918 resultados para CPU load


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La dinámica estructural estudia la respuesta de una estructura ante cargas o fenómenos variables en el tiempo. En muchos casos, estos fenómenos requieren realizar análisis paramétricos de la estructura considerando una gran cantidad de configuraciones de diseño o modificaciones de la estructura. Estos cambios, ya sean en fases iniciales de diseño o en fases posteriores de rediseño, alteran las propiedades físicas de la estructura y por tanto del modelo empleado para su análisis, cuyo comportamiento dinámico se modifica en consecuencia. Un caso de estudio de este tipo de modificaciones es la supervisión de la integridad estructural, que trata de identificar la presencia de daño estructural y prever el comportamiento de la estructura tras ese daño, como puede ser la variación del comportamiento dinámico de la estructura debida a una delaminación, la aparición o crecimiento de grieta, la debida a la pérdida de pala sufrida por el motor de un avión en vuelo, o la respuesta dinámica de construcciones civiles como puentes o edificios frente a cargas sísmicas. Si a la complejidad de los análisis dinámicos requeridos en el caso de grandes estructuras se añade la variación de determinados parámetros en busca de una respuesta dinámica determinada o para simular la presencia de daños, resulta necesario la búsqueda de medios de simplificación o aceleración del conjunto de análisis que de otra forma parecen inabordables tanto desde el punto de vista del tiempo de computación, como de la capacidad requerida de almacenamiento y manejo de grandes volúmenes de archivos de datos. En la presente tesis doctoral se han revisado los métodos de reducción de elementos .nitos más habituales para análisis dinámicos de grandes estructuras. Se han comparado los resultados de casos de estudio de los métodos más aptos, para el tipo de estructuras y modificaciones descritas, con los resultados de aplicación de un método de reducción reciente. Entre los primeros están el método de condensación estática de Guyan extendido al caso con amortiguamiento no proporcional y posteriores implementaciones de condensaciones dinámicas en diferentes espacios vectoriales. El método de reducción recientemente presentado se denomina en esta tesis DACMAM (Dynamic Analysis in Complex Modal space Acceleration Method), y consiste en el análisis simplificado que proporciona una solución para la respuesta dinámica de una estructura, calculada en el espacio modal complejo y que admite modificaciones estructurales. El método DACMAM permite seleccionar un número reducido de grados de libertad significativos para la dinámica del fenómeno que se quiere estudiar como son los puntos de aplicación de la carga, localizaciones de los cambios estructurales o puntos donde se quiera conocer la respuesta, de forma que al implementar las modificaciones estructurales, se ejecutan los análisis necesarios sólo de dichos grados de libertad sin pérdida de precisión. El método permite considerar alteraciones de masa, rigidez, amortiguamiento y la adición de nuevos grados de libertad. Teniendo en cuenta la dimensión del conjunto de ecuaciones a resolver, la parametrización de los análisis no sólo resulta posible, sino que es también manejable y controlable gracias a la sencilla implementación del procedimiento para los códigos habituales de cálculo mediante elementos .nitos. En el presente trabajo se muestra la bondad y eficiencia del método en comparación con algunos de los métodos de reducción de grandes modelos estructurales, verificando las diferencias entre sí de los resultados obtenidos y respecto a la respuesta real de la estructura, y comprobando los medios empleados en ellos tanto en tiempo de ejecución como en tamaño de ficheros electrónicos. La influencia de los diversos factores que se tienen en cuenta permite identificar los límites y capacidades de aplicación del método y su exhaustiva comparación con los otros procedimientos. ABSTRACT Structural dynamics studies the response of a structure under loads or phenomena which vary over time. In many cases, these phenomena require the use of parametric analyses taking into consideration several design configurations or modifications of the structure. This is a typical need in an engineering o¢ ce, no matter the structural design is in early or final stages. These changes modify the physical properties of the structure, and therefore, the finite element model to analyse it. A case study, that exempli.es this circumstance, is the structural health monitoring to predict the variation of the dynamical behaviour after damage, such as a delaminated structure, a crack onset or growth, an aircraft that suffers a blade loss event or civil structures (buildings or bridges) under seismic loads. Not only large structures require complex analyses to appropriately acquire an accurate solution, but also the variation of certain parameters. There is a need to simplify the analytical process, in order to bring CPU time, data .les, management of solutions to a reasonable size. In the current doctoral thesis, the most common finite element reduction methods for large structures are reviewed. Results of case studies are compared between a recently proposed method, herein named DACMAM (Dynamic Analysis in Complex Modal space Acceleration Method), and different condensation methods, namely static or Guyan condensation and dynamic condensation in different vectorial spaces. All these methods are suitable for considering non-classical damping. The reduction method DACMAM consist of a structural modification in the complex modal domain which provides a dynamic response solution for the reduced models. This process allows the selection of a few degrees of freedom that are relevant for the dynamic response of the system. These d.o.f. are the load application points, relevant structural points or points in which it is important to know the response. Consequently, an analysis with structural modifications implies only the calculation of the dynamic response of the selected degrees of freedom added, but with no loss of information. Therefore, mass, stiffness or damping modifications are easily considered as well as new degrees of freedom. Taking into account the size of the equations to be solved, the parameterization of the dynamic solutions is not only possible, but also manageable and controllable due to the easy implementation of the procedure in the standard finite element solvers. In this thesis, the proposed reduction method for large structural models is compared with other published model order reduction methods. The comparison shows and underlines the efficiency of the new method, and veri.es the differences in the response when compared with the response of the full model. The CPU time, the data files and the scope of the parameterization are also addressed.

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The wavelet transform and Lipschitz exponent perform well in detecting signal singularity.With the bridge crack damage modeled as rotational springs based on fracture mechanics, the deflection time history of the beam under the moving load is determined with a numerical method. The continuous wavelet transformation (CWT) is applied to the deflection of the beam to identify the location of the damage, and the Lipschitz exponent is used to evaluate the damage degree. The influence of different damage degrees,multiple damage, different sensor locations, load velocity and load magnitude are studied.Besides, the feasibility of this method is verified by a model experiment.

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We present an optical sensing methodology to estimate the fatigue damage state of structures made of carbon fiber reinforced polymer (CFRP), by measuring variations on the surface roughness. Variable amplitude loads (VAL), which represent realistic loads during aeronautical missions of fighter aircraft (FALSTAFF) have been applied to coupons until failure. Stiffness degradation and surface roughness variations have been measured during the life of the coupons obtaining a Pearson correlation of 0.75 between both variables. The data were compared with a previous study for Constant Amplitude Load (CAL) obtaining similar results. Conclusions suggest that the surface roughness measured in strategic zones is a useful technique for structural health monitoring of CFRP structures, and that it is independent of the type of load applied. Surface roughness can be measured in the field by optical techniques such as speckle, confocal perfilometers and interferometry, among others.

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We conclude that Bet v 1 and Bos d 5 not only structurally mimic human LCN2, but also functionally by their ability to bind iron via siderophores. The apo-forms promote Th2 cells, whereas the holo-forms appear to be immunosuppressive. These results provide for the first time a functional understanding on the principle of allergenicity of major allergens from entirely independent sources, like birch and milk.

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The risk of disease associated with persistent virus infections such as HIV-I, hepatitis B and C, and human T-lymphotropic virus-I (HTLV-I) is strongly determined by the virus load. However, it is not known whether a persistent class I HLA-restricted antiviral cytotoxic T lymphocyte (CTL) response reduces viral load and is therefore beneficial or causes tissue damage and contributes to disease pathogenesis. HTLV-I-associated myelopathy (HAM/TSP) patients have a high virus load compared with asymptomatic HTLV-I carriers. We hypothesized that HLA alleles control HTLV-I provirus load and thus influence susceptibility to HAM/TSP. Here we show that, after infection with HTLV-I, the class I allele HLA-A*02 halves the odds of HAM/TSP (P < 0.0001), preventing 28% of potential cases of HAM/TSP. Furthermore, HLA-A*02+ healthy HTLV-I carriers have a proviral load one-third that (P = 0.014) of HLA-A*02− HTLV-I carriers. An association of HLA-DRB1*0101 with disease susceptibility also was identified, which doubled the odds of HAM/TSP in the absence of the protective effect of HLA-A*02. These data have implications for other persistent virus infections in which virus load is associated with prognosis and imply that an efficient antiviral CTL response can reduce virus load and so prevent disease in persistent virus infections.

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Kinesin is a dimeric motor protein that transports organelles in a stepwise manner toward the plus-end of microtubules by converting the energy of ATP hydrolysis into mechanical work. External forces can influence the behavior of kinesin, and force-velocity curves have shown that the motor will slow down and eventually stall under opposing loads of ≈5 pN. Using an in vitro motility assay in conjunction with a high-resolution optical trapping microscope, we have examined the behavior of individual kinesin molecules under two previously unexplored loading regimes: super-stall loads (>5 pN) and forward (plus-end directed) loads. Whereas some theories of kinesin function predict a reversal of directionality under high loads, we found that kinesin does not walk backwards under loads of up to 13 pN, probably because of an irreversible transition in the mechanical cycle. We also found that this cycle can be significantly accelerated by forward loads under a wide range of ATP concentrations. Finally, we noted an increase in kinesin’s rate of dissociation from the microtubule with increasing load, which is consistent with a load dependent partitioning between two recently described kinetic pathways: a coordinated-head pathway (which leads to stepping) and an independent-head pathway (which is static).

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Using an event-related functional MRI design, we explored the relative roles of dorsal and ventral prefrontal cortex (PFC) regions during specific components (Encoding, Delay, Response) of a working memory task under different memory-load conditions. In a group analysis, effects of increased memory load were observed only in dorsal PFC in the encoding period. Activity was lateralized to the right hemisphere in the high but not the low memory-load condition. Individual analyses revealed variability in activation patterns across subjects. Regression analyses indicated that one source of variability was subjects’ memory retrieval rate. It was observed that dorsal PFC plays a differentially greater role in information retrieval for slower subjects, possibly because of inefficient retrieval processes or a reduced quality of mnemonic representations. This study supports the idea that dorsal and ventral PFC play different roles in component processes of working memory.

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Allostatic load (AL) has been proposed as a new conceptualization of cumulative biological burden exacted on the body through attempts to adapt to life's demands. Using a multisystem summary measure of AL, we evaluated its capacity to predict four categories of health outcomes, 7 years after a baseline survey of 1,189 men and women age 70–79. Higher baseline AL scores were associated with significantly increased risk for 7-year mortality as well as declines in cognitive and physical functioning and were marginally associated with incident cardiovascular disease events, independent of standard socio-demographic characteristics and baseline health status. The summary AL measure was based on 10 parameters of biological functioning, four of which are primary mediators in the cascade from perceived challenges to downstream health outcomes. Six of the components are secondary mediators reflecting primarily components of the metabolic syndrome (syndrome X). AL was a better predictor of mortality and decline in physical functioning than either the syndrome X or primary mediator components alone. The findings support the concept of AL as a measure of cumulative biological burden.

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The association between human immunodeficiency virus type I (HIV-1) RNA load changes and the emergence of resistant virus variants was investigated in 24 HIV-1-infected asymptomatic persons during 2 years of treatment with zidovudine by sequentially measuring serum HIV-1 RNA load and the relative amounts of HIV-1 RNA containing mutations at reverse transcriptase (RT) codons 70 (K-->R), 41 (M-->L), and 215 (T-->Y/F). A mean maximum decline in RNA load occurred during the first month, followed by a resurgence between 1 and 3 months, which appeared independent of drug-resistance. Mathematical modeling suggests that this resurgence is caused by host-parasite dynamics, and thus reflects infection of the transiently increased numbers of CD4+ lymphocytes. Between 3 and 6 months of treatment, the RNA load returned to baseline values, which was associated with the emergence of virus containing a single lysine to arginine amino acid change at RT codon 70, only conferring an 8-fold reduction in susceptibility. Despite the relative loss of RNA load suppression, selection toward mutations at RT codons 215 and 41 continued. Identical patterns were observed in the mathematical model. While host-parasite dynamics and outgrowth of low-level resistant virus thus appear responsible for the loss of HIV-1 RNA load suppression, zidovudine continues to select for alternative mutations, conferring increasing levels of resistance.

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Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

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The Chesapeake Bay is the largest estuary in the United States supporting a complex ecosystem that sustains many habitats and the organisms that depend on them. The bay also supports economic, recreational, and cultural activities to over 16 million people residing in the watershed. Changes within the watershed have caused excessive levels of nutrients, mainly nitrogen and phosphorous, to pollute the bay. The Chesapeake Bay Program, guided by a complex agreement, was created to address these and other issues and oversee the restoration of the bay. The most recent version of this agreement, the Chesapeake 2000, declares its continued commitment to restore the bay with over 100 goals to be met by the year 2010. Reports show that although intensive efforts have been made to promote nutrient reduction, very little reduction has actually resulted. This project described these efforts. The final results reveal obstacles affecting progress, shortcomings to current approaches and possible solutions for future implementation.

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A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

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A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.