3 resultados para European Educational Research Association

em Universidade do Minho


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This paper is a study of the full content of articles published by RPER, the Portuguese Review of Regional Studies, from the time it was launched in 2003 until the first quarter of 2015. RPER is a journal edited by the Portuguese section of the European Regional Science Association, which was established in the first half of the 1980s. The Association (APDR) and the journal are the result of contributions by researchers and technicians from different scientific fields, including mainly Economics, Geography, Sociology, Engineering and Architecture. The main focus of these contributions is the socio-economic life of concrete sites, and the way this life is conditioned by resources and capabilities, the historical and cultural heritage and institutions. Content analysis was undertaken to identify the main subjects chosen during the total period under analysis, the nature of the articles published (theoretical or empirical) and the main analytical framework used. The analysis also covers sub-periods to investigate major trends found in terms of subjects chosen and analytical methods, questioning the rationale behind them. The paper concludes with a few notes regarding the social echo the research received and an identification of the main limitations of the research. In the first part of the article, we conduct a summary review of the genesis and evolution of Regional Science at international level to serve as a basis for the empirical approach developed.

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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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Tese de Doutoramento em Ciências da Educação (área de especialização em Organização e Administração Escolar).