On A Simpler and Faster Derivation of Single Use Reliability Mean and Variance for Model-Based Statistical Testing

Markov chain usage-based statistical testing has proved sound and effective in providing audit trails of evidence in certifying software-intensive systems. The system end-toend reliability is derived analytically in closed form, following an arc-based Bayesian model. System reliability is represented by an important statistic called single use reliability, and defined as the probability of a randomly selected use being successful. This paper continues our earlier work on a simpler and faster derivation of the single use reliability mean, and proposes a new derivation of the single use reliability variance by applying a well-known theorem and eliminating the need to compute the second moments of arc failure probabilities. Our new results complete a new analysis that could be shown to be simpler, faster, and more direct while also rendering a more intuitive explanation. Our new theory is illustrated with three simple Markov chain usage models with manual derivations and experimental results

Investigation of Downey model for speedup prediction

In parallel computing, accurate prediction of speedup is important for job schedulers with adaptive resource allocation. The predicted speedup determines the expected runtime on a certain number of nodes and the efficiency by which the resources are used. Among the existing speedup prediction models, the Downey model [5, 6] is simple but promising. However, the prediction accuracy of the Downey model needs to be investigated in realistic scenario setups. In this thesis, we use the NAS benchmarks and synthetic benchmarks [19] to generate scenarios in which the performance of the Downey model is examined. Based on these experiments, conditions are suggested for the successful application of the Downey model

Service providers' adherence to methadone maintenance treatment protocol in China.

BACKGROUND:Methadone maintenance treatment (MMT) programs have expanded rapidly in China during the last decade. However, variance in service providers' practice may have an impact on the quality of care received by the patients. This study examined Chinese service providers' adherence to the MMT protocol and its associated factors. METHODS:The study used baseline data from a randomized intervention trial implemented in MMT clinics in five provinces of China. The data were collected from January 2012 to August 2013. A total of 418 service providers from 68 MMT clinics participated in the study. Demographic and job-related characteristics were collected. The providers' adherence to the MMT protocol, MMT knowledge, negative attitudes towards people who use drugs (PWUD), and perceived institutional support were assessed. RESULTS:The average adherence score was 36.7 ± 4.3 (out of 9-45). Fewer providers adhered to the protocol items where communications with patients or families were required. After controlling for potential confounders, adherence to the MMT protocol was positively associated with perceived institutional support (standardized β = 0.130; p = 0.0052), and negatively associated with prejudicial attitudes towards PWUD (standardized β = -0.357; p < 0.0001). Reception of national-level MMT training was not associated with higher level of adherence to protocol. CONCLUSION:The findings suggest the potential benefits of providing institutional support to MMT providers to enhance their level of adherence to the MMT protocol. Intervention effort is needed to reduce negative attitudes towards PWUD among MMT service providers to achieve greater consistency with best-practice recommendations