• IE interfaces
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• v.15 no.2
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• pp.114-125
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• 2002

The objective of this paper is to describe a systematic accident scenario analysis method(SASA) adept at creating accident scenarios for the design of safer products. This approach was inspired by the Quality Function Deployment(QFD) method, which is conventionally used in quality management. In this study, the QFD provides a formal and systematic scheme to devise accident scenarios while maintaining objectivity. SASA consists of three key stages to be broken down into a series of consecutive steps:(1) developing an accident analysis tableau,(2) devising the accident scenarios using the accident analysis tableau,(3) performing a feasibility test, a clustering process and a patterning process, and finally(4) performing quantitative evaluation of each accident scenario. The SASA was applied to a case study of child safety seats. The accident analysis tableau devised 2828(maximum) accident scenarios from all possible relationships between the hazard factors and situation characteristics. Among them, 270 scenarios were devised through the feasibility test and the clustering process. The patterning process reduced them to 29 patterns representative of all accident scenarios. Based on an intensive analysis of the accident patterns, design guidelines for a safer child safety seat were recommended. The implications of the study on the child safety seat case were then discussed.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.77-82
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• 2018

This paper aims to analyze the accident based on changing patterns of traffic culture index. For this purpose, this paper particularly focuses on classifying the traffic culture patterns and developing the traffic accidents using panel count data model. The main results are as follows. First, the traffic culture patterns are divided into 'increasing', 'decreasing' and 'other' patterns. The null hypotheses that the number of accident are the same over patterns are rejected. Second, 4 fixed effect negative binomial models which are all statistically significant are developed. Third, the regions with 'increasing' pattern are analyzed to be mostly the counties, and to demand the traffic law enforcement. Fourth, the regions with 'decreasing' pattern are evaluated to be mainly the districts and to require such the traffic culture as turn signal usage. Finally, the regions with 'other' pattern are analyzed to be mostly the cities and to ask for enhancing the level of traffic culture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.805-808
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• 2008

In this paper, it was performed the analysis on various intersection acoustic patterns for detection rate improvement of accident sound detection system : an acoustic pattern analysis on general traffic noise, an acoustic pattern analysis on engine noise, an acoustic pattern analysis on obstruct factors for accident sound detection system. There are remarkable differences between the acoustic patterns of traffic noise and accident sound, and we most consider the acoustic patterns when we compose the accident traffic detection system by acoustic because there is error range of 20[dB] according to the volume of traffic in intersection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.133-140
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• 2006

This paper suggests to reclassify railroad accident types and to standardize them as the standardized code for the railroad safety management system. The existing railroad accident types in both domestic and foreign cases have been carefully analyzed in the beginning. Based on the case studies, the new railroad accident types are classified into 9 classes which are not overlapped one another and 9 classes have been subdivided into 40 different accident patterns. All these patterns are linked with 9 different accident objects and 6 accident locations. Therefore, this study suggested the combination of 4 distinct code factors: accident class, accident pattern, accident object, and accident location to standardize them. In addition, inter-operation between the proposed codes and the existing accident types is suggested. This code will play a major role in the railroad safety management system composed of accident prevention, accident preparedness, accident response, and accident recovery.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.58-64
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• 2018

Recently, a lot of accident report documents have accumulated in almost all of industries, including critical information of accidents. Accordingly, text data contained in accident report documents are considered useful information for understanding accident processes. However, there has been a lack of systematic approaches to analyzing accident report documents. In this respect, this paper aims at proposing text analytics approach to extracting critical information on accident processes. To be specific, major causes of the accident occurrence are classified based on text information contained in accident report documents by using both textmining and latent Dirichlet allocation (LDA) algorithms. The textmining algorithm is used to structure the document-term matrix and the LDA algorithm is applied to extract latent topics included in a lot of accident report documents. We extract ten topics of accidents as accident types and related keywords of accidents with respect to each accident type. The cause-and-effect diagram is then depicted as a tool for navigating processes of the accident occurrence by structuring causes extracted from LDA. Further, the trends of accidents are identified to explore patterns of accident occurrence in each of types. Three patterns of increasing to decreasing, decreasing to increasing, or only increasing are presented in the case of a chemical plant. The proposed approach helps safety managers systematically supervise the causes and processes of accidents through analysis of text information contained in accident report documents.

• Smart Media Journal
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• v.5 no.4
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• pp.75-82
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• 2016

Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.469-474
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• 1997

To provide tile information ell severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore was performed to investigate the effect of thermal hydraulic design parameters ell severe accident progression of pressurized water reactors (PWRs), Nine parameters, which are considered important in NPP design or severe accident progression, were selected among the various thermal hydraulic design parameters. The backpropagation neural network (BPN) was used to determine parameters, which might more strongly affect the severe accident progression, among mile parameters. For training. different input patterns were generated by the latin hypercube sampling (LHS) technique and then different target patterns that contain core uncovery time and vessel failure time were obtained for Young Gwang Nuclear (YGN) Units 3&4 using modular accident analysis program (MAAP) 3.0B code. Three different severe accident scenarios, such as two loss of coolant accidents (LOCAs) and station blackout(SBO), were considered in this analysis. Results indicated that design parameters related to refueling water storage tank (RWST), accumulator and steam generator (S/G) have more dominant effects on the progression of severe accidents investigated, compared to tile other six parameters.

• The Korean Journal of Emergency Medical Services
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• v.11 no.2
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• pp.67-86
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• 2007

This study is about the drunken drivers' accident patterns and behavior and aims at providing basic data for developing measures to secure safety against accidents by drunken drivers and programs to cultivate good drinking habits. For this purpose, this study conducted a questionnaire of 800 persons over 20 years of age in the selected 20 companies with more than 30 employees in the 4 regions(Daegu, Masan, Changwon, and Jinhae) and analysed the 653 sheets except invalid ones among the returned 673 survey sheets in total(return rate 84.13%), and the researcher conducted a man-to-man interview with each subject from June 20th to July 31st 2006. The result are as the following. As the experience of causing an accident by drinking, the 79.1% of them had the experience, and in case of the subjects with excessive drinking over 4 times a year, the rate of the accident by drinking showed as high as 90.5%. As the patterns of accidents, in male subjects, violence(38.5%) and traffic accidents(37.1%) showed high, while in the female, hurts from falls and fall accidents(40.2%) were found be high. In case of the traffic accidents among the accidents by drinking, the rate of causing serious damage to the life was found to be 89.3%, so it showed that the traffic accidents caused by drinking were influencing on the life much. In conclusion, the drinking problem may be controlled by each individual's will, but without change of social environment and system around people, the problem can not be eradicated. Therefore there should be social infrastructure which can help people to actively live their life with exercises and hobbies, and in order to prevent the reoccurrence of a drink accident, and social structure in which there are education programs for drink accident causers and one can change the perception about drinking culture, should be formed.

• Journal of the Korea Safety Management & Science
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• v.8 no.2
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• pp.13-23
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• 2006

The present study has investigated the patterns and the causes of safety -accidents on the accident-data in semiconductor Industries through near miss report the cases in the advanced companies. The ratio of incomplete actions to incomplete state was 4 to 6 as the cases of accidents in semiconductor industries in the respect of Human-ware, Hard- ware, Environment-ware and System-ware. The ratio of Human to machine in the attributes of semiconductor accident was 4 to 1. The study also investigated correlation among the system related to production, accident, losses and time. In semiconductor industry, we found that pattern of safety-accident analysis is organized potential, interaction, complexity, medium. Therefore, this study find out that semiconductor model consists of organization, individual, task, machine, environment and system.

• Journal of the Korean Regional Science Association
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• v.11 no.1
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• pp.21-30
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• 1995

This paper deals with the forecasting models for traffic accident by region. Its objectives are to develop the appropriate model for projecting the accident and to analyze the regional characteristics of the accident model. The main results are as follow. First, the literature review, statistical tests and sensitivity analyses show that the joint model combined both PTM and Exponential functions is appropriate to project the traffic accidents by region. Second, the statistical analyses by region. Second, the statistical analyses on the regional accident models indicate that the levels of significance in terms of t-value, $R^2$ and F-value are very high. Finally, the comparative analyses among regions show that the regional differences on the accident patterns can be explained by the joint models and the accident indices (parameters, $P_{max}$, 1/b, $\eta$ etc.) of each region.