• 한국전자통신학회논문지
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• 제7권2호
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• pp.457-463
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• 2012

영상만을 기반으로 하는 유고감지 시스템은 다양한 주변 환경의 변화에 영향을 받아 성능이 크게 저하될 수 있다. 그 중 가장 큰 요인으로 야간에 차량 헤드라이트의 영향과 갑작스런 기상 변화에 따른 관심영역 (ROI) 및 배경정보가 변화되어 오감지율이 증가한다는 점이다. 따라서 본 논문에서는 영상에 기반을 둔 시스템에 레이저 스캐너를 활용한 시스템을 통합한 시스템을 제안하고 구현하였다. 실험에서 영상 기반을 둔 시스템의 대다수의 문제점을 극복할 수 있었고, 이로 인한 시스템에 대한 신뢰성 문제도 향상 될 수 있음을 인식할 수 있는 유의한 결과를 얻을 수 있었다.

• Nuclear Engineering and Technology
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• 제37권3호
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• pp.245-258
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• 2005

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population outside the plant boundary due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR with 144 meteorological sequences were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence. This could provide valuable insights into areas for further research aiming at reducing the uncertainties.

• 대한안전경영과학회지
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• 제10권4호
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• pp.1-9
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• 2008

It is very important to evaluate the priority of prevention factors and strategies in order to minimize industrial accident. It provides decisive information for accident prevention and safety management. Therefore, this paper proposes evaluation method of the priority through statistic testing with prevention factors and strategies by the cause analysis of cause and effect models. Especially, this paper uses priority matrix criterion to justify application of rank and objectivity. This paper is based on the results of a questionnaire of workers and managers who are engaged by real manufacturing and construction industries with less than 300 workers in the central region of Korea, where most of the fatal accidents have happened. Finally, the result provides one way to implement safety management for industrial accident prevention.

• 자동차안전학회지
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• 제12권2호
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• pp.40-46
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• 2020

Modern traffic accidents are a complex occurrence. Various indicators are needed to analyze traffic accidents. Countries that have been investigating traffic accidents for a long time accumulate various data to analyze traffic accidents. The Korean In-Depth Accident Study (KIDAS) database collected damaged vehicles and severity of injury caused by Collision Deformation Classification code (CDC code), Abbreviated Injury Scale (AIS), and Injury Severity Score (ISS). As a result of the investigation, data relating to the injuries of the occupants can be easily obtained, but it was difficult to analyze human severity based on the information of the damaged vehicle. This study suggests a method to measure the speed change at the time of an accident, which is one of the most important indicators in the vehicle crash database, to help advance KIDAS research.

• 대한인간공학회지
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• 제30권1호
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• pp.41-53
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• 2011

Objective: The purpose of this paper is to introduce new research trends of human error and accident modeling and to suggest future promising research directions in those areas. Background: Various methods and techniques have been developed to understand the nature of human errors, to classify them, to analyze their causes, to prevent their negative effects, and to use their concepts during design process. However, it has been reported that they are impractical and ineffective for modern complex systems, and new research approaches are needed to secure the safety of those systems. Method: Six different perspectives to study human error and system safety are explained, and then seven recent research trends are introduced in relation to the six perspectives. The implications of the new research trends and viable research directions based on them are discussed from a cognitive systems engineering point of view. Results: Traditional methods for analyzing human errors and identifying causes of accidents have critical limitations in complex systems, and recent research trends seem to provide some insights and clues for overcoming them. Conclusion: Recent research trends of human error and accident modeling emphasize different concepts and viewpoints, which include systems thinking, sociotechnical perspective, ecological modelling, system resilience, and safety culture. Application: The research topics explained in this paper will help researchers to establish future research programmes.

• 기술사
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• 제30권5호
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• pp.96-104
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• 1997

This study analyze industrial safety and health planning report for manufacture. The purpose of accident analysis is to obtain accurate and objective information about the causes of accidents in order to prevent accidents from reoccurring. This study investigated the causes and conditions of occupational accidents in Korean industry. As the most accidents are occurred in lifting material, the questionnaire analyses about injuries are operated for occur to deal with the Manual Materials Handing. The results show that there are some characteristics in the accidents of Korean industry since 1986: (1) accidents rates tend to have lower since 1983(1994-1.18%, 1995-0.99%, 1996-0.88%), (2) larger companies tend to have lower accident rates than the smaller ones, (3) inexperience is related to high accident rates(1995-51.26%, 1996-48.82%1, because of the careless education for freshman such as OJT which in order to prevent accident, and (4) the body sites most vulnerable to injury are the hands and fingers and increased the back(caused of Back pain). The results of questionnaire analysis show that operator(n= 104) interested in reinforce the back & belly(42.86%). These finding identified in this study can be used to prevent the industrial accidents, and used to improving directions based on analyzed result.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 1997년도 International Symposium on Fire Science and Technology
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• pp.252-259
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• 1997

A method to automate hazard analysis of chemical plants is proposed in this paper. The proposed system is composed of three knowledge bases - unit knowledge base, organizational knowledge base and material knowledge base, and three hazard analysis algorithms - deviation, malfunction and accident analysis algorithm. Hazard analysis inference procedure is developed based on the actual hazard analysis procedures and accident development sequence. The proposed algorithm can perform hazard analysis in two methods and represent all conceivable types of accidents using accident analysis algorithm. In addition, it provides intermediate steps in the accident propagation, and enables the analysis result to give a useful information to hazard assessment. The proposed method is successfully demonstrated by being applied to diammonium phosphate manufacturing process. A system to automate hazard analysis is developed by using the suggested method. The developed system is expected to be useful in finding the propagation path of a fault or the cause of a malfunction as it is capable to approach causes of faults and malfunctions simultaneously.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권10호
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• pp.995-999
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• 2010

매년 차량의 수가 꾸준히 증가함에 따라 이에 비례하여 도로의 혼잡도와 사고 발생률 또한 증가되고 있다. 이와 같은 교통문제를 완화하기 위해서 도로 설계 및 신호 체계 등이 발전되고 있음에도 불구하고 교통사고로 인한 인명 및 재산 피해는 감소되지 않고 있다. 본 논문에서는 발생원 사고를 실시간으로 인식하여 이에 빠르게 대응함으로써 후속사고를 예방하고 사고 원인을 파악하기 위한 실시간 사고 인식 및 분석 시스템을 제안한다. 제안하는 시스템은 특정 교차로에서 뿐만 아니라 교통흐름과 디자인이 다른 교차로에서 발생한 사고를 정확히 인식하는 것이 목적이다. 본 연구에서는 실제 교차로에서 수집되는 데이터가 정확하다고 보장할 수 없고, 사고 발생에 쓰이는 데이터는 서로 유기적으로 복잡한 관계가 있기 때문에 정확한 사고 인식을 위해 확률기반 연산을 하는 동적 베이지안 네트워크를 이용하였다.

• 산업경영시스템학회지
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• 제41권4호
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• pp.171-178
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• 2018

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

• 대한안전경영과학회지
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• 제22권1호
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• pp.9-14
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• 2020

Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.