812 resultados para Automatic Thoughts Questionnaire


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This questionnaire aims to evaluate your experience of taking part in the project you are carrying out at the university. The questionnaire is anonymous and will not take more than 10 minutes of your time to complete. We would appreciate your honest opinion, in order that the data we gather here can be as useful as possible for improving the project.

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This questionnaire aims to evaluate your experience of taking part in the project you are carrying out at the university. The questionnaire is anonymous and will not take more than 10 minutes of your time to complete. We would appreciate your honest opinion, in order that the data we gather here can be as useful as possible for improving the project.

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Abstract

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The most adequate approach for benchmarking web accessibility is manual expert evaluation supplemented by automatic analysis tools. But manual evaluation has a high cost and is impractical to be applied on large websites. In reality, there is no choice but to rely on automated tools when reviewing large web sites for accessibility. The question is: to what extent the results from automatic evaluation of a web site and individual web pages can be used as an approximation for manual results? This paper presents the initial results of an investigation aimed at answering this question. He have performed both manual and automatic evaluations of the accessibility of web pages of two sites and we have compared the results. In our data set automatically retrieved results could most definitely be used as an approximation manual evaluation results.

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This paper proposes to enrich RBMTdictionaries with Named Entities(NEs) automatically acquired fromWikipedia. The method is appliedto the Apertium English-Spanishsystem and its performance comparedto that of Apertium with and withouthandtagged NEs. The system withautomatic NEs outperforms the onewithout NEs, while results vary whencompared to a system with handtaggedNEs (results are comparable forSpanish to English but slightly worstfor English to Spanish). Apart fromthat, adding automatic NEs contributesto decreasing the amount of unknownterms by more than 10%.

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The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.

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OBJECTIVES: To evaluate the performance of the INTERMED questionnaire score, alone or combined with other criteria, in predicting return to work after a multidisciplinary rehabilitation program in patients with non-specific chronic low back pain. METHODS: The INTERMED questionnaire is a biopsychosocial assessment and clinical classification tool that separates heterogeneous populations into subgroups according to case complexity. We studied 88 patients with chronic low back pain who followed an intensive multidisciplinary rehabilitation program on an outpatient basis. Before the program, we recorded the INTERMED score, radiological abnormalities, subjective pain severity, and sick leave duration. Associations between these variables and return to full-time work within 3 months after the end of the program were evaluated using one-sided Fisher tests and univariate logistic regression followed by multivariate logistic regression. RESULTS: The univariate analysis showed a significant association between the INTERMED score and return to work (P<0.001; odds ratio, 0.90; 95% confidence interval, 0.86-0.96). In the multivariate analysis, prediction was best when the INTERMED score and sick leave duration were used in combination (P=0.03; odds ratio, 0.48; 95% confidence interval, 0.25-0.93). CONCLUSION: The INTERMED questionnaire is useful for evaluating patients with chronic low back pain. It could be used to improve the selection of patients for intensive multidisciplinary programs, thereby improving the quality of care, while reducing healthcare costs.