40 resultados para Dynamic code generation


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As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

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Video coding technologies have played a major role in the explosion of large market digital video applications and services. In this context, the very popular MPEG-x and H-26x video coding standards adopted a predictive coding paradigm, where complex encoders exploit the data redundancy and irrelevancy to 'control' much simpler decoders. This codec paradigm fits well applications and services such as digital television and video storage where the decoder complexity is critical, but does not match well the requirements of emerging applications such as visual sensor networks where the encoder complexity is more critical. The Slepian Wolf and Wyner-Ziv theorems brought the possibility to develop the so-called Wyner-Ziv video codecs, following a different coding paradigm where it is the task of the decoder, and not anymore of the encoder, to (fully or partly) exploit the video redundancy. Theoretically, Wyner-Ziv video coding does not incur in any compression performance penalty regarding the more traditional predictive coding paradigm (at least for certain conditions). In the context of Wyner-Ziv video codecs, the so-called side information, which is a decoder estimate of the original frame to code, plays a critical role in the overall compression performance. For this reason, much research effort has been invested in the past decade to develop increasingly more efficient side information creation methods. This paper has the main objective to review and evaluate the available side information methods after proposing a classification taxonomy to guide this review, allowing to achieve more solid conclusions and better identify the next relevant research challenges. After classifying the side information creation methods into four classes, notably guess, try, hint and learn, the review of the most important techniques in each class and the evaluation of some of them leads to the important conclusion that the side information creation methods provide better rate-distortion (RD) performance depending on the amount of temporal correlation in each video sequence. It became also clear that the best available Wyner-Ziv video coding solutions are almost systematically based on the learn approach. The best solutions are already able to systematically outperform the H.264/AVC Intra, and also the H.264/AVC zero-motion standard solutions for specific types of content. (C) 2013 Elsevier B.V. All rights reserved.

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Low-density parity-check (LDPC) codes are nowadays one of the hottest topics in coding theory, notably due to their advantages in terms of bit error rate performance and low complexity. In order to exploit the potential of the Wyner-Ziv coding paradigm, practical distributed video coding (DVC) schemes should use powerful error correcting codes with near-capacity performance. In this paper, new ways to design LDPC codes for the DVC paradigm are proposed and studied. The new LDPC solutions rely on merging parity-check nodes, which corresponds to reduce the number of rows in the parity-check matrix. This allows to change gracefully the compression ratio of the source (DCT coefficient bitplane) according to the correlation between the original and the side information. The proposed LDPC codes reach a good performance for a wide range of source correlations and achieve a better RD performance when compared to the popular turbo codes.

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Purpose: The most recent Varian® micro multileaf collimator(MLC), the High Definition (HD120) MLC, was modeled using the BEAMNRCMonte Carlo code. This model was incorporated into a Varian medical linear accelerator, for a 6 MV beam, in static and dynamic mode. The model was validated by comparing simulated profiles with measurements. Methods: The Varian® Trilogy® (2300C/D) accelerator model was accurately implemented using the state-of-the-art Monte Carlo simulation program BEAMNRC and validated against off-axis and depth dose profiles measured using ionization chambers, by adjusting the energy and the full width at half maximum (FWHM) of the initial electron beam. The HD120 MLC was modeled by developing a new BEAMNRC component module (CM), designated HDMLC, adapting the available DYNVMLC CM and incorporating the specific characteristics of this new micro MLC. The leaf dimensions were provided by the manufacturer. The geometry was visualized by tracing particles through the CM and recording their position when a leaf boundary is crossed. The leaf material density and abutting air gap between leaves were adjusted in order to obtain a good agreement between the simulated leakage profiles and EBT2 film measurements performed in a solid water phantom. To validate the HDMLC implementation, additional MLC static patterns were also simulated and compared to additional measurements. Furthermore, the ability to simulate dynamic MLC fields was implemented in the HDMLC CM. The simulation results of these fields were compared with EBT2 film measurements performed in a solid water phantom. Results: Overall, the discrepancies, with and without MLC, between the opened field simulations and the measurements using ionization chambers in a water phantom, for the off-axis profiles are below 2% and in depth-dose profiles are below 2% after the maximum dose depth and below 4% in the build-up region. On the conditions of these simulations, this tungsten-based MLC has a density of 18.7 g cm− 3 and an overall leakage of about 1.1 ± 0.03%. The discrepancies between the film measured and simulated closed and blocked fields are below 2% and 8%, respectively. Other measurements were performed for alternated leaf patterns and the agreement is satisfactory (to within 4%). The dynamic mode for this MLC was implemented and the discrepancies between film measurements and simulations are within 4%. Conclusions: The Varian® Trilogy® (2300 C/D) linear accelerator including the HD120 MLC was successfully modeled and simulated using the Monte CarloBEAMNRC code by developing an independent CM, the HDMLC CM, either in static and dynamic modes.

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Trabalho de relatório de Estágio de natureza científica para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Edificações

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Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

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Micro-generation is the small scale production of heat and/or electricity from a low carbon source and can be a powerful driver for carbon reduction, behavior change, security of supply and economic value. The energy conversion technologies can include photovoltaic panels, micro combined heat and power, micro wind, heat pumps, solar thermal systems, fuel cells and micro hydro schemes. In this paper, a small research of the availability of the conversion apparatus and the prices for the micro wind turbines and photovoltaic systems is made and a comparison between these two technologies is performed in terms of the availability of the resource and costs. An analysis of the new legal framework published in Portugal is done to realize if the incentives to individualspsila investment in sustainable and local energy production is worth for their point of view. An economic evaluation for these alternatives, accounting with the governmentpsilas incentives should lead, in most cases, into attractive return rates for the investment. Apart from the attractiveness of the investment there are though other aspects that should be taken into account and those are the benefits that these choices have to us all. The idea is that micro-generation will not only make a significant direct contribution to carbon reduction targets, it will also trigger a multiplier effect in behavior change by engaging hearts and minds, and providing more efficient use of energy by householders. The diversified profile of power generation by micro-generators, both in terms of location and timing, should reduce the impact of intermittency or plant failures with significant gains for security of supply.

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The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

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The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

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This paper proposes an efficient scalable Residue Number System (RNS) architecture supporting moduli sets with an arbitrary number of channels, allowing to achieve larger dynamic range and a higher level of parallelism. The proposed architecture allows the forward and reverse RNS conversion, by reusing the arithmetic channel units. The arithmetic operations supported at the channel level include addition, subtraction, and multiplication with accumulation capability. For the reverse conversion two algorithms are considered, one based on the Chinese Remainder Theorem and the other one on Mixed-Radix-Conversion, leading to implementations optimized for delay and required circuit area. With the proposed architecture a complete and compact RNS platform is achieved. Experimental results suggest gains of 17 % in the delay in the arithmetic operations, with an area reduction of 23 % regarding the RNS state of the art. When compared with a binary system the proposed architecture allows to perform the same computation 20 times faster alongside with only 10 % of the circuit area resources.

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Workflows have been successfully applied to express the decomposition of complex scientific applications. This has motivated many initiatives that have been developing scientific workflow tools. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from workflow tasks specification, decentralizing the control of workflow activities, and allowing their tasks to run autonomous in distributed infrastructures, for instance on Clouds. Furthermore many workflow tools only support the execution of Direct Acyclic Graphs (DAG) without the concept of iterations, where activities are executed millions of iterations during long periods of time and supporting dynamic workflow reconfigurations after certain iteration. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on the Process Networks model, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures, e. g. on Clouds. Each AWA executes a Task developed as a Java class that implements a generic interface allowing end-users to code their applications without concerns for low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables support to dynamic workflow reconfiguration and monitoring of the execution of workflows. We describe how AWARD supports dynamic reconfiguration and discuss typical workflow reconfiguration scenarios. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to a small dedicated cluster and the Amazon (Elastic Computing EC2) Cloud.

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We propose a low complexity technique to generate amplitude correlated time-series with Nakagami-m distribution and phase correlated Gaussian-distributed time-series, which is useful for the simulation of ionospheric scintillation effects in GNSS signals. To generate a complex scintillation process, the technique requires solely the knowledge of parameters Sa (scintillation index) and σφ (phase standard deviation) besides the definition of models for the amplitude and phase power spectra. The concatenation of two nonlinear memoryless transformations is used to produce a Nakagami-distributed amplitude signal from a Gaussian autoregressive process.

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Many studies have demonstrated the relationship between the alpha activity and the central visual ability, in which the visual ability is usually assessed through static stimuli. Besides static circumstance, however in the real environment there are often dynamic changes and the peripheral visual ability in a dynamic environment (i.e., dynamic peripheral visual ability) is important for all people. So far, no work has reported whether there is a relationship between the dynamic peripheral visual ability and the alpha activity. Thus, the objective of this study was to investigate their relationship. Sixty-two soccer players performed a newly designed peripheral vision task in which the visual stimuli were dynamic, while their EEG signals were recorded from Cz, O1, and O2 locations. The relationship between the dynamic peripheral visual performance and the alpha activity was examined by the percentage-bend correlation test. The results indicated no significant correlation between the dynamic peripheral visual performance and the alpha amplitudes in the eyes-open and eyes-closed resting condition. However, it was not the case for the alpha activity during the peripheral vision task: the dynamic peripheral visual performance showed significant positive inter-individual correlations with the amplitudes in the alpha band (8-12 Hz) and the individual alpha band (IAB) during the peripheral vision task. A potential application of this finding is to improve the dynamic peripheral visual performance by up-regulating alpha activity using neuromodulation techniques.

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This paper describes a modular solid-state switching cell derived from the Marx generator concept to be used in topologies for generating multilevel unipolar and bipolar high-voltage (HV) pulses into resistive loads. The switching modular cell comprises two ON/OFF semiconductors, a diode, and a capacitor. This cell can be stacked, being the capacitors charged in series and their voltages balanced in parallel. To balance each capacitor voltage without needing any parameter measurement, a vector decision diode algorithm is used in each cell to drive the two switches. Simulation and experimental results, for generating multilevel unipolar and bipolar HV pulses into resistive loads are presented.

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Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.