924 resultados para Linguistic input


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Climate change is one of the major challenges facing economic systems at the start of the 21st century. Reducing greenhouse gas emissions will require both restructuring the energy supply system (production) and addressing the efficiency and sufficiency of the social uses of energy (consumption). The energy production system is a complicated supply network of interlinked sectors with 'knock-on' effects throughout the economy. End use energy consumption is governed by complex sets of interdependent cultural, social, psychological and economic variables driven by shifts in consumer preference and technological development trajectories. To date, few models have been developed for exploring alternative joint energy production-consumption systems. The aim of this work is to propose one such model. This is achieved in a methodologically coherent manner through integration of qualitative input-output models of production, with Bayesian belief network models of consumption, at point of final demand. The resulting integrated framework can be applied either (relatively) quickly and qualitatively to explore alternative energy scenarios, or as a fully developed quantitative model to derive or assess specific energy policy options. The qualitative applications are explored here.

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This paper draws on ethnographic case-study research conducted amongst a group of first and second generation immigrant children in six inner-city schools in London. It focuses on language attitudes and language choice in relation to cultural maintenance, on the one hand, and career aspirations on the other. It seeks to provide insight into some of the experiences and dilemmatic choices encountered and negotiations engaged in by transmigratory groups, how they define cultural capital, and the processes through which new meanings are shaped as part of the process of defining a space within the host society. Underlying this discussion is the assumption that alternative cultural spaces in which multiple identities and possibilities can be articulated already exist in the rich texture of everyday life amongst transmigratory groups. The argument that whilst the acquisition of 'world languages' is a key variable in accumulating cultural capital, the maintenance of linguistic diversity retains potent symbolic power in sustaining cohesive identities is a recurring theme.

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Williams syndrome (WS) is characterized by apparent relative strengths in language, facial processing and social cognition but by profound impairment in spatial cognition, planning and problem solving. Following recent research which suggests that individuals with WS may be less linguistically able than was once thought, in this paper we begin to investigate why and how they may give the impression of linguistic proficiency despite poor standardized test results. This case study of Brendan, a 12-year-old boy with WS, who presents with a considerable lack of linguistic ability, suggests that impressions of linguistic competence may to some extent be the result of conversational strategies which enable him to compensate for various cognitive and linguistic deficits with a considerable degree of success. These conversational strengths are not predicted by his standardized language test results, and provide compelling support for the use of approaches such as Conversation Analysis in the assessment of individuals with communication impairments.

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Williams syndrome (WS) is a rare genetic disorder resulting from a deletion on chromosome 7. A number of studies have shown that individuals with WS have a superior linguistic profile compared to their non-verbal abilities, however the evidence has been inconclusive, as many studies have disputed such a profile. The vast majority of studies on WS have assumed a single, homogeneous WS linguistic profile in order to support various theoretical viewpoints. The present study investigated the linguistic profiles of 5 individuals with WS on a number of standardized verbal measures and in conversational settings. The results indicated substantially variable performance in all aspects of the verbal domain, which supports the view that WS, linguistically, is a rather heterogeneous condition and this should be taken into consideration when referring to it in theoretical accounts of language acquisition and debates on modularity.

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The potential of clarification questions (CQs) to act as a form of corrective input for young children's grammatical errors was examined. Corrective responses were operationalized as those occasions when child speech shifted from erroneous to correct (E -> C) contingent on a clarification question. It was predicted that E -> C sequences would prevail over shifts in the opposite direction (C -> E), as can occur in the case of nonerror-contingent CQs. This prediction was tested via a standard intervention paradigm, whereby every 60s a sequence of two clarification requests (either specific or general) was introduced into conversation with a total of 45 2- and 4-year-old children. For 10 categories of grammatical structure, E -> C sequences predominated over their C -> E counterparts, with levels of E -> C shifts increasing after two clarification questions. Children were also more reluctant to repeat erroneous forms than their correct counterparts, following the intervention of CQs. The findings provide support for Saxton's prompt hypothesis, which predicts that error-contingent CQs bear the potential to cue recall of previously acquired grammatical forms.

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In immediate recall tasks, visual recency is substantially enhanced when output interference is low (Cowan, Saults, Elliott, & Moreno, 2002; Craik, 1969) whereas auditory recency remains high even under conditions of high output interference. Ibis auditory advantage has been interpreted in terms of auditory resistance to output interference (e.g., Neath & Surprenant, 2003). In this study the auditory-visual difference at low output interference re-emerged when ceiling effects were accounted for, but only with spoken output. With written responding the auditory advantage remained significantly larger with high than with low output interference. These new data suggest that both superior auditory encoding and modality-specific output interference contribute to the classic auditory-visual modality effect.

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The comparison of cognitive and linguistic skills in individuals with developmental disorders is fraught with methodological and psychometric difficulties. In this paper, we illustrate some of these issues by comparing the receptive vocabulary knowledge and non-verbal reasoning abilities of 41 children with Williams syndrome, a genetic disorder in which language abilities are often claimed to be relatively strong. Data from this group were compared with data from typically developing children, children with Down syndrome, and children with non-specific learning difficulties using a number of approaches including comparison of age-equivalent scores, matching, analysis of covariance, and regression-based standardization. Across these analyses children with Williams syndrome consistently demonstrated relatively good receptive vocabulary knowledge, although this effect appeared strongest in the oldest children.

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The combination of model predictive control based on linear models (MPC) with feedback linearization (FL) has attracted interest for a number of years, giving rise to MPC+FL control schemes. An important advantage of such schemes is that feedback linearizable plants can be controlled with a linear predictive controller with a fixed model. Handling input constraints within such schemes is difficult since simple bound contraints on the input become state dependent because of the nonlinear transformation introduced by feedback linearization. This paper introduces a technique for handling input constraints within a real time MPC/FL scheme, where the plant model employed is a class of dynamic neural networks. The technique is based on a simple affine transformation of the feasible area. A simulated case study is presented to illustrate the use and benefits of the technique.

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In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

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