989 resultados para Distributed linear precoding


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The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

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A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

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In this paper we explore the use of non-linear transformations in order to improve the performance of an entropy based voice activity detector (VAD). The idea of using a non-linear transformation comes from some previous work done in speech linear prediction (LPC) field based in source separation techniques, where the score function was added into the classical equations in order to take into account the real distribution of the signal. We explore the possibility of estimating the entropy of frames after calculating its score function, instead of using original frames. We observe that if signal is clean, estimated entropy is essentially the same; but if signal is noisy transformed frames (with score function) are able to give different entropy if the frame is voiced against unvoiced ones. Experimental results show that this fact permits to detect voice activity under high noise, where simple entropy method fails.

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Os parâmetros dosimétricos de um feixe de raios X de pequeno diâmetro para um sistema de radiocirurgia comercial foram medidos em água com um detector de diodo de Si do tipo p. As razões tecido-máximo, o fator de espalhamento total e os perfis dos feixes a profundidades de 5 e 10 cm foram medidos para 17 feixes de diâmetros circulares de 5 mm a 50 mm, em incrementos de 2,5 mm. Os fatores de espalhamento totais caíram lentamente, de 0,947 para 0,888 entre os cones de 50 mm e 12,5 mm de diâmetro (variação de 7%); para os cones entre 10 mm e 5 mm de diâmetro, esta queda foi bem maior, de 0,854 para 0,666 (variação de 28%). Os valores obtidos para a relação tecido-máximo são consistentes com dados publicados. Os perfis dos feixes foram medidos nas direções x e y, e estão dentro de 0,2 mm para todos os cones entre as duas direções. A medida da largura à meia-altura se encontra dentro de 1 mm com o diâmetro nominal dos cones.

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Este trabalho apresenta a parte operacional do processo final envolvido na implantação de um programa de controle de qualidade por meio de testes rotineiros mecânicos e de radiação. O programa de controle de qualidade, durante 35 meses, mostrou a estabilidade excelente deste acelerador.

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Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

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To evaluate antibody specificities induced by simian immunodeficiency virus (SIV) versus human immunodeficiency virus type 1 (HIV-1) envelope antigens in nonhuman primate (NHP), we profiled binding antibody responses to linear epitopes in NHP studies with HIV-1 or SIV immunogens. We found that, overall, HIV-1 Env IgG responses were dominated by V3, with the notable exception of the responses to the vaccine strain A244 Env that were dominated by V2, whereas the anti-SIVmac239 Env responses were dominated by V2 regardless of the vaccine regimen.

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Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

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Already in ancient Greece, Hippocrates postulated that disease showed a seasonal pattern characterised by excess winter mortality. Since then, several studies have confirmed this finding, and it was generally accepted that the increase in winter mortality was mostly due to respiratory infections and seasonal influenza. More recently, it was shown that cardiovascular disease (CVD) mortality also displayed such seasonality, and that the magnitude of the seasonal effect increased from the poles to the equator. The recent study by Yang et al assessed CVD mortality attributable to ambient temperature using daily data from 15 cities in China for years 2007-2013, including nearly two million CVD deaths. A high temperature variability between and within cities can be observed (figure 1). They used sophisticated statistical methodology to account for the complex temperature-mortality relationship; first, distributed lag non-linear models combined with quasi-Poisson regression to obtain city-specific estimates, taking into account temperature, relative humidity and atmospheric pressure; then, a meta-analysis to obtain the pooled estimates. The results confirm the winter excess mortality as reported by the Eurowinter3 and other4 groups, but they show that the magnitude of ambient temperature.

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Today’s commercial web sites are under heavy user load and they are expected to be operational and available at all times. Distributed system architectures have been developed to provide a scalable and failure tolerant high availability platform for these web based services. The focus on this thesis was to specify and implement resilient and scalable locally distributed high availability system architecture for a web based service. Theory part concentrates on the fundamental characteristics of distributed systems and presents common scalable high availability server architectures that are used in web based services. In the practical part of the thesis the implemented new system architecture is explained. Practical part also includes two different test cases that were done to test the system's performance capacity.

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The present work describes the development of a fast and robust analytical method for the determination of 53 antibiotic residues, covering various chemical groups and some of their metabolites, in environmental matrices that are considered important sources of antibiotic pollution, namely hospital and urban wastewaters, as well as in river waters. The method is based on automated off-line solid phase extraction (SPE) followed by ultra-high-performance liquid chromatography coupled to quadrupole linear ion trap tandem mass spectrometry (UHPLC–QqLIT). For unequivocal identification and confirmation, and in order to fulfill EU guidelines, two selected reaction monitoring (SRM) transitions per compound are monitored (the most intense one is used for quantification and the second one for confirmation). Quantification of target antibiotics is performed by the internal standard approach, using one isotopically labeled compound for each chemical group, in order to correct matrix effects. The main advantages of the method are automation and speed-up of sample preparation, by the reduction of extraction volumes for all matrices, the fast separation of a wide spectrum of antibiotics by using ultra-high-performance liquid chromatography, its sensitivity (limits of detection in the low ng/L range) and selectivity (due to the use of tandem mass spectrometry) The inclusion of β-lactam antibiotics (penicillins and cephalosporins), which are compounds difficult to analyze in multi-residue methods due to their instability in water matrices, and some antibiotics metabolites are other important benefits of the method developed. As part of the validation procedure, the method developed was applied to the analysis of antibiotics residues in hospital, urban influent and effluent wastewaters as well as in river water samples