• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.36-56
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• 2022

Traffic accidents occur in Korea are calculated with the 「Automobile Accident Negligence Ratio Certification Standard」 prepared by the 'General Insurance Association of Korea' and the insurance company's agreement or judgment is made. However, disputes are frequently occurring in calculating the negligence ratio. Therefore, it is thought that a more effective response would be possible if accident type according to the standard could be quickly identified using traffic accident information prepared by police. Therefore, this study aims to develop a model that learns the accident information prepared by the police and classifies it to match the accident type in the standard. In particular, through data mining, keywords necessary to classify the accident types of the standard were extracted from the accident data of the police. Then, models were developed to derive the types of accidents by learning the extracted keywords through decision trees and random forest models.

• The Journal of Korean Association of Computer Education
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• v.11 no.4
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• pp.1-12
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• 2008

This paper proposes basic algorithmic thinking based problem models applicable immediately without additional learnings and it problems basic problems and evaluation methods using material factors in an elementary course of mathematics For these purposes, an algorithmic thinking based problem model and it's basic problem models are proposed based on flowchart design methods with 5 degrees of difficulties. And algorithmic thinking based basic problems are developed by applying the proposed basic problem models into material domain in an elementary course of mathematics. And this paper proves the validity of developed basic problems in defining then as algorithmic thinking based basic problems through experiments and statistical analyses. The experimental results are analyzed in views of variety and effectiveness evaluation of answer algorithms and suitability of allocating 5 degrees of difficulties to the developed basic problems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.332-335
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• 2016

2000년대 들어 정보기술의 발달로 정보공유와 수집을 쉽게 할 수 있게 되면서 많은 정보를 활용하여 미래의 사람들의 행동과 생각을 예측하기에 이른다. 특히, 정부는 보안과 위험관리 분야에 빅데이터 개념을 도입하여 미래에 대한 위험을 예측하고 효과적으로 관리할 수 있게 되었다. 선박도 사람과 마찬가지로 선박운항과 관련된 수많은 정보들을 만들어낸다. 이렇게 생성된 정보는 각 기관에 흩어져 관리되고 있으며, VTS센터에서 수집되는 정보들은 아직까지 체계적인 관리조차 이루어지지 않고 있다. 본 제언은 국내 VTS센터, 나아가 인근 국가의 VTS센터에서 생성되는 각종 정보들과 관련 기관에서 활용되는 정보들을 한 곳에서 통합하여 관리하는 시스템을 구축하고 이곳에서 공유 분석되는 정보를 통해 조금이나마 선박사고의 위험성을 감소시킬 수 있는 관제 방법에 대해서 생각해보았다. 이에 대한 방안 중 하나로 정보공유를 통한 선박 사고 개연성 예측 모델을 제시하고자 한다. 이후 연구를 통해, 본 제언에서 제시된 사고 개연성 예측 모델을 위한 위험유발 인자와 사고의 발생과의 상관을 통계적으로 해명할 수 있게 된다면 본 모델을 활용하여 보다 선제적이고, 효율적인 선박관제를 수행할 수 있을 것으로 생각된다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.339-340
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• 2017

화학공장의 누출사고는 초기에 적절히 대응하지 못할 경우 화재 폭발과 같은 2차 3차의 복합재난사고로 확산될 위험성이 매우 높다. 이러한 이유로 누출사고 발생 초기에 누출이 발생한 지점을 신속히 파악하여 현장안전요원에게 알림으로써, 보다 체계적이고 효율적인 초기대응을 가능하게 하여, 사고피해를 완화시킬 수 있는 통합적인 누출사고 대응시스템 구축은 매우 중요하다고 할 수 있다. 본 연구에서는, 통합적인 누출사고 대응시스템 구축을 위한 선행연구로, 딥러닝 기반의 누출원추적 모델 개발을 제안한다. 여수에 위치한 실제 화학공장을 대상으로 누출사고 시나리오에 대한 Computational Fluid Dynamics (CFD) 시뮬레이션을 진행한 뒤, 화학공장 경계면에 배치된 각 센서별 위치에서의 농도, 풍향 그리고 풍속데이터를 추출하고, 센서 좌표를 추가하여 인공신경망을 학습시켰다. 학습된 모델은 40개의 누출후보군에 대해 학습에 사용되지 않은 상황들에서도 75.43%의 정확도로 누출이 일어난 지점을 실시간 예측해냄을 확인하였다. 또한 누출지점 예측이 일치하지 않은 경우도, 예측된 지점이 실제 누출이 일어난 지점과 물리적으로 매우 인접함을 확인함으로써 제안된 모델을 실제 현장에 적용할시 기대되는 효과는 더 클 것으로 판단하였다.

• Journal of the Korean Institute of Gas
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• v.2 no.1
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• pp.90-98
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• 1998

In order to establish detailed plans for fire protection and reduce the possible fire accidents in the future, collection of domestic and foreign fire accident cases and fundamental analysis are very important. In this study the classification model for fire accidents was developed and the direction to a new model was suggested by comparison ours with the accidents classification model of NFPA of United States of America and Japan. A new developed PC-based database program for fire accidents (FADBS) was used to analyse fire accidents easily and efficiently.

• Journal of the Korean Chemical Society
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• v.44 no.6
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• pp.600-610
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• 2000

The purpose of this study was to design the new teaching strategy based on the particulate model facilitating the reflective thinking (RE-PM) in the learning of the particulate nature of matter, and to investigate the effect of the new teaching strategy in compare with the traditional teaching strategy (TS-PM) after treating with new teaching strategy on preliminary teachers of elementary school. The problems of traditional teaching strategy are as follows: 1) Most of students didn't think the particulate model connected with practical material. 2) Most of students have a tendency of the rote memory on learning of the traditional particulate model. 3) The ratio of changing the view of continuous matter into the view of particulate nature of matter was very low, after learning the particulate model using of the traditional teaching strategy. The new teaching strategy facilitating the reflective thinking was more effective on the understanding of particulate nature of matter and the driving of motivation than the traditional teaching strategy in the learning of the particulate nature of matter.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.219-221
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• 2023

첨단 디지털기술이 적용된 자율운항선박과 같이 인간의 개입을 획기적으로 줄인 첨단 시스템의 운용은, 대상 시스템의 운용 중 시스템에 영향을 미치는 다양한 변수들의 변화를 실시간으로 검토하여 안전한 시스템 운용을 위한 의사결정을 지원할 수 있는 위험도평가 방법론의 적용이 요구된다. 본 논문은, 자율운항선박의 충돌 사고 위험도를 실시간으로 분석하기 위한 위험도 모델의 개발을 목적으로, 자율운항선박 충돌 사고 시나리오에 대한 위험도분석 작업 수행 내용과 실시간 충돌 위험도를 표현하기 위하여 검토한 간략한 위험도 모델 개념들을 제시하고 있다. 위험도 모델 개발을 위하여, 먼저 자율운항선박의 항해, 통신, 비상대응 기능들을 분석하고, 기능분석 결과를 바탕으로 충돌 사고 빈도 산출을 위한 Fault Tree Analysis와 충돌 사고로 인한 영향 산출을 위한 Event Tree Analysis를 수행하였다. 또한, Fault Tree와 Event Tree의 입력값 중 외부 조건에 따라 변화하는 변수들을 식별하였고, 각 변수들에 입력값은 자율운항선박의 운항 조건에서 발생할 수 있는 가상 데이터를 만들어 사용하였으며, 식별된 각 변수들의 변화로 인한 자율운항선박 충돌 위험도 변화량을 검토하였다.

• Korean Journal of Construction Engineering and Management
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• v.22 no.5
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• pp.55-65
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• 2021

Compared with other industries, construction industry shows a higher rate of death accidents and recently companies' legal responsibilities are to be increasingly enforced. The trend causes tremendous concerns for construction firms and increases the importance of forecasting and pro-actively managing death accidents in construction fields. The objective of the study is to develop a predictive analytics model for forecasting death accidents in building projects based on a decision tree technique, which enables to forecast the probabilities of death accidents by trade. The use of the model helps to decrease risks of legal punishments and to assist the safe execution of building projects by forecasting and pro-actively managing death accidents.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.55-60
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• 2023

The IoT environment is very vulnerable to security threats, and if an intrusion occurs, it can cause great damage. In order to strengthen the security of the IoT environment, a curriculum that considers the characteristics of the IoT environment is needed. In this paper, we propose a curriculum model for cyber incident response in the Internet of Things environment. The proposed curriculum model was designed as a model for security threats in the IoT environment, types of intrusion incidents, and incident response procedures. The proposed curriculum model is expected to contribute to improving security awareness in the IoT environment and fostering cyber incident response experts in the IoT field. The proposed curriculum model strengthens the security of the IoT environment and is expected to be safe through security incident response in the IoT.