• 한국도로학회논문집
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• 제17권3호
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• pp.117-124
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• 2015

PURPOSES : The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS : To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS : This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including ${\chi}^2/df$, GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS : Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

• 한국학교ㆍ지역보건교육학회지
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• 제12권1호
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• pp.71-89
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• 2011

Objectives: The purpose of this study is to identify risk behavior related to the school accident between male and female elementary school students. Methods: 838 School accident data provided by Seoul School Safety Council were analyzed by gender. Based on the results above, survey questionnaires on characteristics of school accident were developed. Self-reported data were collected from a sample population of 433 students in grade 5 to 6 students attending 4 elementary schools in Seoul. Results: The students who answered they experienced the accident in school for the past 1 year, accounts 60.5% of male and 39.5% of females students, which has statistically significant difference. The male's cases happened most around corridor/door, while female's cases happened most in the playground/gymnasium. As for the accident risk behavior, male students had the risk behavior by using the personal belongings/toys, while the female students had much risk behavior related to physical facility/playground. When classifying the characteristics of risk behaviors according to the accident causes, male students showed higher score in the accident risk behaviors related to play/fight than in those of the female students(p<0.05). Conclusions: Health care providers should develop school safety programs by characteristics of risk behavior between male and female elementary school students.

• Journal of Biosystems Engineering
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• 제3권2호
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• pp.126-132
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• 1978

This study was carried out through the survey questionaries in order to get the information for proper operating technique of the two-wheel tractors which are widely used in the farm, and investigated various accidents which occurred during the operation of two-wheel tractors for farm works in 7 Provinces of Korea. The summarized results are as follows ; 1. Annual accident frequency of the two-wheel tractor was 2.07 times, and the average rate of accident was 0.72 times per hour. Its value was the largest in the pre-operations , and the smallest in the threshing operation. 2. The accident distribution according to each month was nearly propertional to the operating hours of the two-wheel tractor. More than 60 % of total accident was concentrated during the rice transplanting and harvesting season. 3. The careless accident was more than 50% of total accident , and inevitable accident about 18% . The rate of careless accident showed the highest in pre-operation such as engine starting, check, and adjustment, and belt change. 4. The serious wounded operator was 7.1 % to total wounded operator , and about 50 % of accident of casualties to operators occurred during haruling operations. 5. The amount of casualties to property was range of 1,000 to 10,000 won, and annual total amount per unit tractor could be estimated to be 10 , 000 won.

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

• 대한인간공학회지
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• 제35권3호
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• pp.155-163
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• 2016

Objective: This study aims to draw the characteristics of occupational accidents occurred in cabling work, and assess accident severity based on occupational injury data. Background: Accident factors and accident risk are different by the place of work in cabling work. Field managers require information on accident prevention that can be easily understood by workers. However, there has been a lack of studies that focus on cabling work in Korea. Method: This study classifies 450 injured persons caused in cabling work by process, and analyzes the characteristics of occupational injuries from the aspects of age, work experience and accident type. This study also analyzes accident frequency and severity of injury. Results: Results show that preparing/finishing (33.3%) was the most common type of cabling process in injuries, followed by maintenance (28.4%), routing/income (23.1%) and wiring/installation (15.1%) process. The critical incidents in the level of risk management were falls from height in the routing/incoming process, and falls from height in the maintenance process. And, incidents ranked as 'High' level of risk management were slips and trips, fall from height and vehicle incident in the preparing/finishing process, and fall from height in the wiring/installation process. Conclusion and Application: The relative frequency of accident and its severity by working process serve as important information for accident prevention, and are critical for determining priorities in preventive measures.

• 대한전자공학회논문지TC
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• 제44권1호
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• pp.85-92
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• 2007

교통사고는 해마다 감소하고 있는 추세이다. 그러나 대형사고나 뺑소니 사고는 계속 증가하고 이다. 뿐만 아니라, 교통사고는 주변지역의 교통 정체를 유발하게 되어 사회적 비용이 들게 된다. 이 때문에 우리는 본 논문에서 교통사고를 예방할 수 있는 방안을 제시하고, 교통사고가 발생한 경우 교통사고를 신속히 처리할 수 있는 방안을 제시하였다. 운전자는 DMB를 사용함으로서 교통상황을 청각과 시각을 통해서 보다 정확히 알 수 있다. 끝으로, 우리는 TPEG으로 보다 효과적인 교통정보를 제공하는 방안을 제안하였다.

• Nuclear Engineering and Technology
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• 제54권7호
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• pp.2475-2490
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• 2022

The Accident Tolerant Fuel (ATF) is a new concept of fuel, which can not only withstand the consequences of the accident for a longer time, but also maintain or improve the performance under operating conditions. ISAA is a self-developed severe accident analysis code, which uses modular structures to simulate the development processes of severe accidents in nuclear plants. The basic version of ISAA is developed based on UO₂-Zr fuel. To study the potential safety gain of ATF cladding, an improved version of ISAA, referred to as ISAA-ATF, is introduced to analyze the station blackout accident of PWR using ATF cladding. The results show that ATF cladding enable the core to maintain a longer time compared to zirconium alloy cladding, thereby enhancing the accident mitigation capability. Meanwhile, the generation of hydrogen is significantly reduced and delayed, which proves that ATF can improve the safety characteristics of the nuclear reactor.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.744-751
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• 2022

Construction is among the most dangerous industries with numerous accidents occurring at job sites. Following an accident, an investigation report is issued, containing all of the specifics. Analyzing the text information in construction accident reports can help enhance our understanding of historical data and be utilized for accident prevention. However, the conventional method requires a significant amount of time and effort to read and identify crucial information. The previous studies primarily focused on analyzing related objects and causes of accidents rather than the construction activities. This study aims to extract construction activities taken by workers associated with accidents by presenting an automated framework that adopts a deep learning-based approach and natural language processing (NLP) techniques to automatically classify sentences obtained from previous construction accident reports into predefined categories, namely TRADE (i.e., a construction activity before an accident), EVENT (i.e., an accident), and CONSEQUENCE (i.e., the outcome of an accident). The classification model was developed using Convolutional Neural Network (CNN) showed a robust accuracy of 88.7%, indicating that the proposed model is capable of investigating the occurrence of accidents with minimal manual involvement and sophisticated engineering. Also, this study is expected to support safety assessments and build risk management systems.

• 한국안전학회지
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• 제39권1호
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• pp.104-113
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• 2024

Unlike in general manufacturing process, safety management in laboratory-based research area is complicated because the latter generally involves trying untested methods or handling unusual substances in small amounts. Laboratory accidents in South Korea have recently shown an increasing trend. Unfortunately, statistics on such accidents are not officially published by any domestic public agencies. In this study, multivariate analysis was performed on the relationships between variables to develop effective strategies for preventing laboratory accidents. A Cross-Tabulation Analysis of accident-related factors in 179 accident cases revealed that the laboratory type, accident type, and unsafe-act type are all statistically significant, whereas the unsafe condition and management factors differ with the statistical criteria. Furthermore, the results of a Multiple-Correspondence Analysis showed that accidents can be divided largely into three groups having different accident causes and injury types; this confirms the necessity of different strategies to prevent accidents of each type. The findings also reveal differences between the distribution of accident types mentioned in the accident case collection books and actual reported cases. This suggests that an official statistical system administered by a public institution would be necessary for effective prevention of laboratory accidents.

• 대한토목학회논문집
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• 제37권1호
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• pp.111-117
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• 2017

교통사고 발생위험예보의 목적은 교통사고를 저감하기 위한 것이다. 따라서 본 연구는 조건에 따른 교통사고발생 확률을 산정하여 효과적인 교통사고 위험 예보를 목적으로 하였다. 국내에서는 인터넷 등을 통해 사망사고 정보를 포함한 교통사고의 통계수준의 정보를 제공하고 있으며 최근에는 날씨에 따른 광역지자체 단위의 지역별 주간 교통사고 위험도수준 정도의 정보를 개략적으로 제공하고 있다. 그러나 모든 운전자에게 동일내용의 정보를 제공하는 것은 개인의 특성과 환경을 반영하지 못한 것으로 한계가 있다. 그러므로 본 연구에서는 부산시 주간선도로의 68개 주요 교차로를 중심으로 교통사고, 교차로 기하 구조, 강수량 등의 정보를 종합적으로 교통사고 발생에 대한 노드와 링크 단위의 위험도 예보를 하고자 하였다. 구체적으로, 운전자특성과 운전상황 같은 동적정보와 교차로 기하 구조데이터를 이용하여 각 상황에 맞는 상대적 사고발생 위험도를 산정하였다. 또한 사고유형을 '차대차', '차대사람'으로 분류하여 각각의 구체적인 사고발생 위험도를 산정하였다. 최종적으로는 산정한 결과 값에 기초하여 교차로 기반의 운전자 맞춤형 사고위험도 정보를 제공하고자 하였다. 사고예보정보에 따른 안전한 경로를 서비스함으로서 맞춤형 경로선택의 기회를 제공하며 운전자의 안전운행에 도움을 주고자 하였다.