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        Performance based design optimum of CBFs using bee colony algorithm

        Mansouri, Iman,Soori, Sanaz,Amraie, Hamed,Hu, Jong Wan,Shahbazi, Shahrokh TECHNO-PRESS 2018 COMPUTERS AND CONCRETE Vol. No.

        The requirement to safe and economical buildings caused to the exploitation of nonlinear capacity structures and optimization of them. This requirement leads to forming seismic design method based on performance. In this study, concentrically braced frames (CBFs) have been optimized at the immediate occupancy (IO) and collapse prevention (CP) levels. Minimizing structural weight is taken as objective function subjected to performance constraints on inter-story drift ratios at various performance levels. In order to evaluate the seismic capacity of the CBFs, pushover analysis is conducted, and the process of optimization has been done by using Bee Algorithm. Results indicate that performance based design caused to have minimum structural weight and due to increase capacity of CBFs.

      • KCI등재

        Performance based design optimum of CBFs using bee colony algorithm

        Iman Mansouri,Sanaz Soori,Hamed Amraie,허종완,Shahrokh Shahbazi 국제구조공학회 2018 Steel and Composite Structures, An International J Vol.27 No.5

        The requirement to safe and economical buildings caused to the exploitation of nonlinear capacity structures and optimization of them. This requirement leads to forming seismic design method based on performance. In this study, concentrically braced frames (CBFs) have been optimized at the immediate occupancy (IO) and collapse prevention (CP) levels. Minimizing structural weight is taken as objective function subjected to performance constraints on inter-story drift ratios at various performance levels. In order to evaluate the seismic capacity of the CBFs, pushover analysis is conducted, and the process of optimization has been done by using Bee Algorithm. Results indicate that performance based design caused to have minimum structural weight and due to increase capacity of CBFs.

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        Determination of maternal risk factors of preterm delivery: adjusted for sparse data bias; results from a population-based case-control study in Iran

        ( Mehrdad Valipour ),( Erfan Ayubi ),( Narges Shiravand ),( Yousef Moradi ),( Abolfazl Abbaszadeh ),( Firooz Amrai ),( Shahin Mokhtari ),( Kaveh Bahmanpour ),( Kamyar Mansori ) 대한산부인과학회 2020 Obstetrics & Gynecology Science Vol.63 No.2

        Objective To determine the maternal risk factors associated with preterm delivery in Iran. Methods A population-based case-control study was conducted including 48 women having preterm delivery (case group) and 100 women having term delivery (control group) between March 2007 and March 2012 in the maternity hospitals of the Selseleh County, Lorestan province, Iran. Information regarding maternal risk factors was collected by structured interview and reviewing the medical records. The maternal risk factors associated with preterm delivery were identified using univariate and multivariable logistic regression analysis after adjusting the sparse data bias. The area under the receiver operating characteristic (ROC) curves was estimated to evaluate the discrimination power of the statistical models. Results Multivariable analysis demonstrated that multiparty (odds ratio [OR], 14.23; 95% confidence interval [CI], 1.60-127.05), history of gestational diabetes (OR, 0.10; 95% CI, 0.01-0.99), thyroid dysfunction (OR, 97.32; 95% CI, 5.78-1,637.80), urinary tract infection (OR, 16.60; 95% CI, 3.20-85.92), and taking care during pregnancy (OR, 0.12; 95% CI, 0.03-0.50) had significant impact on preterm delivery after adjusting the potential confounders. The area under the ROC curve for the aforementioned maternal risk factors was 0.86 (95% CI, 0.80-0.92). Conclusion Our study provides evidence for the associations between multiparty, history of gestational diabetes, thyroid dysfunction, urinary tract infection, as well as taking care during pregnancy, and preterm delivery.

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