• Journal of the Korean GEO-environmental Society
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• v.21 no.3
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• pp.13-21
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• 2020

The purpose of this study is to evaluate the concentrations of heavy metals in the marine sediments near the Masan bay and the Nakdong estuary, and to investigate the pollution intensity levels of six heavy metals using the existing pollution intensity assessment method. According to the US environmental protection agency, in the case of Cu, the B1 area was classified as severe pollution, while in Ni and Zn, it was classified as moderate pollution in some areas. According to the classification of Igeo, EF and PERF, the A and B regions were polluted by Cd. In particular, in the B1 region, Igeo, EF, and PERF values were the highest in all regions, and were regarded as serious pollution. According to the mean PEL quotient classification, which takes into account the effects of all six heavy metals, there is a 21% probability of toxicity from heavy metals in all regions. The highest concentration of Cd in the B1 region is 1.5 mg/kg. Therefore, the contamination of Cd contained in sediment near Masan Bay is serious, so it is necessary to clarify the cause and take careful approach to future treatment.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1289-1300
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• 2009

The double sampling scheme is effective in reducing the sampling cost. However, the doubly sampled data is contaminated by two types of error, namely false-positive and false-negative errors. These would make the statistical analysis more difficult, and it would require more sophisticate analysis tools. For instance, the Wald method for the interval estimation of a proportion would not work well. In fact, it is well known that the Wald confidence interval behaves very poorly in many sampling schemes. In this note, the property of the Wald interval is investigated in terms of the coverage probability and the expected width. An alternative confidence interval based on the Agresti-Coull's approach is recommended.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.909-916
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• 2010

This study aims to establish storage stability conditions for cook-chilled korean ethenic foods. In order to achieve this aims, we establish a probability model of microbial counts of cook-chilled korean side dishes product-seasoned soybean sprouts. And seasoned soybean sprouts were stored during 1 to 5 days under constant temperature conditions at 0, 5, 10 and $15^{\circ}C$. Next we find confidence intervals for variation in the microbiological quality of seasoned soybean sprouts.

• Journal of the Korean earth science society
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• v.31 no.4
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• pp.301-312
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• 2010

Geochemical data have been regarded as one of the important environmental variables in the environmental management. Since they are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction for further analysis. The main objective of this paper is to exemplify how indicator geostatistics can be effectively applied to geochemical data processing for providing decision-supporting information as well as spatial distribution of the geochemical data. A whole geostatistical analysis framework, which includes probabilistic uncertainty modeling, classification and risk analysis, was illustrated through a case study of cadmium mapping. A conditional cumulative distribution function (ccdf) was first modeled by indicator kriging, and then e-type estimates and conditional variance were computed for spatial distribution of cadmium and quantitative uncertainty measures, respectively. Two different classification criteria such as a probability thresholding and an attribute thresholding were applied to delineate contaminated and safe areas. Finally, additional sampling locations were extracted from the coefficient of variation that accounts for both the conditional variance and the difference between attribute values and thresholding values. It is suggested that the indicator geostatistical framework illustrated in this study be a useful tool for analyzing any environmental variables including geochemical data for decision-making in the presence of uncertainty.

• Journal of Environmental Impact Assessment
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• v.29 no.4
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• pp.286-297
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• 2020

This research studied human health risk assessment of PAHs (Polycyclic Aromatic Hydrocarbons) in road dust sediments collected from 6 sites in four different cities in Korea. PAHs are well known to be human carcinogens and toxic compounds that are commonly generated from incomplete combustion of fuels and energy products. Such compounds which is absorbed by atmospheric suspended dust can be emitted into air in gaseous form and often deposited on road dust sediments. The PAHs which is deposited on sediment particles can also be re-dispersed by vehicles or winds on the road surface. It can be harmful for humans when exposed via breathing, ingestion and dermal contact. This study examined human health risk assessment of PAHs in deposited road dust sediments. Results showed that the excess cancer risk estimates were above 1.0×10-6 at main traffic roads and resident area in Ulsan city. According to the result of deterministic risk assessment, dermal-contact was the major pathway, while the contribution of the risk from inhalation was less than 1%. The probabilistic risk assessment showed similar levels of cancer risk derived from the deterministic risk assessment. The result of sensitivity analysis reveal that exposure time is the most contributing factor (69%). Since the values of carcinogenic risk assessment were higher than 1.0 × 10^-6, further detailed monitoring and refined risk assessment for PAHs may be required to identify more reliable and potential cancer risks for those who live in the study locations in Ulsan city.

• Korean Journal of Food Science and Technology
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• v.52 no.6
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• pp.661-669
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• 2020

Samgak-Kimbap is a popular ready-to-eat (RTE) food at convenience stores, in Korea. Although Samgak-Kimbap is distributed through the cold chain supply system, inappropriate temperature storage conditions prior to consumption are a cause of concern. The objective of this study was to evaluate the risk of Staphylococcus aureus growth in Samgak-Kimbap in the retail market. The prevalence and contamination levels of S. aureus in Samgak-Kimbap (n=170) were monitored, and the predictive growth model of a five-strain cocktail of enterotoxin-producing S. aureus (SEA, SEB, SEC, SED, and SEE) was developed in Samgak-Kimbap as a function of temperature (4, 10, 11, 20, 25, and 37℃). We could not observe the growth of S. aureus and enterotoxin-producing S. aureus in Samgak-Kimbap at temperatures below 10℃. The probability of illness with S. aureus per serving of Samgak-Kimbap was 1.44×10-10 per day. The most influential factor in increasing the risk of foodborne illnesses was the contamination level of S. aureus in Samgak-Kimbap.

• Korean Journal of Food Science and Technology
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• v.50 no.6
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• pp.621-628
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• 2018

We developed a quantitative microbial risk assessment model for determning the effect of seasoning on Clostridium perfringens behavior in beef jerky under aerobic and anaerobic conditions. C. perfringens was not detected (<0.5 log CFU/g) in beef jerky samples (n=275), regardless of storage conditions or the presence of seasoning. Survival models of C. perfringens on beef jerky were developed as a function of temperature (10, 17, 25, and $35^{\circ}C$). Risk of C. perfringens due to the consumption of beef jerky was estimated with @RISK and FDA-iRISK. The probability of foodborne illness due to C. perfringens through consumption of seasoned, vacuum packed beef jerky was estimated to be $2.77{\times}10^{-16}$ per person per day. Overall, the risk of contamination of beef jerky with C. perfringens is very low.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.53-60
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• 2010

LPG(Liquefied Petroleum Gas) vehicles in metropolitan area are being applied to improve air quality and have been proven effective for the reduction of air pollutant. In addition, LPG demand is growing rapidly as an environmentally friendly energy source and its gas station is also increasing every year. Consequently, this study tries to find out the influence of flame caused by the VCE(Vapor Cloud Explosion) in filling station on the adjacent combustibles and people by simulating relevant quantity of TNT. In addition, the damage estimation was conducted by using API regulations. If the scale of the radiation heat is known by calculating the distance of flame influence from the explosion site, the damage from the site can be easily estimated. And the accident damage was estimated by applying the influence on the adjacent structures and people into the PROBIT model. According to the probit analyze, the spot which is 30m away from the flame has 100% of the damage probability by the first-degree burn, 99.2% of the damage probability by the second-degree burn and 93.4% of the death probability by the fire.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.99-109
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• 2019

We compared the confidence intervals of estimators using various bootstrap methods for a Random Coefficient Autoregressive(RCA) model. We consider a Quasi score estimator and M-Quasi score estimator using Huber, Tukey, Andrew and Hempel functions as bounded functions, that do not have required assumption of distribution. A standard bootstrap method, percentile bootstrap method, studentized bootstrap method and hybrid bootstrap method were proposed for the estimations, respectively. In a simulation study, we compared the asymptotic confidence intervals of the Quasi score and M-Quasi score estimator with the bootstrap confidence intervals using the four bootstrap methods when the underlying distribution of the error term of the RCA model follows the normal distribution, the contaminated normal distribution and the double exponential distribution, respectively.

• Food Science and Preservation
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• v.30 no.3
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• pp.459-471
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• 2023

The Bayesian network (BN) model was applied to analyze the characteristic variables that affect compliance with safety inspections of farmed eel during the production stage, using the data from 30,063 cases of eel aquafarm safety inspection in the Integrated Food Safety Information Network (IFSIN) from 2012 to 2021. The dataset for establishing the BN model included 77 non-conforming cases. Relevant HACCP data, geographic information about the aquafarms, and environmental data were collected and mapped to the IFSIN data to derive explanatory variables for nonconformity. Aquafarm HACCP certification, detection history of harmful substances during the last 5 y, history of nonconformity during the last 5 y, and the suitability of the aquatic environment as determined by the levels of total coliform bacteria and total organic carbon were selected as the explanatory variables. The highest achievable eel aquafarm noncompliance rate by manipulating the derived explanatory variables was 24.5%, which was 94 times higher than the overall farmed eel noncompliance rate reported in IFSIN between 2017 and 2021. The established BN model was validated using the IFSIN eel aquafarm inspection results conducted between January and August 2022. The noncompliance rate in the validation set was 0.22% (15 nonconformances out of 6,785 cases). The precision of BN model prediction was 0.1579, which was 71.4 times higher than the non-compliance rate of the validation set.