5 resultados para Structure learning

em University of Queensland eSpace - Australia


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A manager's perception of industry structure (dynamism) has the potential to impact various organizational strategies and behaviors. This may be particularly so with regard to perceptions driving organizational learning orientations and innovation based marketing strategy. The position taken here suggests that firms operating within a competitive industry tend to pursue innovative ways of performing value-creating activities, which requires the development of learning capabilities. The results of a study of SMEs suggest that market focused learning, relative to other learning capabilities plays a key role in the relationships between industry structure, innovation and brand performance. The findings also show that market focused learning and internally focused learning influence innovation and that innovation influences a brand's performance. (c) 2005 Elsevier Inc. All rights reserved.

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Three experiments are reported that examined the process by which trainees learn decision-making skills during a critical incident training program. Formal theories of category learning were used to identify two processes that may be responsible for the acquisition of decision-making skills: rule learning and exemplar learning. Experiments I and 2 used the process dissociation procedure (L. L. Jacoby, 1998) to evaluate the contribution of these processes to performance. The results suggest that trainees used a mixture of rule and exemplar learning. Furthermore, these learning processes were influenced by different aspects of training structure and design. The goal of Experiment 3 was to develop training techniques that enable trainees to use a rule adaptively. Trainees were tested on cases that represented exceptions to the rule. Unexpectedly, the results suggest that providing general instruction regarding the kinds of conditions in which a decision rule does not apply caused them to fixate on the specific conditions mentioned and impaired their ability to identify other conditions in which the rule might not apply. The theoretical, methodological, and practical implications of the results are discussed.

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Background: The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for predicting a continuum secondary structure, i.e. assigning probabilities to the conformational states of a residue. We train our methods using data derived from high-quality NMR models. Results: Several probabilistic models not only successfully estimate the continuum secondary structure, but also provide a categorical output on par with models directly trained on categorical data. Importantly, models trained on the continuum secondary structure are also better than their categorical counterparts at identifying the conformational state for structurally ambivalent residues. Conclusion: Cascaded probabilistic neural networks trained on the continuum secondary structure exhibit better accuracy in structurally ambivalent regions of proteins, while sustaining an overall classification accuracy on par with standard, categorical prediction methods.

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Pseudowords with inconsistent vs. consistent spellings (e.g., nurch, with rhyme neighbours search, lurch & perch, vs. mish, with neighbours dish, wish) were presented with definitions for naming either twice or 6 times. In an oral spelling test, there were main and interactive effects of consistency and the number of training trials on accuracy and main effects only on response latency, with the improvement in accuracy from 2 to 6 training trials greater for the more poorly learned inconsistent items. Of most interest, the smaller effect of training on accuracy in the consistent condition was reliable; contrary to the most obvious prediction of dual route spelling models that the sublexical procedure should produce correct spellings for consistent items early in training. In a second task students wrote spellings of multisyllabic words containing unstressed indeterminate (schwa) vowels. In their errors on the schwa vowel, students showed sensitivity to the most common spelling overall but also they were influenced by differences in schwa spellings in English words as a function of the number of syllables and schwa position. These results indicate that dual route models of spelling will need to accommodate the consistency of spellings within categories defined by lexical structure variables.