4 resultados para Chronic Low-level Exposure

em Universidade do Minho


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This study analyzed the mediating role of psychological morbidity and the variables that discriminated low versus high disability, in patients receiving physiotherapy and acupuncture. A total of 203 patients answered measures of illness and medication representations, coping, depression, anxiety, quality of life, and functional disability. Morbidity was a mediator between functional disability and quality of life. Treatment consequences and quality of life, in the acupuncture group, and emotional representations, quality of life, depression, anxiety, and active strategies for pain relief, in the physiotherapy group, discriminated patients with low versus high disability. These results have important implications for identifying high-risk patients.

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Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

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This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%

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Dissertação de mestrado em Educação Especial (área de especialização em Dificuldades de Aprendizagem Específicas)