7 resultados para data centric storage

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Changes in the oceanic heat storage (HS) can reveal important evidences of climate variability related to ocean heat fluxes. Specifically, long-term variations in HS are a powerful indicator of climate change as HS represents the balance between the net surface energy flux and the poleward heat transported by the ocean currents. HS is estimated from sea surface height anomaly measured from the altimeters TOPEX/Poseidon and Jason 1 from 1993 to 2006. To characterize and validate the altimeter-based HS in the Atlantic, we used the data from the Pilot Research Moored Array in the Tropical Atlantic (PIRATA) array. Correlations and rms differences are used as statistical figures of merit to compare the HS estimates. The correlations range from 0.50 to 0.87 in the buoys located at the equator and at the southern part of the array. In that region the rms differences range between 0.40 and 0.51 x 10(9) Jm(-2). These results are encouraging and indicate that the altimeter has the precision necessary to capture the interannual trends in HS in the Atlantic. Albeit relatively small, salinity changes can also have an effect on the sea surface height anomaly. To account for this effect, NCEP/GODAS reanalysis data are used to estimate the haline contraction. To understand which dynamical processes are involved in the HS variability, the total signal is decomposed into nonpropagating basin-scale and seasonal (HS(l)) planetary waves, mesoscale eddies, and small-scale residual components. In general, HS(l) is the dominant signal in the tropical region. Results show a warming trend of HS(l) in the past 13 years almost all over the Atlantic basin with the most prominent slopes found at high latitudes. Positive interannual trends are found in the halosteric component at high latitudes of the South Atlantic and near the Labrador Sea. This could be an indication that the salinity anomaly increased in the upper layers during this period. The dynamics of the South Atlantic subtropical gyre could also be subject to low-frequency changes caused by a trend in the halosteric component on each side of the South Atlantic Current.

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The Amazon basin is a region of constant scientific interest due to its environmental importance and its biodiversity and climate on a global scale. The seasonal variations in water volume are one of the examples of topics studied nowadays. In general, the variations in river levels depend primarily on the climate and physics characteristics of the corresponding basins. The main factor which influences the water level in the Amazon Basin is the intensive rainfall over this region as a consequence of the humidity of the tropical climate. Unfortunately, the Amazon basin is an area with lack of water level information due to difficulties in access for local operations. The purpose of this study is to compare and evaluate the Equivalent Water Height (Ewh) from GRACE (Gravity Recovery And Climate Experiment) mission, to study the connection between water loading and vertical variations of the crust due to the hydrologic. In order to achieve this goal, the Ewh is compared with in-situ information from limnimeter. For the analysis it was computed the correlation coefficients, phase and amplitude of GRACE Ewh solutions and in-situ data, as well as the timing of periods of drought in different parts of the basin. The results indicated that vertical variations of the lithosphere due to water mass loading could reach 7 to 5 cm per year, in the sedimentary and flooded areas of the region, where water level variations can reach 10 to 8 m.

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The Amazon basin is a region of constant scientific interest due to its environmental importance and its biodiversity and climate on a global scale. The seasonal variations in water volume are one of the examples of topics studied nowadays. In general, the variations in river levels depend primarily on the climate and physics characteristics of the corresponding basins. The main factor which influences the water level in the Amazon Basin is the intensive rainfall over this region as a consequence of the humidity of the tropical climate. Unfortunately, the Amazon basin is an area with lack of water level information due to difficulties in access for local operations. The purpose of this study is to compare and evaluate the Equivalent Water Height (Ewh) from GRACE (Gravity Recovery And Climate Experiment) mission, to study the connection between water loading and vertical variations of the crust due to the hydrologic. In order to achieve this goal, the Ewh is compared with in-situ information from limnimeter. For the analysis it was computed the correlation coefficients, phase and amplitude of GRACE Ewh solutions and in-situ data, as well as the timing of periods of drought in different parts of the basin. The results indicated that vertical variations of the lithosphere due to water mass loading could reach 7 to 5 cm per year, in the sedimentary and flooded areas of the region, where water level variations can reach 10 to 8 m.

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Objectives: To determine the micro-hardness profile of two dual cure resin cements (RelyX - U100 (R), 3M-ESPE and Panavia F 2.0 (R), Kuraray) used for cementing fiber-reinforced resin posts (Fibrekor (R) - Jeneric Pentron) under three different curing protocols and two water storage times. Material and methods: Sixty 16mm long bovine incisor roots were endodontically treated and prepared for cementation of the Fibrekor posts. The cements were mixed as instructed, dispensed in the canal, the posts were seated and the curing performed as follows: a) no light activation; b) light-activation immediately after seating the post, and; c) light-activation delayed 5 minutes after seating the post. The teeth were stored in water and retrieved for analysis after 7 days and 3 months. The roots were longitudinally sectioned and the microhardness was determined at the cervical, middle and apical regions along the cement line. The data was analyzed by the three-way ANOVA test (curing mode, storage time and thirds) for each cement. The Tukey test was used for the post-hoc analysis. Results: Light-activation resulted in a significant increase in the microhardness. This was more evident for the cervical region and for the Panavia cement. Storage in water for 3 months caused a reduction of the micro-hardness for both cements. The U100 cement showed less variation in the micro-hardness regardless of the curing protocol and storage time. Conclusions: The micro-hardness of the cements was affected by the curing and storage variables and were material-dependent.

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Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.

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Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.

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Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.