814 resultados para swd: Benchmark


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Geomagnetic activity has long been known to exhibit approximately 27 day periodicity, resulting from solar wind structures repeating each solar rotation. Thus a very simple near-Earth solar wind forecast is 27 day persistence, wherein the near-Earth solar wind conditions today are assumed to be identical to those 27 days previously. Effective use of such a persistence model as a forecast tool, however, requires the performance and uncertainty to be fully characterized. The first half of this study determines which solar wind parameters can be reliably forecast by persistence and how the forecast skill varies with the solar cycle. The second half of the study shows how persistence can provide a useful benchmark for more sophisticated forecast schemes, namely physics-based numerical models. Point-by-point assessment methods, such as correlation and mean-square error, find persistence skill comparable to numerical models during solar minimum, despite the 27 day lead time of persistence forecasts, versus 2–5 days for numerical schemes. At solar maximum, however, the dynamic nature of the corona means 27 day persistence is no longer a good approximation and skill scores suggest persistence is out-performed by numerical models for almost all solar wind parameters. But point-by-point assessment techniques are not always a reliable indicator of usefulness as a forecast tool. An event-based assessment method, which focusses key solar wind structures, finds persistence to be the most valuable forecast throughout the solar cycle. This reiterates the fact that the means of assessing the “best” forecast model must be specifically tailored to its intended use.

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Using a linear factor model, we study the behaviour of French, Germany, Italian and British sovereign yield curves in the run up to EMU. This allows us to determine which of these yield curves might best approximate a benchmark yield curve post EMU. We find that the best approximation for the risk free yield is the UK three month T-bill yield, followed by the German three month T-bill yield. As no one sovereign yield curve dominates all others, we find that a composite yield curve, consisting of French, Italian and UK bonds at different maturity points along the yield curve should be the benchmark post EMU.

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The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.

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Arbuscular mycorrhizal fungi (AMF) are crucial to the functioning of the plant–soil system, but little is known about the spatial structuring of AMF communities across landscapes modified by agriculture. AMF community composition was characterized across four sites in the highly cleared south-western Australian wheatbelt that were originally dominated by forb-rich eucalypt woodlands. Environmentally induced spatial structuring in AMF composition was examined at four scales: the regional scale associated with location, the site scale associated with past management (benchmark woodlands with no agricultural management history, livestock grazing, recent revegetation), the patch scale associated with trees and canopy gaps, and the fine scale associated with the herbaceous plant species beneath which soils were sourced. Field-collected soils were cultured in trap pots; then, AMF composition was determined by identifying spores and through ITS1 sequencing. Structuring was strongest at site scales, where composition was strongly related to prior management and associated changes in soil phosphorus. The two fields were dominated by the genera Funneliformis and Paraglomus, with little convergence back to woodland composition after revegetation. The two benchmark woodlands were characterized by Ambispora gerdemannii and taxa from Gigasporaceae. Their AMF communities were strongly structured at patch scales associated with trees and gaps, in turn most strongly related to soil N. By contrast, there were few patterns at fine scales related to different herbaceous plant species, or at regional scales associated with the 175 km distance between benchmark woodlands. Important areas for future investigation are to identify the circumstances in which recolonization by woodland AMF may be limited by fungal propagule availability, reduced plant diversity and/or altered chemistry in agricultural soils.

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The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.

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Este trabalho estuda o diferencial de retorno entre fundos de ações com benchmark em índices de renda fixa e fundos de ações com benchmark em índices de renda variável. A escolha de um índice de renda fixa como benchmark para um FIA, em média tende a ser pior para o cotista, pois gera um potencial de ganho financeiro para o gestor não associado ao real valor por ele criado. Portanto, como a remuneração dos gestores através da taxa de performance depende em parte do benchmark escolhido, fundos com benchmark em renda fixa deveriam apresentar melhores desempenhos a fim de compensarem seus cotistas por este custo. Os resultados encontrados sugerem que os gestores de fundos com benchmark em renda fixa obtêm um retorno líquido de taxas de performance e administração superior para seus cotistas e também apresentam uma menor correlação com o Índice Bovespa.

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A globalização dos mercados, aliado à saída da intervenção governamental da cadeia produtiva do leite e a estabilização da economia do País a partir de 1990, ocasionou grandes modificações nos diferentes segmentos do sistema agroindustrial do leite. Assim, acompanhar o progresso tecnológico da indústria processadora passou a exigir um posicionamento mais sofisticado do setor produtivo, sendo necessário à realização de novos investimentos que, além de apresentarem maior capacidade de resposta à produtividade e à qualidade da matériaprima, passassem a garantir melhores condições de competição tanto à indústria como para o setor primário. Desta forma, com a intenção de auxiliar o setor produtivo a se profissionalizar na atividade leiteira, a Avipal Alimentos S.A. implementou o Sistema Benchmarking no ano de 2000, o qual serviu como estratégia para melhorar o desempenho técnico e econômico das Unidades Produtoras do estado do Rio Grande do Sul. Dentro deste contexto, o presente trabalho tem como objetivo avaliar a evolução dos coeficientes de desempenho técnico e econômico das Unidades Produtoras benchmark que participaram dos três períodos de análise do Sistema Benchmarking. Para tanto, foi realizado um estudo de caráter descritivo e exploratório, o qual possibilitou avaliar a pertinência e os efeitos da técnica de benchmarking sobre o setor primário da atividade leiteira. Após esta avaliação, concluiu-se que a técnica de benchmarking tem exercido um papel fundamental para o processo de tomada de decisão e gestão das Unidades Produtoras Esta técnica tem auxiliado os Produtores Benchmark a medir o grau de eficiência da atividade leiteira, bem como a detectar os pontos fracos do sistema produtivo. A divulgação das informações obtidas através da identificação das Unidades Produtoras benchmark tem proporcionado às demais Unidades Produtoras a copiarem as práticas, processos, procedimentos e indicadores apontados como ponto de referência para o alcance de um melhor desempenho na exploração leiteira. Além disso, este conhecimento poderá auxiliar as instituições responsáveis pelo fornecimento de assistência técnica, a reformular seus planos de ação e, desta forma, melhor atender as necessidades do setor primário. Os órgãos governamentais, as cooperativas, os laticínios, assim como os demais envolvidos com a cadeia produtiva do leite, também poderão direcionar suas competências para o fortalecimento das atividades desempenhadas pelo setor produtivo.

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Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

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In the Spring of 2009, the University of Nebraska Panhandle Research and Extension Center was contacted by a representative from the Institute of Farm Economics at the Johann Heinrich von Thunen Institute (vTI) in Braunschweig, Germany. In the initial meeting, a partnership was arranged to provide Western Nebraska irrigated economic data for the Agri Benchmark project operated by vTI, with the University of Nebraska receiving access to the worldwide data set that exists within the project. This relationship has grown over the past 18 months to include a number of other opportunities.

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Studio critico e bibliografico sullo stato dell'arte nel campo dei Database con valori incerti e sperimentazione e benchmark con il DBMS Orion utilizzando dataset realistici creati artificialmente.

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Il software Smart-M3, ereditato dal progetto europeo SOFIA, conclusosi nel 2011, permette di creare una piattaforma d'interoperabilità indipendente dal tipo di dispositivi e dal loro dominio di utilizzo e che miri a fornire un Web Semantico di informazioni condivisibili fra entità software e dispositivi, creando ambienti intelligenti e collegamenti tra il mondo reale e virtuale. Questo è un campo in continua ascesa grazie al progressivo e regolare sviluppo sia della tecnologia, nell'ambito della miniaturizzazione dei dispositivi, che delle potenzialità dei sistemi embedded. Questi sistemi permettono, tramite l'uso sempre maggiore di sensori e attuatori, l'elaborazione delle informazioni provenienti dall’esterno. È evidente, come un software di tale portata, possa avere una molteplicità di applicazioni, alcune delle quali, nell’ambito della Biomedica, può esprimersi nella telemedicina e nei sistemi e-Heath. Per e-Health si intende infatti l’utilizzo di strumenti basati sulle tecnologie dell'informazione e della comunicazione, per sostenere e promuovere la prevenzione, la diagnosi, il trattamento e il monitoraggio delle malattie e la gestione della salute e dello stile di vita. Obiettivo di questa tesi è fornire un set di dati che mirino ad ottimizzare e perfezionare i criteri nella scelta applicativa di tali strutture. Misureremo prestazioni e capacità di svolgere più o meno velocemente, precisamente ed accuratamente, un particolare compito per cui tale software è stato progettato. Ciò si costruisce sull’esecuzione di un benchmark su diverse implementazioni di Smart-M3 ed in particolare sul componente centrale denominato SIB (Semantic Information Broker).