5 resultados para Computing clouds

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.

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The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

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The development of cloud computing services is speeding up the rate in which the organizations outsource their computational services or sell their idle computational resources. Even though migrating to the cloud remains a tempting trend from a financial perspective, there are several other aspects that must be taken into account by companies before they decide to do so. One of the most important aspect refers to security: while some cloud computing security issues are inherited from the solutions adopted to create such services, many new security questions that are particular to these solutions also arise, including those related to how the services are organized and which kind of service/data can be placed in the cloud. Aiming to give a better understanding of this complex scenario, in this article we identify and classify the main security concerns and solutions in cloud computing, and propose a taxonomy of security in cloud computing, giving an overview of the current status of security in this emerging technology.

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Cirrus clouds are an interesting point in the research of the atmosphere due their behavior and the effect on the earth radiation budget. They can affect the atmospheric radiation budget by reflecting the incoming solar radiation and absorbing the outgoing terrestrial radiation. Also, this cloud type is involved in the dehydration of the upper troposphere and lower stratosphere. So, it is interesting to increment the measurements of this type of clouds from the ground. During November and December 2012, through the CHUVA-SUL campaign, measurements with lidar in Santa Maria, Rio Grande do Sul were conducted. The system installed in Santa Maria site (29.8 °S; 53.7 °W, 100 m asl) was a single elastic-backscatter lidar using the wavelength of 532 nm. Some days with cirrus clouds lidar measurements were detected. Four days with presence of cirrus cloud are showed in the present study. These days, 7, 8, 19 and 28 November 2012, was selected due the persistence of cirrus clouds over many hours. The raw retrieval lidar signals and inverted backscatter coefficient profiles were analyzed for the selected days. Base and top height was obtained by analysis of raw signal and backscatter coefficient. Extinction coefficient profiles were obtained by the assumption of the lidar ratio. Cirrus cloud optical depth (COD) values were calculated, from the integration of the extinction coefficient between the base and top altitudes of the cirrus clouds.

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We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ∼2.4 km by ∼5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.