Using error bounds to compare aggregated generalized transportation models

A comparative study of aggregation error bounds for the generalized transportation problem is presented. A priori and a posteriori error bounds were derived and a computational study was performed to (a) test the correlation between the a priori, the a posteriori, and the actual error and (b) quantify the difference of the error bounds from the actual error. Based on the results we conclude that calculating the a priori error bound can be considered as a useful strategy to select the appropriate aggregation level. The a posteriori error bound provides a good quantitative measure of the actual error.

An adaptive chart for monitoring the process mean and variance

Traditionally, an (X) over bar chart is used to control the process mean and an R chart is used to control the process variance. However, these charts are not sensitive to small changes in the process parameters. The adaptive ($) over bar and R charts might be considered if the aim is to detect small disturbances. Due to the statistical character of the joint (X) over bar and R charts with fixed or adaptive parameters, they are not reliable in identifing the nature of the disturbance, whether it is one that shifts the process mean, increases the process variance, or leads to a combination of both effects. In practice, the speed with which the control charts detect process changes may be more important than their ability in identifying the nature of the change. Under these circumstances, it seems to be advantageous to consider a single chart, based on only one statistic, to simultaneously monitor the process mean and variance. In this paper, we propose the adaptive non-central chi-square statistic chart. This new chart is more effective than the adaptive (X) over bar and R charts in detecting disturbances that shift the process mean, increase the process variance, or lead to a combination of both effects. Copyright (c) 2006 John Wiley & Sons, Ltd.

Synthetic control chart for monitoring the pprocess mean and variance

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.

Modelo de Gompertz com sazonalidade e autocorrelação nos erros para ajuste do crescimento ponderal em vaca leiteira

In recent work (Kroll, 1990) on dairy cattle growth using its monthly weights, a Gompertz function, first considering the autocorrelated error structure, and second, the independent error structure, was fitted. The last explained 25% more of the total variance than the former. In this work, a Gompertz function was fitted with autocorrelated error structure adding seasonality to the model. This was suggested taking into account the time series autocorrelation function. In order to estimate the six parameters, an iterative procedure was used, employing a matrix X = [G\S], where G is the usual matrix for fitting the Gompertz function, and S is a 0s, 1s, -1s matrix necessary to take into account seasonality. With this model, the adjustment was better in terms of the coefficient determination.

Difference variance dispersion graphs for comparing response surface designs with applications in food technology

Variance dispersion graphs have become a popular tool in aiding the choice of a response surface design. Often differences in response from some particular point, such as the expected position of the optimum or standard operating conditions, are more important than the response itself. We describe two examples from food technology. In the first, an experiment was conducted to find the levels of three factors which optimized the yield of valuable products enzymatically synthesized from sugars and to discover how the yield changed as the levels of the factors were changed from the optimum. In the second example, an experiment was conducted on a mixing process for pastry dough to discover how three factors affected a number of properties of the pastry, with a view to using these factors to control the process. We introduce the difference variance dispersion graph (DVDG) to help in the choice of a design in these circumstances. The DVDG for blocked designs is developed and the examples are used to show how the DVDG can be used in practice. In both examples a design was chosen by using the DVDG, as well as other properties, and the experiments were conducted and produced results that were useful to the experimenters. In both cases the conclusions were drawn partly by comparing responses at different points on the response surface.

X charts with supplementary samples to control the mean and variance

A standard X chart for controlling a process takes regular individual observations, for instance every half hour. This article proposes a modification of the X chart that allows one to take supplementary samples. The supplementary sample is taken (and the (X) over bar and R values computed) when the current value of X falls outside the control limits. With the supplementary sample, the signal of out-of-control is given by an (X) over bar value outside the (X) over bar chart's control limits or an R value outside the R chart's control limit. The proposed chart is designed to hold the supplementary sample frequency, during the in-control period, as low as 5% or less. In this context, the practitioner might prefer to verify an out-of-control condition by simply comparing the (X) over bar and R values with the control limits. In other words, without plotting the (X) over bar and R points. The X chart with supplementary samples has two major advantages when compared with the standard (X) over bar and A charts: (a) the user will be plotting X values instead of (X) over bar and R values; (b) the shifts in the process mean and/or changes in the process variance are detected faster.

Error function approximations of interest in electrochemistry.

The error function is present in several equations describing eletrode processes. But, only approximations of this function are used. In this work, these and other approximations are studied and evaluated according to precision.

Effects of direction and curvature on variable error pattern of reaching movements

A number of studies have analyzed various indices of the final position variability in order to provide insight into different levels of neuromotor processing during reaching movements. Yet the possible effects of movement kinematics on variability have often been neglected. The present study was designed to test the effects of movement direction and curvature on the pattern of movement variable errors. Subjects performed series of reaching movements over the same distance and into the same target. However, due either to changes in starting position or to applied obstacles, the movements were performed in different directions or along the trajectories of different curvatures. The pattern of movement variable errors was assessed by means of the principal component analysis applied on the 2-D scatter of movement final positions. The orientation of these ellipses demonstrated changes associated with changes in both movement direction and curvature. However, neither movement direction nor movement curvature affected movement variable errors assessed by area of the ellipses. Therefore it was concluded that the end-point variability depends partly, but not exclusively, on movement kinematics.

Fatores genéticos e de Meio na idade ao primeiro parto de caprinos leiteiros

Data on age at first kidding (IPP) were collected on seven farms in the Brazilian Southeastern region which explored breds. Least squares (LS) were used to evaluate the effects of environmental factors and to estimate variance components, and the derivative-free restricted maximum likelihood (DFREML) method was used to estimate the variance components of IPP and to genetically evaluate the goats used in the southest region of Brazil. The LS mean and standard error of IPP were 607.18 +/- 17.09 days. The interaction of year x kidding season had a significantly influenced IPP, indicating that management conditions varied among the seasons within each specific year, with a direct influence on body weight which is the main criterion adopted by farmers to decide when the animal is ready to breed. The effect of farm-breed combination influenced the IPP. The compararison among levels of farm-breed were done by cluster analysis. The results indicated that the individual goat management within each farm had a greater influence than breed, since goats of different breeds showed high and similar values on those farms having a high mean IPP. Heritability estimates obtained by LS using intraclass correlations among paternal half-sibs and those obtained by REML were 0.220 and 0.369, respectively.

Validity and reliability of the Portuguese version of Mandibular Function Impairment Questionnaire

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monitoring the process mean and variance using a synthetic control chart with two-stage testing

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effect of juvenility on cutting propagation of red pitaya

Introduction. Pitaya (Hylocereus undatus) is an exotic fruit species little known in Brazil and which needs basic studies about plant nutrition, propagation and physiology. Emphasizing the co-existence of juvenile and adult stages in the pitaya canopy, the plant is generally propagated by cuttings. Materials and methods. A completely randomized design with four treatments and five replications was adopted. Each treatment was represented by the part of the canopy from which the cutting was taken ( upper, middle and lower cutting and cuttings from young plants). The following variables were registered: % cuttings with roots, % of live cuttings, root density, root diameter, root area, root length and root dry mass. Results were submitted to variance analyses, Tukey's test at 0.01 probability error and simple correlation analysis. Results and discussion. The results indicated that the position from which the cutting is taken had a quantitative effect on rooting formation of pitaya cuttings. Juvenile cuttings presented 35% more cuttings with roots than adult cuttings. Root density, root area, root length and root dry mass depended on juvenility, the highest results being registered for juvenile cuttings, independently of the variable. Conclusion. Juvenile and adult stages co-exist in the pitaya canopy. Juvenility is an important rooting factor for red pitaya cuttings.

Use of the Normalized Absorbance Ratio as an Internal Standardization Approach To Minimize Measurement Error in Enzyme-Linked Immunosorbent Assays for Diagnosis of Human Papillomavirus Infection

The serological detection of antibodies against human papillomavirus (HPV) antigens is a useful tool to determine exposure to genital HPV infection and in predicting the risk of infection persistence and associated lesions. Enzyme-linked immunosorbent assays (ELISAs) are commonly used for seroepidemiological studies of HPV infection but are not standardized. Intra-and interassay performance variation is difficult to control, especially in cohort studies that require the testing of specimens over extended periods. We propose the use of normalized absorbance ratios (NARs) as a standardization procedure to control for such variations and minimize measurement error. We compared NAR and ELISA optical density (OD) values for the strength of the correlation between serological results for paired visits 4 months apart and HPV-16 DNA positivity in cervical specimens from a cohort investigation of 2,048 women tested with an ELISA using HPV-16 virus-like particles. NARs were calculated by dividing the mean blank-subtracted (net) ODs by the equivalent values of a control serum pool included in the same plate in triplicate, using different dilutions. Stronger correlations were observed with NAR values than with net ODs at every dilution, with an overall reduction in nonexplained regression variability of 39%. Using logistic regression, the ranges of odds ratios of HPV-16 DNA positivity contrasting upper and lower quintiles at different dilutions and their averages were 4.73 to 5.47 for NARs and 2.78 to 3.28 for net ODs, with corresponding significant improvements in seroreactivity-risk trends across quintiles when NARs were used. The NAR standardization is a simple procedure to reduce measurement error in seroepidemiological studies of HPV infection.

Multivariated variance analysis applied to biological experiments: An analysis with curves of rats teeth growth as influenced by colchicine

The evaluation of the growth of incisor teeth of rats as influenced by colchicine (doses of 25, 50, 100 and 200 μg/kg) injected during 10 and 18 days is performed using a multivariated variance analysis, which allowed a global view of the results, showing that: there are differences in the growth of teeth of control group (untreated rats) and those treated with colchicine, in the measurements made at the 4th, 7th and 10th days of experiment); there is no difference in the growth of the teeth between the groups treated during 10 and 18 days, except in the measurements made at the 7th day; there is no influence of the doses of colchicine in the group treated during 10 days and in the group treated during 18 days - only at the 7th day is observed an influence of the doses used; and there was no significant interaction between treatment and days of measurement, showing the similarity of the groups during the experiment.

The variance of the index (R) of aggregation of Clark and Evans

The exact formula for the variance of the Index (R) of aggregation of Clark and Evans is derived. Due to the fact that R is a dimensionless number, its variance is independent of population density, being only a function of the sample size and so can be manipulated. © 1985 Springer-Verlag.