• Structural Engineering and Mechanics
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• v.91 no.3
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• pp.279-289
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• 2024

The purpose of this study is to represent a useful alternative for the preliminary seismic vulnerability assessment of existing reinforced concrete buildings by introducing a statistical approach employing the binary logistic regression technique. Two different predictive statistical models, namely full and reduced models, were generated utilizing building characteristics obtained from the damage database compiled after 1999 Düzce earthquake. Among the inspected building parameters, number of stories, overhang ratio, priority index, soft story index, normalized redundancy ratio and normalized lateral stiffness index were specifically selected as the predictor variables for vulnerability classification. As a result, normalized redundancy ratio and soft story index were identified as the most significant predictors affecting seismic vulnerability in terms of life safety performance level. In conclusion, it is revealed that both models are capable of classifying the set of buildings being severely damaged or collapsed with a balanced accuracy of 73%, hence, both are able to filter out high-priority buildings for life safety performance assessment. Thus, in this study, having the same high accuracy as the full model, the reduced model using fewer predictors is proposed as a simple and viable classifier for determining life safety levels of reinforced concrete buildings in the preliminary seismic risk assessment.

• Earthquakes and Structures
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• v.22 no.4
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• pp.387-399
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• 2022

To study the seismic damage of masonry structures and understand the characteristics of the multi-intensity region, according to the Dujiang weir urbanization of China Wenchuan earthquake, the deterioration of 3991 masonry structures was summarized and statistically analysed. First, the seismic damage of multistory masonry structures in this area was investigated. The primary seismic damage of components was as follows: Damage of walls, openings, joints of longitudinal and transverse walls, windows (lower) walls, and tie columns. Many masonry structures with seismic designs were basically intact. Second, according to the main factors of construction, seismic intensity code levels survey, and influence on the seismic capacity, a vulnerability matrix calculation model was proposed to establish a vulnerability prediction matrix, and a comparative analysis was made based on the empirical seismic damage investigation matrix. The vulnerability prediction matrix was established using the proposed vulnerability matrix calculation model. The fitting relationship between the vulnerability prediction matrix and the actual seismic damage investigation matrix was compared and analysed. The relationship curves of the mean damage index for macrointensity and ground motion parameters were drawn through calculation and analysis, respectively. The numerical analysis was performed based on actual ground motion observation records, and fitting models of PGA, PGV, and MSDI were proposed.

• Journal of Korean Society of Rural Planning
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• v.21 no.1
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• pp.77-87
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• 2015

In this study, we try to quantify resident's conflict by rural development project based on previous researches about community capacities required for residents and social networks in rural village for suggesting efficient project model. we analyzed conflict elements in six category such as 'conflict in residents', 'conflict in residents and leaders', 'conflict in leaders', 'conflict in villages', 'conflict in development fund', 'conflict in village by common income project'. These results also analyzed by personal background(age, role, education, income) of respondent in questionary survey. Results show that 'conflict in residents and leaders', 'conflict in leaders', 'conflict in development fund' are perceived differently by age, role, education, and income in 5% significance level. Especially, relatively young age(below 40 years old) expressed clearly about conflict and high scored in item of 'residents and leaders'. Regression model show statistical significance(F=39.807, P=0.000) in influence relation analysis of conflict, network, leadership, and project fund. In this model, network ${\beta}=-0.237$, leadership ${\beta}=-0.375$, project fund ${\beta}=-0.000$ show network and leadership have negative relation to conflict but project fund is difficult to find relation with conflict. In this study, we defined social vulnerability using conflict, network, and leadership and verified the vulnerability of rural village applying regional community capacity in analysis results; vulnerability increased by the size of region and show inverse correlation to future vision of residents.

• Steel and Composite Structures
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• v.21 no.1
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• pp.93-107
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• 2016

Seismic fragility analysis is a probabilistic decision-making framework which is widely implemented for evaluating vulnerability of a building under earthquake loading. It requires ingredient named probabilistic model and commonly developed using statistics requiring collecting data in large quantities. Preparation of such a data-base is often costly and time-consuming. Therefore, in this paper, by developing generic seismic drift demand model for regular-multi-story steel moment resisting frames is tried to present a novel application of the probabilistic decision-making analysis to practical purposes. To this end, a demand model which is a linear function of intensity measure in logarithmic space is developed to predict overall maximum inter-story drift. Next, the model is coupled with a set of regression-based equations which are capable of directly estimating unknown statistical characteristics of the model parameters.To explicitly address uncertainties arise from randomness and lack of knowledge, the Bayesian regression inference is employed, when these relations are developed. The developed demand model is then employed in a Seismic Fragility Analysis (SFA) for two designed building. The accuracy of the results is also assessed by comparison with the results directly obtained from Incremental Dynamic analysis.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• Journal of Preventive Medicine and Public Health
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• v.57 no.4
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• pp.370-378
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• 2024

Objectives: Comorbidities increase susceptibility to severe coronavirus disease 2019 (COVID-19) infections, but limited information has been published regarding human immunodeficiency virus (HIV) and COVID-19 co-infections. This study explored the relationships among socioeconomic characteristics, sexual behaviors, and COVID-19 infection rates among Korean men who have sex with men (MSM) who are also living with HIV. Methods: Data were collected through a web survey aimed at members of the largest gay portal site in Korea, supported by the National Research Foundation of Korea (n=1005). The primary independent variables included COVID-19-related vaccinations and sexual behaviors. The dependent variable was the incidence of COVID-19 infection among respondents during the pandemic. For statistical analysis, hierarchical multiple logistic regression was performed, controlling for potential confounding variables. Results: Model I indicated that older MSM were less likely to contract COVID-19 (adjusted odds ratio [aOR], 0.98; 95% confidence interval [CI], 0.96 to 0.99). Model II demonstrated that HIV-positive MSM were nearly twice as likely to be infected with COVID-19 compared to their HIV-negative counterparts (aOR, 1.97; 95% CI, 1.14 to 3.41). Furthermore, even after accounting for COVID-19 vaccination status in model III, HIV-positive MSM continued to show a higher risk of infection (aOR, 1.93; 95% CI, 1.12 to 3.35). Conclusions: The findings of this study indicate that HIV-positive MSM are at an increased risk of contracting COVID-19, even when their vaccination status is considered. Therefore, it is essential to prioritize the prevention of COVID-19 infections in HIV-positive individuals by administering appropriate antiretroviral therapy and ensuring adherence to public health guidelines.