• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.122-128
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• 2017

Korean government announced long-term railway safety investment plan for the safety improvement by 2020. But no research have been done about differential analysis on railroad safety investment and safety improvement. In this study, recent 10 year data on safety investments and accident data are analysed for the differential analysis. Three main safety investments are analysed on regard to accident rate and accident fatalities. Three safety measures include level crossing accident, platform fatalities, and track trespass fatalities. About 90% of railway accident fatalities are caused by these three kind of accidents. Differential analysis shows about 4 to 6 years delay after railroad safety investment and safety improvement. This result can be utilized for the decision making on safety measures and safety target. Which required long term approach.

• Journal of Auto-vehicle Safety Association
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• v.4 no.1
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• pp.5-11
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• 2012

This paper discusses the evaluation of the safety impact of the Adaptive Cruise Control (ACC) system in Korea. To evaluate the safety impact, this paper suggests an analysis method by using the test scenario and field operational test data. The test scenario is composed to represent the main component factor of the ACC system and ACC related accident situation such as rear-end collision, lane-change, and road-curvature, etc. Also, from the field operation test data, the system's potential to increase the safety can be measured ideally. Besides, field operational testdata was used to revise the expected safety impact value as Korean road conditions. By using the proposed evaluation method, enhanced safety impact of the ACC system can be estimated scientifically.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.59-60
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• 2018

The purpose of this study is to predict and classify the accident types based on the KOSHA (Korea Occupational Safety & Health Agency) and weather data. We also have an effort to suggest an important management method according to accident types by deriving feature importance. We designed two models based on accident data and weather data (model(a)) and only weather data (model(b)). As a result of random forest method, the model(b) showed a lack of accuracy in prediction. However, the model(a) presented more accurate prediction results than the model(b). Thus we presented safety management plan based on the results. In the future, this study will continue to carry out real time prediction to occurrence types to prevent safety accidents by supplementing the real time accident data and weather data.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1215-1221
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• 2010

Railway safety management information systems are now being developed by various railway related organizations. A large number of railway safety related data were gathered from railway operators, railway infrastructure manager and railway intendance, etc. The meaning of these data can easily be defined by each organization or developer with little regard for reusing of data by others. Until the present, the main efforts for data management focused on classifying the railway safety data by subject for the developer's convenience and how to combine these data each other is not interested in. In this study, data integration is considered from the viewpoint of combining them semantically in order to get more useful information from partially informed data of multi agencies.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.703-712
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• 2017

The railway system is an interface industry that can be safely operated by organically operating the lines, vehicles, controls, etc. Various data are generated in the operation and maintenance activities of the railway system. These data are utilized in cooperation with safety and maintenance activities in each field, but amount of data is insufficient for data analysis of safety management due to relevant data being produced without any synchronous criteria such as time or space. In particular, reference data such as location and time of failure data for each field are set to different criteria according to the work characteristics in each field. So, it is not easy to analyze data integrally based on location and time. Therefore, mapping of reference data can be required for integrated analysis of data defined in different formats. By selecting data mapping tools and verifying the results of safety relevant data with the same criteria, the purpose of this paper is to enable integrated analysis of railway safety management data occurring in different fields based on location and time.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.26 no.3
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• pp.188-196
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• 2019

Purpose: The purpose of this study was to investigate the relationships among fatigue, patient safety culture and safety care activities of hospital nurses, and to identify and explain factors influencing safety care activities. Methods: The research participants were 187 nurses from a urban general hospital located in Korea. Self-evaluation questionnaires were used to collect the data. Data collection was done from January 10 to 31, 2019. Data were analyzed using descriptive statistics, independent t-test, One-way ANOVA, Pearson correlation coefficients and multiple regression with the SPSS 24.0 program. Results: There were significant negative relationships between fatigue and safety care activities (r=-.22, p=.003), and significant positive relationships between patient safety culture and safety care activities (r=.22, p=.003). Factors influencing safety care activities in hospital nurses were identified as type of unit (ICU) (${\beta}=.28$), patient safety culture (${\beta}=.24$) and fatigue (${\beta}=-.19$). The explanation power of this regression model was 16% and it was statistically significant (F=8.29, p<.001). Conclusion: These results suggest the need to develop further management strategies for enhancement of safety care activities in hospital. To improve the levels of patient safety, education programs on patient safety should be developed and provided to nurses in hospitals.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.17-22
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• 2011

A considerable number of construction disasters occur on pathways. Safety management is usually performed on construction sites to prevent accidents in activity areas. This means that the safety management level of hazards on pathways is relatively minimized. Many researchers have noted that hazard identification is fundamental to safety management. Thus, algorithms for helping safety managers to identify hazardous areas are developed using automated data collection technology. These algorithms primarily search for potential hazardous areas by comparing workers' location logs based on a real-time location system and optimal routes based on BIM. Potential hazardous areas are filtered by identified hazardous areas and activity areas. After that, safety managers are provided with information about potential hazardous areas and can establish proper safety countermeasures. This can help to improve safety on construction sites.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.160-165
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• 2021

In order to identify and analyze potential aviation safety hazards, analysis of aviation safety report data must be preceded. Therefore, in consideration of the provisions of the Aviation Safety Act and the recommendations of ICAO Doc 9859 SMM Edition 4th, personal information in the reporting data and sensitive information of the reporter, etc. It identifies the scope of de-identification targets and suggests a method for applying de-identification processing technology to personal and sensitive information including unstructured text data.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.386-390
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• 2007

At recent times, an essential issue in the replacement of the old analogue I&C to computer-based digital systems in nuclear power plants becomes the quantitative software reliability assessment. Software reliability models have been successfully applied to many industrial applications, but have the unfortunate drawback of requiring data from which one can formulate a model. Software that is developed for safety critical applications is frequently unable to produce such data for at least two reasons. First, the software is frequently one-of-a-kind, and second, it rarely fails. Safety critical software is normally expected to pass every unit test producing precious little failure data. The basic premise of the rare events approach is that well-tested software does not fail under normal routine and input signals, which means that failures must be triggered by unusual input data and computer states. The failure data found under the reasonable testing cases and testing time for these conditions should be considered for the quantitative reliability assessment. We presented the quantitative reliability assessment methodology of safety critical software for rare failure cases in this paper.