• Journal of the Korean Geotechnical Society
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• v.34 no.6
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• pp.25-36
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• 2018

Soil liquefaction is one of the types of major seismic damage. Soil liquefaction is a phenomenon that can cause enormous human and economic damages, and it must be examined before designing geotechnical structures. In this study, we proposed a practical method of developing a multi-hazard fragility surface for liquefaction of levee considering earthquake magnitude and water level. Limit state for liquefaction of levee was defined by liquefaction potential index (LPI), which is frequently used to assess the liquefaction susceptibility of soils. In order to consider the uncertainty of soil properties, Monte Carlo Simulation based probabilistic analysis was performed. Based on the analysis results, a 3D fragility surface representing the probability of failure by soil liquefaction as a function of the ground motion and water level has been established. The prepared multi-hazard fragility surface can be used to evaluate the safety of levees against liquefaction and to assess the risk in earthquake and flood prone areas.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.493-500
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• 2014

This paper presents findings from the assessment of the volcanic ash fragility for multi-hazard resisting vinyl greenhouse and livestock shed among the agricultural facilities. The volcanic ash fragility was evaluated by using a combination of the FOSM (first-order second-moment) method, available statistics of volcanic load, facility specifications, and building code. In this study, the evaluated volcanic ash fragilities represent the conditional probability of failure of the agricultural facilities over the full range of volcanic ash loads. For the evaluation, 6 types(ie., 2 single span, 2 tree crop, and 2 double span types) of multi-hazard resisting vinyl greenhouses and 3 types(ie., standard, coast, and mountain types) of livestock sheds are considered. All volcanic ash fragilities estimated in this study were fitted by using parameters of the GEV(generalized extreme value) distribution function, and the obtained parameters were complied into a database to be used in future. The volcanic ash fragilities obtained in this study are planning to be used to evaluate risk by volcanic ash when Mt. Baekdu erupts.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.5
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• pp.53-64
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• 2010

Seismic fragility curves of structures represent the probability of exceeding the prescribed structural damage state for a given various levels of ground motion intensity, such as peak ground acceleration (PGA). This means that seismic fragility curves are essential to the evaluation of structural seismic performance and assessments of risk. Most of existing studies have not considered the near- and far-fault earthquake effect on the seismic fragility curves. In order to evaluate the effect of near- and far-fault earthquakes, seismic fragility curves for PSC box girder bridges subjected to near- and far-fault earthquakes are calculated and compared. The seismic fragility curves are strongly dependent on the earthquake characteristics such as fault distance. This paper suggests that the effect of near- and far-fault earthquakes on seismic fragility curves of PSC box girder bridge structure should be considered.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1025-1032
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• 2013

The purpose of this study was to examine how socio-demographic characteristics and delinquent behaviors affect the suicidal ideation among the Korean high school students. Using the 35,668 senior high school student cases of 2009 Korean Youth Health Risk Behavior On-line Survey data, it conducted a secondary data analysis. Frequency analysis, chi-square test and logistic regression analysis was done. Being female, living without parents, low economic status, poor academic record, technical school students, young students, poor academic record, internet addition, problem drinking, smoking cigarettes and experience of drug use significantly increased probability of their suicidal thoughts. Findings may be used for tackle the issues of suicidal thoughts among the Korean senior high school students.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.269-272
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• 2008

The seismic fragility curves of a structure represents the probability of exceeding the prescribed structural damage given various levels of ground motion intensityand the seismic fragility curve is essential to evaluation of structural performance and assessment of risk and loss of structures. The purpose of this paper is to develop seismic fragility functions for bridge structures in Koreaby reviewing those of advanced countries. Therefore, at first, we investigated development conditions of the seismic fragility functions. And the next highway bridges in Korea are classified into a number of categories and several typical bridges are selected to estimate seismic fragilities for using this analysis method in Korea. Finally, fragility curves for PSC Box girder bridge are estimated. The results show that the bridge classification and damage state play an important role in estimation of seismic damage and seismic fragility analysis for bridge structures.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.57-62
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• 2014

In this paper, we proposed and implemented a crime pattern analysis algorithm using big data. The proposed algorithm uses crime-related big data collected and published in the supreme prosecutors' office. The algorithm analyzed crime patterns in Seoul city from 2011 to 2013 using the spatial statistics analysis like the standard deviational ellipse and spatial density analysis. Using crime frequency, We calculated the crime probability and danger factors of crime areas, time, date, and places. Through a result we analyzed spatial statistics. As the result of the proposed algorithm, we could grasp differences in crime patterns of Seoul city, and we calculated degree of risk through analysis of crime pattern and danger factor.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.241-250
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• 2005

New product development (NPD) is defined as the transformation of a market opportunity and a set of assumptions about product technology into a product available for sale. Managers charged with project selection decisions in the NPD process, such as go/no-go choices and specific resource allocation decisions, are faced with a complicated problem. Therefore, the ability to develop new successful products has identifies as a major determinant in sustaining a firm's competitive advantage. The purpose of this study is to develop a new evaluation model for NPD project selection in the high -tech industry using support vector machines (SYM). The evaluation model is developed through two phases. In the first phase, binary (go/no-go) classification prediction model, i.e. SVM for high-tech NPD project selection is developed. In the second phase. using the predicted output value of SVM, feasibility grade is calculated for the final NPD project decision making. In this study, the feasibility grades are also divided as three level grades. We assume that the frequency of NPD project cases is symmetrically determined according to the feasibility grades and misclassification errors are partially minimized by the multiple grades. However, the horizon of grade level can be changed by firms' NPD strategy. Our proposed feasibility grade method is more reasonable in NPD decision problems by considering particularly risk factor of NPD in viewpoints of future NPD success probability. In our empirical study using Korean NPD cases, the SVM significantly outperformed ANN and logistic regression as benchmark models in hit ratio. And the feasibility grades generated from the predicted output value of SVM showed that they can offer a useful guideline for NPD project selection.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1236-1241
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• 2016

Cancer has been the most frequent in Korea, and pathogenesis and progression of cancer have been known to be occurred through various causes and stages. Recently, the research of chromosomal and genetic disorder and the research about prognostic factor to predict occurrence, recurrence and progress of chromosomal and genetic disorder have been performed actively. In this paper, we analyzed DNA methylation data downloaded from TCGA (The Cancer Genome Atlas), open database, to research bladder cancer which is the most frequent among urinary system cancers. Using three level of methylation data which had the most preprocessing, 59 candidate CpG island were extracted from 480,000 CpG island, and then we analyzed extracted CpG island applying data mining technique. As a result, cg12840719 CpG island were analyzed significant, and in Cox's regression we can find the CpG island with high relative risk in comparison with other CpG island. Shown in the result of classification analysis, the CpG island which have high correlation with bladder cancer are cg03146993, cg07323648, cg12840719, cg14676825 and classification accuracy is about 76%. Also we found out that positive predictive value, the probability which predicts cancer in case of cancer was 72.4%. Through the verification of candidate CpG island from the result, we can utilize this method for diagnosing and treating cancer.

• Journal of the Korean Society of School Health
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• v.22 no.1
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• pp.49-59
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• 2009

Purpose: The aim of this study was to identify the factors related with the intention of smoking abstinence among elementary students in a metropolitan city in Korea. Methods: All the elementary schools in the city were stratified by region, and then schools as a primary sampling units (PSU) were selected by probability proportional to size (PPS) sampling. One class per grade was sampled randomly from 5th and 6th grade in the sampled schools from October to December in 2004. The students completed a standardized self-administered questionnaire anonymously. A total number of 1,712 respondents who did not smoke was included in the final analysis. The dependent variable was an intention of smoking in the future, and it was dichotomized into 'absolutely confident in smoking abstinence' and 'others'. The risk of non-absolute confidence in smoking abstinence was calculated with simple and multiple logistic regression, which were conducted with STATA 9.0 by a design-based analysis considering strata variable, PSU, and sampling weight. Results: In the final model of multiple logistic regression analysis, those who were more likely to have non-absolute confidence in smoking abstinence were male students (OR=2.66, p<0.001); barely attending religious services (OR=3.32, p=0.002) or having no religion (OR=1.95, p=0.027); exposure to environmental tobacco smoke outside home 1${\sim}$2 days per week (OR=1.60, p=0.013); having friends who smoked (OR=1.93, p=0.011); non-absolute confidence in refusing to smoke (OR=5.35, p<0.001); having relatively less negative attitude (OR=2.88, p<0.001), positive attitude (OR=2.35, p<0.001), and indifference (OR=4.05, p=0.034) toward peer smoking; not good relationship with mother (OR=1.52, p=0.016). Conclusion: The factors related with non-absolute confidence in smoking abstinence were coincided with those of smoking among children. The results of this study suggest the smoking prevention education should be applied to the children more actively, especially who are not confident in smoking abstinence in the future.

• The Plant Pathology Journal
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• v.31 no.4
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• pp.350-362
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• 2015

A disease forecast model for bacterial grain rot (BGR) of rice, which is caused by Burkholderia glumae, was developed in this study. The model, which was named 'BGRcast', determined daily conduciveness of weather conditions to epidemic development of BGR and forecasted risk of BGR development. All data that were used to develop and validate the BGRcast model were collected from field observations on disease incidence at Naju, Korea during 1998-2004 and 2010. In this study, we have proposed the environmental conduciveness as a measure of conduciveness of weather conditions for population growth of B. glumae and panicle infection in the field. The BGRcast calculated daily environmental conduciveness, $C_i$, based on daily minimum temperature and daily average relative humidity. With regard to the developmental stages of rice plants, the epidemic development of BGR was divided into three phases, i.e., lag, inoculum build-up and infection phases. Daily average of $C_i$ was calculated for the inoculum build-up phase ($C_{inf}$) and the infection phase ($C_{inc}$). The $C_{inc}$ and $C_{inf}$ were considered environmental conduciveness for the periods of inoculum build-up in association with rice plants and panicle infection during the heading stage, respectively. The BGRcast model was able to forecast actual occurrence of BGR at the probability of 71.4% and its false alarm ratio was 47.6%. With the thresholds of $C_{inc}=0.3$ and $C_{inf}=0.5$, the model was able to provide advisories that could be used to make decisions on whether to spray bactericide at the preand post-heading stage.