• Journal of Applied Reliability
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• v.17 no.1
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• pp.38-49
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• 2017

Purpose: The purpose of this study is to introduce the assessment model for industrial accidents prevention policy. Methods: 10 years of industrial accidents data are explored through EDA approach. Case control study is tried in order to assess the effectiveness of the measures taken by Korea Safety and Health Agency, Civilian, and 'Ministry of Employment and Labor'. Propensity score matching is used to match the characteristics of the two groups compared, and then case control study is again conducted. Next, logistic and Poisson regressions are used to assess the risk factors. Results: According to case control study involvement of 'Korea Safety and Health Agency' and 'Ministry of Employment and Labor' were not effective, but Civilian was. Propensity score matching leads to the same conclusion. Poisson regression reveals the impact of the risk factors on the industrial accidents. Industrial accidents occur more often as the number of employees grows. Mining, farming, fishing, 'transportation storage and telecommunication' and forestry have a higher level of industrial accidents but service industry has a lower level. It is odd that more involvement of Korea Safety and Health Agency, Civilian, and Ministry of Employment and Labor means more industrial accidents. Conclusion: 'Korea Safety and Health Agency', Civilian, and 'Ministry of Employment and Labor' seem to visit those industries with more industrial accidents.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.39-46
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• 2015

PURPOSES: The operational characteristics of roundabouts are generally influenced by location as well as traffic volume. The goal of this study is to develop urban and rural roundabout accident models and to discuss safety improvement guidelines based on the model. METHODS : To analyze accidents, count data models are utilized in this study. This study used accident data from 2010 to 2013 for 56 roundabouts collected from the Traffic Accident Analysis System (TASS) of Road Traffic Authority. Poisson and negative binomial regression models were developed for this study using NLOGIT 4.0. RESULTS : The main results are as follows. First, the hypotheses that there are distributional differences in the number of accidents and injuries/fatalities among rural and urban roundabouts were accepted. Second, Poisson and negative binomial regression accident models, which were all statistically significant, were developed. Seven independent variables, which were statistically significant, were adopted. Third, the common variable of models was evaluated to be traffic volume. CONCLUSIONS : This study developed two negative binomial roundabout accident models and suggested some accident reduction strategies. The results are expected to give some implications to the safety improvement of roundabout.

• Smart Media Journal
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• v.8 no.1
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• pp.82-91
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• 2019

This study provides the analysis and prediction of fruits diseases related to weather conditions (temperature, wind speed, solar power, rainfall and humidity) using Linear Model and Poisson Regression. The main goal of the research is to control the method of fruits diseases and also to prevent diseases using less agricultural pesticides. So, it is needed to predict the fruits diseases with weather data. Initially, fruit data is used to detect the fruit diseases. If diseases are found, we move to the next process and verify the condition of the fruits including their size. We identify the growth of fruit and evidence of diseases with Linear Model. Then, Poisson Regression used in this study to fit the model of fruits diseases with weather conditions as an input provides the predicted diseases as an output. Finally, the residuals plot, Q-Q plot and other plots help to validate the fitness of Linear Model and provide correlation between the actual and the predicted diseases as a result of the conducted experiment in this study.

• Journal of Preventive Medicine and Public Health
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• v.43 no.6
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• pp.543-548
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• 2010

Objectives: The objective of this study was to calculate sample size and power in an ongoing cohort, Korea radiation effect and epidemiology cohort (KREEC). Method: Sample size calculation was performed using PASS 2002 based on Cox regression and Poisson regression models. Person-year was calculated by using data from '1993-1997 Total cancer incidence by sex and age, Seoul' and Korean statistical informative service. Results: With the assumption of relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, sample size calculation was 405 events based on a Cox regression model. When the relative risk was assumed to be 1.5 then number of events was 170. Based on a Poisson regression model, relative risk=1.3, exposure:non-exposure=1:2 and power=0.8 rendered 385 events. Relative risk of 1.5 resulted in a total of 157 events. We calculated person-years (PY) with event numbers and cancer incidence rate in the nonexposure group. Based on a Cox regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, 136 245PY was needed to secure the power. In a Poisson regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, person-year needed was 129517PY. A total of 1939 cases were identified in KREEC until December 2007. Conclusions: A retrospective power calculation in an ongoing study might be biased by the data. Prospective power calculation should be carried out based on various assumptions prior to the study.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.103-110
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• 2012

PURPOSES : In Korea, over 70 percent of the land consists of mountainous and rolling area. Thus, tunnels continue its upward trend as road network are extended. In these circumstances, the importance of tunnel has been increased nowadays and then its safety investigation and research should be performed. This study is focus on confirming and improving the safety of tunnel. On tunnel hood, sunglare effect can irritate driver's behavior instantly and this can result in incident. METHODS : The study of this phenomenon is rarely conducted in domestic and foreign papers, so there is no proper measure for this. This study analyzes the driving environment of the effect of sunglare effect on tunnel hood. RESULTS : Traffic accidents stem from complex set of factors. This study build the Traffic Accident Prediction Models to find out the effect of sunglare effect on tunnel's hood. The independent variables are traffic volume, geometric design of road, length of tunnel and road side environment. Using these variables, this model estimates accident frequency on tunnel hood by Poisson regression model and Negative binomial regression model. Although Poisson regression model have more proper goodness of fit than Negative binomial regression model, Poisson regression model has overdipersion problem. So the Negative binomial regression model is used in this analysis. CONCLUSIONS : Consequently, the model shows that sunglare effect can play a role in driving safety on tunnel hood. As a result, the information of sunglare effect should be noticed ahead of tunnel hood so this can prevent drivers from being in hazard situation.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.65-76
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• 2013

Traffic accidents at signalized intersections have been increased annually so that it is required to examine the causation to reduce the accidents. However, the current existing accident models were developed mainly by using non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal the complicated causation for traffic accidents, though they are the right choice to study randomness and non-linearity of accidents. Therefore, it is required to utilize another statistical method to make up for the lack of the non-linear regression methods. This study developed accident prediction models for 4 legged signalized intersections with Poisson methods and compared them with structural equation models. This study used structural equation methods to reveal the complicated causation of traffic accidents, because the structural equation method has merits to explain more causational factors for accidents than others.

• Journal of the Korean Society of Safety
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• v.30 no.2
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• pp.70-76
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• 2015

This study deals with the traffic accident of circular intersections. The purpose of the study is to develop the accident models by traffic violation type. In pursuing the above, this study gives particular attention to analyzing various factors that influence traffic accident and developing such the optimal models as Poisson and Negative binomial regression models. The main results are the followings. First, 4 negative binomial models which were statistically significant were developed. This was because the over-dispersion coefficients had a value greater than 1.96. Second, the common variables in these models were not adopted. The specific variables by model were analyzed to be traffic volume, conflicting ratio, number of circulatory lane, width of circulatory lane, number of traffic island by access road, number of reduction facility, feature of central island and crosswalk.

• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.43-65
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• 2017

We propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest has the Poisson distribution and the time for the event follows the gamma-G family of distributions. The extended family of gamma-G failure-time models with long-term survivors is flexible enough to include many commonly used failure-time distributions as special cases. We consider a frequentist analysis for parameter estimation and derive appropriate matrices to assess local influence on the parameters. Further, various simulations are performed for different parameter settings, sample sizes and censoring percentages. We illustrate the performance of the proposed regression model by means of a data set from the medical area (gastric cancer).

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1337-1347
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• 2016

This study investigates factors affecting the number of insurance solicitor's turnovers of life insurance companies based on questionnaire about them. Since the response variable which is the number of insurance solicitor's turnovers is count data, it is analyzed by Poisson regression which is one of generalized regression. When work year in current company, which is direct influential factor on the number of insurance solicitor's turnovers, is controlled, affiliated corporation has been found to be the most influential factor. In addition, age, motivation to work as financial planner, monthly income, a number of average new contract per month, and final education have been identified to be important factors. If insurance solicitor's occupant organization is large company, the number of turnovers becomes small, but if the organization is general agent(GA), it becomes larger. When insurance solicitor's age is high, the number of insurance solicitor's turnovers are reduced. If the motivation to become a financial planner is due to acquaintance such as family and relatives, the number of turnovers becomes small.