• Journal of Korean Society of Transportation
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• v.22 no.1 s.72
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• pp.63-72
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• 2004

In conducting traffic safety programs, it is very important to identify hazardous sites in appropriate manner. The rate qualify control method is generally used in identifying hazardous sites since it can interpret the sites in the statistic aspects. The rate qualify control method is based on the assumption that the occurrences of traffic crashes follow the Poisson's distribution in which the expected value of traffic crashes equals the variance of those. However, there is greater variability than expected statistically, we call this phenomenon over dispersion. This study analyzed the problem related to the rate quality control method under the over dispersed data, and established a methodology to solve the problem. As a result of test on the basis of the field data, the new approach produced more reasonable results than those of the Poisson based rate quality control method.

• 대한예방의학회:학술대회논문집
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• 2002.10a
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• pp.202-203
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• 2002

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5585-5593
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• 2014

This study tested the hypothesis that the significance of the heterogeneous dispersion parameter in safety performance function (SPF) used to estimate the expected crashes is affected by the endogenous heterogeneous prior distributions, and analyzed the impacts of the mis-specified dispersion parameter on the evaluation results for traffic safety countermeasures. In particular, this study simulated the Poisson means based on the heterogeneous dispersion parameters and estimated the SPFs using both the negative binomial (NB) model and the heterogeneous negative binomial (HNB) model for analyzing the impacts of the model mis-specification on the mean and dispersion functions in SPF. In addition, this study analyzed the characteristics of errors in the crash reduction factors (CRFs) obtained when the two models are used to estimate the posterior means and variances, which are essentially estimated through the estimated hyper-parameters in the heterogeneous prior distributions. The simulation study results showed that a mis-estimation on the heterogeneous dispersion parameters through the NB model does not affect the coefficient of the mean functions, but the variances of the prior distribution are seriously mis-estimated when the NB model is used to develop SPFs without considering the heterogeneity in dispersion. Consequently, when the NB model is used erroneously to estimate the prior distributions with heterogeneous dispersion parameters, the mis-estimated posterior mean can produce large errors in CRFs up to 120%.

• Journal of Practical Agriculture & Fisheries Research
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• v.6 no.1
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• pp.81-89
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• 2004

The effects of developed grape bags on the micro-climate changes of bag, physiological disorder, pathogenic decay, quality and harvest time evaluation in 'Campbell Early' grapevines were studied. The temperature and light transmittance of developed grape bags showed no differences compared with the onces of conventional bag and non-bagging, but relative humidity and the amount of water evaporation were changed in all treatments. The occurrence of unfertilized fruit, poorly colored fruit, russet and gray mold rot showed no significant difference in all treatment at harvest time. Developed grape bags decreased effectively the occurrence of cracking fruit and bitter rot in 'Campbell Early' fruit. There was no difference in growth of cluster and berry, soluble solids and total acidity in fruits, degree of skin color and bloom appearance at harvest time. The skin color and fruit boom and harvest time evaluation in developed grape bags were resulted excellent compared with the once of conventional bag and non bagging.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.197-204
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• 2002

교통사고예측 및 예방을 위해서는 실제적으로 도로설계과정에서 제어가 가능한 도로 기하구조요소에 대한 사고관계를 파악함이 타당하다. 즉, 도로의 설계자는 도로건설에 앞서 기하구조요소와 사고와의 관계를 현장자료를 통해 정확히 밝혀 도로설계에 반영해야 한다. 이를 위해, 교통사고의 빈도분포를 박히는 것은 가장 기본이 되는 일이며, 교통사고 예측모형개발에 선행되어야 한다. 일반적으로 교통사고건수의 경우 분산이 평균보다 큰 과분산(overdispersion)의 특징을 가지고 있어 음이항 분포를 따른다고 알려져 있다. 따라서 본 논문은 사고모형의 개발에 앞서, 사고발생지점에 대한 도로설계요소와 기타 잠재적인 사고발생 관련요인이 비교적 잘 파악되어있는 호남고속도로를 중심으로 평면 선형상 곡선부에 대하여 교통사고의 분포를 적합도 검정을 통해 알아보고자 하였다. 사고자료는 한국도로송사의 호남고속도로 5년(1996∼2000)간 자료를 분석에 맞게 정리하였으며, 강민욱과 송봉수(2002)에서 제시한 평면선형에 있어서의 구간분할법을 이용하여 배향곡선구간과 단일곡선구간에 대한 사고분석을 하였다. 적합도 분석결과, 예상대로 음이항분포가 사고건수를 설명하기에 가장 적합한 확률분포로 제시되었으며, 이를 통해 최우추정법을 이용한 음이항회귀모형을 개발하였다. 구간분할법을 적용한 음이항회귀모형의 경우, 기존의 확률회귀토형에 비하여 높은 결정계수를 갖았으며, 모형에서 적용된 기하구조요소로는 차량 노출계수, 곡선반경, 단위거리 당 편경사변화값 등이다.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.33-44
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• 2005

Railroad crossing crashes are fewer than road crashes, but with regard to crash severity, they can be serious injury crashes. There should be, therefore, enormous efforts to increase the safety of railroad crossings. The objective of this paper is to identify and understand factors associated with railroad crossing crashes. Statistical models are used to examine the relationships between crossing accidents and geometric elements of crossings. The results show the Poisson model is the most appropriate method for the crossing accidents, because overdispersion was not observed. This study identifies seven significant factors associated with railroad crossing crashes through the main and variant models. With regard to explanatory factors on crossing safety, the total traffic volume, daily train volume, presence of commercial area around crossings, distance of train detector from crossings, time duration between the activation of warning signals and gates, crossing types, and speed hump were found to affect the safety of railroad crossings.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.135-144
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• 2009

This study estimates the expected number of accidents in Kyungbuk Province to capitalize on experience gained from four years of accident history using the Empirical Bayes (EB) Method. The number of accidents of each site in Kyungbuk Province is recalculated using the Equivalent Property Damage Only (EPDO) method to reflect the severities of the accidents. A cluster analysis is performed to determine similar sites and a unique Safety Performance Function (SPF) is established for each site. The overdispersion parameter is built to correct the difference between the actual number of accidents and the underlying probability distribution. To adjust for varying traffic characteristics of each site, a relative weight is applied and eventually estimates the expected number of accidents. The results show that the highest accident sites are Kimcheon, Youngcheon, and Chilgok, but on the other hand the lowest is Gunwi.

• Journal of Practical Agriculture & Fisheries Research
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• v.7 no.1
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• pp.81-89
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• 2005

The experiment was conducted to evaluate the effect of fruit skin spray of the lime fertilizer in 'Campbell Early' grapes. The T-N, P, K, Ca and Mg of fruit skin and cluster weight, berry weight, cluster length showed no difference between control and lime fertilizer. But soluble solids in fruit was reduced by fruit skin spray of liquid calcium fertilizer extracted from oyster shell after bagging(LCaB). The anthocyanin content of fruit skin was decreased by air-slaked lime(HCa) and LCaB treatment. Also, occurrence of fruit skin bloom was significantly reduced by HCa and oyster shell powder(OS-CaP) treatment. The berry firmness was significantly increased through liquid calcium fertilizer extracted from oyster shell(LCa) and HCa treatment. Conspicuously, berry elasticity was rather decreased by OS-CaP treatment. However, there was no difference of weight loss of fruit among treatments during room temperature storage.

• Korean Chemical Engineering Research
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• v.54 no.1
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• pp.1-5
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• 2016

For obtain fermentable sugar, we conducted acid hydrolysis with lignocellulosic biomass without enzyme. The lignocellulosic biomass used pinus rigida and Palm residues (EFB; empty fruit bunches). In the acid hydrolysis, we consider the hydrolysis condition to reduce a denatured sugar. So this study was conducted 2-step acid hydrolysis. First-step hydrolysis used high concentration (72 wt%) sulfuric acid at $80^{\circ}C$. At the condition, we obtained 11.49 wt%, 32 wt% glucose conversion for pinus rigida and EFB. After the step, the liquor was dilute until 9~15 wt% acid concentration and conducted second hydrolysis at $50{\sim}120^{\circ}C$. In the second hydrolysis, we obtained maximum glucose conversion (pinus rigida 86.8 wt% (39 g/L) and EFB 95.3 wt% (32.4 g/L)) at 9 wt% acid concentration and $120^{\circ}C$ for 80 min. All samples through the process are analyzed on the basis of mass balance.