18 resultados para Multiple priors and posteriors


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The purpose of the study was to determine the degree of relationships among GRE scores, undergraduate GPA (UGPA), and success in graduate school, as measured by first year graduate GPA (FGPA), cumulative graduate GPA, and degree attainment status. A second aim of the study was to determine whether the relationships between the composite predictor (GRE scores and UGPA) and the three success measures differed by race/ethnicity and sex. A total of 7,367 graduate student records (masters, 5,990; doctoral: 1,377) from 2000 to 2010 were used to evaluate the relationships among GRE scores, UGPA and the three success measures. Pearson’s correlation, multiple linear and logistic regression, and hierarchical multiple linear and logistic regression analyses were performed to answer the research questions. The results of the correlational analyses differed by degree level. For master’s students, the ETS proposed prediction that GRE scores are valid predictors of first year graduate GPA was supported by the findings from the present study; however, for doctoral students, the proposed prediction was only partially supported. Regression and correlational analyses indicated that UGPA was the variable that consistently predicted all three success measures for both degree levels. The hierarchical multiple linear and logistic regression analyses indicated that at master’s degree level, White students with higher GRE Quantitative Reasoning Test scores were more likely to attain a degree than Asian Americans, while International students with higher UGPA were more likely to attain a degree than White students. The relationships between the three predictors and the three success measures were not significantly different between men and women for either degree level. Findings have implications both for practice and research. They will provide graduate school administrators with institution-specific validity data for UGPA and the GRE scores, which can be referenced in making admission decisions, while they will provide empirical and professionally defensible evidence to support the current practice of using UGPA and GRE scores for admission considerations. In addition, new evidence relating to differential predictions will be useful as a resource reference for future GRE validation researchers.

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Examining factors that affect vitamin D status in the fast-growing elderly population of Miami-Dade, Florida, is needed. Vitamin D deficiency in older adults has been linked to correlates of disability, including falls and fractures, and cardiovascular disease. The purpose of this study was to determine the proportion of vitamin D insufficient individuals and their relationship with vitamin D insufficiency in older adults (n=97) living in Miami-Dade. We evaluated the association between vitamin D status and 1) dual task physical performance to understand the link between vitamin D and cognition in the context of mobility; and 2) cardiometabolic risk, measured by galvanic skin response, pulse oximetry, and blood pressure to create a composite score based on autonomic nervous system and endothelial function. Participants completed baseline assessments that included serum levels of vitamin D, anthropometrics, body composition, dual task physical performance and cardiometabolic risk. Surveys to evaluate vitamin D intake, sun exposure, physical activity, and depressive symptoms were completed. Spearman’s correlations, independent t-tests, paired t-tests, repeated measures ANOVAs, and multiple logistic and linear regressions were used to examine the relationship of vitamin D insufficiency (25(OH)D /ml) and sufficiency (25(OH)D ≥30 ng/ml) with determinants of vitamin D status, dual task physical performance variables and cardiometabolic risk scores. Although the proportion of vitamin D insufficient individuals was lower when compared to the prevalance of the general United States elderly population, it was still common in healthy community-dwelling older adults living in Miami-Dade County, especially among Hispanics. Factors that affected skin synthesis (ethnicity, and sun exposure), and bioavailability/metabolism (obesity) were significant predictors of vitamin D status. Vitamin D insufficiency was not significantly correlated with worse dual task physical performance; however, cognitive performance was worse in the vitamin D insufficient group. Our results suggest a relationship of vitamin D insufficiency with executive dysfunction, and support an association with cardiometabolic risk using an innovative electro-sensor complex, possibly by modulating autonomic nervous system activity and vascular function, thus affecting cardiac performance.

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With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.