24 resultados para combinations

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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Scalable video coding allows an efficient provision of video services at different quality levels with different energy demands. According to the specific type of service and network scenario, end users and/or operators may decide to choose among different energy versus quality combinations. In order to deal with the resulting trade-off, in this paper we analyze the number of video layers that are worth to be received taking into account the energy constraints. A single-objective optimization is proposed based on dynamically selecting the number of layers, which is able to minimize the energy consumption with the constraint of a minimal quality threshold to be reached. However, this approach cannot reflect the fact that the same increment of energy consumption may result in different increments of visual quality. Thus, a multiobjective optimization is proposed and a utility function is defined in order to weight the energy consumption and the visual quality criteria. Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.

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This study developed a framework for the shape optimization of aerodynamics profiles using computational fluid dynamics (CFD) and genetic algorithms. Agenetic algorithm code and a commercial CFD code were integrated to develop a CFD shape optimization tool. The results obtained demonstrated the effectiveness of the developed tool. The shape optimization of airfoils was studied using different strategies to demonstrate the capacity of this tool with different GA parameter combinations.

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Climate change is an important environmental problem and one whose economic implications are many and varied. This paper starts with the presumption that mitigation of greenhouse gases is a necessary policy that has to be designed in a cost effective way. It is well known that market instruments are the best option for cost effectiveness. But the discussion regarding which of the various market instruments should be used, how they may interact and what combinations of policies should be implemented is still open and very lively. In this paper we propose a combination of instruments: the marketable emission permits already in place in Europe for major economic sectors and a CO(2) tax for economic sectors not included in the emissions permit scheme. The study uses an applied general equilibrium model for the Spanish economy to compute the results obtained with the new mix of instruments proposed. As the combination of the market for emission permits and the CO(2) tax admits different possibilities that depend on how the mitigation is distributed among the economic sectors, we concentrate on four possibilities: cost-effective, equalitarian, proportional to emissions, and proportional to output distributions. Other alternatives to the CO(2) tax are also analysed (tax on energy, on oil and on electricity). Our findings suggest that careful, well designed policies are needed as any deviation imposes significant additional costs that increase more than proportionally to the level of emissions reduction targeted by the EU.

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This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). This package can be used to solve single and multi-objective discrete and continuous optimization problems using EDAs based on undirected and directed probabilistic graphical models. The implementation contains several methods commonly employed by EDAs. It is also conceived as an open package to allow users to incorporate different combinations of selection, learning, sampling, and local search procedures. Additionally, it includes methods to extract, process and visualize the structures learned by the probabilistic models. This way, it can unveil previously unknown information about the optimization problem domain. Mateda-2.0 also incorporates a module for creating and validating function models based on the probabilistic models learned by EDAs.

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The development of techniques for oncogenomic analyses such as array comparative genomic hybridization, messenger RNA expression arrays and mutational screens have come to the fore in modern cancer research. Studies utilizing these techniques are able to highlight panels of genes that are altered in cancer. However, these candidate cancer genes must then be scrutinized to reveal whether they contribute to oncogenesis or are coincidental and non-causative. We present a computational method for the prioritization of candidate (i) proto-oncogenes and (ii) tumour suppressor genes from oncogenomic experiments. We constructed computational classifiers using different combinations of sequence and functional data including sequence conservation, protein domains and interactions, and regulatory data. We found that these classifiers are able to distinguish between known cancer genes and other human genes. Furthermore, the classifiers also discriminate candidate cancer genes from a recent mutational screen from other human genes. We provide a web-based facility through which cancer biologists may access our results and we propose computational cancer gene classification as a useful method of prioritizing candidate cancer genes identified in oncogenomic studies.

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[ES]Este trabajo presenta un algoritmo automatizado cuyo resultado es la determinación de las ganancias óptimas del lazo de control de un mecanismo de cinemática paralela. En concreto se ha aplicado al mecanismo 5R, aunque el método es válido para cualquier otro mecanismo introduciendo el modelo mecatrónico correspondiente. Permite disponer de un procedimiento para poder elegir en un futuro la combinación de motor y reductora más apropiada para un determinado mecanismo evitando realizar adquisiciones sobredimensionadas, como ocurrió con el mecanismo en cuestión.

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The aim of the present study was to investigate the functional role of syllables in sign language and how the different phonological combinations influence sign production. Moreover, the influence of age of acquisition was evaluated. Deaf signers (native and non-native) of Catalan Signed Language (LSC) were asked in a picture-sign interference task to sign picture names while ignoring distractor-signs with which they shared two phonological parameters (out of three of the main sign parameters: Location, Movement, and Handshape). The results revealed a different impact of the three phonological combinations. While no effect was observed for the phonological combination Handshape-Location, the combination Handshape-Movement slowed down signing latencies, but only in the non-native group. A facilitatory effect was observed for both groups when pictures and distractors shared Location-Movement. Importantly, linguistic models have considered this phonological combination to be a privileged unit in the composition of signs, as syllables are in spoken languages. Thus, our results support the functional role of syllable units during phonological articulation in sign language production.

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Several alpine vertebrates share a distribution pattern that extends across the South-western Palearctic but is limited to the main mountain massifs. Although they are usually regarded as cold-adapted species, the range of many alpine vertebrates also includes relatively warm areas, suggesting that factors beyond climatic conditions may be driving their distribution. In this work we first recognize the species belonging to the mentioned biogeographic group and, based on the environmental niche analysis of Plecotus macrobullaris, we identify and characterize the environmental factors constraining their ranges. Distribution overlap analysis of 504 European vertebrates was done using the Sorensen Similarity Index, and we identified four birds and one mammal that share the distribution with P. macrobullaris. We generated 135 environmental niche models including different variable combinations and regularization values for P. macrobullaris at two different scales and resolutions. After selecting the best models, we observed that topographic variables outperformed climatic predictors, and the abruptness of the landscape showed better predictive ability than elevation. The best explanatory climatic variable was mean summer temperature, which showed that P. macrobullaris is able to cope with mean temperature ranges spanning up to 16 degrees C. The models showed that the distribution of P. macrobullaris is mainly shaped by topographic factors that provide rock-abundant and open-space habitats rather than climatic determinants, and that the species is not a cold-adapted, but rather a cold-tolerant eurithermic organism. P. macrobullaris shares its distribution pattern as well as several ecological features with five other alpine vertebrates, suggesting that the conclusions obtained from this study might be extensible to them. We concluded that rock-dwelling and open-space foraging vertebrates with broad temperature tolerance are the best candidates to show wide alpine distribution in the Western Palearctic.

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Póster presentado en: XXII International Congress and General Assembly of the International Union of Crystallography (UICr), 22–30 Agosto 2011. Madrid, España

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Póster presentado en: 11th International Symposium on Applied Bioinorganic Chemistry. 2-5 Diciembre 2011. Barcelona, España (ISABC 2011)

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In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.