• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.157-167
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• 2017

Millions of People die every year from diseases caused by exposure to outdoor air pollution. Especially, one of the most severe types of air pollution is fine particulate matter (PM10, PM2.5). South Korea also has been suffered from severe PM. This paper analyzes regional risks induced by PM10 and PM2.5 that have affected domestic area of Korea during 2014~2016.3Q. We investigated daily maxima of PM10 and PM2.5 data observed on 284 stations in South Korea, and found extremely high outlier. We employed extreme value distributions to fit the PM10 and PM2.5 data, but a single distribution did not fit the data well. For theses reasons, we implemented extreme mixture models such as the generalized Pareto distribution(GPD) with the normal, the gamma, the Weibull and the log-normal, respectively. Next, we divided the whole area into 16 regions and analyzed characteristics of PM risks by developing the FN-curves. Finally, we estimated 1-month, 1-quater, half year, 1-year and 3-years period return levels, respectively. The severity rankings of PM10 and PM2.5 concentration turned out to be different from region to region. The capital area revealed the worst PM risk in all seasons. The reason for high PM risk even in the yellow dust free season (Jun. ~ Sep.) can be inferred from the concentration of factories in this area. Gwangju showed the highest return level of PM2.5, even if the return level of PM10 was relatively low. This phenomenon implies that we should investigate chemical mechanisms for making PM2.5 in the vicinity of Gwangju area. On the other hand, Gyeongbuk and Ulsan exposed relatively high PM10 risk and low PM2.5 risk. This indicates that the management policy of PM risk in the west side should be different from that in the east side. The results of this research may provide insights for managing regional risks induced by PM10 and PM2.5 in South Korea.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.311-316
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• 2016

Breast cancer is one of the most common causes of cancer mortality in Iran. Social determinants of health are among the key factors affecting the pathogenesis of diseases. This cross-sectional study aimed to determine the social determinants of breast cancer survival time with parametric and semi-parametric regression models. It was conducted on male and female patients diagnosed with breast cancer presenting to the Cancer Research Center of Shohada-E-Tajrish Hospital from 2006 to 2010. The Cox proportional hazard model and parametric models including the Weibull, log normal and log-logistic models were applied to determine the social determinants of survival time of breast cancer patients. The Akaike information criterion (AIC) was used to assess the best fit. Statistical analysis was performed with STATA (version 11) software. This study was performed on 797 breast cancer patients, aged 25-93 years with a mean age of 54.7 (${\pm}11.9$) years. In both semi-parametric and parametric models, the three-year survival was related to level of education and municipal district of residence (P<0.05). The AIC suggested that log normal distribution was the best fit for the three-year survival time of breast cancer patients. Social determinants of health such as level of education and municipal district of residence affect the survival of breast cancer cases. Future studies must focus on the effect of childhood social class on the survival times of cancers, which have hitherto only been paid limited attention.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.2
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• pp.223-230
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• 2012

The strength of brittle material has commonly been characterized by a normal distribution or Weibull distribution, but it may fit the gamma distribution for some material. The use of an extreme value distribution is proper when the largest values of a set of stresses dominate the failure of the material. This paper presents a formula for reliability estimation based on stress-strength interference theory that is applicable when the strength of material is distributed like a gamma distribution and the stress is distributed like an extreme value distribution. We verified the validity of the equation for the reliability estimation by examining the relationships among the factor of safety, the coefficient of variation, and the reliability. The required minimum factor of safety and the highest allowable coefficient of variation of stress can be estimated by choosing an objective reliability and estimating the reliabilities obtained for various factors of safety and coefficients of variation.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5571-5575
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• 2014

Background: The ability to predict the survival time of breast cancer patients is important because of the potential high morbidity and mortality associated with the disease. To develop a predictive inference for determining the survival of breast cancer patients, we applied a novel Bayesian method. In this paper, we propose the development of a databased statistical probability model and application of the Bayesian method to predict future survival times for White Hispanic female breast cancer patients, diagnosed in the US during 1973-2009. Materials and Methods: A stratified random sample of White Hispanic female patient survival data was selected from the Surveillance Epidemiology and End Results (SEER) database to derive statistical probability models. Four were considered to identify the best-fit model. We used three standard model-building criteria, which included Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) to measure the goodness of fit. Furthermore, the Bayesian method was used to derive future survival inferences for survival times. Results: The highest number of White Hispanic female breast cancer patients in this sample was from New Mexico and the lowest from Hawaii. The mean (SD) age at diagnosis (years) was 58.2 (14.2). The mean (SD) of survival time (months) for White Hispanic females was 72.7 (32.2). We found that the exponentiated Weibull model best fit the survival times compared to other widely known statistical probability models. The predictive inference for future survival times is presented using the Bayesian method. Conclusions: The findings are significant for treatment planning and health-care cost allocation. They should also contribute to further research on breast cancer survival issues.

• Environmental Analysis Health and Toxicology
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• v.10 no.1_2
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• pp.21-35
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• 1995

Risk assessment processes, which include processes for the estimation of human cancer potency using animal bioassay data and calculation of human exposure, entail uncertainties. In the exposure assessment process, exposure scenarios with various assumptions could affect the exposure amount and excess cancer risk. We compared risk estimates among various exposure scenarios of vinyl chloride, trichloroethylene and tetrachloroethylene in tap water. The contaminant concentrations were analyzed from tap water samples in Seoul from 1993 to 1994. The oral and inhalation cancer potencies of the contaminants were estimated using multistage, Weibull, lognormal, and Mantel-Bryan model in TOX-RISK computer software. In the first case, human excess cancer risk was estimated by the US EPA method used to set the MCL(maximum contaminant level). In the second and third case, the risk was estimated for multi-route exposure with and without adopting Monte-Carlo simulation, respectively. In the second case, exposure input parameters and cancer potencies used probability distributions, and in the third case, those values used point estimates(mean, and maximum or 95% upper-bound value). As a result, while the excess cancer risk estimated by US EPA method considering only direct ingestion tended to be underestimated, the risk which was estimated by considering multi-route exposure without Monte-Carlo simulation and then using the maximum or 95% upper-bound value as input parameters tended to be overestimated. In risk assessment for volatile organic compounds, considering multi-route exposure with adopting Monte-Carlo analysis seems to provide the most reasonable estimations.

• Clinical and Experimental Pediatrics
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• v.63 no.9
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• pp.361-367
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• 2020

Background: Length of stay is a significant indicator of care effectiveness and hospital performance. Owing to the limited number of healthcare centers and facilities, it is important to optimize length of stay and associated factors. Purpose: The present study aimed to investigate factors associated with neonatal length of stay in the neonatal intensive care unit (NICU) using parametric and semiparametric models and compare model fitness according to Akaike information criterion (AIC) between 2016 and 2018. Methods: This retrospective cohort study reviewed 600 medical records of infants admitted to the NICU of Bandar Abbas Hospital. Samples were identified using census sampling. Factors associated with NICU length of stay were investigated based on semiparametric Cox model and 4 parametric models including Weibull, exponential, log-logistic, and log-normal to determine the best fitted model. The data analysis was conducted using R software. The significance level was set at 0.05. Results: The study findings suggest that breastfeeding, phototherapy, acute renal failure, presence of mechanical ventilation, and availability of central venous catheter were commonly identified as factors associated with NICU length of stay in all 5 models (P<0.05). Parametric models showed better fitness than the Cox model in this study. Conclusion: Breastfeeding and availability of central venous catheter had protective effects against length of stay, whereas phototherapy, acute renal failure, and mechanical ventilation increased length of stay in NICU. Therefore, the identification of factors associated with NICU length of stay can help establish effective interventions aimed at decreasing the length of stay among infants.

• Journal of Preventive Medicine and Public Health
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• v.29 no.1 s.52
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• pp.27-41
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• 1996

This study described methods to predict human health risk associated with exposure to environmental carcinogens using animal bioassay data. Also, biological assumption for various dose-response models were reviewed. To illustrate the process of risk estimate using relevant dose-response models such as Log-normal, Mantel-Bryan, Weibull and Multistage model, we used four animal carcinogenesis bioassy data of chloroform and chloroform concentrations of tap water measured in large cities of Korea from 1987 to 1995. As a result, in the case of using average concentration in exposure data and 95% upper boud unit risk of Multistge model, excess cancer risk(RISK I) was about $1.9\times10^{-6}$, in the case of using probability distribution of cumulative exposure data and unit risks, those risks(RISK II) which were simulated by Monte-Carlo analysis were about $2.4\times10^{-6}\;and\;7.9\times10^{-5}$ at 50 and 95 percentile, respectively. Therefore risk estimated by Monte-Carlo analysis using probability distribution of input variables may be more conservative.

• Korean Journal of Veterinary Research
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• v.39 no.4
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• pp.838-845
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• 1999

To determine the prognostic factors for survival of dogs infected with canine parvovirus, clinical and laboratory data of 35 dogs with clinical signs compatible with canine parvoviral enteritis admitted to the Veterinary Medical Teaching Hospital, Seoul National University during the period 1997-1998 were collected. Dogs were grouped by some major covariates, which can be considered as guides to the relative prognosis of dogs in the different subgroups. The Kaplan-Meier survival analysis and Weibull proportional hazard model were used to estimate overall survival, evaluate the comparability between groups, and identify potential prognostic factors. The overall survival rate for all dogs was 45.7% over the study period, and the Kaplan-Meier estimate of one week survival was 0.4989. Gender was the most favorable prognosis ; male dog (median, 6 days) had significantly higher risk of dying than female dog (median, 17 days ; p = 0.0023). In addition to gender, age was significantly associated with survival, with juvenile dogs less than 6-month-old having higher risk (p = 0.0359). Dogs that vaccinated with complete protocol (p = 0.0374) and those of having higher value of mean corpuscular volume (p = 0.0346) were found to be of prognostic importance. The 7 dogs in which white blood cell count of less than 2000 had shorter median survival time (3 days) than the remaining 28 dogs (8 days), but no statistical significance was found between leukopenic and survival. The distribution of packed cell volume and hemoglobin measurement was such that the overall risk of dying in the two groups was comparable. Further studies are needed to more accurately assess these results.

• Journal of Korean Society on Water Environment
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• v.23 no.1
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• pp.87-96
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• 2007

In this paper a methodology of identifying individual pipes according to the internal and external characteristics of pipe is developed, and the methodology is applied to a case study water distribution pipe break database. Using the newly defined individual pipes the hazard rates of the cast iron 6 inch pipes are modeled by implementing the proportional hazards modeling approach for consecutive pipe failures. The covariates to be considered in the modeling procedures are selected by considering the general availability of the data and the practical applicability of the modeling results. The individual cast iron 6 inch pipes are categorized into seven ordered survival time groups according to the total number of breaks recorded in a pipe to construct distinct proportional hazard model (PHM) for each survival time group (STG). The modeling results show that all of the PHMs have the hazard rate forms of the Weibull distribution. In addition, the estimated baseline survivor functions show that the survival probabilities of the STGs generally decrease as the number of break increases. It is found that STG I has an increasing hazard rate whereas the other STGs have decreasing hazard rates. Regarding the first failure the hazard ratio of spun-rigid and spun-flex cast iron pipes to pit cast iron pipes is estimated as 1.8 and 6.3, respectively. For the second or more failures the relative effects of pipe material/joint type on failure were not conclusive. The degree of land development affected pipe failure for STGs I, II, and V, and the average hazard ratio was estimated as 1.8. The effects of length on failure decreased as more breaks occur and the population in a GRID affected the hazard rate of the first pipe failure.

• Journal of Korean Society on Water Environment
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• v.33 no.6
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• pp.626-639
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• 2017

Based on an ecological monitoring in a Korean stream (Gapyeong), Habitat Suitability Index (HSI) of nine fish species was developed for three physical habitat factors : current velocity, water depth and substrate. The species were chosen based on their abundance and frequency in the fish community of the Gapyeong stream. The Weibull model was used as the probability density function to analyze the distribution and number of each fish species according to the three identified physical factors, which showed good results. This HSI equation has advantages because it statistically expresses habitat preferences of fish species simply and clearly. From that, we can quantitatively deduce the central tendency and variation of environmental factors for fish distribution. The selected fish species showed different preferences for each habitat factor respectively. Although there are some exceptions, the distribution and abundance of individual species of nektonic fish (Zacco koreanus, Zacco platypus, Microphysogobio longidorsalis and Pungtungia herzi) were positively skewed to deep water and fine substrate while riffle-benthic fish (Koreocobitis rotundicaudata and Coreoleuciscus splendidus) were normally distributed at the shallow and coarse substrate zone. It seems that the species showing the positively skewed distribution to the current, Z. koreanus, Z. platypus, M. longidorsalis and P. herzi have adapted themselves to the fast current and have expanded their niche.