939 resultados para Statistical Language Model


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Thesis (Ph.D.)--University of Washington, 2016-06

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The phenotypic and genetic factor structure of performance on five Multidimensional Aptitude Battery (MAB) subtests and one Wechsler Adult Intelligence Scale-Revised (WAIS-R) subtest was explored in 390 adolescent twin pairs (184 monozygotic [MZ]; 206 dizygotic (DZ)). The temporal stability of these measures was derived from a subsample of 49 twin pairs, with test-retest correlations ranging from .67 to .85. A phenotypic factor model, in which performance and verbal factors were correlated, provided a good fit to the data. Genetic modeling was based on the phenotypic factor structure, but also took into account the additive genetic (A), common environmental (C), and unique environmental (E) parameters derived from a fully saturated ACE model. The best fitting model was characterized by a genetic correlated two-factor structure with specific effects, a general common environmental factor, and overlapping unique environmental effects. Results are compared to multivariate genetic models reported in children and adults, with the most notable difference being the growing importance of common genes influencing diverse abilities in adolescence. (C) 2003 Elsevier Inc. All rights reserved.

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Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

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Commercial explosives behave non-ideally in rock blasting. A direct and convenient measure of non-ideality is the detonation velocity. In this study, an alternative model fitted to experimental unconfined detonation velocity data is proposed and the effect of confinement on the detonation velocity is modelled. Unconfined data of several explosives showing various levels of nonideality were successfully modelled. The effect of confinement on detonation velocity was modelled empirically based on field detonation velocity measurements. Confined detonation velocity is a function of the ideal detonation velocity, unconfined detonation velocity at a given blasthole diameter and rock stiffness. For a given explosive and charge diameter, as confinement increases detonation velocity increases. The confinement model is implemented in a simple engineering based non-ideal detonation model. A number of simulations are carried out and analysed to predict the explosive performance parameters for the adopted blasting conditions.

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Purpose : The purpose of this article is to critically review the literature to examine factors that are most consistently related to employment outcome following traumatic brain injury (TBI), with a particular focus on metacognitive skills. It also aims to develop a conceptual model of factors related to employment outcome. Method : The first stage of the review considered 85 studies published between 1980 and December 2003 which investigated factors associated with employment outcome following TBI. English-language studies were identified through searches of Medline and PsycINFO, as well as manual searches of journals and reference lists. The studies were evaluated and rated by two independent raters (Kappa = 0.835) according to the quality of their methodology based upon nine criteria. Fifty studies met the criteria for inclusion in the second stage of the review, which examined the relationship between a broad range of variables and employment outcome. Results : The factors most consistently associated with employment outcome included pre-injury occupational status, functional status at discharge, global cognitive functioning, perceptual ability, executive functioning, involvement in vocational rehabilitation services and emotional status. Conclusions : A conceptual model is presented which emphasises the importance of metacognitive, emotional and social environment factors for improving employment outcome.

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The purpose of this work was to model lung cancer mortality as a function of past exposure to tobacco and to forecast age-sex-specific lung cancer mortality rates. A 3-factor age-period-cohort (APC) model, in which the period variable is replaced by the product of average tar content and adult tobacco consumption per capita, was estimated for the US, UK, Canada and Australia by the maximum likelihood method. Age- and sex-specific tobacco consumption was estimated from historical data on smoking prevalence and total tobacco consumption. Lung cancer mortality was derived from vital registration records. Future tobacco consumption, tar content and the cohort parameter were projected by autoregressive moving average (ARIMA) estimation. The optimal exposure variable was found to be the product of average tar content and adult cigarette consumption per capita, lagged for 2530 years for both males and females in all 4 countries. The coefficient of the product of average tar content and tobacco consumption per capita differs by age and sex. In all models, there was a statistically significant difference in the coefficient of the period variable by sex. In all countries, male age-standardized lung cancer mortality rates peaked in the 1980s and declined thereafter. Female mortality rates are projected to peak in the first decade of this century. The multiplicative models of age, tobacco exposure and cohort fit the observed data between 1950 and 1999 reasonably well, and time-series models yield plausible past trends of relevant variables. Despite a significant reduction in tobacco consumption and average tar content of cigarettes sold over the past few decades, the effect on lung cancer mortality is affected by the time lag between exposure and established disease. As a result, the burden of lung cancer among females is only just reaching, or soon will reach, its peak but has been declining for I to 2 decades in men. Future sex differences in lung cancer mortality are likely to be greater in North America than Australia and the UK due to differences in exposure patterns between the sexes. (c) 2005 Wiley-Liss, Inc.

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Sorghum is the main dryland summer crop in NE Australia and a number of agricultural businesses would benefit from an ability to forecast production likelihood at regional scale. In this study we sought to develop a simple agro-climatic modelling approach for predicting shire (statistical local area) sorghum yield. Actual shire yield data, available for the period 1983-1997 from the Australian Bureau of Statistics, were used to train the model. Shire yield was related to a water stress index (SI) that was derived from the agro-climatic model. The model involved a simple fallow and crop water balance that was driven by climate data available at recording stations within each shire. Parameters defining the soil water holding capacity, maximum number of sowings (MXNS) in any year, planting rainfall requirement, and critical period for stress during the crop cycle were optimised as part of the model fitting procedure. Cross-validated correlations (CVR) ranged from 0.5 to 0.9 at shire scale. When aggregated to regional and national scales, 78-84% of the annual variation in sorghum yield was explained. The model was used to examine trends in sorghum productivity and the approach to using it in an operational forecasting system was outlined. (c) 2005 Elsevier B.V. All rights reserved.

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Technological advances have brought about the ever-increasing utilisation of computer-assisted language learning ( CALL) media in the learning of a second language (L2). Computer-mediated communication, for example, provides a practical means for extending the learning of spoken language, a challenging process in tonal languages such as Chinese, beyond the realms of the classroom. In order to effectively improve spoken language competency, however, CALL applications must also reproduce the social interaction that lies at the heart of language learning and language use. This study draws on data obtained from the utilisation of CALL in the learning of L2 Chinese to explore whether this medium can be used to extend opportunities for rapport-building in language teaching beyond the face-to-face interaction of the classroom. Rapport's importance lies in its potential to enhance learning, motivate learners, and reduce learner anxiety. To date, CALL's potential in relation to this facet of social interaction remains a neglected area of research. The results of this exploratory study suggest that CALL may help foster learner-teacher rapport and that scaffolding, such as strategically composing rapport-fostering questions in sound-files, is conducive to this outcome. The study provides an instruction model for this application of CALL.