964 resultados para statistic
Resumo:
In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.
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Elephant grass (Pennisetum purpureum Schum.), was cut after nine weeks of regrowth and mixed with 10, 20, 30 and 40% of sugar cane bagasse (SCB) with the objective of reducing the moisture content of the ensiled mass. Willing of the grass for eight and twelve hours was used as a comparative treatment. Initial dry matter of the grass (13%) increased in the forage mass to 17, 23, 24 and 27% by the addition of 10, 20, 30 and 40% of the SCB respectively. Wilting for eight and twelve hours increased initial dry matter to 18 and 24% respectively. Buffering capacity of elephant grass was reduced by the addition of 40% of SCB. Clostridium spores in the ensiled mass tended to be lower due to the effect of the two pre-treatments. Initial dry matter and number of spores of Clostridium were negatively correlated although without statistic significance. The addition of SCB reduced (P < 0.0.5) soluble carbohydrates and crude protein percentages in the ensiled mass. It was concluded that wilting is more effective than the addition of SCB in the practice of ensiling elephant grass.
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Studies have been carried out on the heat transfer in a packed bed of glass beads percolated by air at moderate flow rates. Rigorous statistic analysis of the experimental data was carried out and the traditional two parameter model was used to represent them. The parameters estimated were the effective radial thermal conductivity, k, and the wall coefficient, h, through the least squares method. The results were evaluated as to the boundary bed inlet temperature, T-o, number of terms of the solution series and number of experimental points used in the estimate. Results indicated that a small difference in T-o was sufficient to promote great modifications in the estimated parameters and in the statistical properties of the model. The use of replicas at points of high parametric information of the model improved the results, although analysis of the residuals has resulted in the rejection of this alternative. In order to evaluate cion-linearity of the model, Bates and Watts (1988) curvature measurements and the Box (1971) biases of the coefficients were calculated. The intrinsic curvatures of the model (IN) tend to be concentrated at low bed heights and those due to parameter effects (PE) are spread all over the bed. The Box biases indicated both parameters as responsible for the curvatures PE, h being somewhat more problematic. (C) 2000 Elsevier B.V. Ltd. All rights reserved.
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Nonparametric simple-contrast estimates for one-way layouts based on Hodges-Lehmann estimators for two samples and confidence intervals for all contrasts involving only two treatments are found in the literature.Tests for such contrasts are performed from the distribution of the maximum of the rank sum between two treatments. For random block designs, simple contrast estimates based on Hodges-Lehmann estimators for one sample are presented. However, discussions concerning the significance levels of more complex contrast tests in nonparametric statistics are not well outlined.This work aims at presenting a methodology to obtain p-values for any contrast types based on the construction of the permutations required by each design model using a C-language program for each design type. For small samples, all possible treatment configurations are performed in order to obtain the desired p-value. For large samples, a fixed number of random configurations are used. The program prompts the input of contrast coefficients, but does not assume the existence or orthogonality among them.In orthogonal contrasts, the decomposition of the value of the suitable statistic for each case is performed and it is observed that the same procedure used in the parametric analysis of variance can be applied in the nonparametric case, that is, each of the orthogonal contrasts has a chi(2) distribution with one degree of freedom. Also, the similarities between the p-values obtained for nonparametric contrasts and those obtained through approximations suggested in the literature are discussed.
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Image orientation is a basic problem in Digital Photogrammetry. While interior and relative orientations were succesfully automated, the same can not be said about absolute orientation. This process can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features in the object space and its homologous in the image space. A build-in self-diagnosis is also used in this method, that is based on the implementation of data snooping statistic test in the process of spatial resection, using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.
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In this paper, we consider the non-central chi-square chart with two stage samplings. During the first stage, one item of the sample is inspected and, depending on the result, the sampling is either interrupted, or it goes on to the second stage, where the remaining sample items are inspected and the non-central chi-square statistic is computed. The proposed chart is not only more sensitive than the joint (X) over bar and R charts, but operationally simpler too, particularly when appropriate devices, such as go-no-go gauges, can be used to decide if the sampling should go on to the second stage or not. (c) 2004 Elsevier B.V. All rights reserved.
Resumo:
The identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.
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Traditionally, an (X) over bar -chart is used to control the process mean and an R-chart to control the process variance. However, these charts are not sensitive to small changes in process parameters. A good alternative to these charts is the exponentially weighted moving average (EWMA) control chart for controlling the process mean and variability, which is very effective in detecting small process disturbances. In this paper, we propose a single chart that is based on the non-central chi-square statistic, which is more effective than the joint (X) over bar and R charts in detecting assignable cause(s) that change the process mean and/or increase variability. It is also shown that the EWMA control chart based on a non-central chi-square statistic is more effective in detecting both increases and decreases in mean and/or variability.
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The study of the spatial variability of soil attributes under different crop helps the study of changes due the management. This research was carried out to determine spatial variability the particle-size distribution, using of the classic statistic and geostatistics, of a soil cultivated with pasture and native vegetation. Soil samples were collected in the layer 0-0.20m, at the crossing points of a regular grid with 10m-intervals, summing up 64 samples points in each area. In the pasture area the fractions of coarse and total sand presented larger mean values in relation to the native vegetation, and negative correlation with the altitude of the points samples in the two areas. All of the fractions presented moderate to high spatial dependence in the two areas and with the defined still, with exception of the fine sand and the silt in the pasture. Much of this variability occurs as a function of water erosion.
Resumo:
The T-2 and the generalized variance vertical bar S vertical bar charts are used for monitoring the mean vector and the covariance matrix of multivariate processes. In this article, we propose for bivariate processes the use of the T-2 and the VMAX charts. The points plotted on the VMAX chart correspond to the maximum of the sample variances of the two quality characteristics. The reason to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is the user's familiarity with the computation of simple sample variances; we can't say the same with regard to the computation of the generalized variance vertical bar S vertical bar.
Resumo:
In this article, we propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample vat-lances of the two quality characteristics, shortly VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these two variances. The reasons to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar are faster detection of process changes and better diagnostic feature, that is, with the VMAX statistic It is easier to identify the out-of-control variable.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.
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The present study aimed to evaluate the effects of three different stock densities (0.33; 0.67 e 1.00 fish L-1) on freshwater angelfish productive performance reared in aquarium. Fish were fed with commercial diets during 35 days in two diary meals. The experimental design was entirely randomized and for each density were used four replicates. Were evaluated physical-chemical water parameters: temperature, oxygen dissolved concentration and total ammonia concentration and growth performance parameters: weight gain, feed conversion, specific growth rate, final standard length, conduction factor and length uniformity. Results were submitted to variance analysis and means were compared by Tukey's test (alpha = 0.05), it was used the statistic program ESTAT 2.0. Mortality was not observed in any tested density. on physical-chemical water parameters, total ammonia level increased significantly with stock density increasing, but they did not showed clinical signs of ammonia toxicity. As there were no significant differences between treatments, stock density 1.00 fish L-1 is the most indicated because it allows higher production.
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This paper analyses the dew occurrence in Botucatu, Sao Paulo State, Brazil, in the period from 1971 to 1984. The phenomenon was observed on the grass plot of the Climatological Station in the 'Presidente Medici' Experimental Farm. The station is installed on soil 'Terra Roxa Estruturada', on a middle slope, declivity of 8% and east exposure. Days with dew were summed for the following periods: month, year, season, no rainy period and rainy period. For each period the following values were calculated: mean, mean standard errors and mean confidence interval. Also the absolute extreme values and the amplitude of variation were determined. The confidence interval of the mean were calculated by the 't' statistic, at the level of 5% of error probability. The means were compared by using the 't' statistic, at the level of 5% of error probability. The following table of values corresponds to the regime of dew occurrence in Botucatu, expressed in number of days with dew. The dew occurrence regime in Botucatu was analysed comparatively with the regime at Itatinga, in Sao Paulo State and with the regime of Rio Grande, in Rio Grande do Sul State. -English summary