869 resultados para distributed parameter systems


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Designs for deep geological respositories of nuclear waste include bentonite as a hydraulic and chemisorption buffer material to protect the biosphere from leakage of radionuclides. Bentonite is chosen because it is a cheap, naturally occurring material with the required properties. It consists essentially of montmorillonite, a swelling clay mineral. Upon contact with groundwater such clays can seal the repository by incorporating water in the interlayers of their crystalline structure. The intercalated water exhibits significantly different properties to bulk water in the surrounding interparticle pores, such as lower diffusion coefficients (González Sánchez et. al. 2008). This doctoral thesis presents water distribution and diffusion behavior on various time and space scales in montmorillonite. Experimental results are presented for Na- and Cs-montmorillonite samples with a range of bulk dry densities (0.8 to 1.7 g/cm3). The experimental methods employed were neutron scattering (backscattering, diffraction, time-of-flight), adsorption measurements (water, nitrogen) and tracer-through diffusion. For the tracer experiments the samples were fully saturated via the liquid phase under volume-constrained conditions. In contrast, for the neutron scattering experiments, the samples were hydrated via the vapor phase and subsequently compacted, leaving a significant fraction of interparticle pores unfilled with water. Owing to these differences in saturation, the water contents of the samples for neutron scattering were characterized by gravimetry whereas those for the tracer experiments were obtained from the bulk dry density. The amount of surface water in interlayer pores could be successfully discriminated from the amount of bulk-like water in interparticle pores in Na- and Csmontmorillonite using neutron spectroscopy. For the first time in the literature, the distribution of water between these two pore environments was deciphered as a function of gravimetric water content. The amount was compared to a geometrical estimation of the amount of interlayer and interparticle water determined by neutron diffraction and adsorption measurements. The relative abundances of the 1 to 4 molecular water layers in the interlayer were determined from the area ratios of the (001)-diffraction peaks. Depending on the characterization method, different fractions of surface water and interlayer water were obtained. Only surface and interlayer water exists in amontmorillonite with water contents up to 0.18 g/g according to spectroscopic measurements and up to 0.32 g/g according to geometrical estimations, respectively. At higher water contents, bulk-like and interparticle water also exists. The amounts increase monotonically, but not linearly, from zero to 0.33 g/g for bulk-like water and to 0.43 g/g for interparticle water. It was found that water most likely redistributes between the surface and interlayer sites during the spectroscopic measurements and therefore the reported fraction is relevant only below about -10 ºC (Anderson, 1967). The redistribution effect can explain the discrepancy in fractions between the methods. In a novel approach the fractions of water in different pore environments were treated as a fixed parameter to derive local diffusion coefficients for water from quasielastic neutron scattering data, in particular for samples with high water contents. Local diffusion coefficients were obtained for the 1 to 4 molecular water layers in the interlayer of 0.5·10–9, 0.9·10–9, 1.5·10–9 and 1.4·10–9 m²/s, respectively, taking account of the different water fractions (molecular water layer, bulk-like water). The diffusive transport of 22Na and HTO through Na-montmorillonite was measured on the laboratory experimental scale (i.e. cm, days) by tracer through-diffusion experiments. We confirmed that diffusion of HTO is independent of the ionic strength of the external solution in contact with the clay sample but dependent on the bulk dry density. In contrast, the diffusion of 22Na was found to depend on both the ionic strength of the pore solution and on the bulk dry density. The ratio of the pore and surface diffusion could be experimentally determined for 22Na from the dependence of the diffusion coefficient on the ionic strength. Activation energies were derived from the temperaturedependent diffusion coefficients via the Arrhenius relation. In samples with high bulk dry density the activation energies are slightly higher than those of bulk water whereas in low density samples they are lower. The activation energies as a function of ionic strengths of the pore solutions are similar for 22Na and HTO. The facts that (i) the slope of the logarithmic effective diffusion coefficients as a function of the logarithmic ionic strength is less than unity for low bulk dry densities and (ii) two water populations can be observed for high gravimetric water contents (low bulk dry densities) support the interlayer and interparticle porosity model proposed by Glaus et al. (2007), Bourg et al. (2006, 2007) and Gimmi and Kosakowski (2011).

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Long Term Evolution (LTE) represents the fourth generation (4G) technology which is capable of providing high data rates as well as support of high speed mobility. The EU FP7 Mobile Cloud Networking (MCN) project integrates the use of cloud computing concepts in LTE mobile networks in order to increase LTE's performance. In this way a shared distributed virtualized LTE mobile network is built that can optimize the utilization of virtualized computing, storage and network resources and minimize communication delays. Two important features that can be used in such a virtualized system to improve its performance are the user mobility and bandwidth prediction. This paper introduces the architecture and challenges that are associated with user mobility and bandwidth prediction approaches in virtualized LTE systems.

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This article reconceptualizes shared rule and uses novel data to measure it, thus addressing two shortcomings of federal literature. First, while most studies focus on self-rule, one question that is largely neglected is how lower-level governments can influence politics at a higher level in the absence of “second” chambers. The answer is through shared rule. A second shortcoming is that even when addressing this question, scholars concentrate on constitutional-administrative aspects of vertical intergovernmentalism, neglecting more informal, “political” dynamics. Comparing the twenty-six Swiss cantons allows drawing two lessons for federal studies: That shared rule is multifaceted and complex, and that to study informal territorial actors as well as direct political processes is indispensable to understand how power is actually distributed in federal political systems.

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BACKGROUND: To investigate if non-rigid image-registration reduces motion artifacts in triggered and non-triggered diffusion tensor imaging (DTI) of native kidneys. A secondary aim was to determine, if improvements through registration allow for omitting respiratory-triggering. METHODS: Twenty volunteers underwent coronal DTI of the kidneys with nine b-values (10-700 s/mm2 ) at 3 Tesla. Image-registration was performed using a multimodal nonrigid registration algorithm. Data processing yielded the apparent diffusion coefficient (ADC), the contribution of perfusion (FP ), and the fractional anisotropy (FA). For comparison of the data stability, the root mean square error (RMSE) of the fitting and the standard deviations within the regions of interest (SDROI ) were evaluated. RESULTS: RMSEs decreased significantly after registration for triggered and also for non-triggered scans (P < 0.05). SDROI for ADC, FA, and FP were significantly lower after registration in both medulla and cortex of triggered scans (P < 0.01). Similarly the SDROI of FA and FP decreased significantly in non-triggered scans after registration (P < 0.05). RMSEs were significantly lower in triggered than in non-triggered scans, both with and without registration (P < 0.05). CONCLUSION: Respiratory motion correction by registration of individual echo-planar images leads to clearly reduced signal variations in renal DTI for both triggered and particularly non-triggered scans. Secondarily, the results suggest that respiratory-triggering still seems advantageous.J. Magn. Reson. Imaging 2014. (c) 2014 Wiley Periodicals, Inc.

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Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

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Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

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In this paper we present BitWorker, a platform for community distributed computing based on BitTorrent. Any splittable task can be easily specified by a user in a meta-information task file, such that it can be downloaded and performed by other volunteers. Peers find each other using Distributed Hash Tables, download existing results, and compute missing ones. Unlike existing distributed computing schemes relying on centralized coordination point(s), our scheme is totally distributed, therefore, highly robust. We evaluate the performance of BitWorker using mathematical models and real tests, showing processing and robustness gains. BitWorker is available for download and use by the community.

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Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

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In this work, electrophoretic preconcentration of protein and peptide samples in microchannels was studied theoretically using the 1D dynamic simulator GENTRANS, and experimentally combined with MS. In all configurations studied, the sample was uniformly distributed throughout the channel before power application, and driving electrodes were used as microchannel ends. In the first part, previously obtained experimental results from carrier-free systems are compared to simulation results, and the effects of atmospheric carbon dioxide and impurities in the sample solution are examined. Simulation provided insight into the dynamics of the transport of all components under the applied electric field and revealed the formation of a pure water zone in the channel center. In the second part, the use of an IEF procedure with simple well defined amphoteric carrier components, i.e. amino acids, for concentration and fractionation of peptides was investigated. By performing simulations a qualitative description of the analyte behavior in this system was obtained. Neurotensin and [Glu1]-Fibrinopeptide B were separated by IEF in microchannels featuring a liquid lid for simple sample handling and placement of the driving electrodes. Component distributions in the channel were detected using MALDI- and nano-ESI-MS and data were in agreement with those obtained by simulation. Dynamic simulations are demonstrated to represent an effective tool to investigate the electrophoretic behavior of all components in the microchannel.

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Interannual environmental variability in Peru is dominated by the El Niño Southern Oscillation (ENSO). The most dramatic changes are associated with the warm El Niño (EN) phase (opposite the cold La Niña phase), which disrupts the normal coastal upwelling and affects the dynamics of many coastal marine and terrestrial resources. This study presents a trophic model for Sechura Bay, located at the northern extension of the Peruvian upwelling system, where ENSO-induced environmental variability is most extreme. Using an initial steady-state model for the year 1996, we explore the dynamics of the ecosystem through the year 2003 (including the strong EN of 1997/98 and the weaker EN of 2002/03). Based on support from literature, we force biomass of several non-trophically-mediated 'drivers' (e.g. Scallops, Benthic detritivores, Octopus, and Littoral fish) to observe whether the fit between historical and simulated changes (by the trophic model) is improved. The results indicate that the Sechura Bay Ecosystem is a relatively inefficient system from a community energetics point of view, likely due to the periodic perturbations of ENSO. A combination of high system productivity and low trophic level target species of invertebrates (i.e. scallops) and fish (i.e. anchoveta) results in high catches and an efficient fishery. The importance of environmental drivers is suggested, given the relatively small improvements in the fit of the simulation with the addition of trophic drivers on remaining functional groups' dynamics. An additional multivariate regression model is presented for the scallop Argopecten purpuratus, which demonstrates a significant correlation between both spawning stock size and riverine discharge-mediated mortality on catch levels. These results are discussed in the context of the appropriateness of trophodynamic modeling in relatively open systems, and how management strategies may be focused given the highly environmentally influenced marine resources of the region.

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The use of modular or ‘micro’ maximum power point tracking (MPPT) converters at module level in series association, commercially known as “power optimizers”, allows the individual adaptation of each panel to the load, solving part of the problems related to partial shadows and different tilt and/or orientation angles of the photovoltaic (PV) modules. This is particularly relevant in building integrated PV systems. This paper presents useful behavioural analytical studies of cascade MPPT converters and evaluation test results of a prototype developed under a Spanish national research project. On the one hand, this work focuses on the development of new useful expressions which can be used to identify the behaviour of individual MPPT converters applied to each module and connected in series, in a typical grid-connected PV system. On the other hand, a novel characterization method of MPPT converters is developed, and experimental results of the prototype are obtained: when individual partial shading is applied, and they are connected in a typical grid connected PV array

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Knowledge management is critical for the success of virtual communities, especially in the case of distributed working groups. A representative example of this scenario is the distributed software development, where it is necessary an optimal coordination to avoid common problems such as duplicated work. In this paper the feasibility of using the workflow technology as a knowledge management system is discussed, and a practical use case is presented. This use case is an information system that has been deployed within a banking environment. It combines common workflow technology with a new conception of the interaction among participants through the extension of existing definition languages.

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An extended 3D distributed model based on distributed circuit units for the simulation of triple‐junction solar cells under realistic conditions for the light distribution has been developed. A special emphasis has been put in the capability of the model to accurately account for current mismatch and chromatic aberration effects. This model has been validated, as shown by the good agreement between experimental and simulation results, for different light spot characteristics including spectral mismatch and irradiance non‐uniformities. This model is then used for the prediction of the performance of a triple‐junction solar cell for a light spot corresponding to a real optical architecture in order to illustrate its suitability in assisting concentrator system analysis and design process.