Determination of recovery effort for a probabilistic recovery system under various inventory control policies

In this study we investigate the desired level of recovery under various inventory control policies when the success of recovery is probabilistic. All the used and returned items go into a recovery process that is modelled as a single stage operation. The recovery effort is represented by the expected time spent for it. The effect of increasing recovery effort on the success probability together with unit cost of the operation is included by assuming general forms of dependencies. Alternative to recovered items, demand is satisfied by brand-new items. Four inventory control policies that differ in timing of and information used in purchasing decision are proposed. The objective is to find the recovery level together with inventory control parameter that minimize the long-run average total cost. A numerical study covering a wide range of system parameters is carried out. Finally computational results are presented with their managerial implications.     

Let Me Go: The Influences of Crawling Experience and Temperament on the Development of Anger Expression

Infants’ emerging ability to move independently by crawling is associated with changes in multiple domains, including an increase in expressions of anger in situations that block infants’ goals, but it is unknown whether increased anger is specifically because of experience with being able to move autonomously or simply related to age. To examine the influence of locomotion on developmental change in anger, infants’ (N = 20) anger expressions during an arm restraint procedure were observed longitudinally at a precrawling baseline assessment and 2 and 6 weeks after the onset of crawling. Infant age at each crawling stage was unrelated to the frequency of anger expressed in response to arm restraint. At 6 weeks postcrawling onset, infants whose mothers rated them as temperamentally higher in distress to limitations, compared with those rated lower, showed a greater increase in the frequency of anger expressed during the arm restraint relative to earlier assessments and took longer to reduce the frequency of anger expressed when no longer restrained. Findings suggest that experience with autonomous crawling has an effect on anger expression, independent of age, and that a temperamental tendency to become distressed by limitations may exacerbate the effect of crawling on anger expression.     

Too Scared or Too Capable? Why Do College Students Stay Away from the H1N1 Vaccine?

Although college students were among the populations that had the highest frequency of infection for H1N1 influenza, only 8% of them received H1N1 vaccine this past flu season nationwide. During the peak of this pandemic, information about H1N1 vaccine was widely available. However, knowledge test and behavioral data indicated that most college students were not equipped with basic facts about H1N1 and the H1N1 vaccine. To investigate socio‐psychological factors that might have deterred this high‐risk population from learning about and getting the H1N1 vaccine, this study tested the utility of a risk information seeking model in addressing this health communication problem. Data collected from an online survey of 371 college students showed that respondents seemed to overestimate how much they knew about the vaccine. Risk information seeking, however, positively influenced their intentions to get the vaccine. Results suggested that to communicate effectively to this population, it is important to emphasize the difference between perceived knowledge and actual knowledge, monitor emotional responses to potential risks, and promote getting flu vaccination as a socially desirable behavior.     

Viewing the child as a participant within context

This paper explores tensions between the social nature of learning and the current emphasis upon individual support. The paper contrasts the focus upon context in discussions with parents and practitioners, with the focus upon the individual within formal and informal written documents. The analysis is partly situated within the first author’s experiences as a parent researcher, drawing additionally upon ethnographic research carried out with families involved in early intervention, including an evaluation of over 150 pages of documentation provided by a parent. It identifies the need for assessment and evaluation to focus upon and record the broad range of context that influences learning.     

Evaluation of scheduling strategies for a dynamic job shop in a tool-shared,flexible manufacturing environment

A two-phase approach is used to examine the impact of job scheduling rules and tool selection policies for a dynamic job shop system in a tool-shared, flexible manufacturing environment. The first phase develops a generalized simulation model and analyses 'simple' job scheduling rules and tool selection policies under various operating scenarios. The results from this investigation are then used to develop and analyse various bi-criteria rules in the second phase of this study. The results show that the scheduling rules have the most significant impact on system performance, particularly at high shop load levels. Tool selection policies affect some of the performance measures, most notably, proportion of tardy jobs, to a lesser degree. Higher machine utilizations can be obtained at higher tool duplication levels but at the expense of increased tooling costs and lower tool utilization. The results also show that using different processing time distributions may have a significant impact on shop performance.     

Methods to assess measurement error in questionnaires of sedentary behavior

Sedentary behavior has already been associated with mortality, cardiovascular disease, and cancer. Questionnaires are an affordable tool for measuring sedentary behavior in large epidemiological studies. Here, we introduce and evaluate two statistical methods for quantifying measurement error in questionnaires. Accurate estimates are needed for assessing questionnaire quality. The two methods would be applied to validation studies that measure a sedentary behavior by both questionnaire and accelerometer on multiple days. The first method fits a reduced model by assuming the accelerometer is without error, while the second method fits a more complete model that allows both measures to have error. Because accelerometers tend to be highly accurate, we show that ignoring the accelerometer's measurement error, can result in more accurate estimates of measurement error in some scenarios. In this article, we derive asymptotic approximations for the mean-squared error of the estimated parameters from both methods, evaluate their dependence on study design and behavior characteristics, and offer an R package so investigators can make an informed choice between the two methods. We demonstrate the difference between the two methods in a recent validation study comparing previous day recalls to an accelerometer-based ActivPal.     

A nonparametric hypothesis test for heteroscedasticity

In this paper, a hypothesis test for heteroscedasticity is proposed in a nonparametric regression model. The test statistic, which uses the residuals from a nonparametric fit of the mean function, is based on an adaptation of the well-known Levene's test. Using the recent theory for analysis of variance when the number of factor levels goes to infinity, the asymptotic distribution of the test statistic is established under the null hypothesis of homocedasticity and under local alternatives. Simulations suggest that the proposed test performs well in several situations, especially when the variance is a nonlinear function of the predictor.     

Subsampling-extrapolation bandwidth selection in bivariate kernel density estimation

This paper focuses on bivariate kernel density estimation that bridges the gap between univariate and multivariate applications. We propose a subsampling-extrapolation bandwidth matrix selector that improves the reliability of the conventional cross-validation method. The proposed procedure combines a U-statistic expression of the mean integrated squared error and asymptotic theory, and can be used in both cases of diagonal bandwidth matrix and unconstrained bandwidth matrix. In the subsampling stage, one takes advantage of the reduced variability of estimating the bandwidth matrix at a smaller subsample size m (m < n); in the extrapolation stage, a simple linear extrapolation is used to remove the incurred bias. Simulation studies reveal that the proposed method reduces the variability of the cross-validation method by about 50% and achieves an expected integrated squared error that is up to 30% smaller than that of the benchmark cross-validation. It shows comparable or improved performance compared to other competitors across six distributions in terms of the expected integrated squared error. We prove that the components of the selected bivariate bandwidth matrix have an asymptotic multivariate normal distribution, and also present the relative rate of convergence of the proposed bandwidth selector.     

Prediction of future failures times based on Type-I hybrid censored samples of random sample sizes

In this article, we consider the prediction of future failure times based on Type-I hybrid censored samples. Point predictors and prediction intervals using different procedures are discussed for a general model. The exponential and Rayleigh distributions are used as illustrative examples to show the most simplified forms of the so obtained predictors as well as prediction intervals. Intensive simulation study and a real life dataset are presented to illustrate our findings and results.