• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.5
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• pp.809-822
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• 2018

A quantitative risk assessment has been introduced to quantitatively evaluate fire risk as a means of performance based fire protection design in the design of railway tunnel disaster prevention facilities. However, there are insufficient studies to examine the effect of various risk factors on the risk. Therefore, in this study, the risk assessment was conducted on the model tunnel in order to examine the effects of the evacuation start time delay and the fire growth curve on the quantitative risk assessment. As a result of the analysis of the scenario, the fatalities occurred mainly when escapes in the same direction as the direction of the fire smoke movement. In addition, after the FED exceeded 0.3, the maximum fatalities occurred within 10 minutes. In the range of relatively low risk, distance between cross passages, evacuation delay time and fire growth curve were found to affect the risk, but they were found to have little effect on the condition that the risk reached the limit. Especially, in this study, it was evaluated that the evacuation delay time reduction, fire intensity and duration reduction effect were not observed when the distance between cross passages was more than 1500 m.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.178-185
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• 2023

Rapid urbanization and advancements in technology have led to a surge in the number of automobiles, resulting in frequent traffic accidents, and consequently, an increase in human casualties and economic losses. Therefore, there is a need for technology that can predict the risk of traffic accidents to prevent them and minimize the damage caused by them. Traffic accidents occur due to various factors including traffic congestion, the traffic environment, and road conditions. These factors give traffic accidents spatiotemporal characteristics. This paper analyzes traffic accident data to understand the main characteristics of traffic accidents and reconstructs the data in a time series format. Additionally, an LSTM-MLP based model that excellently captures spatiotemporal characteristics was developed and utilized for traffic accident prediction. Experiments have proven that the proposed model is more rational and accurate in predicting the risk of traffic accidents compared to existing models. The traffic accident risk prediction model suggested in this paper can be applied to systems capable of real-time monitoring of road conditions and environments, such as navigation systems. It is expected to enhance the safety of road users and minimize the social costs associated with traffic accidents.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.428-432
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• 2016

자연재해는 전 세계적으로 몇 조원에 이르는 피해를 주고 있으며 근래에는 기후변화로 인한 이상기후현상으로 집중호우의 빈도가 증가하고 있으며 홍수, 산사태 토석류 등 발생빈도가 늘어나고 있는 추세이다. 최근 2011년 서울에서 발생한 우면산 토석류의 피해와 강원도 일부 지역의 피해로 인해 많은 피해가 일어났으며, 국가에서는 산사태 피해를 최소화하기 위해서는 장기적으로는 위험한 지역에 구조물을 설치하는 등 예방사방을 실시하고, 단기적으로는 위험요소의 제거와 위험지역의 예측을 통한 경계피난체재를 철저히 할 필요성이 강조되고 있는 실정이다. 특히, 강원도는 산지로 이루어져 있으며, 매년 집중호우나 태풍이 지나간 다음, 많은 양의 강우량으로 인해 산길을 지나는 도로에 토석류로 인해 길이 막혀 이동이 불가능 하게 되거나 산지 아래에 있는 건물이 산에서 쓸려서 내려오는 토사와 나무에 의해 파괴되어 물질적인 피해를 입는 영상이 뉴스를 통해 많이 접하고 있다. 본 연구에서는 토석류에 대한 전반적인 특성을 설명하고 체계적인 관리가 필요하다. 연구 지역은 춘천지역을 대상으로 SINMAP 모델 기법의 조도계수와 특성을 고려한 위험지도를 작성하였고 산사태 일부 지역에 대한 위험도 평가를 하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.59-73
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• 2016

The demand for subsurface transport is increasing. The users and the operators of road tunnels are exposed to risks with different causes. One main cause, however, is the traffic situation in the event of accidents. The importance of a Quantified Risk Assessment is increasing to quantify the safety of road tunnels and to balance the requirements (capacity, reliability, availability, maintainability and safety) of various stakeholders. Although there are classical methods for risk assessments, such as ETA and FTA. These methods are used for relatively simple cases because it could not relevantly reflect the diversity and relationship of the parameters. Therefore, a quantitative risk assessment based on Bayesian Probabilistic Networks considering interdependence between the parameters of a complex underground system as a double deck tunnel is provided.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.32-45
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• 2018

This study aims to compare the mutual perception gap on dangerous driving behavior between male and female drivers in multiple aspects, analyze them, and identify factors that trigger this different perception. To understand the mutual perception gap on dangerous driving behavior, DBQ(Driving Behavior Questionnaire) was applied as a rating scale. By applying results into the Co-oreintation model, this study compared the mutual perception gap between male drivers and female drivers and analyze results. In addition, factors that generate the perception gap between both genders were drawn by analyzing factors. This study suggested that objective consistency identified the perception gap that driving behaviors of others were more dangerous between two genders. In addition, subjective consistency was different as both genders assumed that the counterpart's driving behavior takes more risks than their own actual driving behaviors. In regard to the accuracy, men were aware that female driving behaviors are more dangerous than their behaviors. However, female driving behavior assumed by women was consistent with male perception in all factors, which indicated that women perceive men precisely. In addition, results were compared and analyzed in both perspectives of male drivers and female drivers by combining predictive models. Based on these results, both genders perceived that counterpart's driving behavior is more dangerous among both genders.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.26-34
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• 2014

This study focuses on development of a risk level evaluation model for the intersection dilemma zone based on vehicle speed distribution approaching the intersection. The study results show that dilemma zone exists for all approaches selected for the study because the values of amber time have not been properly set, and that re-optimized values significantly reduce the dilemma zone risk level. It is also found that when normal distribution is assumed for vehicle approach speed the risk values similar to those for actual speed distributions can be obtained. When the risk level is found to be high, the amber time must be adjusted to reduce the length of the dilemma zone, or speed calming measures must be introduced so that vehicle speed be maintained under the speed value used when determining the amber time.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.134-143
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• 2010

This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.40-50
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• 2008

Most of satellite program process consists of mission analysis, thermal, structure, electronics design, and operation, etc. Each step has several steps like design phase, development phase, and verification phase, etc. As to do this kind of process, very high costs and much time are required, further high risk is included. So for solving those difficulties, satellite developers have designed and used satellite simulator system. In early stage of satellite development, simulator system was just used for a fragment of development and verification, so it could not give enough advantage on satellite development. In order to get high advantage on satellite development, full system level simulators which can be used for several steps for development and verification are evolved. So This paper introduces the trend of simulation systems for satellite development and verification used by several satellite developers.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.625-633
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• 2015

In this study, a coupled probabilistic framework is developed to assess wind risk on apartment buildings by using the convolution of wind hazard and fragility functions. In this framework, typhoon induced extreme wind is estimated by applying the developed Monte Carlo simulation model to the climatological data of typhoons affecting Korean peninsular from 1951 to 2013. The Monte Carlo simulation technique is also used to assess wind fragility function for 4 different damage states by comparing the probability distributions of the window system's resistance performance and wind load. Wind hazard and fragility functions are modeled by the Weibull and lognormal probability distributions based on simulated wind speeds and failure probabilities. The modeled functions are convoluted to obtain the wind risk for the different damage levels. The developed probabilistic framework clearly shows that wind risk are influenced by various important characteristics of terrain and apartment building such as location of building, exposure category, topographic condition, roof angle, height of building, etc. The risk model presented in this paper can be used as tools to predict economic loss estimation and to establish wind risk mitigation plan for the existing building inventory.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.1-6
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• 2020

In this study, we propose an association inference model based on data bias optimization for road hazard detection. This is a mining model based on association analysis to collect user's personal characteristics and surrounding environment data and provide traffic accident prevention services. This creates transaction data composed of various context variables. Based on the generated information, a meaningful correlation of variables in each transaction is derived through correlation pattern analysis. Considering the bias of classified categorical data, pruning is performed with optimized support and reliability values. Based on the extracted high-level association rules, a risk detection model for personal characteristics and driving road conditions is provided to users. This enables traffic services that overcome the data bias problem and prevent potential road accidents by considering the association between data. In the performance evaluation, the proposed method is excellently evaluated as 0.778 in accuracy and 0.743 in the Kappa coefficient.