914 resultados para Power Network in Loop Simulation


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Continuous-valued recurrent neural networks can learn mechanisms for processing context-free languages. The dynamics of such networks is usually based on damped oscillation around fixed points in state space and requires that the dynamical components are arranged in certain ways. It is shown that qualitatively similar dynamics with similar constraints hold for a(n)b(n)c(n), a context-sensitive language. The additional difficulty with a(n)b(n)c(n), compared with the context-free language a(n)b(n), consists of 'counting up' and 'counting down' letters simultaneously. The network solution is to oscillate in two principal dimensions, one for counting up and one for counting down. This study focuses on the dynamics employed by the sequential cascaded network, in contrast to the simple recurrent network, and the use of backpropagation through time. Found solutions generalize well beyond training data, however, learning is not reliable. The contribution of this study lies in demonstrating how the dynamics in recurrent neural networks that process context-free languages can also be employed in processing some context-sensitive languages (traditionally thought of as requiring additional computation resources). This continuity of mechanism between language classes contributes to our understanding of neural networks in modelling language learning and processing.

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There is increasing evidence of a reciprocal fronto-limbic network in the pathogenesis of mood disorders. Prior in vivo proton ((1)H) spectroscopy studies provide evidence of abnormal neurochemical levels in the cingulate and dorsolateral prefrontal cortex (DLPFC) of adult subjects with major depressive disorder (MOD). We examined whether similar abnormalities occur in children and adolescents with MDD. We collected two-dimensional multi-voxel in vivo 1H spectroscopy data at 1.5 Tesla to quantify levels of N-acetyl-aspartate (NAA), glycerolphosphocholine plus phosphocholine (GPC + PC), and phosphocreatine plus creatine (PCr + Cr) in the DLPFC, medial prefrontal cortex (MPFC), and anterior cingulate (AC) of children and adolescents aged 8-17 years with MDD (n = 16) compared with healthy control subjects (n = 38). Analysis of covariance with age and gender as covariates was performed. MDD subjects showed significantly lower levels of NAA in the right MPFC and right AC than controls. MDD subjects also had significantly lower levels of GPC + PC in the right AC than control subjects. There were no significant differences in other metabolites in the studied regions. Pediatric patients with MDD exhibit neurochemical alterations in prefrontal cortex regions that are important in the monitoring and regulation of emotional states. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

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Objective: To examine the changes in slow (8-10 Hz)and fast (10-12 Hz) alpha bands of EEG in three groups of subjects submitted to different amounts of functional electrostimulation (FES). Our hypothesis is that different amounts of electrostimulation may cause different patterns of activation in the sensorimotor cortex. In particular, we expect to see an increase in alpha power due to habituation effects. We examine the two bands comprised by alpha rhythm (i.e., slow and fast alpha), since these two sub-rhythms are related to distinct aspects: general energy demands and specific motor aspects, respectively. Methods: The sample was composed of 27 students, both sexes, aging between 25 and 40 years old. The subjects were randomly distributed in three groups: control (n = 9), G24 (n = 9) and G36 (n = 9). A FES equipment (Neuro Compact-2462) was used to stimulate the right index finger extension. Simultaneously, the electroencephalographic signal was acquired. We investigated the absolute power in slow and fast alpha bands in the sensorimotor cortex. Results: The G36 indicated a significant increasing in absolute power values in lower and higher alpha components, respectively, when compared with the control group. Particularly, in the following regions: pre-motor cortex and primary motor cortex. Discussion: FES seems to promote cortical adaptations that are similar to those observed when someone learns a procedural task. FES application in the G36 was more effective in promoting such neural changes. The lower and higher components of alpha rhythms behave differently in their topographical distribution during FES application. These results suggest a somatotopic organization in primary motor cortex which can be represented by the fast alpha component. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

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The molecular mechanism that controls the response to phosphate shortage in Neurospora crassa involves four regulatory genes - nuc-2, preg, pgov, and nuc-1. Phosphate shortage is sensed by the nuc-2 gene, the product of which inhibits the functioning of the PREG-PGOV complex. This allows the translocation of the transcriptional factor NUC-1 into the nucleus, which activates the transcription of phosphate-repressible phosphatases. The nuc-2A mutant strain of N. crassa carries a loss-of-function mutation in the nuc-2 gene, which encodes an ankyrin-like repeat protein. In this study, we identified transcripts that are downregutated in the nuc-2A mutant strain. Functional grouping of these expressed sequence tags allowed the identification of genes that play essential roles in different cellular processes such as transport, transcriptional regulation, signal transduction, metabolism, protein synthesis, protein fate, and development. These results reveal novel aspects of the phosphorus-sensing network in N. crassa. (C) 2009 Elsevier GmbH. All rights reserved.

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In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

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A range of lasers. is now available for use in dentistry. This paper summarizes key current and emerging applications, for lasers in clinical practice. A major diagnostic application of low power lasers is the detection of caries, using fluorescence elicited from hydroxyapatite or from bacterial by-products. Laser fluorescence is an effective method for detecting and quantifying incipient occlusal and cervical,carious lesions, and with further refinement could be used in the, same manner for proximal lesions. Photoactivated dye techniques have been developed which use low power lasers to elicit a photochemical reaction, Photoactivated dye techniques' can be used to disinfect root canals, periodontal pockets, cavity preparations and sites of peri-implantitis. Using similar principles, more powerful lasers tan be used for photodynamic therapy in the treatment of malignancies of the oral mucosa. Laser-driven photochemical reactions can also be used for tooth whitening. In combination with fluoride, laser irradiation can improve the resistance of tooth structure to demineralization, and this application is of particular benefit for susceptible sites in high caries risk patients. Laser technology for caries' removal, cavity preparation and soft tissue surgery is at a high state of refinement, having had several decades of development up to the present time. Used in conjunction with or as a replacement for traditional methods, it is expected that specific laser technologies will become an essential component of contemporary dental practice over the next decade.

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The big proliferation of mobile communication systems has caused an increased concern about the interaction between the human body and the antennas of mobile handsets. In order to study the problem, a multiband antenna was designed, fabricated and measured to operate over two frequency sub bands 900 and 1800 MHz. After that, we simulated the same antenna, but now, in the presence of a human head model to analyze the head's influence. First, the influence of the human head on the radiation efficiency of the antenna has been investigated as a function of the distance between the head and the antenna and with the inclination of the antenna. Furthermore, the relative amount of the electromagnetic power absorbed in the head has been obtained.

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The big proliferation of mobile communication systems has caused an increased concern about the interaction between the human body and the antennas of mobile handsets. In order to study the problem, a multiband antenna was designed, fabricated and measured to operate over two frequency sub bands 900 and 1800 MHz. After that, we simulated the same antenna, but now, in the presence of a human head model to analyze the head's influence. First, the influence of the human head on the radiation efficiency of the antenna has been investigated as a function of the distance between the head and the antenna and with the inclination of the antenna. Furthermore, the relative amount of the electromagnetic power absorbed in the head has been obtained. In this study the electromagnetic analysis has been performed via FDTD (Finite Difference Time Domain).

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HENRE II (Higher Education Network for Radiography in Europe)

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A recente norma IEEE 802.11n oferece um elevado débito em redes locais sem fios sendo por isso esperado uma adopção massiva desta tecnologia substituindo progressivamente as redes 802.11b/g. Devido à sua elevada capacidade esta recente geração de redes sem fios 802.11n permite um crescimento acentuado de serviços audiovisuais. Neste contexto esta dissertação procura estudar a rede 802.11n, caracterizando o desempenho e a qualidade associada a um serviço de transmissão de vídeo, recorrendo para o efeito a uma arquitectura de simulação da rede 802.11n. Desta forma é caracterizado o impacto das novas funcionalidades da camada MAC introduzidas na norma 801.11n, como é o caso da agregação A-MSDU e A-MPDU, bem como o impacto das novas funcionalidades da camada física como é o caso do MIMO; em ambos os casos uma optimização da parametrização é realizada. Também se verifica que as principais técnicas de codificação de vídeo H.264/AVC para optimizar o processo de distribuição de vídeo, permitem optimizar o desempenho global do sistema de transmissão. Aliando a optimização e parametrização da camada MAC, da camada física, e do processo de codificação, é possível propor um conjunto de configurações que permitem obter o melhor desempenho na qualidade de serviço da transmissão de conteúdos de vídeo numa rede 802.11n. A arquitectura de simulação construída nesta dissertação é especificamente adaptada para suportar as técnicas de agregação da camada MAC, bem como para suportar o encapsulamento em protocolos de rede que permitem a transmissão dos pacotes de vídeo RTP, codificados em H.264/AVC.

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The introduction of wind power generation in several countries around the world, including in European countries, where energy policy directives have encouraged the use of renewables, led to several changes in market and power systems operation. The intensive integration of these sources has led to situations in which the demand is lower than the available renewable resources. In these situations a part of the available generation is wasted if not used for storage or to supply additional demand. This paper proposes a real time demand response methodology based on changing the electricity price for the consumers expecting an increase in the demand in the periods in which that demand is lower than the available renewable generation. The consumers response to the changes in electricity price is characterized by their price elasticity of demand considered distinct for each consumer type. The proposed methodology is applied to the Portuguese power system, in the context of the Iberian electricity market (MIBEL). The renewable-based producers are considered as special producers, with special tariffs, and so it is important to use the energy available as it will be paid anyway. In this context, consumers are entities actively participating in the operation of the market.

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The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

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Sustainable development concerns are being addressed with increasing attention, in general, and in the scope of power industry, in particular. The use of distributed generation (DG), mainly based on renewable sources, has been seen as an interesting approach to this problem. However, the increasing of DG in power systems raises some complex technical and economic issues. This paper presents ViProd, a simulation tool that allows modeling and simulating DG operation and participation in electricity markets. This paper mainly focuses on the operation of Virtual Power Producers (VPP) which are producers’ aggregations, being these producers mainly of DG type. The paper presents several reserve management strategies implemented in the scope of ViProd and the results of a case study, based on real data.

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This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.