967 resultados para Optimal frame-level timing estimator
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Journal of Bacteriology (Junho 2008) 4272-4280
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This paper analyzes Knowledge Management (KM) as a political activity, made by the great political leaders of the world. We try to inspect if at the macro political level KM is made, and how. The research is interesting because given that we live in a Knowledge society, in the Information Era, it is more or less obvious that the political leaders should also do KM. However we don’t know of any previous study on KM and world leaders and this paper wants to be a first step to fill that gap. As a methodology we use literature review: given this one is a first preliminary study we use data we found in the Internet and other databases like EBSCO. We divide the analysis in two main parts: theoretical ideas first, and an application second. The second part is it self divided in two segments: the past and the present times. We find that rather not surprisingly, KM always was and is pervasive in the activity of the world leaders, and has become more and more diverse has power itself became to be more and more disseminated in the world. The study has the limitation of relying on insights and texts and not on interviews. But we believe it is very interesting to make this kind of analysis and such studies may help improving the democracies in the world.
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This paper presents a model for the simulation of an offshore wind system having a rectifier input voltage malfunction at one phase. The offshore wind system model comprises a variable-speed wind turbine supported on a floating platform, equipped with a permanent magnet synchronous generator using full-power four-level neutral point clamped converter. The link from the offshore floating platform to the onshore electrical grid is done through a light high voltage direct current submarine cable. The drive train is modeled by a three-mass model. Considerations about the smart grid context are offered for the use of the model in such a context. The rectifier voltage malfunction domino effect is presented as a case study to show capabilities of the model. (C) 2015 Elsevier Ltd. All rights reserved.
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Energy efficiency plays an important role to the CO2 emissions reduction, combating climate change and improving the competitiveness of the economy. The problem presented here is related to the use of stand-alone diesel gen-sets and its high specific fuel consumptions when operates at low loads. The variable speed gen-set concept is explained as an energy-saving solution to improve this system efficiency. This paper details how an optimum fuel consumption trajectory based on experimentally Diesel engine power map is obtained.
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A detailed knowledge of the 3-D arrangement and lateral facies relationships of the stacking patterns in coastal deposits is essential to approach many geological problems such as precise tracing of sea level changes, particularly during small scale fluctuations. These are useful data regarding the geodynamic evolution of basin margins and yield profit in oil exploration. Sediment supply, wave-and tidal processes, coastal morphology, and accommodation space generated by eustasy and tectonics govern the highly variable architecture of sedimentary bodies deposited in coastal settings. But these parameters change with time, and erosional surfaces may play a prominent role in areas located towards land. Besides, lateral shift of erosional or even depositional loci very often results in destruction of large parts of the sediment record. Several case studies illustrate some commonly found arrangements of facies and their distinguishing features. The final aim is to get the best results from the sedimentological analysis of coastal units.
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A synthesis about the Neogene and Quaternary of Algarve (Southern Portugal) is presented. New isotopic 87Sr/86Sr ages as well as biostratigraphic data about the Miocene deposits allow to present a new stratigraphic frame for the previously characterized units. The Lagos-Portimão Formation corresponds to deposits of temperate carbonate platform sedimentological type, developed during a long time span (Lower Burdigalian to Upper Serravallian). A major change in sedimentation conditions (carbonate to siliciclastic environments) occurred in the Lower Tortonian with the deposition of yellowish sands. Spongoliths rich in microfossils are represented in Algarve inland. Their age is not well established; calcareous nannofossils indicate the CN5a zone (Upper Serravallian) while foraminifera point out at least Nl6 zone (Lower Tortonian). In the Upper Tortonian, the sedimentation is widespread in Eastern Algarve, related with the Guadalquivir Basin infill. The deposits begin with detrital limestones, locally very rich in Heterostegina, passing to fossiliferous conglomerates and siltstones (Cacela Formation). Coarse-grained conglomerates at Galvana (Faro) pose some age problems. K/Ar age on glauconite indicates 6.72±0.17 Ma. However, glauconites may be reworked from older deposits (Cacela Formation). The Galvana Conglomerate could be related to Pliocene deposits are not well characterized. Olhos de Água sands, with a thin marine intercalation rich in marine vertebrates (fishes, a crocodile, cetaceans, sirenians), may be Upper Pliocene; however, the vertebrates point out to a Serravallian to Tortonian age. 87Sr/86Sr ages on oysters from above the level with vertebrates point out to 3.0(+2.5-1.0) Ma. Similar sand deposits occur at Morgadinho (Luz de Tavira). These sands are overlain by marls, lignite clays, lacustrine limestones and a silty calcareous crust. A small mammals association indicate an age span between Upper Pliocene and Lower Middle Pleistocene (MN17-MN20). A Biharian mammal fauna (Lower Pleistocene) was collected at Algoz in similar deposits. In the present state of knowledge, Morgadinho and Algoz deposits may be correlative.
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A schistosomiasis control program was implemented between 1974/87 in Peri-Peri,. MG (622 inhabitants). Molluscicide (niclosamide) was applied at three monthly intervals in water sources with Biomphalaria glabrata, and individuals eliminating Schistosoma mansoni eggs in the feces were treated annually with oxamniquine. From 1974 to 1983 the control measures were undertaken by staff of the "René Rachou" Research Center FIOCRUZ (CPqRR), and from 1984 to 1987 these measures were included in the Capim Branco basic health network activities. During both periods, the prevalence, incidence, intensity of infection and hepatosplenic form as well as the number of infected snails decreased significantly. The prevalence decreased from 43.5 to 4.4%, the incidence from 19.0 to 2.9%, the overall intensity of S. mansoni from 281 to 87 and of the hepatosplenic form from 5.9 to 0.0%. The results obtained suggest that the municipal management of control measures was as effective as the vertical program conducted by CPqRR staff.
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Modular design is crucial to manage large-scale systems and to support the divide-and-conquer development approach. It allows hierarchical representations and, therefore, one can have a system overview, as well as observe component details. Petri nets are suitable to model concurrent systems, but lack on structuring mechanisms to support abstractions and the composition of sub-models, in particular when considering applications to embedded controllers design. In this paper we present a module construct, and an underlying high-level Petri net type, to model embedded controllers. Multiple interfaces can be declared in a module, thus, different instances of the same module can be used in different situations. The interface is a subset of the module nodes, through which the communication with the environment is made. Module places can be annotated with a generic type, overridden with a concrete type at instance level, and constants declared in a module may have a new value in each instance.
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The formulation of a bending vibration problem of an elastically restrained Bernoulli-Euler beam carrying a finite number of concentrated elements along its length is presented. In this study, the authors exploit the application of the differential evolution optimization technique to identify the torsional stiffness properties of the elastic supports of a Bernoulli-Euler beam. This hybrid strategy allows the determination of the natural frequencies and mode shapes of continuous beams, taking into account the effect of attached concentrated masses and rotational inertias, followed by a reconciliation step between the theoretical model results and the experimental ones. The proposed optimal identification of the elastic support parameters is computationally demanding if the exact eigenproblem solving is considered. Hence, the use of a Gaussian process regression as a meta-model is addressed. An experimental application is used in order to assess the accuracy of the estimated parameters throughout the comparison of the experimentally obtained natural frequency, from impact tests, and the correspondent computed eigenfrequency.
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Journal of Hydraulic Engineering, Vol. 135, No. 11, November 1, 2009
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This paper is about a PV system linked to the electric grid through power converters under cloud scope. The PV system is modeled by the five parameters equivalent circuit and a MPPT procedure is integrated into the modeling. The modeling for the converters models the association of a DC-DC boost with a three-level inverter. PI controllers are used with PWM by sliding mode control associated with space vector modulation controlling the booster and the inverter. A case study addresses a simulation to assess the performance of a PV system linked to the electric grid. Conclusions regarding the integration of the PV system into the electric grid are presented. © IFIP International Federation for Information Processing 2015.
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This paper presents a coordination approach to maximize the total profit of wind power systems coordinated with concentrated solar power systems, having molten-salt thermal energy storage. Both systems are effectively handled by mixed-integer linear programming in the approach, allowing enhancement on the operational during non-insolation periods. Transmission grid constraints and technical operating constraints on both systems are modeled to enable a true management support for the integration of renewable energy sources in day-ahead electricity markets. A representative case study based on real systems is considered to demonstrate the effectiveness of the proposed approach. © IFIP International Federation for Information Processing 2015.
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This paper is on a simulation for offshore wind systems in deep water under cloud scope. The system is equipped with a permanent magnet synchronous generator and a full-power three-level converter, converting the electric energy at variable frequency in one at constant frequency. The control strategies for the three-level are based on proportional integral controllers. The electric energy is injected through a HVDC transmission submarine cable into the grid. The drive train is modeled by a three-mass model taking into account the resistant stiffness torque, structure and tower in the deep water due to the moving surface elevation. Conclusions are taken on the influence of the moving surface on the energy conversion. © IFIP International Federation for Information Processing 2015.
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The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.
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Introdução: A prematuridade constitui um fator de risco para a ocorrência de lesões ao nível do sistema nervoso central, sendo que uma idade gestacional inferior a 36 semanas potencia esse mesmo risco, nomeadamente para a paralisia cerebral (PC) do tipo diplegia espástica. A sequência de movimento de sentado para de pé (SPP), sendo uma das aprendizagens motoras que exige um controlo postural (CP) ao nível da tibiotársica, parece ser uma tarefa funcional frequentemente comprometida em crianças prematuras com e sem PC. Objetivo(s): Descrever o comportamento dos músculos da tibiotársica, tibial anterior (TA) e solear (SOL), no que diz respeito ao timing de ativação, magnitude e co-ativação muscular durante a fase I e início da fase II na sequência de movimento de SPP realizada por cinco crianças prematuras com PC do tipo diplegia espástica e cinco crianças prematuras sem diagnóstico de alteração neuromotoras, sendo as primeiras sujeitas a um programa de intervenção baseado nos princípios do conceito de Bobath – Tratamento do Neurodesenvolvimento (TND). Métodos: Foram avaliadas 10 crianças prematuras, cinco com PC e cinco sem diagnóstico de alterações neuromotoras, tendo-se recorrido à eletromiografia de superfície para registar parâmetros musculares, nomeadamente timings, magnitudes e valores de co-ativação dos músculos TA e SOL, associados à fase I e inico da fase II da sequência de movimento de SPP. Procedeu-se ao registo de imagem de modo a facilitar a avaliação dos componentes de movimento associados a esta tarefa. Estes procedimentos foram realizados num único momento, no caso das crianças sem diagnóstico de alterações neuromotoras e em dois momentos, antes e após a aplicação de um programa de intervenção segundo o Conceito de Bobath – TND no caso das crianças com PC. A estas foi ainda aplicado o Teste da Medida das Funções Motoras (TMFM–88) e a Classificação Internacional da Funcionalidade Incapacidade e Saúde – crianças e jovens (CIF-CJ). Resultados: Através da eletromiografia constatou-se que ambos os grupos apresentaram timings de ativação afastados da janela temporal considerada como ajustes posturais antecipatórios (APAs), níveis elevados de co-ativação, em alguns casos com inversão na ordem de recrutamento muscular o que foi possível modificar nas crianças com PC após o período de intervenção. Nestas, verificou-se ainda que, a sequência de movimento de SPP foi realizada com menor número de compensações e com melhor relação entre estruturas proximais e distais compatível com o aumento do score final do TMFM-88 e modificação positiva nos itens de atividade e participação da CIF-CJ. Conclusão: As crianças prematuras com e sem PC apresentaram alterações no CP da tibiotársica e níveis elevados de co-ativação muscular. Após o período de intervenção as crianças com PC apresentaram modificações positivas no timing e co-ativação muscular, com impacto funcional evidenciado no aumento do score final da TMFM-88 e modificações positivas na CIF-CJ.