54 resultados para performance index

em Deakin Research Online - Australia


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This paper introduces a novel method to detect texture objects from satellite images. First, a hierarchical strategy is developed to extract texture objects according to their roughness. Then, an artificial immune approach is presented to automatically generate segmentation thresholds and texture filters, which are used in the hierarchical strategy. In this approach, texture objects are regarded as antigens, and texture object filters and segmentation thresholds are regarded as antibodies. The clonal selection algorithm inspired by human immune system is employed to evolve antibodies. The population of antibodies is iteratively evaluated according to a statistical performance index corresponding to object detection ability, and evolves into the optimal antibody using the evolution principles of the clonal selection. Experimental results of texture object detection on satellite images are presented to illustrate the merit and feasibility of the proposed method.


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The theory of H/sup /spl infin// optimal control has the feature of minimizing the worst-case gain of an unknown disturbance input. When appropriately modified, the theory can be used to design a "switching" controller that can be applied to insulin injection for blood glucose (BG) regulation. The "switching" controller is defined by a collection of basic insulin rates and a rule that switches the insulin rates from one value to another. The rule employed an estimation of BG from noisy measurements, and the subsequent optimization of a performance index that involves the solution of a "jump" Riccati differential equation and a discrete-time dynamic programming equation. With an appropriate patient model, simulation studies have shown that the controller could correct BG deviation using clinically acceptable insulin delivery rates.

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This paper introduces a novel methodology for object detection using genetic algorithms and morphological processing. The method employs a kind of object oriented structuring element, which are derived using genetic algorithm operating. The population of morphological filters iteratively evaluated according to a statistical performance index corresponding to object extraction ability, and evolves into an optimal structuring elements using the evolution principles of genetic search. Experimental results of object extraction in high resolution satellite images are presented to illustrate the merit and feasibility of the proposed method.

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This paper proposes a new type of algorithm aimed at finding the traditional maximum-likelihood (TML) estimate of the position of a target given time-difference-of-arrival (TDOA) information, contaminated by noise. The novelty lies in the fact that a performance index, akin to but not identical with that in maximum likelihood (ML), is a minimized subject to a number of constraints, which flow from geometric constraints inherent in the underlying problem. The minimization is in a higher dimensional space than for TML, and has the advantage that the algorithm can be very straightforwardly and systematically initialized. Simulation evidence shows that failure to converge to a solution of the localization problem near the true value is less likely to occur with this new algorithm than with TML. This makes it attractive to use in adverse geometric situations.

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Studies of the interrecipient allocation of aid may be categorized threefold. First, there are those that attempt to explain the observed allocation of aid. Second, there are those that seek to describe or evaluate the allocation of aid against normative criteria. Third, there are those that seek to prescribe the interrecipient allocation of aid by calculating the amounts of aid each country should receive, also based on normative criteria. This article looks at the second and third categories of studies. It commences by looking at the different approaches and a descriptive measure used, and then repeats this exercise for the prescriptive literature. It then looks at differences between the prescribed allocations of the different approaches used in the literature. These allocations are then compared with actual allocations and evaluated against various normative criteria. This reveals significant differences, both between prescribed and actual allocations and the evaluations of the different prescriptive approaches.

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This article evaluates the robustness of rankings obtained from composite indices that combine information from two or more components via a weighted sum. It examines the empirical prevalence of robust comparisons using the method proposed by Foster et al. (2010). Indices examined are the Human Development Index (HDI), the Index of Economic Freedom (IEF), and the Environmental Performance Index (EPI). Key theoretical results demonstrate links between the prevalence of robust comparisons, Kendall’s tau rank correlation coefficient, and statistical association across components. Implications for redundancy among index components are also examined.

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This paper examines and analyzes different aggregation algorithms to improve accuracy of forecasts obtained using neural network (NN) ensembles. These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). The predictive performance of these algorithms are evaluated using Australian electricity demand data. The output of the aggregation algorithms of NN ensembles are compared with a Naive approach. Mean absolute percentage error is applied as the performance index for assessing the quality of aggregated forecasts. Through comprehensive simulations, it is found that the aggregation algorithms can significantly improve the forecasting accuracies. The BMA algorithm also demonstrates the best performance amongst aggregation algorithms investigated in this study.

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 An optimisation framework is proposed to enable investors to select the right risk measures in portfolio selection. Verification is deployed by performing experiments in developed markets (e.g., the US stock market), emerging markets (e.g., the South Korean stock market) and global investments. A preselection procedure dealing with large datasets is also introduced to eliminate stocks that have low diversification potential before running the portfolio optimisation model. Portfolios are evaluated by four performance indices, i.e., the Sortino ratio, the Sharpe ratio, the Stutzer performance index, and the Omega measure. Experimental results demonstrate that high performance and also well-diversified portfolios are obtained if modified value-at-risk, variance, or semi-variance is concerned whereas emphasising only skewness, kurtosis or higher moments in general produces low performance and poorly diversified portfolios. In addition, the preselection applied to large datasets results in portfolios that have not only high performance but also high diversification degree.

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Load frequency Control (LFC) is used for many years as part of Automatic Generation Control (AGC) in power system around the world. In a mixed power system, it is usual to find an area regulated by hydro generation interconnected to another area regulated by thermal generation or in combination of both. In the following study, performance of AGC for Thermal, Hydro and Thermal turbine based power system is examined, including how frequency bias setting influences AGC responseand inadvertent interchange. Control performance analysis of three area interconnected systems is simulated and studied through Matlab Simulink software. Integral square error and Integral time absolute error has been used as performance criterion. It is shown that integral timeabsolute error (ITAE) as performance index leads to faster optimization of controller gain.

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Drawing on Michel Foucault’s later genealogies of the Self the paper will illustrate particular dimensions of the increasingly powerful individualizing and normalizing processes shaping the lifeworlds of worker-citizens in a globalizing risk society. Processes that require those who wish to be positively identified as professional, entrepreneurial, resilient, effective, athletic to do particular sorts of work on themselves. Here the paper argues that we can identify the emergence of what we call New Work Ethics. We illustrate this more general argument via an analysis of the ways in which a large Information Technology (IT) organization seeks to produce—via a workplace health and fitness program—employees who imagine themselves as embodying the behaviours and dispositions that mark the person as a corporate athlete. Knowledge of the Self in these terms can, it is promised, enhance the performance of the Self, and the organization.

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Purpose: This study aimed to examine the effect of glycemic index of pre-exercise carbohydrate (CHO) ingestion on exercise metabolism and performance.

Methods: Eight endurance trained men ingested a high glycemic index (HGI), low glycemic index (LGI), or a placebo (CON) meal 45 min before exercise and then cycled for 50 min at 67% V·O2max. Subjects subsequently performed a 15-min self-paced performance ride in which total work (kJ) was recorded.

Results: Plasma glucose concentrations were higher (P < 0.01) after ingestion in HGI compared with LGI and CON (7.53 ± 0.64 vs 5.55 ± 0.21 and 4.65 ± 0.14 mmol·L-1 for HGI, LGI, and CON, respectively, 30 min postprandial; mean ± SE) but declined at the onset of exercise and were lower (P < 0.01) compared with LGI and CON (4.03 ± 0.31 vs 4.64 ± 0.24 and 5.09 ± 0.16 mmol·L-1 for HGI, LGI, and CON respectively; mean ± SE) at 10 min of exercise. Plasma glucose remained depressed (P < 0.01) until 30 min into exercise in HGI compared with other trials. Plasma insulin concentrations were higher (P < 0.01) following ingestion during rest and exercise in HGI compared with LGI and CON. Plasma FFA concentrations were lower (P < 0.05) following ingestion in HGI and LGI compared with CON and higher (P < 0.05) in LGI compared with HGI at the start and end of exercise. RER and CHO oxidation was higher (P < 0.01) in HGI compared with LGI and CON during submaximal exercise. There were no differences in work output during the performance cycle.


Conclusions: These data indicate that pre-exercise CHO feedings with varying glycemic indexes do not affect exercise performance following short term submaximal exercise despite alterations in metabolism.

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The osteogenicity of a given exercise may be estimated by calculating an osteogenic index (OI) consisting of magnitude and rate of strain. Volleyball involves repetitive jumping and requires high power output and thus may be expected to be beneficial to bone and performance. The purpose of the present study was to examine if habitual volleyball playing is reflected in OI. Ten elderly habitual volleyball players [age 69.9 (SD 4.4) years] and ten matched controls volunteered [age 69.7 (4.2) years] as subjects. Distal tibia (d), tibial mid-shaft (50) and femoral neck (F) bone characteristics were measured using pQCT and DXA. To estimate skeletal rigidity, cross-sectional area (ToA50), and compressive (BSId) and bending strength indices (SSImax50) were calculated. Maximal performance was assessed with eccentric ankle plantar flexion, isometric leg press and countermovement jump (CMJ). A fast Fourier transform (FFT) was calculated from the acceleration of the center of mass during the CMJ. Maximal acceleration (MAG) and mean magnitude frequency (MMF) were selected to represent the constituents of OI. OI was calculated as the sum of the products of magnitudes and corresponding frequencies. Volleyball players had 7% larger ToA50 and 37% higher power in CMJ, 15% higher MAG and 36% higher OI (P B 0.047) than the matched controls. No difference was observed in leg press, plantar flexion or the MMF (P C 0.646). In conclusion, habitual volleyball players may be differentiated from their matched peers by their dynamic jumping performance, and the differences are reflected in the magnitude but not rate of loading.

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To investigate the effect of low glycemic index (LGI) carbohydrate meal on subjective, metabolic and physiological responses, and endurance performance in the Ramadan fasted state.