• Journal of the Korean Institute of Gas
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• v.13 no.1
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• pp.14-20
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• 2009

As the consumption of LNG has increased, the capacity and number of LNG facilities are getting bigger and bigger. Such circumstances supports the need for a dedicated risk analysis model to help review and check major issues of the safer construction and operation of LNG storage facilities systematically. Therefore this study suggests an appropriate risk analysis model that enables us to evaluate hazards of LNG storage facilities more easily and systematically, and then to use its result in siting, design and construction stages of the facilities. ill order to develop the model, lots of existing studies and domestic and foreign codes and standards were fully reviewed and a series of case studies also were carried out. The suggested model consists of 4-stage evaluations: in selecting a site, in determining a layout, in designing and constructing the facilities, and in operating them. This model also suggests the weather condition necessary for estimating the consequence of accident-scenarios, and the easy, systematic approach to the analysis of their probability. We expect that the model may help secure LNG storage facilities' inherent safety in determining their site and layout.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.89-101
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• 2017

Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.

• The Journal of Engineering Geology
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• v.20 no.3
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• pp.243-255
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• 2010

The slope design of an open-pit mine must consider economical efficiency and stability. Thus, the overall slope angle is the principal factor because of limited support or reinforcement options available in such a setting. In this study, slope displacement, as monitored by a GPS system, was analyzed for a coal mine at Pasir, Indonesia. Predictions of failure time by inverse velocity analysis showed good agreement with field observations. Therefore, the failure time of an unstable slope can be roughly estimated prior to failure. A GIS model that combines fuzzy theory and the analytical hierarchy process (AHP) was developed to assess slope instability in open-pit coal mines. This model simultaneously considers seven factors that influence the instability of open-pit slopes (i.e., overall slope gradient, slope height, surface flows, excavation plan, tension cracks, faults, and water body). Application of the proposed method to an open-pit coal mine revealed an enhanced prediction accuracy of failure time and failure site compared with existing methods.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.99-100
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• 2022

화학산업이 발전함에 따라 잠재적인 화학물질 폭발사고 위험 또한 증가하고 있다. 순식간에 치명적인 인명, 재산피해를 남기는 폭발에 대한 영향을 예측, 분석하기 위해 다양한 해석모델이 활용되고 있지만, 폭발의 물리적 특성상 다양한 형태의 건물이 밀집된 지역에 대해서는 해석모델 사용만으로 높은 정확도의 분석을 진행하기에는 어려움이 있다. 따라서 본 연구는 GIS 공간정보와 3D 폭발 시뮬레이션의 약결합 방식을 적용하였다. 실제 연구지역과 동일한 환경을 구현하여 시뮬레이션을 구동하였고 이에 따른 폭발 규모와 폭발에 노출된 대상별 가해지는 압력 값을 도출하였다. TNT를 기준으로 위험물 저장 및 취급시설에 대한 최저 기준인 지정수량 200kg을 적용하였음에도 최대 2,960kPa의 압력이 발생하는 것으로 확인되었다. 본 연구로 도출된 결과에 건축물의 용도와 중요도를 적용한다면 토지이용계획 및 공간활용에 반영할 수 있으며, 안전관리자로 하여금 리스크 평가, BC분석, 안전관리계획 수립 등에 활용 가능하다고 사료된다.

• Journal of the Korean Institute of Gas
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• v.9 no.4 s.29
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• pp.57-61
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• 2005

The objective of paper is to carry out a comparative Quantitative Risk Assessment (QRA) of two KOGAS tank designs using a fault tree methodology, a standard 'Full Containment' tank and a 'Membrane' tank. For the membrane tank, both the initial KOGAS design and 4 modified KOGAS designs have been assessed, giving six separate cases. In this paper, the frequencies of releases are quantified using a fault tree approach. For clarity in the analysis, and to ensure consistency, all cases have been quantified using the same fault tree. Logic within the fault tree is used to select each of the cases. Full quantification of risks is often difficult, owing to a lack of relevant failure data, but the aim of this study has been to be as quantitative as possible, with full transparency of failure information. The most significant general cause of external LNG leaks is predicted to be a seismic event, which has been quantified nominally. 4modified KOGAS desiens to Prevent damage of bottom membrane panels that was shown in preparatory estimation could quantitively confirm safety improvement. According to result, the predicted frequencies of an external LNG leak for the full containment and modified membrane tanks are very similar, failures due to dropped pumps are predicted to be significantly greater for the membrane tank with thickened plate than for the full containment tank.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2009.04a
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• pp.311-317
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• 2009

우리나라에서 발생하는 화재의 대부분은 건축물 화재이며, 이중 노후화된 시가지 등 화재에 취약한 지역에서 화재발생시 도시화재로 확대될 우려가 높다. 이러한 도시화재 확대를 방지하기 위한 도시화재의 물리적 연소성상예측모델과 도시화재 리스크평가기법의 개발이 필요하다. 본 연구에서는 우리나라의 도시화재위험성평가 구축을 위한 한 일 공동연구체계와 주요 대상인 화제경계지구에 대하여 소개하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.419-422
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• 2024

최근 인공지능 기술의 발전과 함께 기계학습과 빅데이터를 융합한 서비스가 증가하게 되었고, 무분별한 데이터 수집과 학습으로 인한 개인정보 유출 위험도가 커졌다. 따라서 프라이버시를 보호하면서 기계학습을 수행할 수 있는 기술이 중요해졌다. 동형암호 기술은 정보 주체자의 개인정보 기밀성을 유지하면서 기계학습을 할 수 있는 방법 중 하나이다. 그러나 평문 크기에 비례하여 암호문 크기와 연산 결과의 노이즈가 커지는 동형암호의 특징으로 인해 기계학습 모델의 예측 정확도가 감소하고 학습 시간이 오래 소요되는 문제가 발생한다. 본 논문에서는 부분 동형암호화된 데이터셋으로 로지스틱 회귀 모델을 학습할 수 있는 기법을 제안한다. 실험 결과에 따르면 제안하는 기법이 종래 기법보다 예측 정확도를 59.4% 향상시킬 수 있었고, 학습 소요 시간을 63.6% 개선할 수 있었다.

• Information Systems Review
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• v.18 no.2
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• pp.173-198
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• 2016

Financial distress can damage stakeholders and even lead to significant social costs. Thus, financial distress prediction is an important issue in macroeconomics. However, most existing studies on building a financial distress prediction model have only considered idiosyncratic risk factors without considering systematic risk factors. In this study, we propose a prediction model that considers both the idiosyncratic risk based on a financial ratio and the systematic risk based on a business cycle. Ultimately, we build several IT artifacts associated with financial ratio and add them to the idiosyncratic risk factors as well as address the imbalanced data problem by using an oversampling technique and synthetic minority oversampling technique (SMOTE) to ensure good performance. When considering systematic risk, our study ensures that each data set consists of both financially distressed companies and financially sound companies in each business cycle phase. We conducted several experiments that change the initial imbalanced sample ratio between the two company groups into a 1:1 sample ratio using SMOTE and compared the prediction results from the individual data set. We also predicted data sets from the subsequent business cycle phase as a test set through a built prediction model that used business contraction phase data sets, and then we compared previous prediction performance and subsequent prediction performance. Thus, our findings can provide insights into making rational decisions for stakeholders that are experiencing an economic crisis.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.590-591
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• 2023

최근 사람들의 건강에 대한 관심이 많아지고 다양한 운동 컨텐츠가 확산되면서 실내에서 운동을 할 수 있는 기회가 많아졌다. 하지만, 전문가의 도움없이 정확하지 않은 동작을 수행하다 큰 부상을 입을 위험성이 높다. 본 연구는 CNN 기반 요가 자세 분류 모델을 생성하고 설명가능 인공지능 기술을 적용하여 예측 결과에 대한 해석을 제시한다. 사용자에게 설명성과 신뢰성 있는 모델을 제공하여 자신에게 맞게 올바른 자세를 결정할 수 있고, 무리한 동작으로 부상을 입을 확률 또한 낮출 수 있을 것으로 보인다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.197-207
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• 2018

SMEs manufacturing Factory, which are small-scale production systems of various types, mass-produce and sell products in order to meet customer needs. This means that the company has an excessive amount of material supply to reduce the loss due to lack of inventory and high inventory maintenance cost. And the products that fail to respond to the demand are piled up in the management warehouse, which is the reality that the storage cost is incurred. To overcome this problem, this paper uses ARIMA model, a time series analysis technique, to predict demand in terms of seasonal factors. In this way, demand forecasting model based on economic order quantity model was developed to prevent stock shortage risk. Simulation is carried out to evaluate the effectiveness of the development model and to demonstrate the effectiveness of the development model as applied to SMEs in the future.