• Archives of Craniofacial Surgery
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• v.19 no.4
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• pp.270-274
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• 2018

Background: Nasal bone fractures occur frequently because the nasal bone is located at the forefront of the face. The goal of this study was to examine the cause, change in severity, change in incidence, and demographics of nasal bone fracture according to today's lifestyle. Methods: A total of 2,092 patients diagnosed as having nasal bone fractures at our department between 2002 and 2017 were included in this study. We retrospectively examined patients' medical records to extract information regarding age, sex, cause of injury, combined facial bone fractures, and related injuries such as skull base fracture, spinal cord injury, brain hemorrhage, and other bone fractures. Fracture severity was classified by nasal bone fracture type. Results: No statistically significant difference was found in annual number of patients treated for nasal bone fracture. The proportion of patients who underwent closed reduction was significantly decreased over time for those with nasal bone fractures caused by traffic accidents. However, it was not significantly changed for those with nasal bone fractures due to other causes. The number of patients with combined facial bone fractures increased over time. Incidences of severe nasal bone fracture also increased over time. Conclusion: The study suggested that there is a decrease in the frequency and increase in the severity of nasal bone fracture due to traffic accident. Many protective devices prevent nasal bone fractures caused by a small amount of external force; however, these devices are not effective against higher amounts of external force. This study highlights the importance of preoperative thorough evaluation to manage patients with nasal bone fractures due to traffic accident.

• Journal of Auto-vehicle Safety Association
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• v.7 no.2
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• pp.15-18
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• 2015

The availability of in-depth accident data is a prerequisite for each efficient traffic safety management system. Identification and definition of the relevant problem together with knowledge of the data and parameters describing this problem is essential for its successful solution. Comprehensive, up-to-date, accident data is needed for recognition of the scope of road safety problems and for raising public awareness. Reliable and relevant data enable the identification of the contributory factors of the individual accidents, and an unveiling of the background of the risk behaviour of the road users. It offers the best way to explore the prevention of accidents, and ways to implement measures to reduce accident severity. In this study, reviewing the existing iGlad and GIDAS system, KIDAS data format can be finalized through feasibility evaluation. The progressive approach is proposed to successful settlement of Korea in-depth accident study. As the initial stage of in-depth investigation DB construction, the KIDAS is not repetition of the current police based TAAS. It is essential part of improving vehicle safety and reduction of traffic fatality in Korea. 72 Contributing factors like road and traffic characteristics, vehicle parameters, and information about the people involved in the accident have to be investigated and registered as well in the KIDAS.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.123-133
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• 2010

The national standards for the installation of pedestrian crosswalks prohibits installation of crosswalks within 200 meters of nearby overpasses, underpasses, or crosswalks. In case the exceptional installation is required, the feasibility study is to be thoroughly conducted by the local police agency. However, it is an undeniable fact that the specific installation standards for optimal types and locations of crosswalks are not yet to be established. This paper examines the development of traffic accident prediction model applicable to different types and locations of bus stops(type A and type B) at mid-block intersections. Furthermore, it develops the poisson regression model which sets the "number of traffic accidents" and "traffic accident severity" as dependent variables, while using "traffic volumes", "pedestrian traffic volumes" and "the distance between crosswalks and bus stops" as independent variables. According to the traffic accident prediction model applicable to the type A bus stop location, the traffic accident severity increases relative to the number of traffic volumes, the number of pedestrian traffic volumes, and the distance between crosswalks and bus stops. In case of the type B bus stop model, the further the bus stop is from crosswalks, the number of traffic accidents decreases while it increases when traffic volumes and pedestrian traffic volumes increase. Therefore, it is reasonable to state that the bus stop design which minimizes the traffic accidents is the type C design, which is the one in combination of type A and type B, and the optimal distance is found to be 65 meters. In case of the type A design and the type B design, the optimal distances are found to be within range 60~70meters.

• Journal of the Korean Society of Safety
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• v.33 no.1
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• pp.142-147
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• 2018

This study aims to analyze and discuss the accidents based on the level of traffic culture (LOT). In pursuing the above, LOT are divided into three categories based on the standardized index of traffic culture. Also, this study focuses on developing the accident models using GLM (generalized linear model). The main results are as follows. First, the null hypotheses that the ratios of fatal and serious injured persons (FSI) are the same over categories are rejected. Second, as the common variables, the ratio of turn signal usage and elderly population are analysed to be impacted to the ratio of FSI. Third, the traffic culture indicators among 5 accident factors which give impact to 'high level' are judged to affect the reduction of FSI. Fourth, compared to other levels, the traffic law violations among 7 accident factors of 'medium level' are estimated to influence the increase of FSI. Finally, in 'low level', the increasing ratio of traffic culture index compared to that of previous year and the number of hospital beds per person are evaluated to be significant to reducing the ratio of FSI. This study can be expected to give some policy implications to regional traffic safety policy-making.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.9-15
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• 2022

The analysis of the causes of accidents in workplaces where machines and tools are used is essential to improve the effectiveness and efficiency of safety prevention policies in places of employment in Korea. The causes of workplace accidents are not fully understood mainly due to difficulties in analyzing available descriptive information. This study focuses on the automated accident cause analysis in workplaces based on the accident abstracts found in industrial accident reports written in an unstructured descriptive format. The method proposed in this paper is based on text data mining and uses the keyword search function of Excel software to automate the analysis. The analysis results indicate that the primary reason for the frequency of accidents is related to technical aspects at a stage in which dangerous situations occur in the workplace. Accidents due to managerial causes are typically observed when danger exists in the workplace; however, managerial actions play a more important role in reducing accident severity. A small company tends to use unsafe machines and devices, leading to further accidents due to technical causes, whereas managerial causes are more conspicuous as the company grows. To preclude the occurrence of accidents due to inadequate knowledge, the implementation of safety management and the provision of safety education to elderly workers at the early stage of their employment are particularly important for small companies with less than 100 workers.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.230-237
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• 2022

It is difficult to predict industrial accidents in the construction industry because many accident factors, such as human-related factors and environment-related factors, affect the accidents. Many studies have analyzed the severity of injuries and types of accidents; however, there were few studies on the prediction of injured body parts. This study aims to develop a classification model to predict the part of the injured body based on accident-related factors. Construction accident cases from June 2018 to July 2021 provided by the Korea Construction Safety Management Integrated Information were collected through web crawling and then preprocessed. A naïve Bayes classifier, one of the supervised learning algorithms, was employed to construct a classification model of the injured body part, which has four categories: 1) torso, 2) upper extremity, 3) head, and 4) lower extremity. The predictor variables are accident type, type of work, facility type, injury source, and activity type. As a result, the average accuracy for each injured body part was 50.4%. The accuracy of the upper extremity and lower extremity was relatively higher than the cases of the torso and head. Unlike the other classifications, such as spam mail filtering, a naïve Bayes classifier does not provide a good classification performance in construction accidents. The reasons are discussed in the study. Based on the results of this study, more detailed guidelines for construction safety management can be provided, which help establish safety measures at the construction site.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.371-380
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• 2023

Currently, as construction projects in Korea are becoming larger and more complex, the hazard rate of the construction industry is steadily increasing, contrary to other industries. This can be seen as an indication that the safety technology and safety consciousness of construction workers are insufficient compared to the improved construction technology. In addition, due to the characteristics of the construction industry based on manpower, most accidents appear in conventional forms such as fall and trip due to human errors. Therefore, analyzing the relationship between the characteristics of human resources and accidents and establishing detailed safety plans is an essential part of reducing construction accidents. In this study, a correlation analysis was conducted using 62,805 cases of construction accident cases over 3 years to derive the characteristics of accident occurrence focusing on the age of workers. As a result of the analysis, the relationship between the age of workers and the frequency and severity of accidents for each accident type was derived, focusing on the top 10 accident types.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.107-116
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• 2002

Crash Cushion is a kind of safety facilities on roadside which acts the role of absorbing impact energy when vehicles are driven out of normal route such as Gore area of freeway off ramp. Criteria for severity index considering accident occurrence possibility are needed to have strong effect on installing the facilities. However, present criteria for establishing crash cushion design do not include such processes. Therefore, the paper presents two kinds of study to develop criteria for severity index. First of all, development of accident forecasting model on freeway off ramp is presented. The module is a relationship between accidents and road environment by negative binomial distribution (NB) which is called to reflect very well quality of accidents at Gore of crash cushion installed freeway Secondly, freeway exiting behavior model is developed because the human factor is the most important one. However, many literatures have shown between road environment and accidents which are more quantitative than human factor. The study supposed advanced process steps on actual freeway and analysed correlation between variables and accidents. The criteria for severity index is presented to determine whether to install or not by benefit cost analysis for each module. The standard for severity index will help to determine whether to install the crash cushion or not and to estimate severity for freeway and off ramp.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.167-182
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• 2022

The accident data attributes of the traffic accident report are used not only in traditional traffic safety-related research to identify the cause of traffic accidents, but also as basis data for the development of the automated vehicle driving performance verification scenarios. However, since the data attributes of the traffic accident report are limited for the purpose of reconstructing the traffic situation and developing scenarios, this study aims to provide the directions for improvement of traffic accident report, ultimately for its expanded usability for the automated vehicle test scenarios. The directions for improvement of the traffic accident report are provided by categorizing the traffic situation before the accident (pre-crash), the situation immediately before or during the accident (on-crash), and the situation after the accident (post-crash), respectively. Additional data items or data processing methods are presented. Furthermore, data elements that can be extracted from the traffic accident process data in the unstructured narrative form are explored and provided.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7329-7334
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• 2015

This is to analyze of driver behavioral and the accident characteristics in rollover. The study period was January 2011 to May 2014 and the subject of study was 102 person who were drivers visited the emergency room. Research tool includes a damage information of the vehicle, accident mechanism, damage to the patient clinical information with the injury data from the ROAD Traffic Authority. For data analysis, SPSS 18.0 was used for t-test, ANOVA and Chi-square test. Injury Severity Score average score according to the vehicle type is 6.00 points in the smaller vehicle, at high vehicle 11.78 points, from the other vehicle that showed 14.70 points. Significant differences between the three groups did not show (P=.267). Men did not use a seat belt significantly compared to women(P=.007). Vehicle type and weather, this was no correlation with whether or not use the seat belt(P=.755, P=.793). But showed a tendency to smaller size vehicles drivers do not use a seat belt, the weather could see a little more inclined to use a seat belt rather than a sunny day. Finally, in rollover accidents as in other types of accident it was confirmed that the seat belt has a great influence on the damage.