• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.63-72
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• 2007

The purpose of this study is to develop a traffic characteristic analysis, a correlation analysis with the variables of traffic characteristics, and accident estimation models while recognizing the seriousness of the traffic accidents. The analyses deal with the 181 4-legged signalized intersections that accounted for 1,183 out of 3,115 accidents in Cheongju in 2004. After measuring ADT, intersection area, average lane width, elevation, and other items as independent variables and the number of traffic accidents, the traffic accident rate (accidents per million entering vehicles) and equivalent property damage only (EPDO) figures as dependent variables which are estimated as influencing signalized intersection accidents, the estimation models are developed using correlation analysis and multiple regression analysis. In the analysis of the number of traffic accidents, the model indicates an $R^2$ of 0.612, and five independent variables are taken as significant factors. In the analysis of traffic accident rates, the model indicates an $R^2$ of 0.304 and five significant factors, including intersection area and ADT. Also, for the analysis or the EPDO numbers, which coincides with understanding the seriousness of the traffic accidents and the traffic characteristic analysis, the model indicates an $R^2$ of 0.559, and four independent variables (ADT, main street average lane width, elevation, and speed limit) as significant factors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.350-359
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• 2014

With the rapid growth of Internet, the importance of application traffic analysis is increasing for efficient network management. The statistical information in traffic flows can be efficiently utilized for application traffic identification. However, the packet out-of-order and retransmission occurred at the traffic collection point reduces the performance of the statistics-based traffic analysis. In this paper, we propose a novel method to detect and resolve the packet out-of-order and retransmission problem in order to improve completeness and accuracy of the traffic identification. To prove the feasibility of the proposed method, we applied our method to a real traffic analysis system using statistical flow information, and compared the performance of the system with the selected 9 popular applications. The experiment showed maximum 4% of completeness growth in traffic bytes, which shows that the proposed method contributes to the analysis of heavy flow.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.87-97
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• 2018

The traffic accident reports that are generated by the Traffic Broadcasting Networks(TBN) are unstructured data. It, however, has the value as some sort of real-time traffic information generated by the viewpoint of the drives and/or pedestrians that were on the roads, the time and spots, not the offender or the victim who caused the traffic accidents. However, the traffic accident reports, which are big data, were not applied to traffic accident analysis and traffic related research commonly. This study adopting text-mining technique was able to provide a clue for utilizing it for the impacts of traffic accidents. Seven years of traffic reports were grasped by this analysis. By analyzing the reports, it was possible to identify the road names, accident spot names, time, and to identify factors that have the greatest influence on other drivers due to traffic accidents. Authors plan to combine unstructured accident data with traffic reports for further study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.133-144
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• 2012

This study focused on estimating influential factors of traffic accidents and analyzing traffic accident severity of elderly and non elderly using traffic accident data. In order to reclassify elderly and non elderly traffic accident by a statistical method from entire traffic accident data, multiple discriminant analysis was applied. Also ordered logit model was applied for analyzing traffic accident severities using traffic accident severities as an independent variable and transportation facilities, road conditions and human characteristics as dependent variables. As results of the comparison between elderly and non elderly traffic accident, the traffic accident severity was affected by the age, types of traffic accidents, human characteristics and road conditions as well. Also, transportation facilities and road conditions affected to more elderly traffic accident than non elderly. Therefore, traffic accident severity would be decreased with the improvement of transportation facilities and road conditions for the elderly.

• Journal of Industrial Convergence
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• v.17 no.4
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• pp.53-58
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• 2019

It is important to collect and analyze the data from the traffic accident analysis system and the National Statistical Office to reduce the traffic accident rate of the elderly, who are the weakest. In particular, it is more important to analyze the data in areas where the elderly population is large and where accidents occur frequently. This paper visualizes and analyzes the data of elderly traffic accidents that occurred in recent 5 years in the area where many elderly people live in Buyeo-gun. The elderly traffic accident type, accident area, and location data of the elderly can be useful for the improvement measures and related decision making to reduce the elderly traffic accidents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.13-20
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• 2022

Road conditions and weather conditions are very important factors in the case of traffic accident fatalities in fog and ice sections that occur on roads in winter. In this paper, a simulation was performed to estimate the traffic accident risk rate assuming traffic accident prediction data. In addition, in this paper, in order to reduce traffic accidents and prevent traffic accidents, factor analysis and traffic accident fatality rates were predicted using the WEKA data mining technique and TENSOR FLOW open source data on traffic accident fatalities provided by the Korea Transportation Corporation.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.47-57
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• 2016

PURPOSES : This study aims to examine the differences between the existing traffic demand forecasting method and the traffic demand forecasting method considering future regional development plans and new road construction and expansion plans using a four-step traffic demand forecast for a more objective and sophisticated national highway maintenance. This study ultimately aims to present future pavement deterioration and budget forecasting planning based on the examination. METHODS : This study used the latest data offered by the Korea Transport Data Base (KTDB) as the basic data for demand forecast. The analysis scope was set using the Daejeon Metropolitan City's O/D and network data. This study used a traffic demand program called TransCad, and performed a traffic assignment by vehicle type through the application of a user equilibrium-based multi-class assignment technique. This study forecasted future traffic demand by verifying whether or not a realistic traffic pattern was expressed similarly by undertaking a calibration process. This study performed a life cycle cost analysis based on traffic using the forecasted future demand or existing past pattern, or by assuming the constant traffic demand. The maintenance criteria were decided according to equivalent single axle loads (ESAL). The maintenance period in the concerned section was calculated in this study. This study also computed the maintenance costs using a construction method by applying the maintenance criteria considering the ESAL. The road user costs were calculated by using the user cost calculation logic applied to the Korean Pavement Management System, which is the existing study outcome. RESULTS : This study ascertained that the increase and decrease of traffic occurred in the concerned section according to the future development plans. Furthermore, there were differences from demand forecasting that did not consider the development plans. Realistic and accurate demand forecasting supported an optimized decision making that efficiently assigns maintenance costs, and can be used as very important basic information for maintenance decision making. CONCLUSIONS : Therefore, decision making for a more efficient and sophisticated road management than the method assuming future traffic can be expected to be the same as the existing pattern or steady traffic demand. The reflection of a reliable forecasting of the future traffic demand to life cycle cost analysis (LCCA) can be a very vital factor because many studies are generally performed without considering the future traffic demand or with an analysis through setting a scenario upon LCCA within a pavement management system.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.8
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• pp.4577-4581
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• 2013

Background: The objective of this study was to determine the practice of skin cancer prevention among Malaysian road traffic police officers. Materials and Methods: This cross-sectional study involved 202 Malaysian Road Police Traffic officers. Inclusion criteria were those officers who work wearing white uniform regulating traffic. The survey took place at the Police Traffic Station, Jln Tun H.S. Lee, Kuala Lumpur, the main Head Quarters of Malaysian's Traffic Department where almost 600 police traffic officers are employed. The police traffic officers are given the task to take care of the traffic from the main office of the police station, then, according to the task, the officers drive to their given location for their duty. Each task is approved by the Chief Traffic Inspector of Kuala Lumpur. Data collected in this study were analyzed using SPSS 13, with the T-test for univariate analysis and multiple linear regression for multivariate analysis. Results: A total of 202 road traffic police officers participated. The majority were older than 30 years of age, male, Malay, married, with secondary education, with monthly income more than 2000 Ringgit Malaysia (66.3%, 91.1%, 86.6%, 84.7%, 96%, 66.3%; respectively). Regarding the practice of skin cancer prevention, 84.6% of the study participants were found to wear hats, 68.9% sunglasses and 85.6% clothing that covering most of the body but only 16.9% used a sunscreen when they were outdoors. When analysis of the factors that influenced the practice of skin cancer prevention was performed, univariate analysis revealed that gender, age and monthly income significantly influenced the practice of skin cancer prevention. For multivariate analysis, gender, monthly income and race significantly influenced the practice of using sunscreen among road traffic police officers (p<0.001, p=0.019, p=0.027; respectively). Conclusions: The practice of skin cancer prevention among the traffic police officers showed good practices in terms of wearinga hat, sun glasses and clothing that covers most of the body. However, the study revealed a poor practice of the use of sunscreen. The factors that influence the practice of sunscreen use were found to be gender, income, and race. The study suggests that more awareness campaign among traffic police officers is needed. Providing sunscreen for free for police traffic officers should be considered by the Police authorities.

• Korean Management Science Review
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• v.26 no.1
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• pp.161-169
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• 2009

A traffic analysis on the Internet has an advantage for obtaining the characteristics of transferred packets. There were many studies to understand the characteristics of the Internet traffic with mathematical statistical approach. The approach of this study is different from previous studies. We first introduced a virtual network concept to present the Internet as a simplified mathematical model. It also represents each traffic flowing on the Internet as a parallel Gaussian channel on the virtual network. We suggest the optimal capacity of each parallel Gaussian channel using some related studies on the Gaussian channel model.

• Journal of Korean Society of Transportation
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• v.10 no.3
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• pp.59-74
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• 1992

The change of industrial structure, the expansion of economic scale, the elevation of national life level and rapid motorization bring about social problems that are traffic accident, traffic congestion, etc. Especially, big traffic accidents bring about the great number of dead and wounded person with damage of property. But there are no study results available mainly focused on the big traffic accident analysis. Accordingly, this study is essentially for the factor analysis of big accident types including laws violation and the assaulting driver's death using Quantification ll method.