27 research outputs found
Surrogateâassisted design of microstrip corporate feeds integrated with linear microstrip array apertures for required sidelobe levels
BMI at school age and incident asthma admissions in early adulthood: a prospective study of 310,211 children
Charlotte Suppli Ulrik,1,2 Søren N Lophaven,3 Zorana Jovanovic Andersen,3 Thorkild IA Sørensen,4 Jennifer L Baker4,5 1Department of Respiratory Medicine, Hvidovre Hospital, Hvidovre, Denmark; 2Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; 3Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark; 4Section of Metabolic Genetics and Section of Epidemiology, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark; 5Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark Background: Excess body weight in adulthood is associated with risk for asthma admission (AA). Our aim was to investigate if this association also applies to the relation between body mass index (BMI) in childhood and AAs in early adulthood (age 20–45 years). Methods: This was a prospective study of 310,211 schoolchildren (born 1930–1989) from the Copenhagen School Health Records Register. Height and weight were measured annually, and generated BMI z-scores were categorized as low (lower quartile), normal (interquartile) and high (upper quartile). Associations between BMI at ages 7–13 and AA were estimated by Cox regressions, and presented as hazard ratios (HRs) and 95% confidence intervals (CI). Main outcome was incident hospital AAs (extracted from the Danish National Patient Register) in early adulthood. Results: During 4,708,607 person-years of follow-up, 1,813 incident AAs were observed. Non-linear associations were detected between childhood BMI and AAs. The risk of AA increased for females in the highest BMI category in childhood, with the highest HR of 1.3 (95% CI 1.16–1.55) at the age of 13 years. By contrast, males in the low BMI category had a higher risk of AA in early adulthood, with the highest HR of 1.24 (95% CI 1.03–1.51) at the age of 12 years. Females with an increase in BMI between ages 7 and 13 years had an increased risk of AA compared with females with stable BMI (HR 1.28, 95% CI 1.10–1.50). Conclusion: The association between childhood BMI and AA in early adulthood is non-linear. High BMI increases the risk of AA in females, whereas low BMI increases the risk in males. Keywords: BMI, childhood, asthma, admissions, sex, adiposit
Analysis of circular polarization antenna design tradeâoffs using lowâcost EMâdriven multiobjective optimization
Fast Calculating Surrogate Models for Leg and Head Impact in VehicleâPedestrian Collision Simulations
Classic Kriging versus
Kriging is a popular method for estimating the global optimum of a simulated system. Kriging approximates the input/output function of the simulation model. Kriging also estimates the variances of the predictions of outputs for input combinations not yet simulated. These predictions and their variances are used by âefficient global optimizationâ (EGO), to balance local and global search. This article focuses on two related questions: (1) How to select the next combination to be simulated when searching for the global optimum? (2) How to derive confidence intervals for outputs of input combinations not yet simulated? Classic Kriging simply plugs the estimated Kriging parameters into the formula for the predictor variance, so theoretically this variance is biased. This article concludes that practitioners may ignore this bias, because classic Kriging gives acceptable confidence intervals and estimates of the optimal input combination. This conclusion is based on bootstrapping and conditional simulation
Comparing error estimation measures for polynomial and kriging approximation of noise-free functions
Monotonicity-preserving bootstrapped Kriging metamodels for expensive simulations
Kriging metamodels (also called Gaussian process or spatial correlation models) approximate the Input/Output functions implied by the underlying simulation models. Such metamodels serve sensitivity analysis, especially for computationally expensive simulations. In practice, simulation analysts often know that this Input/Output function is monotonic. To obtain a Kriging metamodel that preserves this characteristic, this article uses distribution-free bootstrapping assuming each input combination is simulated several times to obtain more reliable averaged outputs. Nevertheless, these averages still show sampling variation, so the Kriging metamodel does not need to be an exact interpolator; bootstrapping gives a noninterpolating Kriging metamodel. Bootstrapping may use standard Kriging software. The method is illustrated through the popular M/M/1 model with either the mean or the 90% quantile as output; these outputs are monotonic functions of the traffic rate. The empirical results demonstrate that monotonicity-preserving bootstrapped Kriging gives higher probability of covering the true outputs, without lengthening the confidence interval