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Multiple heavy side step functions are used to model the local deviations by using distributed mass, stiffness and thickness elements.
We present an approach to solving problems of state estimation, stability, boundedness relatively to given sets, rejection of bounded external disturbances and initial deviations by using static linear state feedback, based on matrix comparison systems method and differential linear matrix inequalities.
Mean deviations: By using Theorem 4, the mean deviation from the mean and the mean deviation from the median of Weibull - N{exponential} distribution can be obtained by replacing S (μ,0,i) and S (M,0,i) with c i c γ c ∑ k = 0 ∞ ( - 1 ) k γ ck i ck k !
(5) Mean deviations: By using Theorem 4, the mean deviation from the mean and the mean deviation from the median of Weibull - N{exponential} distribution can be obtained by replacing S (μ,0,i) and S (M,0,i) with c i c γ c ∑ k = 0 ∞ ( - 1 ) k γ ck i ck k !
Ranges [ 10] and interquartile ranges [ 11] were converted to standard deviations by using previously published methods where necessary.
Standard deviations of change from the baseline to the endpoint were extracted when provided, and imputed for the article with missing standard deviations by using the method referenced in the Cochrane Handbook for Systematic Reviews of Interventions.
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The choice of thermal conductivity model has a noticeable impact on the plate-fin multi-stream heat exchanger design, and the maximum deviation by using different thermal conductivity models is 7.5%.
We first tried to correct this global deviation by using the coefficients of ancestry estimated by STRUCTURE for each individual as covariates in the ANOVA.
Continuous variables were presented as means (standard deviation) by using Student's t-test in the analysis or medians (interquartile range) by using Wilcoxon rank-sum test.
Furthermore, in this arrangement we can also obtain the standard deviation by using the ranked probe sets of each individual array (Ref. [ 10], Supplementary Material).
For each value of T, we estimate the standard deviation by using 1,000 simulated epidemics on the original urban network (without intervention).
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