885 resultados para FEC using Reed-Solomon and Tornado codes
Resumo:
“Many-core” systems based on a Network-on-Chip (NoC) architecture offer various opportunities in terms of performance and computing capabilities, but at the same time they pose many challenges for the deployment of real-time systems, which must fulfill specific timing requirements at runtime. It is therefore essential to identify, at design time, the parameters that have an impact on the execution time of the tasks deployed on these systems and the upper bounds on the other key parameters. The focus of this work is to determine an upper bound on the traversal time of a packet when it is transmitted over the NoC infrastructure. Towards this aim, we first identify and explore some limitations in the existing recursive-calculus-based approaches to compute the Worst-Case Traversal Time (WCTT) of a packet. Then, we extend the existing model by integrating the characteristics of the tasks that generate the packets. For this extended model, we propose an algorithm called “Branch and Prune” (BP). Our proposed method provides tighter and safe estimates than the existing recursive-calculus-based approaches. Finally, we introduce a more general approach, namely “Branch, Prune and Collapse” (BPC) which offers a configurable parameter that provides a flexible trade-off between the computational complexity and the tightness of the computed estimate. The recursive-calculus methods and BP present two special cases of BPC when a trade-off parameter is 1 or ∞, respectively. Through simulations, we analyze this trade-off, reason about the implications of certain choices, and also provide some case studies to observe the impact of task parameters on the WCTT estimates.
Resumo:
The power systems operation in the smart grid context increases significantly the complexity of their management. New approaches for ancillary services procurement are essential to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. These approaches should include market mechanisms which allow the participation of small and medium distributed energy resources players in a competitive market environment. In this paper, an energy and ancillary services joint market model used by an aggregator is proposed, considering bids of several types of distributed energy resources. In order to improve economic efficiency in the market, ancillary services cascading market mechanism is also considered in the model. The proposed model is included in MASCEM – a multi-agent system electricity market simulator. A case study considering a distribution network with high penetration of distributed energy resources is presented.
Resumo:
Dissertação apresentada para a obtenção do Grau de Doutor em Informática
Resumo:
The objective of the present study was to determine the prevalence of certain mycoplasma species, i.e., Mycoplasma hominis, Ureaplasma urealyticum and Mycoplasma penetrans, in urethral swabs from HIV-1 infected patients compared to swabs from a control group. Mycoplasmas were detected by routine culture techniques and by the Polymerase Chain Reaction (PCR) technique, using 16SrRNA generic primers of conserved region and Mycoplasma penetrans specific primers. The positivity rates obtained with the two methods were comparable. Nevertheless, PCR was more sensitive, while the culture techniques allowed the quantification of the isolates. The results showed no significant difference (p < 0.05) in positivity rates between the methods used for mycoplasma detection.
Resumo:
Early life-stage bioassays have been used as an alternative to short-term adult toxicity tests since they are cost-effective. A single couple can produce hundreds or thousands of embryos and hence can be used as a simple high-throughput approach in toxicity studies. In the present study, zebrafish and sea urchin embryo bioassays were used to test the toxicity of four pharmaceuticals belonging to different therapeutic classes: diclofenac, propranolol, simvastatin and sertraline. Simvastatin was the most toxic tested compound for zebrafish embryo, followed by diclofenac. Sertraline was the most toxic drug to sea urchin embryos, inducing development abnormalities at the ng/L range. Overall, our results highlight the potential of sea urchin embryo bioassay as a promising and sensitive approach for the high-throughput methods to test the toxicity of new chemicals, including pharmaceuticals, and identify several drugs that should go through more detailed toxicity assays.
Resumo:
This work measures and tries to compare the Antioxidant Capacity (AC) of 50 commercial beverages of different kinds: 6 wines, 12 beers, 18 soft drinks and 14 flavoured waters. Because there is no reference procedure established for this purpose, three different optical methods were used to analyse these samples: Total Radical trapping Antioxidant Parameter (TRAP), Trolox Equivalent Antioxidant Capacity (TEAC) and Ferric ion Reducing Antioxidant Parameter (FRAP). These methods differ on the chemical background and nature of redox system. The TRAP method involves the transfer of hydrogen atoms while TEAC and FRAP involves electron transfer reactions. The AC was also assessed against three antioxidants of reference, Ascorbic acid (AA), Gallic acid (GA) and 6-hydroxy-2,5,7,8-tetramethyl- 2-carboxylic acid (Trolox). The results obtained were analyzed statistically. Anova one-way tests were applied to all results and suggested that methods and standards exhibited significant statistical differences. The possible effect of sample features in the AC, such as gas, flavours, food colouring, sweeteners, acidity regulators, preservatives, stabilizers, vitamins, juice percentage, alcohol percentage, antioxidants and the colour was also investigated. The AC levels seemed to change with brand, kind of antioxidants added, and kind of flavour, depending on the sample. In general, higher ACs were obtained for FRAP as method, and beer for kind of sample, and the standard expressing the smaller AC values was GA.
Resumo:
The Western blot technique was used to demonstrate the presence of antibodies in the blood of dogs that presented canine visceral leishmaniasis. This technique was used against some specific molecules present in the lysate of the promastigote form of Leshmania chagasi.Through the association of the results of the Western blot technique with the morphological alterations seen as a result of the serum neutralization technique performed in McCoy cells (which mimetizes the macrophage) it was possible to observe the role of some molecules of great relevance in determining the disease in symptomatic dogs as well as that of some other molecules associated with asymptomatic infected dogs that may become transmitters as well as differentiating them as asymptomatic resistant dogs. In the sera analyses carried out during the immunobloting a variation of 9 to 27 immunoreacting bands was observed, which were then compared using Dice's similarity coefficient. In the dendrogram constructed on the basis of the coefficient, 50% similarity was observed among the total number of reagent bands with the promastigote lysate, thus creating five groups. The main difference observed related to the clinical condition of the dogs: symptomatic and asymptomatic dogs were found in separate groups. The asymptomatic group of dogs was distributed in two different places in the dendrogram because they presented two different behavior patterns regarding the cellular morphology in the serum neutralization reaction: the presence or absence of cellular lysis. According to this analysis it is possible to evaluate the immune status and associate it with specific markers observed in the reaction found in the Western blot strips.
Resumo:
In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.
Resumo:
In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.
Resumo:
In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.
Resumo:
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Resumo:
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
Resumo:
African elections often reveal low levels of political accountability. We assess different forms of voter education during an election in Mozambique. Three interventions providing information to voters and calling for their electoral participation were randomized; an SMS-based information campaign, an SMS hotline for electoral misconduct, and the distribution of a free newspaper. To measure impact, we look at official electoral results, reports by electoral observers, behavioral and survey data. We find positive effects of all treatments on voter turnout. We observe that the distribution of the newspaper led to more accountability-based participation and to a decrease in electoral problems.
Resumo:
The assessment of wind energy resource for the development of deep offshore wind plants requires the use of every possible source of data and, in many cases, includes data gathered at meteorological stations installed at islands, islets or even oil platforms—all structures that interfere with, and change, the flow characteristics. This work aims to contribute to the evaluation of such changes in the flow by developing a correction methodology and applying it to the case of Berlenga island, Portugal. The study is performed using computational fluid dynamic simulations (CFD) validated by wind tunnel tests. In order to simulate the incoming offshore flow with CFD models a wind profile, unknown a priori, was established using observations from two coastal wind stations and a power law wind profile was fitted to the existing data (a=0.165). The results show that the resulting horizontal wind speed at 80 m above sea level is 16% lower than the wind speed at 80 m above the island for the dominant wind direction sector.