8 resultados para active-reactive OPF

em Universitat de Girona, Spain


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Selenium (Se) is an element with important health implications that is emitted in significant amounts from volcanoes. Attracted by the fertility of volcanic soils, around 10% of the world population lives within 100 km of an active volcano. Nevertheless, the behaviour of Se in volcanic environments is poorly understood. Therefore, the main aim of this thesis is to investigate the role of soils in the Se cycling in volcanic environments. Prior to the geochemical studies, precise and accurate methods for the determination of Se contents, speciation and isotopic signatures were developed. Afterwards, a combination of field studies and lab controlled experiments were performed with soils from two contrasting European volcanic settings: Mount Etna in Sicily (Italy) and Mount Teide in Tenerife (Spain). The results showed a strong link between Se behaviour and soil development, indicating that Se mobility in volcanic soils is controlled by sorption processes and soil mineralogy.

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The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

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In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

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An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

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This paper deals with the problem of stabilizing a class of structures subject to an uncertain excitation due to the temporary coupling of the main system with another uncertain dynamical subsystem. A Lyapunov function based control scheme is proposed to attenuate the structural vibration. In the control design, the actuator dynamics is taken into account. The control scheme is implemented by using only feedback information of the main system. The effectiveness of the control scheme is shown for a bridge platform with crossing vehicle

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An implicitly parallel method for integral-block driven restricted active space self-consistent field (RASSCF) algorithms is presented. The approach is based on a model space representation of the RAS active orbitals with an efficient expansion of the model subspaces. The applicability of the method is demonstrated with a RASSCF investigation of the first two excited states of indole

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A new practical method to generate a subspace of active coordinates for quantum dynamics calculations is presented. These reduced coordinates are obtained as the normal modes of an analytical quadratic representation of the energy difference between excited and ground states within the complete active space self-consistent field method. At the Franck-Condon point, the largest negative eigenvalues of this Hessian correspond to the photoactive modes: those that reduce the energy difference and lead to the conical intersection; eigenvalues close to 0 correspond to bath modes, while modes with large positive eigenvalues are photoinactive vibrations, which increase the energy difference. The efficacy of quantum dynamics run in the subspace of the photoactive modes is illustrated with the photochemistry of benzene, where theoretical simulations are designed to assist optimal control experiments

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In the past 2009/10 academic year, we took steps towards introduction of active methodologies, from a multidisciplinar approach, into a conventional lecture-based Dental Education program. We consolidated these practices in the current 2010/11 year, already within a new Bologna-adapted scheme. Transition involved (i) critical assessment of the limitations of traditional teaching (ii) identification of specific learning topics allowing for integration of contents, (iii) implementation of student-centred learning activities in old curricular plans (iv) assessment of students' satisfaction and perceived learning outcomes, (v) implementation of these changes in new Bologna-adapted curricula