131 resultados para parental selection.


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Two experiments are described which explore the relationship between parental reports of infants' receptive vocabularies at 1; 6 (Experiment 1a) or 1-3, 1;6 and 1;9 (Experiment 1b) and the comprehension infants demonstrated in a preferential looking task. The instrument used was the Oxford CD1, a British English adaptation of the MacArthur-Bates CD1 (Words & Gestures). Infants were shown pairs of images of familiar objects, either both name-known or both name-unknown according to their parent's responses on the CD1. At all ages, and on both name-known and name-unknown trials, preference for the target image increased significantly from baseline when infants heard the target's label. This discrepancy suggests that parental report underestimates infants' word knowledge.

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Background Little is known about the relative effects of exposure to postnatal depression and parental conflict on the social functioning of school-aged children. This is, in part, because of a lack of specificity in the measurement of child and parental behaviour and a reliance on children's reports of their hypothetical responses to conflict in play. Methods In the course of a prospective longitudinal study of children of postnatally depressed and well women, 5-year-old children were videotaped at home with a friend in a naturalistic dressing-up play setting. As well as examining possible associations between the occurrence of postnatal depression and the quality of the children's interactions, we investigated the influence of parental conflict and co-operation, and the continuity of maternal depression. The quality of the current mother-child relationship was considered as a possible mediating factor. Results Exposure to postnatal depression was associated with increased likelihood, among boys, of displaying physical aggression in play with their friend. However, parental conflict mediated the effects of postnatal depression on active aggression during play, and was also associated with displays of autonomy and intense conflict. While there were no gender effects in terms of the degree or intensity of aggressive behaviours, girls were more likely to express aggression verbally using denigration and gloating whereas boys were more likely to display physical aggression via interpersonal and object struggles. Conclusions The study provided evidence for the specificity of effects, with strong links between parental and child peer conflict. These effects appear to arise from direct exposure to parental conflict, rather than indirectly, through mother-child interactions.

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Given the paucity of research in this area, the primary aim of this study was to explore how parents of infants with unclear sex at birth made sense of 'intersex'. Qualitative methods were, used (semi-structured interviews, interpretative phenomenological analysis) with 10 parents to generate pertinent themes and provide ideas for further research. Our analysis highlights the fundamental shock engendered by the uncertain sex status of children, and documents parental struggles to negotiate a coherent sex identity for their children. Findings are discussed in light of the rigid two-sex system which pervades medicine and everyday life, and we argue that greater understanding of the complexity of sex and gender is required in order to facilitate better service provision and, ultimately, greater informed consent and parental participation regarding decisions about their children's status.

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Supplier selection has a great impact on supply chain management. The quality of supplier selection also affects profitability of organisations which work in the supply chain. As suppliers can provide variety of services and customers demand higher quality of service provision, the organisation is facing challenges for making the right choice of supplier for the right needs. The existing methods for supplier selection, such as data envelopment analysis (DEA) and analytical hierarchy process (AHP) can automatically perform selection of competitive suppliers and further decide winning supplier(s). However, these methods are not capable of determining the right selection criteria which should be derived from the business strategy. An ontology model described in this paper integrates the strengths of DEA and AHP with new mechanisms which ensure the right supplier to be selected by the right criteria for the right customer's needs.

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In this paper, we present a feature selection approach based on Gabor wavelet feature and boosting for face verification. By convolution with a group of Gabor wavelets, the original images are transformed into vectors of Gabor wavelet features. Then for individual person, a small set of significant features are selected by the boosting algorithm from a large set of Gabor wavelet features. The experiment results have shown that the approach successfully selects meaningful and explainable features for face verification. The experiments also suggest that for the common characteristics such as eyes, noses, mouths may not be as important as some unique characteristic when training set is small. When training set is large, the unique characteristics and the common characteristics are both important.

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An orthogonal forward selection (OFS) algorithm based on the leave-one-out (LOO) criterion is proposed for the construction of radial basis function (RBF) networks with tunable nodes. This OFS-LOO algorithm is computationally efficient and is capable of identifying parsimonious RBF networks that generalise well. Moreover, the proposed algorithm is fully automatic and the user does not need to specify a termination criterion for the construction process.

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An orthogonal forward selection (OFS) algorithm based on leave-one-out (LOO) criteria is proposed for the construction of radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines an RBF node, namely, its center vector and diagonal covariance matrix, by minimizing the LOO statistics. For regression application, the LOO criterion is chosen to be the LOO mean-square error, while the LOO misclassification rate is adopted in two-class classification application. This OFS-LOO algorithm is computationally efficient, and it is capable of constructing parsimonious RBF networks that generalize well. Moreover, the proposed algorithm is fully automatic, and the user does not need to specify a termination criterion for the construction process. The effectiveness of the proposed RBF network construction procedure is demonstrated using examples taken from both regression and classification applications.