We propose and develop a genetic algorithm (GA) for generating D‐optimal designs where the experimental region is an irregularly shaped polyhedral region. Our approach does not require selection of points from a user‐defined candidate set of mixtures and allows movement through a continuous region that includes highly constrained mixture regions. This approach is useful in situations where extreme vertices (EV) designs or conventional exchange algorithms fail to find a near‐optimal design. For illustration, examples with three and four components are presented with comparisons of our GA designs with those obtained using EV designs and exchange‐point algorithms over an irregularly shaped polyhedral region. The results show that the designs produced by the GA perform better than, if not as well as, the designs produced by the exchange‐point algorithms; however, the designs produced by the GA perform better than the designs produced by the EV. This suggests that GA is an alternative approach for constructing the D‐optimal designs in problems of mixture experiments when EV designs or exchange‐point algorithms are insufficient. Copyright © 2012 John Wiley & Sons, Ltd.
The success of language learning significantly depends on multiple sets of complex factors; among these are language-learning strategies of which learners in different countries may show different preferences. Needed areas of language learning strategy research include, among others, the strategy of grammar learning and the context-based approach to learning strategies. To fill in these gaps, this study aimed at finding the grammar learning strategies adopted by high school students as well as exploring the national differences between Chinese and Thai students. The results showed that in general the strategies significantly taken up by the high achievers in the grammar test included the metacognitive, the memory, the social and the cognitive. In terms of the national differences, the strategies that characterized the Thai students were the social and the affective. Regarding the Chinese, even though they generally applied all strategy categories at lower frequencies, they were found to prefer different sub-strategies in the following three categories: memory (revision and space reliance), cognitive (note taking) and metacognitive (lesson preview). The findings lead to implications for learners of grammar, interesting future research in grammar strategies and culturally responsive grammar teaching.
Significant evidence has shown that southern Thailand is prone to the highest risk of repeated flooding. However, psychological distress and mental health problems caused by the flash floods and landslides have been under-researched among Thai survivors. This cross-sectional study aimed to explore characteristics and factors associated with the prevalence of psychological distress, probable post traumatic stress disorder (PTSD), probable depression, suicide risk, and alcohol problems 4 to 6 months after the flooding. The research examined 326 survivors from households in flooded communities in Nakhon Si Thammarat province during 2011. Descriptive statistics, correlation analysis and a binary logistic regression model were applied to the data representing demographics, household damage, perceived mental health impact, social support and mental health problems. The results showed that the prevalence rate of probable PTSD, probable depression, psychological distress, suicide risk, and alcohol problems were 44.48, 31.29, 29.45, 17.18 and 4.60 %, respectively. Risk factors that variously affected those mental health problems were age, gender, prior physical condition, perception of mental health impacts, skin infection, and injury incurred during the flood. On the other hand, a significant protective factor was the degree of social support. Results suggest that rapid actions should be taken immediately after flooding, especially management with the risk survivor group and promotion of social support to minimize the mental health impacts associated with the flooding.
Among the numerous alphabetical optimality criteria is the IV-criterion that is focused on prediction variance. We propose a new criterion, called the weighted IV-optimality. It is similar to IV-optimality, because the researcher must first specify a model. However, unlike IV-optimality, a suite of "reduced" models is also proposed if the original model is misspecified via over-parameterization. In this research, weighted IV-optimality is applied to mixture experiments with a set of prior weights assigned to the potential mixture models of interest. To address the issue of implementation, a genetic algorithm was developed to generate weighted IV-optimal mixture designs that are robust across multiple models. In our examples, we assign models with p parameters to have equal weights, but weights will vary based on varying p. Fraction-of-design-space (FDS) plots are used to compare the performance of an experimental design in terms of the prediction variance properties. An illustrating example is presented. The result shows that the GA-generated designs studied are robust across a set of potential mixture models.
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