• Proceedings of the Korean Society of Toxicology Conference
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• 2002.05a
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• pp.137-137
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• 2002

Biologically Based Dose-Response (BBDR) models were developed using biomarkers for cancer risk assessment. To establish the relationship among biomarkers, exposure dose and tumor response, biomarkers in the lung, liver, stomach or blood were measured after a single or continuous administration of selected carcinogen (; BaP) in mice or rats.(omitted)

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.283-288
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• 2005

Value at Risk(VaR) has been proven useful in finance literature as a tool of risk management(cf. Jorion(2001)). This article is concerned with introducing VaR to various Korean financial time series. Five daily data sets with sample period ranging from 2000 and 2004 such as KOSPI, KOSPI 200, KOSDAQ, KOSDAQ 50 and won-dollar exchange rate are analyzed using GARCH modeling and in turn VaR is obtained for each data.

• Fire Science and Engineering
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• v.32 no.3
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• pp.76-87
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• 2018

This study describes the damage effects modeling for a quantitative prediction about the hazardous distances from pressurized chlorine saturated liquid tank, which has two-phase leakage. The heavy gas, chlorine is an accidental substance that is used as a raw material and intermediate in chemical plants. Based on the evaluation method for damage prediction and accident effects assessment models, the operating conditions were set as the standard conditions to reveal the optimal variables on an accident due to the leakage of a liquid chlorine storage vessel. A model of the atmospheric diffusion model, ALOHA (V5.4.4) developed by USEPA and NOAA, which is used for a risk assessment of Off-site Risk Assessment (ORA), was used. The Yeosu National Industrial Complex is designated as a model site, which manufactures and handles large quantities of chemical substances. Weather-related variables and process variables for each scenario need to be modelled to derive the characteristics of leakage accidents. The estimated levels of concern (LOC) were calculated based on the Gaussian diffusion model. As a result of ALOHA modeling, the hazardous distance due to chlorine diffusion increased with increasing air temperature and the wind speed decreased and the atmospheric stability was stabilized.

• Fire Science and Engineering
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• v.30 no.5
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• pp.116-123
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• 2016

The quantitative risk assessment methods for thermal failure in targets were studied using fire modeling. To this end, Fire Dynamics Simulator (FDS), as a representative fire model, was used and the probabilities related to thermal damage to an electrical cable were evaluated according to the change in fire area inside a specific compartment. 'The maximum probability of exceeding the damage thresholds' adopted in a conservative point of view and 'the probability of failure' including the time to damage were compared. The probability of failure suggested in the present study could evaluate the quantitative fire risk more realistically, compared to the maximum probability of exceeding the damage thresholds with the assumption that thermal damage occurred the instant the target reached its minimum failure criteria in terms of the surface temperature and heat flux.

• Clinical and Experimental Emergency Medicine
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• v.5 no.4
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• pp.230-239
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• 2018

Objective The suicide rate in South Korea is very high and is expected to increase in coming years. Intoxication is the most common suicide attempt method as well as one of the common reason for presenting to an emergency medical center. We used decision tree modeling analysis to identify predictors of risk for suicide by intentional intoxication. Methods A single-center, retrospective study was conducted at our hospital using a 4-year registry of the institute from January 1, 2013 to December 31, 2016. Demographic factors, such as sex, age, intentionality, therapeutic adherence, alcohol consumption, smoking status, physical disease, cancer, psychiatric disease, and toxicological factors, such as type of intoxicant and poisoning severity score were collected. Candidate risk factors based on the decision tree were used to select variables for multiple logistic regression analysis. Results In total, 4,023 patients with intoxication were enrolled as study participants, with 2,247 (55.9%) identified as cases of intentional intoxication. Reported annual percentages of intentional intoxication among patients were 628/937 (67.0%), 608/1,082 (56.2%), 536/1,017 (52.7), 475/987 (48.1%) from 2013 to 2016. Significant predictors identified based on decision tree analysis were alcohol consumption, old age, psychiatric disease, smoking, and male sex; those identified based on multiple regression analysis were alcohol consumption, smoking, male sex, psychiatric disease, old age, poor therapeutic adherence, and physical disease. Conclusion We identified important predictors of suicide risk by intentional intoxication. A specific and realistic approach to analysis using the decision tree modeling technique is an effective method to determine those groups at risk of suicide by intentional intoxication.

• Journal of Food Hygiene and Safety
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• v.33 no.3
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• pp.157-161
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• 2018

The objective of this study was to develop software to predict the kinetic behavior and the probability of foodborne bacterial growth on processed meat products. It is designed for rapid application by non-specialists in predictive microbiology. The software, named Foodborne bacteria Animal product Modeling Equipment (FAME), was developed using Javascript and HTML. FAME consists of a kinetic model and a probabilistic model, and it can be used to predict bacterial growth pattern and probability. In addition, validation and editing of model equation are available in FAME. The data used by the software were constructed with 5,400 frankfurter samples for the kinetic model and 345,600 samples for the probabilistic model using a variety of combinations including atmospheric conditions, temperature, NaCl concentrations and $NaNO_2$ concentrations. Using FAME, users can select the concentrations of NaCl and $NaNO_2$ meat products as well as storage conditions (atmosphere and temperature). The software displays bacterial growth patterns and growth probabilities, which facilitate the determination of optimal safety conditions for meat products. FAME is useful in predicting bacterial kinetic behavior and growth probability, especially for quick application, and is designed for use by non-specialists in predictive microbiology.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.249-260
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• 2019

The study examines the impact of financial risk, convenience risk, non-delivery risk; return policy risk and product risk on online consumer behavior of Malaysian consumers. The research employed a self-administered survey to collect empirical data from 245 Malaysian online shoppers by using convenience sampling. Cronbach alpha was calculated to confirm the reliability of the data and then normality was assessed. Confirmatory Factor Analysis was then conducted to test the model using the goodness-of-fit tests. And finally, structural equation modeling is used to test the hypotheses and draw conclusions. IBM SPSS AMOS version 22.0 was utilized for data analysis. The research indicates that product risk, convenience risk, and return policy risk have a significant and positive impact on online shopping behavior. Financial risk is found to have insignificant and negative effects on consumer behavior. In addition, the non-delivery risk is found to have a significant and negative impact on online shopping behavior. The findings provide a useful model for measuring and managing perceived risk in online shopping which may result in an increase in participation of Malaysian consumers and reduce their cognitive deficiencies in the e-commerce environment. Several managerial implications are discussed along with the scope for future research.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.672-679
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• 2018

This study was conducted to predict the potential distribution and risk of invasive alien plant, Amaranthus patulus, in an agricultural area of South Korea. We collected 254 presence localities of A. patulus using field survey and literature search and stimulated the potential distribution area of A. patulus using maximum entropy modeling (MaxEnt) with six climatic variables. Two different kinds of agricultural risk index, raster risk index and regional risk index, were estimated. The 'raster risk index' was calculated by multiplying the potential distribution by the field area in $1{\times}1km$ and 'regional risk index' was calculated by multiplying the potential distribution by field area proportion in the total field of South Korea. The predicted potential distribution of A. patulus was almost matched with actual presence data. The annual mean temperature had the highest contribution for distribution modeling of A. patulus. Area under curve (AUC) value of the model was 0.711. The highest regions were Gwangju for potential distribution, Jeju for 'raster risk index' and Gyeongbuk for 'regional risk index'. This different ranks among the index showed the importance about the development of various risk index for evaluating invasive plant risk.

• Journal of the Korean Society of Safety
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• v.32 no.2
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• pp.105-111
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• 2017

This research examined if job stress mediates the relationship between physical environmental risk and safety behavior of employees. In addition, we investigated whether perceived control moderates the physical environmental risk-job stress link. In order to test our hypotheses, 1005 employees in various fields of firms were participated. Using structural equation modeling(SEM), we conducted moderated mediation model analysis that elaborately test the hypotheses. The results demonstrated that job stress mediated the physical environmental risk-safety behavior link. Furthermore, the relationship between physical environmental risk and job stress was moderated by perceived control.

• The Journal of Information Systems
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• v.14 no.1
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• pp.227-249
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• 2005

In this research, four antecedents of trust ad the effect of trust and perceived risk on attitude and purchase intension in internet shopping malls is investigated. In survey, data were collected from 286 male and female internet shopping mall users, and then covariance structure modeling through Amos was used to test the 10 hypotheses. The survey results as follow: First, this research shows that institution base structural assurance and situational normality and knowledge-based familiarity are important antecedents on trust in internet shopping malls. Second, trust affected attitude and purchase intension. Third, it has a negative relationship between trust and perceived risk. But perceived risk does not influence attitude and purchase intension. This study contribute to understanding on the role of trust and perceived risk in internet shopping malls.