• International Journal of Highway Engineering
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• v.20 no.2
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• pp.67-74
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• 2018

PURPOSES : The goal of this study is the development of roundabout accident models for urban and non-urban areas. METHODS : This study performed a comparative analysis of the regional factors affecting accidents. Traffic accident data were collected for the period 2010~2014 from the TAAS data set of the Road Traffic Authority. To develop the roundabout accident models, the Poisson and negative binomial regression models were used. A total of 25 explanatory variables such as geometry, and traffic volume were used. RESULTS : The key findings are as follows: First, it was found that the null hypotheses that the number of accidents is the same should be rejected. Second, three Poisson regression accident models, which are statistically significant (${\rho}^2$ of 0.154 and 0.385) were developed. Third, it was noted that although the common variable of the three models (models I~III) is the number of entry lanes, the specific variables are entry lane width, roundabout sign, number of circulatory roadways, splitter island, number of exit lanes, exit lane width, number of approach roads, and truck apron. CONCLUSIONS : The results of this study can provide suggestive countermeasures for decreasing the number of roundabout accidents.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.755-763
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• 2008

This paper approaches the problem of option pricing in an incomplete market, where the underlying asset price process follows a compound Poisson model. We assume that the price process follows a compound Poisson model under an equivalent martingale measure and it converges weakly to the Black-Scholes model. First, we express the option price as the expectation of the discounted payoff and expand it at the Black-Scholes price to obtain a pricing formula with three unknown parameters. Then we estimate those parameters using the market option data. This method can use the option data on the same stock with different expiration dates and different strike prices.

• Journal of the Korea Concrete Institute
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• v.16 no.2 s.80
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• pp.195-204
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• 2004

Poisson's ratio due to multiaxial creep of concrete reported by existing experimental works was controversial. Poisson's ratio calculated from measured strain is very sensitive to small experimental error. This sensitivity make it difficult to find out whether the Poisson's ratio varies with time or remain constant, and whether the Poisson's ratio has different value with stress states or not. A new approach method is needed to resolve the discrepancy and obtain reliable results. This paper presents analytical study on multiaxial creep test results. Microplane model as a new approach method is applied to optimally fitting the test data extracted from experimental studies on multiaxial creep of concrete. Double-power law is used as a model to present volumetric and deviatoric creep evolutions on a microplane. Six parameters representing the volumetric and deviatoric compliance functions are determined from regression analysis and the optimum fits accurately describe the test data. Poisson's ratio is calculated from the optimum fits and its value varies with time. Regression analysis is also performed assuming that Poisson's ratio remains constant with time. Four parameters are determined for this condition, and the error between the optimum fits and the test data is slightly larger than that for six parameter regression results. The constant Poisson's ratio with time is obtained from four parameter analysis results and the constant value can be used in practice without serious error.

• 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.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.465-472
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• 2003

Creep Poisson's ratio reported by previous experimental studies on multiaxial creep of concrete was controversial. The Poisson's ratio is very sensitive to small experimental error that is inevitably induced, and the sensitivity may cause the controversy. It is difficulty to find out the properties on multiaxial creep of concrete. Therefore, a new approach method to analyze the test results is needed to precisely understand the properties on multiaxial creep of concrete. In this study, microplane model is used as a new approach method in analyzing the multiaxial creep test data. The six data sets extracted from the literature are fitted from regression analysis. Double-power law as a model representing volumetric and deviatoric creep evolutions on microplane is used, and six parameters in volumetric and deviatoric compliances are determined on the assumption that the volumetric and deviatoric creep strains are linearly proportional to corresponding stresses. The optimum fits give very accurate description of the test data. The Poisson's ratio calculated from the optimum fits varies with time and does not depends on the stress states, namely, uniaxial, biaxial, and triaxial stress states. Regression analysis is also performed on the assumption that the Poisson's ratio remains constant with titre. The constant Poisson's ratio can be use in practice without serious error.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.1-12
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• 2006

The aim of this study is to analyse a survey data on the number of charitable donations using a mixture of two Poisson regression models. The survey was conducted in 2002 by Volunteer 21, an nonprofit organization, based on Koreans, who were older than 20. The mixture of two Poisson distributions is used to model the number of donations based on the empirical distribution of the data. The mixture of two Poisson distributions implies the whole population is subdivided into two groups, one with lesser number of donations and the other with larger number of donations. We fit the mixture of Poisson regression models on the number of donations to identify significant covariates. The expectation-maximization algorithm is employed to estimate the parameters. We computed 95% bootstrap confidence interval based on bias-corrected and accelerated method and used then for selecting significant explanatory variables. As a result, the income variable with four categories and the volunteering variable (1: experience of volunteering, 0: otherwise) turned out to be significant with the positive regression coefficients both in the lesser and the larger donation groups. However, the regression coefficients in the lesser donation group were larger than those in larger donation group.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.120-121
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• 2023

Recently, there has been a continuous imbalance between the demand and supply in the shipping industry. Consequently, shipping companies are implementing blank sailing to adjust the supply of vessels and achieve a balance between demand and supply. Blank sailing can create negative ripple effects by delaying cargo transportation, so this study uses Poisson regression analysis,

• Journal of the Korean Society of Safety
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• v.29 no.5
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• pp.154-159
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• 2014

This study deals with the pedestrian accidents of intersections in case of Cheongju. The objective is to develop the pedestrian accident models using Tobit regression model. In pursuing the above, the pedestrian accident data from 2007 to 2011 were collected from TAAS data set of Road Traffic Authority. To analyze the accident, Poisson, negative binomial and Tobit regression models were utilized in this study. The dependent variable were the number of accident by intersection. Independent variables are traffic volume, intersection geometric structure and the transportation facility. The main results were as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of traffic island, crossing length and the pedestrian countdown signal systems were adopted in the above model.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.104-110
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• 2015

This study deals with the roundabout accidents. The goal of this study is to develop the sideswipe accident models at roundabout. In the pursuing the above, this study gives particular attentions to collecting the data of geometric structure and accidents of 54 roundabouts in Korea and developing the Poisson and negative binomial regression models. The main results are as follows. First, sideswipe accident is analyzed to be the highest frequency that is 39.5% of total accident data. Second, Poisson models which is statistically significant is developed. Finally, traffic volume per approach($X_1$), number of circulatory roadway($X_3$), operation of parking lot($X_4$) and width of circulatory roadway($X_6$) are adopted as the common variables. This study might be expected to give some implications to the accident research on the roundabout.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.53-59
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• 2017

PURPOSES : This study deals with traffic accidents involving trucks. The objective of this study is to develop a traffic accident model for trucks at roundabouts. METHODS : To achieve its objective, this study gives particular attention to develop appropriate models using Poisson and negative binomial regression models. Traffic accident data from 2007 to 2014 were collected from TAAS data set of road traffic authority. Thirteen explanatory variables such as geometry and traffic volume were used. RESULTS : The main results can be summarized as follows: (1) two statistically significant Poisson models (${\rho}^2=0.398$ and 0.435) were developed, and (2) the analysis revealed the common variables to be traffic volume, number of exit lanes, speed breakers, and truck apron width. CONCLUSIONS : Our modeling reveals that increasing the number of speed breakers and speed limit signs, and widening the truck apron width are important for reducing the number of truck accidents at roundabouts.