895 resultados para Semantic gap


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Children are increasingly being recognised as a significant force in the retail market place, as primary consumers, influencers of others, and as future customers. This paper adds to the literature on children as consumers by exploring their attitudinal responses to a specific group of products: Fair Trade lines. There has been no research to date that has specifically addressed children as consumers of Fair Trade or the ethical purchase decision-making process in this area. The methodological approach taken here is an essentially interpretive and naturalistic analysis of two focus groups of school children. The analysis found that there is an urgent need to develop meaningful Fair Trade brands that combine strong brand knowledge and positive brand images to bridge the ethical purchase gap between the formation of clear ethical attitudes and actual ethical purchase behaviour. Such an approach would both capture more of the children’s primary market and influence future purchase behaviour. It is argued that Fair Trade actors should coordinate new marketing communications campaigns that build brand knowledge structures holistically around the Fair Trade process and that extend beyond merely raising consumer awareness.

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In induction machines the tooth frequency losses due to permeance variation constitute a signif'icant, portion of the total loss. In order to predict and estimate these losses it, is essential to obtain a clear understanding of the no-load distribution of the air gap magnetic field and the magnitude of flux pulsation in both stator and rotor teeth. The existing theories and methods by which the air gap permeance variation in a doubly slotted structure is calculated are either empirical or restricted. The main objective of this thesis is to obtain a detailed analysis of the no-load air gap magnetic field distribution and the effect of air gap geometry on the magnitude and waveform of the tooth flux pulsation. In this thesis a detaiiled theoretical and experimental analysis of flux distribution not only leads to a better understanding of the distribution of no-load losses but also provides theoretical analysis for calculating the losses with greater accuracy

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Category-specific disorders are frequently explained by suggesting that living and non-living things are processed in separate subsystems (e.g. Caramazza & Shelton, 1998). If subsystems exist, there should be benefits for normal processing, beyond the influence of structural similarity. However, no previous study has separated the relative influences of similarity and semantic category. We created novel examples of living and non-living things so category and similarity could be manipulated independently. Pre-tests ensured that our images evoked appropriate semantic information and were matched for familiarity. Participants were trained to associate names with the images and then performed a name-verification task under two levels of time pressure. We found no significant advantage for living things alongside strong effects of similarity. Our results suggest that similarity rather than category is the key determinant of speed and accuracy in normal semantic processing. We discuss the implications of this finding for neuropsychological studies. © 2005 Psychology Press Ltd.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY WITH PRIOR ARRANGEMENT

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This work explores the relevance of semantic and linguistic description to translation, theory and practice. It is aimed towards a practical model of approach to texts to translate. As literary texts [poetry mainly] are the focus of attention, so are stylistic matters. Note, however, that 'style', and, to some extent, the conclusions of the work, are not limited to so-called literary texts. The study of semantic description reveals that most translation problems do not stem from the cognitive (langue-related), but rather from the contextual (parole-related) aspects of meaning. Thus, any linguistic model that fails to account for the latter is bound to fall short. T.G.G. does, whereas Systemics, concerned with both the 'Iangue' and 'parole' (stylistic and sociolinguistic mainly) aspects of meaning, provides a useful framework of approach to texts to translate. Two essential semantic principles for translation are: that meaning is the property of a language (Firth); and the 'relativity of meaning assignments' (Tymoczko). Both imply that meaning can only be assessed, correctly, in the relevant socio-cultural background. Translation is seen as a restricted creation, and the translator's encroach as a three-dimensional critical one. To encompass the most technical to the most literary text, and account for variations in emphasis in any text, translation theory must be based on typology of function Halliday's ideational, interpersonal and textual, or, Buhler's symbol, signal, symptom, Functions3. Function Coverall and specific] will dictate aims and method, and also provide the critic with criteria to assess translation Faithfulness. Translation can never be reduced to purely objective methods, however. Intuitive procedures intervene, in textual interpretation and analysis, in the choice of equivalents, and in the reception of a translation. Ultimately, translation, theory and practice, may perhaps constitute the touchstone as regards the validity of linguistic and semantic theories.

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In a series of experiments, we tested category-specific activation in normal parti¬cipants using magnetoencephalography (MEG). Our experiments explored the temporal processing of objects, as MEG characterises neural activity on the order of milliseconds. Our experiments explored object-processing, including assessing the time-course of ob¬ject naming, early differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level, and late differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level. In addition to studies using normal participants, we also utilised MEG to explore category-specific processing in a patient with a deficit for living objects. Our findings support the cascade model of object naming (Humphreys et al., 1988). In addition, our findings using normal participants demonstrate early, category-specific perceptual differences. These findings are corroborated by our patient study. In our assessment of the time-course of category-specific effects as well as a separate analysis designed to measure semantic differences between living and nonliving objects, we found support for the sensory/motor model of object naming (Martin, 1998), in addition to support for the cascade model of object naming. Thus, object processing in normal participants appears to be served by a distributed network in the brain, and there are both perceptual and semantic differences between living and nonliving objects. A separate study assessing the influence of the level at which you are asked to identify an object on processing in the brain found evidence supporting the convergence zone hypothesis (Damasio, 1989). Taken together, these findings indicate the utility of MEG in exploring the time-course of object processing, isolating early perceptual and later semantic effects within the brain.

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The topic of this thesis is the development of knowledge based statistical software. The shortcomings of conventional statistical packages are discussed to illustrate the need to develop software which is able to exhibit a greater degree of statistical expertise, thereby reducing the misuse of statistical methods by those not well versed in the art of statistical analysis. Some of the issues involved in the development of knowledge based software are presented and a review is given of some of the systems that have been developed so far. The majority of these have moved away from conventional architectures by adopting what can be termed an expert systems approach. The thesis then proposes an approach which is based upon the concept of semantic modelling. By representing some of the semantic meaning of data, it is conceived that a system could examine a request to apply a statistical technique and check if the use of the chosen technique was semantically sound, i.e. will the results obtained be meaningful. Current systems, in contrast, can only perform what can be considered as syntactic checks. The prototype system that has been implemented to explore the feasibility of such an approach is presented, the system has been designed as an enhanced variant of a conventional style statistical package. This involved developing a semantic data model to represent some of the statistically relevant knowledge about data and identifying sets of requirements that should be met for the application of the statistical techniques to be valid. Those areas of statistics covered in the prototype are measures of association and tests of location.