluative learning theory that relational learning, but not affective learning, is affected by stimulus competition by comparing performance during two conditional stimuli, one trained in a superconditioning procedure and the other in a blocking procedure. Ratings of unconditional stimulus expectancy and electrodermal responses indicated stimulus competition in relational learning. Evidence for stimulus competition in affective learning was provided by verbal ratings of conditional stimulus pleasantness and by measures of blink startle modulation. Taken together, the present experiments demonstrate stimulus competition in relational and affective learning, a result inconsistent with evaluative learning theory. (C) 2001 Academic Press.
Resumo:
We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
Binning and truncation of data are common in data analysis and machine learning. This paper addresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM approach proposed by McLachlan and Jones (Biometrics, 44: 2, 571-578, 1988) for the univariate case is generalized to multivariate measurements. The multivariate solution requires the evaluation of multidimensional integrals over each bin at each iteration of the EM procedure. Naive implementation of the procedure can lead to computationally inefficient results. To reduce the computational cost a number of straightforward numerical techniques are proposed. Results on simulated data indicate that the proposed methods can achieve significant computational gains with no loss in the accuracy of the final parameter estimates. Furthermore, experimental results suggest that with a sufficient number of bins and data points it is possible to estimate the true underlying density almost as well as if the data were not binned. The paper concludes with a brief description of an application of this approach to diagnosis of iron deficiency anemia, in the context of binned and truncated bivariate measurements of volume and hemoglobin concentration from an individual's red blood cells.
Resumo:
Groupers (Epinephelinae) are prominent marine fishes distributed in the warmer waters of the world. Review of the literature suggests that trematodes are known from only 62 of the 159 species and only 9 of 15 genera; nearly 90% of host-parasite combinations have been reported only once or twice. All 20 families and all but 7 of 76 genera of trematodes found in epinephelines also occur in non-epihephelines. Only 12 genera of trematodes are reported from both the Atlantic-Eastern Pacific and the Indo-West Pacific. Few (perhaps no) species are credibly cosmopolitan but some have wide distributions across the Indo-West Pacific. The hierarchical 'relatedness' of epinephelines as suggested by how they share trematode taxa (families, genera, species) shows little congruence with what is known of their phylogeny. The major determinant of relatedness appears to be geographical proximity. Together these attributes suggest that host-parasite coevolution has contributed little to the evolution of trematode communities of epinephelines. Instead, they appear to have arisen through localized episodes of host-switching, presumably both into and out of the epinephelines. The Epinephelinae may well be typical of most groups of marine fishes both in the extent to which their trematode parasites are known and in that, apparently, co-evolution has contributed little to the evolution of their communities of trematodes.
Resumo:
Knowledge is central to the modern economy and society. Indeed, the knowledge society has transformed the concept of knowledge and is more and more aware of the need to overcome the lack of knowledge when has to make options or address its problems and dilemmas. One’s knowledge is less based on exact facts and more on hypotheses, perceptions or indications. Even when we use new computational artefacts and novel methodologies for problem solving, like the use of Group Decision Support Systems (GDSSs), the question of incomplete information is in most of the situations marginalized. On the other hand, common sense tells us that when a decision is made it is impossible to have a perception of all the information involved and the nature of its intrinsic quality. Therefore, something has to be made in terms of the information available and the process of its evaluation. It is under this framework that a Multi-valued Extended Logic Programming language will be used for knowledge representation and reasoning, leading to a model that embodies the Quality-of-Information (QoI) and its quantification, along the several stages of the decision-making process. In this way, it is possible to provide a measure of the value of the QoI that supports the decision itself. This model will be here presented in the context of a GDSS for VirtualECare, a system aimed at sustaining online healthcare services.