Backward capacity-filtering for electronics Fabs

In electronics Fabs such as semiconductor Fabs and liquid crystal display (LCD) Fabs, which are capital-intensive, finite-capacity planning is critical to achieving full-capacity production and on-time production. However, existing finite-capacity planning methods do not adequately reflect the actual capacity profiles of an electronics Fab. In this paper, we propose a new Fab-level capacity-filtering procedure to generate finite-capacity plan: a backward capacity-filtering procedure for generating finite-capacity release plan. When developing the Fab-level filtering procedures, we use stage-level capacity-filtering algorithms as a key building block. In this study, we enhance the previous capacity-filtering algorithms proposed by one of the authors in order to facilitate the practical requirements of electronics Fabs. We apply the proposed capacity-filtering method to a modern LCD–TFT Fab in Korea. Performance analyses demonstrate that the proposed method is superior to existing methods.     

Utilizing Bayesian predictive power in clinical trial design

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.     

Efficient heterogeneous sampling for stochastic simulation with an illustration in health care applications

In modeling disease transmission, contacts are assumed to have different infection rates. A proper simulation must model the heterogeneity in the transmission rates. In this article, we present a computationally efficient algorithm that can be applied to a population with heterogeneous transmission rates. We conducted a simulation study to show that the algorithm is more efficient than other algorithms for sampling the disease transmission in a subset of the heterogeneous population. We use a valid stochastic model of pandemic influenza to illustrate the algorithm and to estimate the overall infection attack rates of influenza A (H1N1) in a Canadian city.     

Modeling the Adenoma and Serrated Pathway to Colorectal CAncer (ASCCA)

Several colorectal cancer (CRC) screening models have been developed describing the progression of adenomas to CRC. Currently, there is increasing evidence that serrated lesions can also develop into CRC. It is not clear whether screening tests have the same test characteristics for serrated lesions as for adenomas, but lower sensitivities have been suggested. Models that ignore this type of colorectal lesions may provide overly optimistic predictions of the screen‐induced reduction in CRC incidence. To address this issue, we have developed the Adenoma and Serrated pathway to Colorectal CAncer (ASCCA) model that includes the adenoma‐carcinoma pathway and the serrated pathway to CRC as well as characteristics of colorectal lesions. The model structure and the calibration procedure are described in detail. Calibration resulted in 19 parameter sets for the adenoma‐carcinoma pathway and 13 for the serrated pathway that match the age‐ and sex‐specific adenoma and serrated lesion prevalence in the COlonoscopy versus COlonography Screening (COCOS) trial, Dutch CRC incidence and mortality rates, and a number of other intermediate outcomes concerning characteristics of colorectal lesions. As an example, we simulated outcomes for a biennial fecal immunochemical test screening program and a hypothetical one‐time colonoscopy screening program. Inclusion of the serrated pathway influenced the predicted effectiveness of screening when serrated lesions are associated with lower screening test sensitivity or when they are not removed. To our knowledge, this is the first model that explicitly includes the serrated pathway and characteristics of colorectal lesions. It is suitable for the evaluation of the (cost)effectiveness of potential screening strategies for CRC.     

Role of Temperament,Parenting Behaviors,and Stress on Turkish Preschoolers’ Internalizing Symptoms

Child‐ and family‐related factors that predict internalizing symptoms are understudied in preschool years and have a negative influence on children's functioning. We examined observational assessments of preschoolers' temperamental fearfulness and exuberance, mother reports of negative control, warmth, and parenting stress in a sample of 109 Turkish preschoolers. High temperamental fearfulness and low joyful/exuberant positive affectivity in addition to low warmth and high parenting stress had significant effects on internalizing symptoms. Parenting stress had both direct and indirect relations to internalizing symptoms via lower maternal warmth. When comorbid elevations in externalizing symptoms were controlled, the results were consistent with the interpretation that poor parenting practices and stress associated with the parenting role predict maladaptation in general but that the specific form of maladaptation may be best predicted by individual differences in children's temperamental characteristics. This study contributes to our understanding of risk and protective factors that predict preschoolers' internalizing symptoms with a sample from a non‐Western population. These findings can guide early prevention and intervention programs to address internalizing problems in a culturally‐sensitive way.     

Popularity Contagion Among Adolescents

This study aimed to support the theory of popularity contagion, which posits that popularity spreads among friends spontaneously and regardless of behavioral changes. Peer nominations of status and behavior were collected annually between 6th and 12th grades from a total of 1062 adolescents. Longitudinal hypotheses were mostly supported using path analyses, showing (1) that individual popularity could be predicted by friends’ popularity levels over time, even when controlling for stability of individual popularity; (2) that this prediction was not accounted for by behavioral contagion of aggressive or prosocial behaviors; and (3) that individual social preference generally could not be predicted by friends’ preference levels over time. Implications, limitations, and directions for future research are discussed.     

Impact of an Overt Response System on Staff Performance and Maintenance of Computer-Based Instruction

Interactive Computer Based Instruction (CBI) systems involve teaching strategies to facilitate greater response opportunities during training in an effort to improve learner performance. The current study investigated the effect of online staff training videos with and without overt response requirements on posttest and maintenance test scores across six block-randomized instructional modules for four employees of a university located in the southeastern region of the United States. The overt response consisted of multiple-choice questions administered throughout select teaching modules using an alternating treatment design. Findings suggest that learning occurred as a result of the CBI training; however, the effectiveness of the overt response system varied across individuals, with no discernible differentiation between learning gains associated with response requirements. Other areas of research for expanding the efficacy of CBI and overt response systems are highlighted.     

Hierarchical likelihood approach to non-Gaussian factor analysis

Factor models, structural equation models (SEMs) and random-effect models share the common feature that they assume latent or unobserved random variables. Factor models and SEMs allow well developed procedures for a rich class of covariance models with many parameters, while random-effect models allow well developed procedures for non-normal models including heavy-tailed distributions for responses and random effects. In this paper, we show how these two developments can be combined to result in an extremely rich class of models, which can be beneficial to both areas. A new fitting procedures for binary factor models and a robust estimation approach for continuous factor models are proposed.     

A robust automatic clustering algorithm for probability density functions with application to categorizing color images

This study develops a robust automatic algorithm for clustering probability density functions based on the previous research. Unlike other existing methods that often pre-determine the number of clusters, this method can self-organize data groups based on the original data structure. The proposed clustering method is also robust in regards to noise. Three examples of synthetic data and a real-world COREL dataset are utilized to illustrate the accurateness and effectiveness of the proposed approach.     

Sexual Victimization and Sex-Related Drinking Motives: How Protective is Emotion Regulation?

One in five college women experience sexual victimization (SV), and SV severity is associated with subsequent psychological distress, including sex-related distress. SV severity may also be associated with drinking motives to cope with sex-related distress and to enhance sex (sex-related drinking motives [SRDMs]), particularly if individuals suffer from emotion regulation (ER) difficulties. College women (N = 151) completed a survey assessment of ER, SV history, childhood sexual abuse (CSA), and SRDMs. Twelve regression models assessed six facets of ER as moderators between SV severity and SRDMs. Among women with no or low levels of prior SV severity, women with greater access to ER strategies were less likely to endorse drinking to cope SRDMs. At higher levels of SV severity, women at all levels of access to ER strategies were equally likely to endorse drinking to cope SRDMs, suggesting that access to ER strategies did not mitigate motivations to drink to cope with sex-related distress for these women. Women with severe SV histories may benefit from interventions that build on existing ER strengths or address other factors. However, greater access to ER strategies may serve as a protective factor against SRDMs when SV severity is low.