• Water for future
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• v.29 no.6
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• pp.179-188
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• 1996

The chronical sequences of daily precipitation are of great practical importance in the planning and operational processes of water resources system. A sequence of days with alternate dry day and wet day can be generated by two state Markov chain model that establish the subsequent daily state as wet or dry by previously calculated vconditional probabilities depending on the state of previous day. In this study, a synthetic generation model for obtaining the daily precipitation series is presented by classifying the precipitation amount in wet days into multi-states. To apply multi-state Markov chain model, the daily precipitation amounts for wet day are rearranged by grouping into thirty states with intervals for each state. Conditional probabilities as transition probability matrix are estimated from the computational scheme for stepping from the precipitation on one day to that on the following day. Statistical comparisons were made between the historical and synthesized chracteristics of daily precipitation series. From the results, it is shown that the proposed method is available to generate and simulate the daily precipitation series with fair accuracy and conserve the general statistical properties of historical precipitation series.

• Health Policy and Management
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• v.24 no.1
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• pp.56-70
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• 2014

Background: Korea shows rapid population aging and increase in healthcare service use and expenditure. Also, this would be accelerated because of the baby boomers who will be 65 years old and more in 2020. Chronic disease is another reason that increases the use of healthcare service and expenditure of the middle- and old-aged households. Catastrophic health expenditure (CHE) is the index which can indicate the households' burden of health spending. Despite the importance, there are few studies on CHE of middle- and old-aged households and especially no panel study yet. This is the reason that this study is carried out. Methods: This study used 3-year data from the Korea Welfare Panel Study conducted from 2009 to 2011. We defined CHE if a household's health expenditure is equal or greater than the threshold value if income remaining after subsistence needs has been met. We used 4 different threshold values which are 10%, 20%, 30%, and 40%. In order to look at the households which experienced CHE, we conducted panel logit analysis after correspondence analysis and conditional transition probability analysis. Results: This study showed three notable results. First, there has been a difference among age groups, which implies that the older people are, the more easily they can experience CHE. Second, the households with no private insurance are shown to have a higher CHE occurrence rate. Lastly, there has been a significant difference among the kinds of chronic diseases. The households which have cancer, cerebrovascular disease, and heart disease have a higher CHE occurrence rate. However, the households with diabetes have no significant effects to CHE occurrence. Also, hypertension has a negative effect to the occurrence. Conclusion: With the results, it can be implied that elderly people with chronic disease are more needed in medical coverage and healthcare. Also, private insurance can play its role in protecting households from CHE. Therefore, it needs to conduct studies on CHE especially about different age groups, private insurance, and chronic disease.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.10
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• pp.4339-4345
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• 2015

Occupational exposure to wood dust is one cause of nasopharyngeal cancer (NPC); however, assessing this exposure remains problematic. Therefore, the objective of this study was to develop a semi-quantitative exposure assessment method and then utilize it to evaluate the association between occupational exposure to wood dust and the development of NPC. In addition, variations in risk by histology were examined. A case-control study was conducted with 327 newly diagnosed cases of NPC at the National Cancer Institute and regional cancer centers in Thailand with 1:1 controls matched for age, gender and geographical residence. Occupational information was obtained through personal interviews. The potential probability, frequency and intensity of exposure to wood dust were assessed on a job-by-job basis by experienced experts. Analysis was performed by conditional logistic regression and presented in odds ratio (ORs) estimates and 95% confidence intervals (CI). Overall, a non significant relationship between occupational wood dust exposure and NPC risk for all subjects was observed (ORs=1.61, 95%CI 0.99-2.59); however, the risk became significant when analyses focused on types 2 and 3 of NPC (ORs=1.62, 95%CI 1.03-2.74). The significant association was stronger for those exposed to wood dust for > 10 year (ORs=2.26, 95%CI 1.10-4.63), for those with first-time exposure at age > 25 year (ORs=2.07, 95%CI 1.08-3.94), and for those who had a high cumulative exposure (ORs=2.17, 95%CI 1.03-4.58) when compared with those considered unexposed. In conclusion, wood dust is likely to be associated with an increased risk of type 2 or 3 NPC in the Thai population. The results of this study show that semi-quantitative exposure assessment is suitable for occupational exposure assessment in a case control study and complements the information from self-reporting.

• Atmosphere
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• v.27 no.1
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• pp.41-54
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• 2017

Organic carbon (OC) and elemental carbon (EC) in $PM_{2.5}$ were measured using Sunset OC/EC Field Analyzer at Seoul Hwangsa Monitoring Center from March to April, 2016. The mean concentrations of OC and EC during the entire period were $4.4{\pm}2.0{\mu}gC\;m^{-3}$ and $1.4{\pm}0.6{\mu}gC\;m^{-3}$, respectively. OC/EC ratio was $3.4{\pm}1.0$. The average concentrations of $PM_{10}$ and $PM_{2.5}$ were $57.4{\pm}25.9$ and $39.7{\pm}19.8{\mu}g\;m^{-3}$, respectively, which were detected by an optical particle counter. The OC and EC peaks were observed in the morning, which were impacted by vehicle emission, however, their diurnal variations were not noticeable. This is determined to be contributed by the long-range transported OC or secondary formation via photochemical reaction by volatile organic compounds at afternoon. A conditional probability function (CPF) model was used to identify the local source of pollution. High concentrations of $PM_{10}$ and $PM_{2.5}$ were observed from the westerly wind, regardless of wind speed. When wind velocity was high, a mixing plume of dust and pollution during long-range transport from China in spring was observed. In contrast, pollution in low wind velocity was from local source, regardless of direction. To know the effect of long-range transport on pollution, a concentration weighted trajectory (CWT) model was analyzed based on a potential source contribution function (PSCF) model in which 75 percentiles high concentration was picked out for CWT analysis. $PM_{10}$, $PM_{2.5}$, OC, and EC were dominantly contributed from China in spring, and EC results were similar in both PSCF and CWT. In conclusion, Seoul air quality in spring was mainly affected by a mixture of local pollution and anthropogenic pollutants originated in China than the Asian dust.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.539-553
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• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.515-523
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• 2015

This study reviewed 612 DP LOP(Loss of Position) incident reports which submitted to IMCA from 2001~2010 and identified 103 human error caused incidents and classified it through HFACS. And, this study analysis of conditional probability of human error on DP LOP incidents through application of bayesian network. As a result, all 103 human error related DP LOP incidents were caused by unsafe acts, and among unsafe acts 70 incidents(68.0 %) were related to skill based error which are the largest proportion of human error causes. Among skill based error, 60(58.3%) incidents were involved inadvertent use of controls and 8(7.8%) incidents were involved omitted step in procedure. Also, 21(20.8%) incidents were involved improper maneuver because of decision error. Also this study identified that unsafe supervision(68%) is effected as the largest latent causes of unsafe acts through application to bayesian network. As a results, it is identified that combined analysis of HFACS and bayesian network are useful tool for human error analysis. Based on these results, this study suggest 9 recommendations such as polices, interpersonal interaction, training etc. to prevent and mitigate human errors during DP operations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.329-338
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• 2019

In this study, we analyze consumer preferences based on the agricultural box scheme attributes, and make a suggestion for business revival. We estimate the marginal willingness to pay (MWTP) for box scheme attributes using a choice experiment. Attributes include the bundle method, the delivery method, and price. To select an efficient model for statistical analysis, we evaluate the conditional logit model, heteroscedastic extreme value model(HEV model), multinomial probit model, and mixed logit model under different assumptions. The results of these four models show that the bundle method, the delivery method, and price are statistically significant in explaining the probability of participation in a box scheme. The results of likelihood ratio tests show that the heteroscedastic extreme value model is the most appropriate for our survey data. The results also indicate that MWTP for a change from fixed type to selection type is KRW 7,096.6. MWTP for a change from parcel service to direct delivery and cold-chain delivery are KRW 3,497.5 and KRW 7,532.7, respectively. The results of this study may contribute to the government's local food policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• 한국노년학
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• v.31 no.1
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• pp.15-31
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• 2011

The purpose of this study is to explore the transition to retirement of the middle-aged in Korea according to the notion of "the career job" and "the bridge job". In order to scrutinize basic elements for the transition, three aspects such as the job history of the middle-aged, the characteristics of the demographic and economic status were investigated through the one to three wave of Korean Retirement and Income Study(KReIS). In addition, the characteristics of the career job and the bridge job were analyzed by both descriptive statistics and the conditional transition probability. Moreover, the influential factors to the job status of the middle-aged were examined by the multi-nominal logistic regression. The results of the study are as followed: first, gradual retirement is increasing in the transition to retirement of the middle-aged in Korea. Over time, the career job is decreasing whilst bridge job is increasing. However, the quality of the bridge job is poorer than the career job in terms of wage, employment status, industry, and occupation. Lastly, the middle-aged who work in the bridge job have vulnerable characteristics, so they work in the bridge job to supplement their economic needs. The results can be influential in the adjustment of the labor policies for the middle-aged in Korea. Moreover, the partial pension system could be a good alternative since the pension system is needed to protect the vulnerable situation of the middle-aged in Korea.

• 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.