• 한국안전학회지
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• 제35권2호
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• pp.94-99
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• 2020

Bikers can be subjected to injuries from unexpected accidents even if they wear basic helmets. A properly designed airbag can efficiently protect the critical areas of the human body. This study introduces a wearable smart airbag system using machine learning techniques to protect human neck and shoulders. When a bicycle accident happens, a microprocessor analyzes the biker's motion data to recognize if it is a critical accident by comparing with accident classification models. These models are trained by a variety of possible accidents through machine learning techniques, like k-means and SVM methods. When the microprocessor decides it is a critical accident, it issues an actuation signal for the gas inflater to inflate the airbag. A protype of the wearable smart airbag with the machine learning techniques is developed and its performance is tested using a human dummy mounted on a moving cart.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2019년도 춘계 학술논문 발표대회
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• pp.45-46
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• 2019

Accident rate in domestic construction industry has been increased rapidly in every year. In particular, the rate of death has been shown very high compared with other industries. It means that safety activities performed by government is not effective in reducing the rate of accident. To solve these problems, the risk factors should be predicted in advance, controlled, monitored and managed from start of project to end of project. However, most studies have been conducted by using frequency of occurrence of accident and only listed the importance of risk. Therefore, the objective of this study is to provide basic material to develop risk quantifying model for human accidents on construction site in South Korea. In the future, it is expected to be used as a reference of study on developing safety mangement checklist in construction industry and model for forecasting accident.

• 한국항해항만학회지
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• 제26권3호
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• pp.329-336
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• 2002

최근 선원재해 감소를 위한 국내선사들의 많은 노력에도 불구하고 그 감소율은 둔감하고 있는 실정이며, 이에 관한 일과성 유사연구 사례는 있으나 선원정책의 인적요소를 중심으로하는 본격적인 연구는 부족한 실정이다. 따라서, 본 연구에서는 현재 승선중이거나 승선경험이 있는 선원을 중심으로 설문조사를 실시하여 선원재해에 관한 의식현황을 분석하여 해상안전 및 선원재해에 관한 대비책을 제시하고자 한다.

• 한국심리학회지 : 문화 및 사회문제
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• 제16권3호
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• pp.267-287
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• 2010

본 연구는 우리나라의 교통사고 조사양식을 개선하고 이를 통해 사고조사 자료의 신뢰성을 확보하여 인적 사고관련 요인 판단에 도움을 줄 수 있는 방안을 모색하기 위해 실시되었다. 먼저 교통사고 조사양식 개선안을 만들기 위해 미국과 영국에서 사용하고 있는 조사양식 및 관련 연구들이 제시한 항목들을 분석하였다. 또, 이렇게 만들어진 조사양식 개선안이 충분한 사고설명력을 가지는지 알아보기 위해 2008년 한 해 동안 경기도에서 발생한 사망사고 중 502건을 새로 분석하여 기존 항목에 의한 분석결과와 비교하였다. 분석결과, 도로환경 부문과 운전자 요인 부문에서 일부 불명확한 내용의 기존항목이 제거되고, 새로운 내용들이 사고조사 양식에 반영되어야 할 필요성이 제기되었다. 본 연구결과를 바탕으로 인적요인을 고려한 교통사고 조사양식 개선안과 추후 연구과제들을 논의와 부록자료를 통해 제안하였다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.2021-2028
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• 2010

국외에서는 대형시스템을 사용하는 항공, 해양, 원자력, 철도 등에서 발생하는 사고 중 인적오류가 포함된 사고에 대한 분석 및 연구가 활발히 진행되고 있다. 우리나라에서는 영국, 미국 등의 철도선진국과 비교하여 인적오류를 고려한 철도시스템의 체계적인 운영이 미흡하며, 관련 기준을 별도로 규명하지 않고 있는 실정이다. 또한, 사고 분석을 위한 방법이나 절차, 인적오류와 관련된 원인요소에 대한 항목이 제한적이어서 사고분석이 어려운 실정이다. 이에 본 연구에서는 철도사고구분에 따른 위험사건들을 체계화하여 기관사, 사령, 역무원을 포함한 철도안전업무종사자의 수행도에 영향을 끼칠 수 있는 인적오류원인들을 국내외 연구결과를 바탕으로 체계화하고, 국내 철도 사고 사례를 통해 적합한 인적오류원인을 도출할 수 있는 분류방안을 마련한다.

• Journal of Multimedia Information System
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• 제5권2호
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• pp.111-114
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• 2018

Traffic accident analysis is important to reduce the occurrence of the accidents. In this paper, we analyze the traffic accident with Apriori algorithm to find out an association rule of traffic accident in Korea. We first design the traffic accident analysis model, and then collect the traffic accidents data. We preprocessed the collected data and derived some new variables and attributes for analyzing. Next, we analyze based on statistical method and Apriori algorithm. The result shows that many large-scale accident has occurred by vans in daytime. Medium-scale accident has occurred more in day than nighttime, and by cars more than vans. Small-scale accident has occurred more in night time than day time, however, the numbers were similar. Also, car-human accident is more occurred than car-car accident in small-scale accident.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.562-569
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• 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.

• 대한인간공학회지
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• 제34권2호
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• pp.103-113
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• 2015

Objective: This study proposes a systematic process to present the analysis methods and solutions of organizational root causes to human errors on the railroad. Background: In fact, organizational root cause such as organizational culture is an important factor in the safety concerns on human errors in the nuclear power plant, railroad and aircraft. Method: The proposed process is as follows: 1) define analysis boundary 2) select human error taxonomy 3) perform accident analysis 4) draw root causes with FGI 5) review root causes analysis with survey 6) chart analysis of root causes, and 7) propose alternatives and solutions. Results: As a result, root causes of the organizations like railroad and nuclear power plant came from the educational problems, violations, payoff system, safety culture and so forth. Conclusion: The proposed process does predict potential railroad accident through retrospect error analysis by building new human error taxonomies and problem solution. Application: This study would contribute to examination of the relationship between human error-based accidents and organizational root causes.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2017년도 추계 학술논문 발표대회
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• pp.195-196
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• 2017

The number of human accidents in the construction industry is increasing every year, and it constitute the highest percentage among industry. This means that activities performed to prevent safety accidents in the country are not efficient to reduce the rate of accidents in the construction industry. In order to solve this issue, research has been conducted from various perspectives. But, research regarding to quantification model of human accidents is insufficient. the objective of this study is to conduct a basic study on quantification model development of human accidents. To achieve the objective, first, Cause of accident is defined the through literature review. Second, a basic statistic analysis is conducted to determine the characteristics of the accident causes. Third, the analysis is conducted after dividing into four categories : accumulate rate, season, total construction cost, and location. In the future, this study can be used as a reference for developing the safety management checklist for safety management in construction site and development of prediction models of human accident.

• 한국환경보건학회지
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• 제46권5호
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• pp.588-598
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• 2020

Objectives: Human indices were developed to determine returning point of residents and damage restoration after the chemical accident Methods: To determine the returning point of residents after the chemical accident, a new concept, the standard man model was introduced as a human index, in which both H-code and its acute effects were main idea. To evaluate the applicability, a hydrogen fluoride leakage accident in Gumi was applied. The returning point were suggested as the conservative remission period of acute effects among relevant hazard effects and compared with actual returning point. The coverage of each age group were considered with reflecting average daily dose expected for actual residents. In addition, a relief-index as a social-scientific approach was reflected as well to apply the damage restoration Results: Actual returning point of residents in Gumi was 88 days; and that of standard man model suggested was 84 days. The expected amount of exposure at aged 12 or under was at least 2.35 times greater than that of this model, 40s, theoretically. However, their population ratio was less than 1%, so 99% of residents could be applied when the standard man model was applied. The relief-index was as an objective and quantitative methodology to apply the qualitative aspect. Conclusions: Although evaluated as a relatively positive result, there was a limitation such as the number of accident applied to the verification of standard man model. The relief index was also considered, but further research should be carried out to find threshold level for the relief.