870 resultados para computerized electrocardiography
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El contexto teórico y empírico de esta investigación sobre entonación, se enmarca dentro de la filosofía lingüística de la teoría sistémico-funcional. El modelo metodológico empleado se basa en la Lingüística de Corpus. La descripción de la adquisición y aprendizaje de la lengua extranjera está justificada dentro del marco teórico de la teoría de interlengua y la adquisición de segundas lenguas y lenguas extranjeras.. El presente estudio del corpus comparativo y longitudinal de aprendices y hablantes nativos de lengua inglesa, tiene como objetivo principal investigar los modelos de entonación producidos por ambos grupos de hablantes. Se pretende demostrar que la diferencia a nivel entonativo entre estos dos grupos no sólo tiene como resultado que los no nativos tengan acento extranjero; sino que puede afectar al mensaje transmitido, en cuanto a la estructura y organización de la información dentro del discurso oral en las metafunciones textual e interpersonal.. Se asume la existencia de un sistema entonativo de interlengua, de esta forma este análisis tiene como objeto no sólo reflejar los errores sino también los posibles sistemas aproximativos de los aprendices mencionados..
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This paper discusses the development of a computerized version of the CID Early Speech Perception Test.
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This paper discusses the creation of a condensed list SRT application of the W-1 for the Macintosh computer.
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The goal of the study was to identify what effect headshaking in the horizontal plane has on Computerized Dynamic Posturography results in normals and patients with unilateral vestibular dysfunction. Additionally, the results were compared to results of the dynamic subjective visual vertical test.
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This paper discusses the rationale, clinical applications, advantages and disadvantages of three common balance function tests: Electronystagmography (ENG), Rotational Chair Testing (RCT), and Computerized Dynamic Posturography (CDP).
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Research shows that poor indoor air quality (IAQ) in school buildings can cause a reduction in the students’ performance assessed by short-term computer-based tests; whereas good air quality in classrooms can enhance children's concentration and also teachers’ productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect IAQ. In school classrooms, the occupancy density is high (1.8–2.4 m2/person) compared to offices (10 m2/person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project, which will aim to investigate the effect of IAQ and ventilation rates on pupils’ performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms. The air quality, ventilation rates and pupils’ performance in classrooms will be evaluated in parallel measurements. In addition, Visual Analogue Scales will be used to assess subjective perception of the classroom environment and SBS symptoms. Pupil performance will be measured with Computerised Assessment Tests (CAT), and Pen and Paper Performance Tasks while physical parameters of the classroom environment will be recorded using an advanced data logging system. A total number of 20 primary schools in the Reading area are expected to participate in the present investigation, and the pupils participating in this study will be within the age group of 9–11 years. On completion of the project, based on the overall data recommendations for suitable ventilation rates for schools will be formulated.
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Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.
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Background: This study was carried out as part of a European Union funded project (PharmDIS-e+), to develop and evaluate software aimed at assisting physicians with drug dosing. A drug that causes particular problems with drug dosing in primary care is digoxin because of its narrow therapeutic range and low therapeutic index. Objectives: To determine (i) accuracy of the PharmDIS-e+ software for predicting serum digoxin levels in patients who are taking this drug regularly; (ii) whether there are statistically significant differences between predicted digoxin levels and those measured by a laboratory and (iii) whether there are differences between doses prescribed by general practitioners and those suggested by the program. Methods: We needed 45 patients to have 95% Power to reject the null hypothesis that the mean serum digoxin concentration was within 10% of the mean predicted digoxin concentration. Patients were recruited from two general practices and had been taking digoxin for at least 4 months. Exclusion criteria were dementia, low adherence to digoxin and use of other medications known to interact to a clinically important extent with digoxin. Results: Forty-five patients were recruited. There was a correlation of 0·65 between measured and predicted digoxin concentrations (P < 0·001). The mean difference was 0·12 μg/L (SD 0·26; 95% CI 0·04, 0·19, P = 0·005). Forty-seven per cent of the patients were prescribed the same dose as recommended by the software, 44% were prescribed a higher dose and 9% a lower dose than recommended. Conclusion: PharmDIS-e+ software was able to predict serum digoxin levels with acceptable accuracy in most patients.