• Journal of the Korean Society of Safety
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• v.27 no.3
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• pp.141-146
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• 2012

This study deals with the accident model using panel data which are composed of time series data of 2005 through 2007 and cross sectional data of link sections in Cheongju. Panel data are repeatedly collected over time from the same sample. The purpose of the study is to develop the traffic accident model using the above panel data. In pursuing the above, this study gives particular attentions to deriving the optimal models among various models including TSCSREG (Time Series Cross Section Regression). The main results are as follows. First, 8 panel data models which explained the various effects of accidents were developed. Second, $R^2$ values of fixed effect models were analyzed to be higher than those of random effect models. Finally, such the variables as the sum of the number of crosswalk on intersections and sum of the number of intersections were analyzed to be positive to the accidents.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.151-159
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• 2017

This study deals with characteristics and risk of a PM based on user survey result, road driving test and data analysis of PM accident. Text mining method is applied to extract PM accident data from Big Data, which are claim data of private insurance company. Road driving test and survey on safety, convenience, noise, overtake ability, steering ability, and climbing ability of PM are performed to evaluate user's safety and convenience considering domestic road condition. As the result of claim data analysis, annual average increase rate of PM accident is 47.4% and average compensation of personal mobility is higher than that of bicycle by maximum 1.5 times. 79.8% of PM accident is self-caused accident due to unskilled driving and age-specific diagnosis rate of driver over 60 is higher than that of under 60. Diagnosis rate of over 60 at lower limb, foot, rib and spine is especially higher than that of under 60. As the result of road driving test and user survey, satisfaction level on safety and convenience of PM is evaluated as close to that of bicycle and satisfaction level of PM is increased after boarding. Overtake ability, steering ability, and climbing ability of PM are evaluated as same or better than that of bicycle but warning equipment to pedestrian or bike such as horn is required because noise level of PM during driving is too low. Finally, user survey result shows that bicycle road is suitable for PM and safety standard, advance-education and insurance are required for PM. It is suggested that drivers' license for PM can be replaced by advance-education. Results of this study can be used to prepare safety measures and legal basis for PM operation.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.687-696
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• 2012

Recently, despite of the development of aviation safety, there has not been any significant decline of the aviation accident rate. Therefore, in the international society, it is more focused on removing risk factors based on data collected and analyzed, in order to improve the aviation safety. This research introduces ECCAIRS, which is a program developed by European Union to collect and analyze data regarding risk factors. This is used in Korea since 2010. Moreover, using national aviation accident data collected through ECCAIRS, this research analyzes the distribution of the aviation accidents/incidents, annual and monthly aviation accident rate, flight phase, and division system. The analyzation regarding the tendency of aviation accident/incident will give the direction to approach the quantitative safety management.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.75-86
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• 2010

The objective of this study is to suggest the process and method of local accident investigation for local authorities with a view to efficient and effective managing traffic accidents. With a project city selected accident-type maps, accident lists, accident diagrams, priority of black-spots/-lengths, site visits, remedial measures, opportunity costs, monitoring etc. are taken into consideration, by using accident data in the last 3 years. Analyzed are accident savings to be expected when applying technical, organizational, and administrative processes attached to local accident investigation.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.427-441
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• 2021

Purpose: This study proposes a method for developing a model that predicts the probability of traffic accidents in advance to prevent the most frequent traffic accidents in the military. Method: For this purpose, CRISP-DM (Cross Industry Standard Process for Data Mining) was applied in this study. The CRISP-DM process consists of 6 stages, and each stage is not unidirectional like the Waterfall Model, but improves the level of completeness through feedback between stages. Results: As a result of modeling the same data set as the previously constructed accident investigation data for the entire group, when the classification criterion was 0.5, Significant results were derived from the accuracy, specificity, sensitivity, and AUC of the model for predicting traffic accidents. Conclusion: In the process of designing the prediction model, it was confirmed that it was difficult to obtain a meaningful prediction value due to the lack of data. The methodology for designing a predictive model using the data set was proposed by reorganizing and expanding a data set capable of rational inference to solve the data shortage.

• Journal of the Korean Society of Safety
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• v.16 no.2
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• pp.103-109
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• 2001

When workers get accidents in doing their works, industrial accident insurance covers the compensation for the accidents. Generally, this kind of costs is applied in terms of Direct Cost. In our society circumstance to terminate the accident, many kinds of cost (Non-Insurance Cost) are also discharged. Non-Insurance Cost resulted from additional compensation for insurance allowance, is the important basic data source to estimate Loss Cost. Several studies have been done for the output of accident cost, but companies have difficult to apply these studies into practice and generalize the amount of accident loss cost. This study means to suggest improving solutions for the output of Accident Loss Cost and to reduce Opportunity Cost caused by Industrial Accident.

• International Journal of Highway Engineering
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• v.15 no.6
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• pp.113-123
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• 2013

PURPOSES : Although numerous researches have been studied to reveal accident causations for road intersections, there are still many research gaps for road segments. It is mainly because of difficulty of data and lack of analytical method. This study aims to study accident causations for rural road segments and develop accident modification factors for safety evaluation. The accident modification factors can be used to improve road safety. METHODS : Methods for developing AMF are diverse. This study developed AMFs using accident prediction models and selected explanatory variables from the accident models. In order to select final AMFs, three different methods were applied in the study. RESULTS : As a result of the study, many AMFs such as horizontal curves or vertical curves were developed and explained the meanings of the results. CONCLUSIONS : This study introduced meaningful methods for developing significant AMFs and also showed several AMFs. It is expected that traffic or road engineers will be able to use the AMFs to improve road segment safety.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.125-129
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• 2005

This study aims to provide divers with improved safe diving practices by analyzing reports on scuba diving casualties that recently(from 1997-2003)occurred in Korea, Japan and USA. The result of this study can contribute toward preventing the diving accident. All the data were collected through the diving accident reports of various sourse, which include KUA(Korea Underwater Association) technical committee, the accident statistical data of National Maritime Police Agency, articles of domestic and foreign scuba diving magazine, accident reports of various newspaper, annual report on decompression illness and diving fatalities by DAN(Diver Alert Network), various type of data on diving accident from local as well as national seminars, and medical treatment data of diving accident.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.6
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• pp.450-459
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• 2023

According to Korea Maritime Safety Tribunal, there have been 14,100 maritime accidents from 2017 to 2021. Among those accidents, ship collision accidents have been up to 1,275 cases. But in the accidents relating to small ships like a fishing vessel, analyzing the causes of the accidents would depend on statements of the persons related because there is often no navigational data. But those statements can be incorrect and give rise to disagreements between them so that it causes conflicts with each other during the trial. So a replay system of ship collision accident (RESCA) has been developed in order to reproduce the ship collision accident by using AIS, V-PASS or radar data. But the reproduced trajectory of ship collision accident is needed to be verified because it can be unreasonable physically. So a method to verify the reproduced trajectory and collect the physical data on ship collision accident is newly designed by using free running test. In the RESCA, the accident is reproduced using the navigational data from the trajectory for a ship and measured from free running model test for the other ship at the same time. Through free running test, the behavior of the model ship is transformed from model scale into real scale. In order to check into the accuracy of the new method, free running model tests by using RESCA are carried out on the actual ship collision accidents.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.497-507
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• 2015

Nonrecurrent congestion of freeway was primarily caused by incident. The main cause of incident was known as a traffic accident. Therefore, accurate prediction of traffic incident clearance time is very important in accident management. Traffic accident data on freeway during year 2008 to year 2014 period were analyzed for this study. KNN(K-Nearest Neighbor) algorithm was hired for developing incident clearance time prediction model with the historical traffic accident data. Analysis result of accident data explains the level of accident significantly affect on the incident clearance time. For this reason, incident clearance time was categorized by accident level. Data were sorted by classification of traffic volume, number of lanes and time periods to consider traffic conditions and roadway geometry. Factors affecting incident clearance time were analyzed from the extracted data for identifying similar types of accident. Lastly, weight of detail factors was calculated in order to measure distance metric. Weight was calculated with applying standard method of normal distribution, then incident clearance time was predicted. Prediction result of model showed a lower prediction error(MAPE) than models of previous studies. The improve model developed in this study is expected to contribute to the efficient highway operation management when incident occurs.