931 resultados para large scale linear system


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A climatology of cyclones with a focus on their relation to wind storm tracks in the Mediterranean region (MR) is presented. Trends in the frequency of cyclones and wind storms, as well as variations associated with the North Atlantic Oscillation (NAO), the East Atlantic/West Russian (EAWR) and the Scandinavian variability pattern (SCAND) are discussed. The study is based on the ERA40 reanalysis dataset. Wind storm tracks are identified by tracking clusters of adjacent grid boxes characterised by extremely high local wind speeds. The wind track is assigned to a cyclone track independently identified with an objective scheme. Areas with high wind activity – quantified by extreme wind tracks – are typically located south of the Golf of Genoa, south of Cyprus, southeast of Sicily and west of the Iberian Peninsula. About 69% of the wind storms are caused by cyclones located in the Mediterranean region, while the remaining 31% can be attributed to North Atlantic or Northern European cyclones. The North Atlantic Oscillation, the East Atlantic/West Russian pattern and the Scandinavian pattern all influence the amount and spatial distribution of wind inducing cyclones and wind events in the MR. The strongest signals exist for the NAO and the EAWR pattern, which are both associated with an increase in the number of organised strong wind events in the eastern MR during their positive phase. On the other hand, the storm numbers decrease over the western MR for the positive phase of the NAO and over the central MR during the positive phase of the EAWR pattern. The positive phase of the Scandinavian pattern is associated with a decrease in the number of winter wind storms over most of the MR. A third of the trends in the number of wind storms and wind producing cyclones during the winter season of the ERA40 period may be attributed to the variability of the North Atlantic Oscillation.

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The time-mean quasi-geostrophic potential vorticity equation of the atmospheric flow on isobaric surfaces can explicitly include an atmospheric (internal) forcing term of the stationary-eddy flow. In fact, neglecting some non-linear terms in this equation, this forcing can be mathematically expressed as a single function, called Empirical Forcing Function (EFF), which is equal to the material derivative of the time-mean potential vorticity. Furthermore, the EFF can be decomposed as a sum of seven components, each one representing a forcing mechanism of different nature. These mechanisms include diabatic components associated with the radiative forcing, latent heat release and frictional dissipation, and components related to transient eddy transports of heat and momentum. All these factors quantify the role of the transient eddies in forcing the atmospheric circulation. In order to assess the relevance of the EFF in diagnosing large-scale anomalies in the atmospheric circulation, the relationship between the EFF and the occurrence of strong North Atlantic ridges over the Eastern North Atlantic is analyzed, which are often precursors of severe droughts over Western Iberia. For such events, the EFF pattern depicts a clear dipolar structure over the North Atlantic; cyclonic (anticyclonic) forcing of potential vorticity is found upstream (downstream) of the anomalously strong ridges. Results also show that the most significant components are related to the diabatic processes. Lastly, these results highlight the relevance of the EFF in diagnosing large-scale anomalies, also providing some insight into their interaction with different physical mechanisms.

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Exascale systems are the next frontier in high-performance computing and are expected to deliver a performance of the order of 10^18 operations per second using massive multicore processors. Very large- and extreme-scale parallel systems pose critical algorithmic challenges, especially related to concurrency, locality and the need to avoid global communication patterns. This work investigates a novel protocol for dynamic group communication that can be used to remove the global communication requirement and to reduce the communication cost in parallel formulations of iterative data mining algorithms. The protocol is used to provide a communication-efficient parallel formulation of the k-means algorithm for cluster analysis. The approach is based on a collective communication operation for dynamic groups of processes and exploits non-uniform data distributions. Non-uniform data distributions can be either found in real-world distributed applications or induced by means of multidimensional binary search trees. The analysis of the proposed dynamic group communication protocol has shown that it does not introduce significant communication overhead. The parallel clustering algorithm has also been extended to accommodate an approximation error, which allows a further reduction of the communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing elements.

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Climate simulations show consistent large-scale temperature responses including amplified land–ocean contrast, high-latitude/low-latitude contrast, and changes in seasonality in response to year-round forcing, in both warm and cold climates, and these responses are proportional and nearly linear across multiple climate states. We examine the possibility that a small set of common mechanisms controls these large-scale responses using a simple energy-balance model to decompose the temperature changes shown in multiple lgm and abrupt4 × CO 2 simulations from the CMIP5 archive. Changes in the individual components of the energy balance are broadly consistent across the models. Although several components are involved in the overall temperature responses, surface downward clear-sky longwave radiation is the most important component driving land–ocean contrast and high-latitude amplification in both warm and cold climates. Surface albedo also plays a significant role in promoting high-latitude amplification in both climates and in intensifying the land–ocean contrast in the warm climate case. The change in seasonality is a consequence of the changes in land–ocean and high-latitude/low-latitude contrasts rather than an independent temperature response. This is borne out by the fact that no single component stands out as being the major cause of the change in seasonality, and the relative importance of individual components is different in cold and warm climates.

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As part of an international intercomparison project, a set of single column models (SCMs) and cloud-resolving models (CRMs) are run under the weak temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistent implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics. CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large-scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation. When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations.

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The landfall of Cyclone Catarina on the Brazilian coast in March 2004 became known as the first documented hurricane in the South Atlantic Ocean, promoting a new view oil how large-scale features can contribute to tropical transition. The aim of this paper is to put the large-scale circulation associated with Catarina`s transition in climate perspective. This is discussed in the light of a robust pattern of spatial correlations between thermodynamic and dynamic variables of importance for hurricane formation. A discussion on how transition mechanisms respond to the present-day circulation is presented. These associations help in understanding why Catarina was formed in a region previously thought to be hurricane-free. Catarina developed over a large-scale area of thermodynamically favourable air/sea temperature contrast. This aspect explains the paradox that such a rare system developed when the sea surface temperature was slightly below average. But, although thermodynamics played an important role, it is apparent that Catarina would not have formed without the key dynamic interplay triggered by a high latitude blocking. The blocking was associated with an extreme positive phase of the Southern Annular Mode (SAM) both hemispherically and locally, and the nearby area where Catarina developed is found to be more cyclonic during the positive phase of the SAM. A conceptual model is developed and a `South Atlantic index` is introduced as a useful diagnostic of potential conditions leading to tropical transition in the area, where large-scale indices indicate trends towards more favourable atmospheric conditions for tropical cyclone formation. Copyright (c) 2008 Royal Meteorological Society

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Biological sequence assembly is an essential step for sequencing the genomes of organisms. Sequence assembly is very computing intensive especially for the large-scale sequence assembly. Parallel computing is an effective way to reduce the computing time and support the assembly for large amount of biological fragments. Euler sequence assembly algorithm is an innovative algorithm proposed recently. The advantage of this algorithm is that its computing complexity is polynomial and it provides a better solution to the notorious “repeat” problem. This paper introduces the parallelization of the Euler sequence assembly algorithm. All the Genome fragments generated by whole genome shotgun (WGS) will be assembled as a whole rather than dividing them into groups which may incurs errors due to the inaccurate group partition. The implemented system can be run on supercomputers, network of workstations or even network of PC computers. The experimental results have demonstrated the performance of our system.

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In data-intensive distributed systems, replication is the most widely used approach to offer high data availability, low bandwidth consumption, increased fault-tolerance and improved scalability of the overall system. Replication-based systems implement replica control protocols that enforce a specified semantics of accessing the data. Also, the performance depends on a number of factors, the chief of which is the protocol used to maintain consistency among object replica. In this paper, we propose a new low-cost and high data availability protocol called the box-shaped grid structure for maintaining consistency of replicated data on networked distributed computing systems. We show that the proposed protocol provides high data availability, low communication costs, and increased fault-tolerance as compared to the baseline replica control protocols.

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The study of the communication networks for distributed systems is very important, since the overall performance of these systems is often depends on the effectiveness of its communication network. In this paper, we address the problem of networks modeling for heterogeneous large-scale cluster systems. We consider the large-scale cluster systems as a typical cluster of clusters system. Since the heterogeneity is becoming common in such systems, we take into account network as well as cluster size heterogeneity to propose the model. To this end, we present an analytical network model and validate the model through comprehensive simulation. The results of the simulation demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.

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In this study, we have demonstrated that a rotating metal wire coil can be used as a nozzle to electrospin nanofibers on a large-scale. Without using any needles, the rotating wire coil, partially immersed in a polymer solution reservoir, can pick up a thin layer of charged polymer solution and generate a large number of nanofibers from the wire surface simultaneously. This arrangement significantly increases the nanofiber productivity. The fiber productivity was found to be determined by the coil dimensions, applied voltage and polymer concentration. The dependency of fiber diameter on the polymer concentration showed a similar trend to that for a conventional electrospinning system using a syringe needle nozzle, but the coil electrospun fibers were thinner with narrower diameter distribution. The profiles of electric field strength in the coil electrospinning was calculated and showed concentrated electric field intensity on the wire surface.

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In this paper, we present some practical experiences on implementing an alert fusion mechanism from our project. After investigation on most of the existing alert fusion systems, we found the current body of work alternatively weighed down in the mire of insecure design or rarely deployed because of their complexity. As confirmed by our experimental analysis, unsuitable mechanisms could easily be submerged by an abundance of useless alerts. Even with the use of methods that achieve a high fusion rate and low false positives, attack is also possible. To find the solution, we carried out analysis on a series of alerts generated by well-known datasets as well as realistic alerts from the Australian Honey-Pot. One important finding is that one alert has more than an 85% chance of being fused in the following five alerts. Of particular importance is our design of a novel lightweight Cache-based Alert Fusion Scheme, called CAFS. CAFS has the capacity to not only reduce the quantity of useless alerts generated by intrusion detection system, but also enhance the accuracy of alerts, therefore greatly reducing the cost of fusion processing. We also present reasonable and practical specifications for the target-oriented fusion policy that provides a quality guarantee on alert fusion, and as a result seamlessly satisfies the process of successive correlation. Our experiments compared CAFS with traditional centralized fusion. The results showed that the CAFS easily attained the desired level of simple, counter-escapable alert fusion design. Furthermore, as a lightweight scheme, CAFS can easily be deployed and excel in a large amount of alert fusions, which go towards improving the usability of system resources. To the best of our knowledge, our work is a practical exploration in addressing problems from the academic point of view. Copyright © 2011 John Wiley & Sons, Ltd.

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Habitat loss and associated fragmentation effects are well-recognised threats to biodiversity. Loss of functional connectivity (mobility, gene flow and demographic continuity) could result in population decline in altered habitat, because smaller, isolated populations are more vulnerable to extinction. We tested whether substantial habitat reduction plus fragmentation is associated with reduced gene flow in three 'decliner' woodland-dependent bird species (eastern yellow robin, weebill and spotted pardalote) identified in earlier work to have declined disproportionately in heavily fragmented landscapes in the Box-Ironbark forest region in north-central Victoria, Australia. For these three decliners, and one 'tolerant' species (striated pardalote), we compared patterns of genetic diversity, relatedness, effective population size, sex-ratios and genic (allele frequency) differentiation among landscapes of different total tree cover, identified population subdivision at the regional scale, and explored fine-scale genotypic (individual-based genetic signature) structure. Unexpectedly high genetic connectivity across the study region was detected for 'decliner' and 'tolerant' species. Power analysis simulations suggest that moderate reductions in gene flow should have been detectable. However, there was evidence of local negative effects of reduced habitat extent and structural connectivity: slightly lower effective population sizes, lower genetic diversity, higher within-site relatedness and altered sex-ratios (for weebill and eastern yellow robin) in 10 x 10 km 'landscapes' with low vegetation cover. We conclude that reduced structural connectivity in the Box-Ironbark ecosystem may still allow sufficient gene flow to avoid the harmful effects of inbreeding in our study species. Although there may still be negative consequences of fragmentation for demographic connectivity, the high genetic connectivity of mobile bird species in this system suggests that reconnecting isolated habitat patches may be less important than increasing habitat extent and/or quality if these need to be traded off.

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Understanding how habitat fragmentation affects population processes (e.g. dispersal) at different spatial scales is of critical importance to conservation. We assessed the effects of habitat fragmentation on dispersal and regional and fine-scale population structure in a currently widespread and common cooperatively breeding bird species found across south-eastern Australia, the superb fairy-wren Malurus cyaneus. Despite its relative abundance and classification as an urban tolerant species, the superb fairy-wren has declined disproportionately from low tree-cover agricultural landscapes across the Box-Ironbark region of north-central Victoria, Australia. Loss of genetic connectivity and disruption to its complex social system may be associated with the decline of this species from apparently suitable habitat in landscapes with low levels of tree cover. To assess whether reduced structural connectivity has had negative consequences for genetic connectivity in the superb fairy-wren, we used a landscape-scale approach to compare patterns of genetic diversity and gene flow at large (landscape/regional) and fine (site-level) spatial scales. In addition, using genetic distances, for each sex, we tested landscape models of decreased dispersal through treeless areas (isolation-by-resistance) while controlling for the effect of isolation-by-distance. Landscape models indicated that larger-scale gene flow across the Box-Ironbark region was constrained by distance rather than by lack of structural connectivity. Nonetheless, a pattern of isolation-by-resistance for males (the less-dispersive sex) and lower genetic diversity and higher genetic similarity within sites in low-cover fragmented landscapes indicated disruption to fine-scale gene flow mechanisms and/or mating systems. Although loss of structural connectivity did not appear to impede gene flow at larger spatial scales, fragmentation appeared to affect fine-scale population processes (e.g. local gene flow mechanisms and/or mating systems) adversely and may contribute to the decline of superb fairy-wrens in fragmented landscapes in the Box-Ironbark region. © 2012 British Ecological Society.

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The impact of salmon farming on the environment has been widely studied; there is, however, no consensus on the magnitude and quality of these effects and little information on their extent over large salmon farming areas. Forty-three salmon farm sites of which 29 are in full operation and grouped in nine locations in southern Chile were evaluated. Using statistical methods (two-way anova), no effects were found on water column variables such as nitrate, ammonia, orthophosphate and chlorophyll, whereas they were significant on sediment variables such as nitrogen (N), phosphorus (P) and organic carbon (OC), among others. Natural variability evaluation of some parameters revealed that P in sediments had the lowest coefficient of variation (23.2%) when compared with N (65.2%), particulate organic matter (POM) (139%) and OC (39%), and showed more marked salmon farming effects with no locality effects. Four of the nine locations showed stronger effects on sediments, with average P values ranging from 150 to 230 mmol that were six to nine times higher than in control sites (25 mmol). Nitrogen and carbon in sediments, while showing significant effects on salmon farming, also showed locality effects that revealed other biogenic processes influencing sediment composition. Thus, P in sediments was proposed as a promising indicator of impact on salmon farming, although the relationship with fauna in sediments was not linear and somewhat variable; more research is therefore needed to understand such connections. Considering entire geographical locations, no relationship was found between sediment conditions under salmon cages and the condition of the water column at a farm. This may indicate the possibility of high dilution rates and recycling processes, which so far preclude the detection of more global impacts beyond the cages shadow.