2 resultados para Cascaded Converter

em Universidad de Alicante


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In this paper, we present a novel coarse-to-fine visual localization approach: contextual visual localization. This approach relies on three elements: (i) a minimal-complexity classifier for performing fast coarse localization (submap classification); (ii) an optimized saliency detector which exploits the visual statistics of the submap; and (iii) a fast view-matching algorithm which filters initial matchings with a structural criterion. The latter algorithm yields fine localization. Our experiments show that these elements have been successfully integrated for solving the global localization problem. Context, that is, the awareness of being in a particular submap, is defined by a supervised classifier tuned for a minimal set of features. Visual context is exploited both for tuning (optimizing) the saliency detection process, and to select potential matching views in the visual database, close enough to the query view.

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Simulated cold-start tests have been carried out to evaluate the performance of H-ZSM-5 and H-BETA zeolites as hydrocarbon traps under simulated gasoline car exhaust gases, paying special attention to the effect of water on their behaviour. It is concluded that the hydrothermal treatment of the zeolites in the acidic form contributes to the better performance of these materials as hydrocarbon traps since the stabilization of the zeolites takes place. Moreover, the decrease of the surface acidity of the zeolites results in an increase of the Si/Al ratio, which contributes to the decrease of the water affinity for adsorption sites. Thus, the competition with hydrocarbon molecules in the exhaust for the adsorption sites is reduced which increases their trap efficiency. The stabilized H-ZSM-5 is the zeolite that showed the best performance with a propene offset temperature of 240 °C, which should be high enough for the three-way catalyst to carry out its role as catalytic converter.