• Safety and Health at Work
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• v.7 no.1
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• pp.38-42
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• 2016

Background: Truck driving is known as one of the occupations with the highest accident rate. This study investigates the characteristics of traffic collisions according to road types (expressway and rural road). Methods: Classifying 267 accidents into expressway and rural road, we analyzed them based on driver characteristics (age, working experience, size of employment), time characteristics (day of accident, time, weather), and accident characteristics (accident causes, accident locations, accident types, driving conditions). Results: When we compared the accidents by road conditions, no differences were found between the driver characteristics. However, from the accident characteristics, the injured person distributions were different by the road conditions. In particular, driving while drowsy is shown to be highly related with the accident characteristics. Conclusion: This study can be used as a guideline and a base line to develop a plan of action to prevent traffic accidents. It can also help to prepare formal regulations about a truck driver's vehicle maintenance and driving attitude for a precaution on road accidents.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.9-15
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• 2023

The Severe Disaster Punishment Act had recently been established in order to promote safety and health (OSH) management system for severe accident prevention. OSH management system is primarily designed based on risk assessments; however, companies in industries have been experiencing difficulties in hazard identification and selecting proper measures for risk assessments and accident prevention. This study intended to introduce an accident analysis method based on epidemiological model in finding hazard and preventive measures. The accident analysis method employed in this study was proposed by the U.S. Department of Energy. To demonstrate the effectiveness of the accident analysis method, this study applied it to two accident cases occurred in construction and manufacturing industries. The application process and results of this study can be utilized in improving OSH management system and preventing severe accidents.

• The Journal of Korean Society for School & Community Health Education
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• v.13 no.1
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• pp.65-75
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• 2012

Objectives: This study aims at grasping the socio-demographic variable, safety education experience, personality type and accident experience and analyzing if the personality type influences on the accident experience. Methods: For 330 third-year students at one middle school located at Gyeonggi-Do, questionnaire survey was performed on 16th, October, 2010. Excepting data of 19 students poor in contents, 311 students' data were analyzed. Results: The results of analysis are like followings. 1. As for relation between the socio-demographic variable and accident experience, it showed statistical significance in sex and how to go to school. And there was no statistical significance in parents' job, educational level of parents, residential type, school record and allowance. 2. As for relation between safety education experience and accident experience, safety education doing school than family lowered accident incidence outstandingly. When safety education frequency increased one time, possibility to experience accident decreased to 30%. 3. As for relation between 4 personality types of MBTI and accident experience, Thinking(T) experienced accident more than Feeling(F). Moreover, it showed difference in accident type and injuried degree. This results were statistically significant. As the result of analyzing the injuried degree by sex only in Thinking(T) and Feeling(F), female students had statistically significant difference. Conclusions: Health care providers should develop school safety programs by characteristics of personality.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.151-156
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• 2005

The objective of this study is to devise an accident scenario analysis method adept at creating accident scenarios at the Preliminary Hazard Analysis(PHA) step of a hazard analysis for railway system. This approach was inspired by the Quality Function Deployment(QFD) method, which is conventionally used in quality management and was used at the systematic accident scenario analysis(SASA) for the design of safer products. In this study, the QFD provides a formal and systematic schema to devise accident scenarios while maintaining objective. The accident scenario analysis method first identifies the hazard factors that cause railway accidents and explains the situation characteristics surrounding the accident. This method includes a feasibility test, a clustering process and a pattering process for a clearer understanding of the accident situation. Since this method enables an accident scenario analysis method to be performed systematically as well as objectively, this method is useful in building better accident prevention strategies. Therefore, this study can serve to reduce railway accident and be an effective tool for a hazard analysis.

• Journal of the Korea Safety Management & Science
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• v.18 no.3
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• pp.17-24
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• 2016

The regulation for industrial accident rate level assessment of construction companies was introduced to the construction industry in the Republic of Korea since 1993 and has brought positive outcome on industrial accidents reduction at construction work sites. There were considerable decrease of industrial accident ratio and enforcing of contrators' safety organizations from the beginning of the regulation for industrial accident rate level assessment. In spite of these positive outcomes, there were some negative effects such as contractors' shrinking accident reports to keep good accident ratios since these figures had a great impact on pre-qualification stage of bidding when general contractors were competing for new construction projects. In addition, Comprehensive evaluation bid system, which replaces the lowest price bid system is applied to government-ordered construction projects since 2016. Comprehensive evaluation bid system includes construction company's accident rate as one of the evaluation items and carries out with the industrial accident rate level assessment of construction companies at the same time. The regulations of two systems have been called for improvement to unify these different procedures and standards which have led business stakeholders to confusion for several years. This study aims to devote on lessening shrinking accident reports and to reduce the waste of business stakeholders through changing the regulation for industrial accident rate level assessment.

• Journal of Korean Medicine Rehabilitation
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• v.18 no.2
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• pp.119-130
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• 2008

Objectives : The purpose of this study was to compare mean values of Factor AA on Skin Resistance Variability(SRV) of traffic accident patient group with those of non-traffic accident patient group(control group) by using 7-Zone-Diagnostic System. Methods : Two groups were selected from those who took the CP-6000A test in College of Oriental Medical Hospital of Sang-Ji University from March 2007 to November 2007. Two groups were control group(n=61) and traffic accident patient group(n=62). Mean values of Factor AA on Skin Resistance Variability(SRV) of two groups were compared. Results and Conclusions : The results suggest that traffic accident patient group and non-traffic accident patient group had problems in circulation but non-traffic accident patient group had more problems than traffic accident patient group, and that after oriental medical therapy, non-traffic accident patient group was more improved than traffic accident patient group. So, further studies will be needed.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.3
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• pp.69-76
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• 2018

General workers who assist various technicians in different fields with their work across the whole construction sites without having a particular skill are at risk of the highest accident rate and their accident form becomes varied. Accordingly, this study was conducted to identify the relationship between form of safety accident and influence factor in general workers and analyze accident severity by influence factor. The followings are the results from this study. First, as a result of analyzing major form of accident and influence factors in general workers with network analysis methodology, nine forms of accident and seventeen influence factors were drawn. Second, it was found that in accident severity among general workers, collapsing, among various forms of accident, appeared the highest, followed by fall, electric shock, fire, hit by an object, bumped against, trip, scission getting cut chopped in order. Third, main points of special, concentrated, and permanent management were presented in order to reduce the safety accident in general workers effectively.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.56-63
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• 2021

The narrative texts of industrial accident reports help to identify accident risk factors. They relate the accident triggers to the sequence of events and the outcomes of an accident. Particularly, a set of related keywords in the context of the narrative can represent how the accident proceeded. Previous studies on text analytics for structuring accident reports have been limited to extracting individual keywords without context. We proposed a context-based analysis using a Natural Language Processing (NLP) algorithm to remedy this shortcoming. This study aims to apply Word2Vec of the NLP algorithm to extract adjacent keywords, known as word embedding, conducted by the neural network algorithm based on supervised learning. During processing, Word2Vec is conducted by adjacent keywords in narrative texts as inputs to achieve its supervised learning; keyword weights emerge as the vectors representing the degree of neighboring among keywords. Similar keyword weights mean that the keywords are closely arranged within sentences in the narrative text. Consequently, a set of keywords that have similar weights presents similar accidents. We extracted ten accident processes containing related keywords and used them to understand the risk factors determining how an accident proceeds. This information helps identify how a checklist for an accident report should be structured.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.50-59
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• 2021

The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.91-102
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• 2009

A traffic accident prediction model developed using various design variables(road design variables, geometric variables, and traffic environmental variables) is one of the most important factors to safety design evaluation system for roads. However, statistical accident models have a crucial problem not applicable for all intersections. To make up this problem, this study developed AMFs(Accident Modification Factors) through statistical modeling methods, historical accident databases, judgment from traffic experts, and literature review by considering design variable's characteristics, traffic accident rates, and traffic accident frequency. AMFs developed in this study include exclusive left-turn lane, exclusive right-turn lane, sight distance, and intersection angle. Predictabilities of the developed AMFs and the existing accident prediction models are compared with real accident historical data. The results showed that performances of the developed AMFs are superior to the existing statistical accident prediction models. These findings show that AMFs should be considered as a important process to develop safety design evaluation algorithms. Additionally, AMFs could be used as an index that can judge the impact of corresponding design variables on accidents in rural intersections.