4 resultados para CLUSTER VALIDATION
em SAPIENTIA - Universidade do Algarve - Portugal
Resumo:
Dissolved oxygen (DO) is one of the most important environmental variables of water quality, especially for marine life. Consequently, oxygen is one of the Chemical Quality Elements required for the implementation of European Union Water Framework Directive. This study uses the example of the Ria Formosa, a meso-tidal lagoon on the south coast of Portugal to demonstrate how monitoring of water quality for coastal waters must be well designed to identify symptoms of episodic hypoxia. New data from the western end of the Ria Formosa were compared to values in a database of historical data and in the published literature to identify long-term trends. The dissolved oxygen concentration values in the database and in the literature were generally higher than those found in this study, where episodic hypoxia was observed during the summer. Analysis of the database showed that the discrepancy was probably related with the time and the sites where the samples had been collected, rather than a long-term trend. The most problematic situations were within the inner lagoon near the city of Faro, where episodic hypoxia (<2 mg dm3 DO) occurred regularly in the early morning. These results emphasise the need for a balanced sampling strategy for oxygen monitoring which includes all periods of the day and night, as well as a representative range of sites throughout the lagoon. Such a strategy would provide adequate data to apply management measures to reduce the risk of more persistent hypoxia that would impact on the ecological, important natural resource. economic and leisure uses of this important natural resource.
Resumo:
A biological disparity energy model can estimate local depth information by using a population of V1 complex cells. Instead of applying an analytical model which explicitly involves cell parameters like spatial frequency, orientation, binocular phase and position difference, we developed a model which only involves the cells’ responses, such that disparity can be extracted from a population code, using only a set of previously trained cells with random-dot stereograms of uniform disparity. Despite good results in smooth regions, the model needs complementary processing, notably at depth transitions. We therefore introduce a new model to extract disparity at keypoints such as edge junctions, line endings and points with large curvature. Responses of end-stopped cells serve to detect keypoints, and those of simple cells are used to detect orientations of their underlying line and edge structures. Annotated keypoints are then used in the leftright matching process, with a hierarchical, multi-scale tree structure and a saliency map to segregate disparity. By combining both models we can (re)define depth transitions and regions where the disparity energy model is less accurate.
Resumo:
Dissertação de mestrado, Qualidade em Análises, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
Resumo:
Dissertação de Mestrado, Qualidade em Análises, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015