914 resultados para Domain-specific visual language


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Recently, goal orientation, a mental framework for understanding how individuals approach learning and achievement situadons, has emerged as an important predictor of performance. This study addressed the effects of domain-specific avoid and prove orientations on performance from the betweenand within-person levels of analysis. One hundred and three participants performed thirty trials of an airtraffic control task. Domain-specific avoid and prove orientations were measured before each trial to assess the effects of changes in goal orientadon on changes in performance (i.e. within-person relationships). Average levels of avoid and prove orientations were calculated to assess the effect of goal orientation on overall performance (i.e. between-person relationships). Findings from the between-person level of analysis revealed that high prove-orientated individuals performed better than low proveorientated individuals. Results also revealed that average goal orientation levels moderated the withinperson relationships. The effect of changes in avoid orientation on changes in performance was stronger for low versus high avoid-oriented individuals while the effect of changes in prove orientadon on changes in performances was stronger for low versus highprove oriented individuals. Implications of these findings are considered.

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Domain specific information retrieval has become in demand. Not only domain experts, but also average non-expert users are interested in searching domain specific (e.g., medical and health) information from online resources. However, a typical problem to average users is that the search results are always a mixture of documents with different levels of readability. Non-expert users may want to see documents with higher readability on the top of the list. Consequently the search results need to be re-ranked in a descending order of readability. It is often not practical for domain experts to manually label the readability of documents for large databases. Computational models of readability needs to be investigated. However, traditional readability formulas are designed for general purpose text and insufficient to deal with technical materials for domain specific information retrieval. More advanced algorithms such as textual coherence model are computationally expensive for re-ranking a large number of retrieved documents. In this paper, we propose an effective and computationally tractable concept-based model of text readability. In addition to textual genres of a document, our model also takes into account domain specific knowledge, i.e., how the domain-specific concepts contained in the document affect the document’s readability. Three major readability formulas are proposed and applied to health and medical information retrieval. Experimental results show that our proposed readability formulas lead to remarkable improvements in terms of correlation with users’ readability ratings over four traditional readability measures.

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This thesis attempts a psychological investigation of hemispheric functioning in developmental dyslexia. Previous work using neuropsychological methods with developmental dyslexics is reviewed ,and original work is presented both of a conventional psychometric nature and also utilising a new means of intervention. At the inception of inquiry into dyslexia, comparisons were drawn between developmental dyslexia and acquired alexia, promoting a model of brain damage as the common cause. Subsequent investigators found developmental dyslexics to be neurologically intact, and so an alternative hypothesis was offered, namely that language is abnormally localized (not in the left hemisphere). Research in the last decade, using the advanced techniques of modern neuropsychology, has indicated that developmental dyslexics are probably left hemisphere dominant for language. The development of a new type of pharmaceutical prep~ration (that appears to have a left hemisphere effect) offers an oppertunity to test the experimental hypothesis. This hypothesis propounds that most dyslexics are left hemisphere language dominant, but some of these language related operations are dysfunctioning. The methods utilised are those of psychological assessment of cognitive function, both in a traditional psychometric situation, and with a new form of intervention (Piracetam). The information resulting from intervention will be judged on its therapeutic validity and contribution to the understanding of hemispheric functioning in dyslexics. The experimental studies using conventional psychometric evaluation revealed a dyslexic profile of poor sequencing and name coding ability, with adequate spatial and verbal reasoning skills. Neuropsychological information would tend to suggest that this profile was indicative of adequate right hemsiphere abilities and deficits in some left hemsiphere abilities. When an intervention agent (Piracetam) was used with young adult dyslexics there were improvements in both the rate of acquisition and conservation of verbal learning. An experimental study with dyslexic children revealed that Piracetam appeared to improve reading, writing and sequencing, but did not influence spatial abilities. This would seem to concord with other recent findings, that deve~mental dyslexics may have left hemisphere language localisation, although some of these language related abilities are dysfunctioning.

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Many studies have assessed the neural underpinnings of creativity, failing to find a clear anatomical localization. We aimed to provide evidence for a multi-componential neural system for creativity. We applied a general activation likelihood estimation (ALE) meta-analysis to 45 fMRI studies. Three individual ALE analyses were performed to assess creativity in different cognitive domains (Musical, Verbal, and Visuo-spatial). The general ALE revealed that creativity relies on clusters of activations in the bilateral occipital, parietal, frontal, and temporal lobes. The individual ALE revealed different maximal activation in different domains. Musical creativity yields activations in the bilateral medial frontal gyrus, in the left cingulate gyrus, middle frontal gyrus, and inferior parietal lobule and in the right postcentral and fusiform gyri. Verbal creativity yields activations mainly located in the left hemisphere, in the prefrontal cortex, middle and superior temporal gyri, inferior parietal lobule, postcentral and supramarginal gyri, middle occipital gyrus, and insula. The right inferior frontal gyrus and the lingual gyrus were also activated. Visuo-spatial creativity activates the right middle and inferior frontal gyri, the bilateral thalamus and the left precentral gyrus. This evidence suggests that creativity relies on multi-componential neural networks and that different creativity domains depend on different brain regions.

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The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. ^ Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. ^ This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model’s parsing mechanism. ^ The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents. ^

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The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model's parsing mechanism. The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Objective: To develop and test the utility of a domain-specific physical activity efficacy scale in adolescents for predicting physical activity behaviour. Design: Two independent studies were conducted. Study 1 examined the psychometric properties of a newly constructed Domain-Specific Physical Activity Efficacy Questionnaire (DSPAEQ) and study 2 tested the utility of the scale for predicting leisure- and school-time physical activity. Methods: In study 1, descriptive physical activity data were used to generate scale items. The scales factor structure and internal consistency were tested in a sample of 272 adolescents. A subsequent sample of Canadian (N = 104) and New Zealand (N = 29) adolescents, was recruited in study 2 to explore the scale's predictive validity using a subjective measure of leisure- and school-time physical activity. Results: A principle axis factor analysis in study 1 revealed a 26-item, five-factor coherent and interpretable solution; representative of leisure and recreation, household, ambulatory, transportation, and school physical activity efficacy constructs, respectively. The five-factor solution explained 81% of the response variance. In study 2 the domain-specific efficacy model explained 16% and 1% of leisure- and school-time physical activity response variance, respectively, with leisure time physical activity efficacy identified as a unique and significant contributor of leisure-time physical activity. Conclusion: Study 1 provides evidence for the tenability of a five factor DSPEAQ, while study 2 shows that the DSPEAQ has utility in predicting domain-specific physical activity. This latter finding underscores the importance of scale correspondence between the behavioural elements (leisure-time physical activity) and cognitive assessment of those elements (leisure-time physical activity efficacy).

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Software environment emulation provides a means for simulating an operational environment of a system. This process involves approximation of systems’ external behaviors and their communications with a system to be tested in the environment. Development of such an environment is a tedious task and involves complex low level coding. Model driven engineering is an avenue to raise the level of abstraction beyond programming by specifying solution directly using problem domain concepts. In this paper we propose a novel domain-specific modeling tool to generate complex testing environments. Our tool employs a suite of domain-specific visual modeling languages for modelling emulation environment at a high level of abstraction. These high level specifications are then automatically transformed to runtimeenvironment for application integration testing, boosting development productivity and ease of use.