Material properties and fire test results

Five material properties commonly used to describe the fire behavior of solids were evaluated as sole explanatory variables for four small‐scale fire tests with pass/fail outcomes by using a physically based probabilistic (phlogistic) burning model. The phlogistic model describes the likelihood of passing vertical Bunsen burner tests and a regulatory heat release rate test reasonably well over a wide range of material properties, as deduced from the correlation coefficient and mean deviation of the predicted and measured values. Of the thermal, combustion, and fire properties examined, the best predictors of the likelihood of passing the fire tests of this study were the heat of combustion of the sample, the heat release capacity, and the heat release parameter. The relative merits and drawbacks of qualitative (threshold) and quantitative (probabilistic) approaches to predicting fire test results using thermal and combustion properties are discussed. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.     

Risk of sick leave associated with outdoor air supply rate, humidification, and occupant complaints

We analyzed 1994 sick leave for 3,720 hourly employees of a large Massachusetts manufacturer, in 40 buildings with 115 independently ventilated work areas. Corporate records identified building characteristics and IEQ complaints. We rated ventilation as moderate (approximately 25 cfm/person, 12 ls-1) or high (approximately 50 cfm/person, 24 ls-1) outdoor air supply based on knowledge of ventilation systems and CO2 measurements on a subset of work areas, and used Poisson regression to analyze sick leave controlled for age, gender, seniority, hours of non-illness absence, shift, ethnicity, crowding, and type of job (office, technical, or manufacturing worker). We found consistent associations of increased sick leave with lower levels of outdoor air supply and IEQ complaints. Among office workers, the relative risk for short-term sick leave was 1.53 (95% confidence 1.22-1.92) with lower ventilation, and 1.52 (1.18-1.97) in areas with IEQ complaints. The effect of ventilation was independent of IEQ complaints and among those exposed to lower outdoor air supply rates the attributable risk of short-term sick leave was 35%. The cost of sick leave attributable to ventilation at current recommended rates was estimated as $480 per employee per year at Polaroid. These findings suggest that net savings of $400 per employee per year may be obtained with increased ventilation. Thus, currently recommended levels of outdoor air supply may be associated with significant morbidity, and lost productivity on a national scale could be as much as $22.8 billion per year. Additional studies of IEQ impacts on productivity and sick leave, and the mechanisms underlying the apparent association are needed.     

An exploratory study for investigating the critical success factors for cloud migration in the Saudi Arabian higher education context

Saudi universities have at their disposal a huge number of low cost IT resources to aid in teaching, research and learning. By migrating to cloud services, Saudi universities will be moving data and programs from local servers to the internet, thereby providing users with the ability to access and share information at any time from multiple devices. The migration to cloud-based IT resources is not yet widespread in Saudi universities due to several challenges including security, legal policies and implementation. At present, there is lack of research and guidance for Saudi universities on how to overcome these challenges and how contextual factors can influence the successful migration to the educational clouds.This research presents a framework for the successful migration to cloud technology in the Saudi Arabian universities. In this research, a set of key critical success factors (CSFs) were identified by synthesizing components from studies concerned with the migration of cloud for higher education and factors identified from the successful implementation of WBL (Web Based Learning) and ERP (Enterprise Resource Planning) on higher education in Saudi Arabia. Based on this knowledge, the proposed framework was evaluated via expert review and a survey by IT specialists from the Saudi universities. The initial CSFs were updated based on the expert reviews and the results were analysed. Based on the findings at this stage, additional CSFs were added to the framework as suggested by the experts. Subsequently, in order to confirm the reviewed CSFs, additional investigation via a structured online questionnaire was conducted and the outcome was analysed via one-sample t-test with the data integrity analysed via Cronbach’s alpha. The outcome indicated the majority of CSFs to be statistically significant except the Physical Location CSF. Potential future study and contributions are discussed.     

A Weighted-Least-Squares Estimation Approach to Comparing Trends in Age-Adjusted Cancer Rates Across Overlapping Regions

Li and Tiwari (2008) recently developed a corrected Z-test statistic for comparing the trends in cancer age-adjusted mortality and incidence rates across overlapping geographic regions, by properly adjusting for the correlation between the slopes of the fitted simple linear regression equations. One of their key assumptions is that the error variances have unknown but common variance. However, since the age-adjusted rates are linear combinations of mortality or incidence counts, arising naturally from an underlying Poisson process, this constant variance assumption may be violated. This paper develops a weighted-least-squares based test that incorporates heteroscedastic error variances, and thus significantly extends the work of Li and Tiwari. The proposed test generally outperforms the aforementioned test through simulations and through application to the age-adjusted mortality data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute.     

Improving the effectiveness of computer-delivered personalized drinking feedback interventions for college students.

This study evaluated methods of enhancing college students' retention of information provided to them in a computer-delivered personalized drinking feedback intervention and whether enhanced retention reduced alcohol consumption during the two-week period following the intervention. Participants were 98 college students who reported at least one heavy drinking episode in the past two weeks. After participating in an online, personalized drinking feedback intervention, students were randomly assigned to one of three experimental conditions: 1) typical, in which they were simply sent home, 2) reading, in which they were asked to spend the next 20 minutes re-reading the feedback, and 3) recall, in which they were asked to spend the next 20 minutes writing down as much of the information from the feedback as they could remember. Two weeks following the intervention, participants completed a recall test and provided information on their alcohol use during the previous two weeks. Results indicated that participants in the reading and recall conditions retained more of the feedback information than did participants in the typical condition. In addition, participants in the reading and recall conditions reported reduced alcohol consumption in the two-week period following the intervention, compared to those in the typical condition. Information retention partially mediated the effects of the reading and recall conditions on drinking outcomes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Comparing the relative fit of categorical and dimensional latent variable models using consistency tests.

A number of recent studies have used Meehl’s (1995) taxometric method to determine empirically whether one should model assessment-related constructs as categories or dimensions. The taxometric method includes multiple data-analytic procedures designed to check the consistency of results. The goal is to differentiate between strong evidence of categorical structure, strong evidence of dimensional structure, and ambiguous evidence that suggests withholding judgment. Many taxometric consistency tests have been proposed, but their use has not been operationalized and studied rigorously. What tests should be performed, how should results be combined, and what thresholds should be applied? We present an approach to consistency testing that builds on prior work demonstrating that parallel analyses of categorical and dimensional comparison data provide an accurate index of the relative fit of competing structural models. Using a large simulation study spanning a wide range of data conditions, we examine many critical elements of this approach. The results provide empirical support for what marks the first rigorous operationalization of consistency testing. We discuss and empirically illustrate guidelines for implementing this approach and suggest avenues for future research to extend the practice of consistency testing to other techniques for modeling latent variables in the realm of psychological assessment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Integrating Industry Experts into Engineering Education: Case Study

An advanced grade control course is described as a model for industry involvement in special topics educational offerings. Several unique aspects of these courses were the lack of textbooks on the topic, little previously developed course content, and the lack of faculty expertise in the subject area. In light of these challenges the course was successfully implemented by selecting industry experts and coordinating their efforts into a cohesive learning experience. The writers worked with representatives from McAninch Corporation, Ziegler Caterpillar, and other organizations to develop the courses at Iowa State University. Since the courses were the first known offerings of their kind, qualitative interviews were conducted to identify appropriate educational outcomes and objectives necessary to expedite the process of becoming an advanced grade control specialist. These outcomes and objectives can be applied to a variety of educational delivery systems and were helpful in determining suitable course material, topics, and structure.     

Using comparison data to differentiate categorical and dimensional data by examining factor score distributions: Resolving the mode problem.

Factor-analytic research is common in the study of constructs and measures in psychological assessment. Latent factors can represent traits as continuous underlying dimensions or as discrete categories. When examining the distributions of estimated scores on latent factors, one would expect unimodal distributions for dimensional data and bimodal or multimodal distributions for categorical data. Unfortunately, identifying modes is subjective, and the operationalization of counting local maxima has not performed very well. Rather than locating and counting modes, the authors propose performing parallel analyses of categorical and dimensional comparison data and calculating an index of the relative fit of these competing structural models. In an extensive Monte Carlo study, the authors replicated prior results for mode counting and found that trimming distributions' tails helped. However, parallel analyses of comparison data achieved much greater accuracy, improved base rate estimation, and afforded consistency checks with other taxometric procedures. Two additional studies apply this approach to empirical data either known to be categorical or presumed to be dimensional. Each study supports this new method for factor-analytic research on the latent structure of constructs and measures in psychological assessment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Predicting recidivism with the Psychopathy Checklist: Are factor score composites really necessary?

In two previous studies on general and violent recidivism (Walters & Heilbrun, 2010; Walters, Knight, Grann, & Dahle, 2008), the summed composite antisocial facet of the Psychopathy Checklist displayed incremental validity relative to the other 3 facets (interpersonal, affective, lifestyle), whereas the other 3 facets generally failed to demonstrate incremental validity relative to the antisocial facet. Because summed composite scores do not account for ordinal item distributions, the 6 Walters et al. (2008) samples were reanalyzed with factor score composites derived from a 4-factor confirmatory factor analysis. The results, however, showed little change from what had been obtained earlier with summed composite scores. Two additional samples not previously included in any incremental validity analyses of the Psychopathy Checklist evidenced a 3-factor structure, with the lifestyle and antisocial facets merged into a single factor. This single factor displayed incremental validity relative to the interpersonal and affective facets, but the reverse was not true regardless of whether summed composite scores or factor score composites were used. A comparison of zero-order correlations from all 8 samples revealed that the antisocial summed composite score predicted significantly better than the summed composite scores for the other 3 facets and that a superordinate factor failed to improve on the performance of either the antisocial summed composite score or the antisocial factor score composite. (PsycINFO Database Record (c) 2011 APA, all rights reserved)