517 research outputs found

    Multi-objective engineering shape optimization using differential evolution interfaced to the Nimrod/O tool

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    This paper presents an enhancement of the Nimrod/O optimization tool by interfacing DEMO, an external multiobjective optimization algorithm. DEMO is a variant of differential evolution – an algorithm that has attained much popularity in the research community, and this work represents the first time that true multiobjective optimizations have been performed with Nimrod/O. A modification to the DEMO code enables multiple objectives to be evaluated concurrently. With Nimrod/O’s support for parallelism, this can reduce the wall-clock time significantly for compute intensive objective function evaluations. We describe the usage and implementation of the interface and present two optimizations. The first is a two objective mathematical function in which the Pareto front is successfully found after only 30 generations. The second test case is the three-objective shape optimization of a rib-reinforced wall bracket using the Finite Element software, Code_Aster. The interfacing of the already successful packages of Nimrod/O and DEMO yields a solution that we believe can benefit a wide community, both industrial and academic

    The Influence of Neighborhood Poverty on Blood Glucose Levels: Findings from the Community Initiative to Eliminate Stroke (CITIES) program

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    Objectives:  To examine the relationship between both individual and neighborhood level characteristics and non-fasting blood glucose levels.Study design: This study used a cross sectional design using data from the Community Initiative to Eliminate Stroke Program in NC (2004-2008).  A total of 12,809 adults nested within 550 census block groups from two adjacent urban counties were included in the analysis.Methods:   Participants completed a cardiovascular risk factor assessment with self-reported demographics, stroke-risk behaviors, and biometric measurements.  Neighborhood level characteristics were based upon census data.  Three multilevel models were constructed for data analysis.Results:  Mean blood glucose level of this sample population was 103.61mg/dL.  The unconditional model 1 suggested a variation in mean blood glucose levels among the neighborhoods (τ00 = 13.39; P < .001).  Both models 2 and 3 suggested that the neighborhood composite deprivation index had a significant prediction on each neighborhood’s mean blood glucose level (¡01= .69; P < 0.001,¡01= .36; P = .004).  Model 3 also suggested that across all the neighborhoods, on average, after controlling for individual level risk factors, deprivation remained a significant predictor of blood glucose levels.Conclusions:  The findings provide evidence that neighborhood disadvantage is a significant predictor of neighborhood and individual level blood glucose levels.  One approach to diabetes prevention could be for policymakers to address the problems associated with environmental determinants of health
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