984 resultados para load balancing


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Sex roles during incubation vary dramatically in socially monogamous shorebirds. The "incubator conspicuousness" hypothesis posits that, for biparentally incubating and sexually dimorphic birds, the more conspicuous sex should incubate when visually foraging predators are inactive, and in many ecosystems this is at night. Therefore, sexually monomorphic species should share incubation equitably throughout the day and night. We examined incubation patterns in Masked Lapwings Vanellus miles and found that the contribution of the sexes to incubation was equitable. Another measure of incubation behavior, bout duration, was similar between the sexes; male bout durations were slightly shorter than for females. This finding is consistent with the predictions of the incubator conspicuousness hypothesis, although other processes may also explain equitable care.

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This thesis examines the parliamentary passage, implementation and ongoing scrutiny of Victoria’s banning notice provisions. Underlying political assumptions and justifications are explored to reveal how banning notices exemplify a move towards police-imposed discretionary justice, which undermines individual rights and reconfigures the notion of balance in the criminal justice system.

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Purpose – The purpose of this paper is to investigate the alternative study load measures (dichotomous full-time/part-time classification and the number of units enrolled) and their association to student performance by using student data from a final year accounting unit in a large Australian university.

Design/methodology/approach – Using regression analysis, the authors compare the two measures to ascertain the explanatory power of the two approaches in explaining student performance.

Findings – A positive association is found between study loads and student performance when using the “number of units enrolled” measure. This relationship was not found when the dichotomous measure (full-time vs part-time) was used. The results suggest that a scaled measure of study loads is a better measure compared to a binary (dichotomous) measure.

Research limitations/implications – The study will assist future researchers to better control for study loads, and also to gain a better understanding of the association between study loads and student performance. This may possibly assist educational institutions and academics to use a more appropriate pedagogical design in the structure of courses when determining study load allocations across the different cohorts.

Practical implications – This study will help in methodology of future researchers controlling for study loads and student performance.
Originality/value – The study adds to existing literature by providing an alternate study load measure in methodology for controlling for student performance.

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This review article aims to evaluate a proposed maximum acceptable work duration model for load carriage tasks. It is contended that this concept has particular relevance to physically demanding occupations such as military and firefighting. Personnel in these occupations are often required to perform very physically demanding tasks, over varying time periods, often involving load carriage. Previous research has investigated concepts related to physiological workload limits in occupational settings (e.g. industrial). Evidence suggests however, that existing (unloaded) workload guidelines are not appropriate for load carriage tasks. The utility of this model warrants further work to enable prediction of load carriage durations across a range of functional workloads for physically demanding occupations. If the maximum duration for which personnel can physiologically sustain a load carriage task could be accurately predicted, commanders and supervisors could better plan for and manage tasks to ensure operational imperatives were met whilst minimising health risks for their workers.

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This paper presents a novel design of interval type-2 fuzzy logic systems (IT2FLS) by utilizing the theory of extreme learning machine (ELM) for electricity load demand forecasting. ELM has become a popular learning algorithm for single hidden layer feed-forward neural networks (SLFN). From the functional equivalence between the SLFN and fuzzy inference system, a hybrid of fuzzy-ELM has gained attention of the researchers. This paper extends the concept of fuzzy-ELM to an IT2FLS based on ELM (IT2FELM). In the proposed design the antecedent membership function parameters of the IT2FLS are generated randomly, whereas the consequent part parameters are determined analytically by the Moore-Penrose pseudo inverse. The ELM strategy ensures fast learning of the IT2FLS as well as optimality of the parameters. Effectiveness of the proposed design of IT2FLS is demonstrated with the application of forecasting nonlinear and chaotic data sets. Nonlinear data of electricity load from the Australian National Electricity Market for the Victoria region and from the Ontario Electricity Market are considered here. The proposed model is also applied to forecast Mackey-glass chaotic time series data. Comparative analysis of the proposed model is conducted with some traditional models such as neural networks (NN) and adaptive neuro fuzzy inference system (ANFIS). In order to verify the structure of the proposed design of IT2FLS an alternate design of IT2FLS based on Kalman filter (KF) is also utilized for the comparison purposes.

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An expedited permitting area has been created to facilitate the development of wind power projects in Maine. The purpose of this project was to investigate the impact of removing areas of conservation interest from the expedited permitting area. We found that the removal of these areas impacts the total wind potential of the state, in an amount proportional to the size of the area removed. The impact on the total wind potential ranged from 0.46-29.0% decrease, depending on the calculation scenario used. These findings may have implications for future policy decisions concerning wind power development.

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The presented work deals with the calibration of a 2D numerical model for the simulation of long term bed load transport. A settled basin along an alpine stream was used as a case study. The focus is to parameterise the used multi fractional transport model such that a dynamically balanced behavior regarding erosion and deposition is reached. The used 2D hydrodynamic model utilizes a multi-fraction multi-layer approach to simulate morphological changes and bed load transport. The mass balancing is performed between three layers: a top mixing layer, an intermediate subsurface layer and a bottom layer. Using this approach bears computational limitations in calibration. Due to the high computational demands, the type of calibration strategy is not only crucial for the result, but as well for the time required for calibration. Brute force methods such as Monte Carlo type methods may require a too large number of model runs. All here tested calibration strategies used multiple model runs utilising the parameterization and/or results from previous run. One concept was to reset to initial bed elevations after each run, allowing the resorting process to convert to stable conditions. As an alternative or in combination, the roughness was adapted, based on resulting nodal grading curves, from the previous run. Since the adaptations are a spatial process, the whole model domain is subdivided in homogeneous sections regarding hydraulics and morphological behaviour. For a faster optimization, the adaptation of the parameters is made section wise. Additionally, a systematic variation was done, considering results from previous runs and the interaction between sections. The used approach can be considered as similar to evolutionary type calibration approaches, but using analytical links instead of random parameter changes.

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This paper studies the electricity load demand behavior during the 2001 rationing period, which was implemented because of the Brazilian energetic crisis. The hourly data refers to a utility situated in the southeast of the country. We use the model proposed by Soares and Souza (2003), making use of generalized long memory to model the seasonal behavior of the load. The rationing period is shown to have imposed a structural break in the series, decreasing the load at about 20%. Even so, the forecast accuracy is decreased only marginally, and the forecasts rapidly readapt to the new situation. The forecast errors from this model also permit verifying the public response to pieces of information released regarding the crisis.

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A resposta da goiabeira à calagem e à adubação pode ser monitorada por análises de tecido vegetal. O perfil nutricional é definido em relação a padrões de teores de nutrientes. No entanto, os teores de nutrientes-padrão são constantemente criticados por não considerarem as interações que ocorrem entre nutrientes e por gerarem tendências numéricas, decorrentes da redundância dos dados, da dependência de escala e da distribuição não normal. As técnicas de análise composicional de dados podem controlar esses dados tendenciosos, equilibrando os grupos de nutrientes, tais como os envolvidos na calagem e na adubação. A utilização das relações log isométricas (ilr) ortonormais, sequencialmente dispostas, evita tendências numéricas inerentes aos dados de composição. Os objetivos do trabalho foram relacionar o balanço de nutrientes dos tecidos vegetais com a produção de goiabeiras em pomares de 'Paluma' diferentemente corrigidos e adubados, e ajustar os atuais padrões de nutrientes com a faixa de equilíbrio das goiabeiras mais produtivas. Um experimento de calagem de sete anos e três, experimentos de três anos com doses de N, P2O5 e K2O, foram conduzidos em pomares de goiabeiras 'Paluma' em um Latossolo Vermelho-Amarelo. Os teores de N, P, K, Ca e Mg na planta foram monitorados anualmente. Selecionaram-se os balanços [N, P, K | Ca, Mg], [N, P | K], [N | P] e [Ca | Mg] para separar os efeitos da calagem (Ca-Mg) e dos fertilizantes (N-K) nos balanços de macronutrientes. Os balanços foram mais influenciados pela calagem do que pela fertilização. A produtividade das goiabeiras e seu balanço nutricional permitiram a definição de faixas de equilíbrio de nutrientes e sua validação com as faixas de concentrações críticas atualmente utilizadas no Brasil e combinadas em coordenadas ilr.

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Present work proposed to map and features the wear mechanisms of structural polymers of engineering derived of the sliding contact with a metallic cylindrical spindle submitted to eccentricity due to fluctuations in it is mass and geometric centers. For this it was projected and makes an experimental apparatus from balancing machine where the cylindrical counterbody was supported in two bearings and the polymeric coupon was situated in a holder with freedom of displacement along counterbody. Thus, the experimental tests were standardized using two position of the two bearings (Fixed or Free) and seven different positions along the counterbody, that permit print different conditions to the stiffness from system. Others parameters as applied normal load, sliding velocity and distance were fixed. In this investigation it was used as coupon two structural polymers of wide quotidian use, PTFE (polytetrafluroethylene) and PEEK (poly-ether-ether-ketone) and the AISI 4140 alloy steel as counterbody. Polymeric materials were characterized by thermal analysis (thermogravimetric, differential scanning calorimetry and dynamic-mechanical), hardness and rays-X diffractometry. While the metallic material was submitted at hardness, mechanical resistance tests and metallographic analysis. During the tribological tests were recorded the heating response with thermometers, yonder overall velocity vibration (VGV) and the acceleration using accelerometers. After tests the wear surface of the coupons were analyzed using a Scanning Electronic Microscopy (SEM) to morphological analysis and spectroscopy EDS to microanalysis. Moreover the roughness of the counterbody was characterized before and after the tribological tests. It was observed that the tribological response of the polymers were different in function of their distinct molecular structure. It were identified the predominant wear mechanisms in each polymer. The VGV of the PTFE was smaller than PEEK, in the condition of minimum stiffness, in function of the higher loss coefficient of that polymer. Wear rate of the PTFE was more of a magnitude order higher than PEEK. With the results was possible developed a correlation between the wear rate and parameter (E/ρ)1/2 (Young modulus, E, density, ρ), proportional at longitudinal elastic wave velocity in the material.

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The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.

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A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

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In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)