• Journal of the Korea Safety Management & Science
• /
• v.16 no.2
• /
• pp.53-61
• /
• 2014

The disaster and safety accidents in any construction site occur inevitably. Since the on-site disaster and accident occurrence became one of major concerning factors in construction site, architects & building executers have been flooded with safety management advices. The purpose of this paper is to survey and analyze the effect of the application of Safety Patrol Management System(SPMS) upon the reduction of disaster & accident occurrences in construction site. In order to estimate and reduce the disaster and accident ratio in construction site, various surveyed data has been analysed. It will establish the suitable design standards and suggest the basic database for estimating disaster and accident ratio.

• Journal of the Korea Safety Management & Science
• /
• v.10 no.4
• /
• pp.39-46
• /
• 2008

In this study, with the objects of 173 institutions of university and research institutions, investigation was carried out through visit investigation ar d questionnaire investigation. Frequency and severity of occurrences was acquired mainly through universities and research institutions which have reported occurrences of accidents to the Ministry of Education, Science, and Technology. Quantitative danger evaluation was conducted through frequency and strength of occurrences. Case study was carried out by selecting bio science laboratory of university and as the result of this study, degree of danger among the inspection objects of bio science laboratories, laboratory work place was evaluated as the most dangerous with the scores of 155.00 and as the result of average danger level, compression gas cylinder was evaluated as the most dangerous with the scores of 6.4000.

• Proceedings of the Safety Management and Science Conference
• /
• 2008.11a
• /
• pp.623-631
• /
• 2008

In this study, with the objects of 173 institutions of university and research institutions, investigation was carried out through visit investigation and questionnaire investigation. Frequency and strength of occurrences was acquired mainly through universities and research institutions which have reported occurrences of accidents to the Ministry of Education, Science, and Technology. Quantitative danger evaluation was conducted through frequency and strength of occurrences. Case study was carried out by selecting bio science laboratory of university and as the result of this study, degree of danger among the inspection objects of bio science laboratories, laboratory work place was evaluated as the most dangerous with the scores of 155.00 and as the result of average danger level, compression gas cylinder was evaluated as the most dangerous with the scores of 6.4000.

• Nuclear Engineering and Technology
• /
• v.50 no.4
• /
• pp.562-569
• /
• 2018

Recently, human errors have very rarely occurred during power generation at nuclear power plants. For this reason, many countries are conducting research on smart support systems of nuclear power plants. Smart support systems can help with operator decisions in severe accident occurrences. In this study, a smart support system was developed by integrating accident prediction functions from previous research and enhancing their prediction capability. Through this system, operators can predict accident scenarios, accident locations, and accident information in advance. In addition, it is possible to decide on the integrity of instruments and predict the life of instruments. The data were obtained using Modular Accident Analysis Program code to simulate severe accident scenarios for the Optimized Power Reactor 1000. The prediction of the accident scenario, accident location, and accident information was conducted using artificial intelligence methods.

• Proceedings of the Korean Nuclear Society Conference
• /
• 2003.05a
• /
• pp.442-442
• /
• 2003

• Journal of the Korean Society of Safety
• /
• v.23 no.6
• /
• pp.171-177
• /
• 2008

As the risk of traffic accidents caused by mists emerged as a social problem, recently safety facilities to be prepared for mists are being actively installed when designing roads. But in some part, the facilities are being installed imprudently without analyzing the extent of occurrences of mists that would increase the risk of traffic accidents and appropriate countermeasures against the occurrences of mists are not being suggested. For that reason, in this study, first questionnaire surveys were executed on road users in order to draw the factors affecting the traffic accidents caused by mists, a mist traffic accident predicting model was developed and an accident seriousness determining model that can determine accident seriousness was developed. In this way, by extracting major factors affecting mist traffic accidents to grasp risk factors in roads to be caused by mists, safety of roads can be enhanced and traffic accidents in road operations can be decreased. As the affecting factors influencing mist traffic accidents, were extracted sightable distances, durations of mists and whether daytime or nighttime as major factors and the plan to install the facilities for the prevention of mist traffic accidents was suggested to prevent the traffic accidents to be caused by those factors and also the plan to operate roads considering sightable distances was suggested to solve the problem of insufficient sightable distances to be caused by mists was suggested. It is judged that the road safety in the areas where mists occur can be improved through foregoing methods.

• Journal of the Korean Society of Safety
• /
• v.37 no.2
• /
• pp.18-27
• /
• 2022

Construction accidents are difficult to prevent because several different types of activities occur simultaneously. The current method of accident analysis only indicates the number of occurrences for one or two variables and accidents have not reduced as a result of safety measures that focus solely on individual variables. Even if accident data is analyzed to establish appropriate safety measures, it is difficult to derive significant results due to a large number of data variables, elements, and qualitative records. In this study, in order to simplify the analysis and approach this complex problem logically, data preprocessing techniques, such as latent class cluster analysis (LCCA) and predictor importance were used to discover the most influential variables. Finally, the correlation was analyzed using an alluvial flow diagram consisting of seven variables and fourteen elements based on accident data. The alluvial diagram analysis using reduced variables and elements enabled the identification of accident trends into four categories. The findings of this study demonstrate that complex and diverse construction accident data can yield relevant analysis results, assisting in the prevention of accidents.

• Journal of Navigation and Port Research
• /
• v.46 no.2
• /
• pp.92-98
• /
• 2022

Maritime accidents result in enormous economic loss and loss of life; thus, such accidents must be prevented, and risks must be managed to prevent these occurrences Risk management must be based on statistical evidence such as variables. Because calculating when variables increase statistically can be difficult, compressing the designated variables is necessary to use the maritime accident data in Korea. Thus, in this study, variables of marine accident data are compressed using statistical methods. The date, ship type, and marine accident type included in all maritime accident data were extracted, the number of optimal variables was confirmed using the hierarchical clustering analysis method, and the data were compressed. For the compressed variables, the validity of the data use was statistically confirmed using analysis of variance, and the data of the variables identified using the variable compression method were designated. Consequently, among the monthly and yearly data, statistical significance was confirmed in yearly data, and compression was possible. The significance of the data was confirmed in six and eight types of ships and accidents, respectively, and these were compressed. These results can be directly used for prevention or prediction based on past maritime accident data. Additionally, the data range extracted from past maritime accidents and the number of applicable data will be studied in the future.

• Journal of Korean Society of Transportation
• /
• v.26 no.4
• /
• pp.173-184
• /
• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• International Journal of Highway Engineering
• /
• v.17 no.6
• /
• pp.65-73
• /
• 2015

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS : To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection's specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables'impact on the likelihood of accident occurrences. CONCLUSIONS : This study shows that the uses of RP is better fitted to the accident data since each observations'specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).