• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.74-88
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• 2010

In this study, the points of LiDAR were modified in order to generate various DEM resolutions by applying LiDAR data in Ulsan. Since the LiDAR data have points with 1m intervals, the number of points for each resolution was modified to the size of 1, 5, 10, 30, 50, 100m by uniformly eliminating the points. A runoff analysis was performed on Taehwa river and its tributary, Dongcheon, with 200 year rainfall exceedance probability. 2-dimensional inundation analysis was performed based on the density of LiDAR data using FLUMEN, which was used to establish domestic flood risk map. Once DEM data obtained from LiDAR survey are used, it is expected that the study results can be used as data in determining optimal grid spacing, which is economical, effective and accurate in establishing flood defence plans including the creation of flood risk map.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.357-363
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• 2022

This study aims to improve the safety inspection awareness of occupational exposure and help radiation safety management by analyzing radiation exposure doses by occupational type of radiation related-workers and radiation workers. Radiation-related workers and radiation workers were classified into three occupations (radiological technologist, doctors, and nurses). A nominal risk coefficient based on ICRP 103 was used to calculate the probability of causing side effects of the lungs due to exposure doses. As a result of analyzing the exposure dose of all workers for one year, the exposure dose of radiological technologist among radiation-related workers was 1.63 ± 2.84 mSv, doctors 0.12 ± 0.22 mSv, and nurses 0.59 ± 1.08 mSv. The one-year deep dose for radiation workers was 2.44 ± 3.30 mSv for radiological technologists, 0.19 ± 0.26 mSv for doctors, and 0.12 ± 0.00 mSv for nurses. Due to this dose, the probability of causing side effects in the lungs was 1.2 per 100,000 radiological technologist, 0.096 doctors, and 0.06 nurses. In this study, it is believed that the probability of side effects on lungs by occupation of radiation exposure dose will be studied and used as useful data for radiation safety management in relation to probabilistic effects in the future.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.4 no.1
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• pp.25-38
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• 1996

본 연구에서는 항공기 사고의 70%이상을 차지하는 이 ${\cdot}$ 착륙단계 중에서, 이륙 직후 저고도에서 동력이 상실되었을 경우에 이륙활주로 방향으로 Turning Back하는 것은 어떠한 안전 한계를 지니고 있는지를 알아보기 위하여, 우선 조종사에 대한 설문 조사를 실시하여 비행 경력별로 이륙 직후 동력 상실시의 비상 처치 경향과 위험에 처할 확률을 조사하였다. 그리고 실제 활공 성능이 우수한 M20J 항공기와 기동 성능이 우수한 FH20 항공기를 이용한 비행 시험을 통하여 이륙 직후 Turning Back to Runway조작 시의 고도 손실과 선회시 하강율을 실험 자료로 구하였다. 비행 시험 자료를 비교 적용함은 물론 선회 소요 시간과 고도 손실, 선회율과 활공 속도와의 관계 등의 항공 역학적 이론을 적용한 분석 근거에 기초하여 안전하게 Turning Back to Runway 조작을 시작할 수 있는 안전 고도 한계 및 선회율을 제시하였다.

• Annual Conference of KIPS
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• 2022.05a
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• pp.441-442
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• 2022

교통사고 예측은 차량의 블랙박스 동영상을 통해 사고 발생을 최대한 빨리 예측하는 것을 목표로 한다. 이는 안전한 자율주행 시스템을 보장하는 데 중요한 역할을 한다. 다양한 교통 상황과 카메라의 제한된 시야로 인해 프레임에서 사고 가능성을 조기에 관찰하는 것은 어려운 도전이다. 예측의 핵심 기술은 객체의 시공간 관계를 학습하는 것이다. 본 논문에서는 블랙박스 동영상에서 사고 예측을 위한 계산 모델을 제안한다. 이것을 사용하여 사고 예방을 강화한다. 이 모델은 사고 위험에 대한 운전자의 시각적 인식에서 영감을 받았다. 객체 탐지기는 동영상 프레임에서 다양한 객체를 탐지한다. 탐지한 객체는 노드 생성기와 특징 추출기 동시에 통과한다. 노드 생성기에서 생성한 노드는 GCN 실행기를 사용한다. GCN 실행기는 각 프레임에 대한 객체의 3D 위치 관계를 계산한 후 공간 특징을 취득한다. 동시에 공간 특징과 특징 추출기에서 얻은 객체의 특징은 GRU 실행기로 보내진다. GRU 실행기 안에 시공간 특징을 암기하고 분석하여 교통사고 확률을 예측한다.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.168-176
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• 2023

The demand for measures to enhance the safety of maritime transportation is growing internationally, and coastal shipping companies are pursuing sustainability by establishing various maritime safety policies. Increased awareness of the safety management system and safety culture of coastal shipping companies will minimize accidents and increase corporate sustainability. This study empirically analyzed the impact of a safety management system (safety policy, risk management, and safety guarantee) on the corporate sustainability of coastal shipping companies through the mediation of safety culture. The survey questions for each variable were constructed based on previous research and a dministered to 204 employees of coastal shipping companies. Analysis founed that safety policy did not have a statistically significant effect on safety culture, but risk management and safety guarantees had a positive significant effect on safety culture, which in turn had a positive and significant effect on sustainability. Furthermore, we found that safety culture has a mediating effect on the relationship between risk management and safety guarantees and sustainability. Coastal shipping companies thus need to systematize and strengthen risk management and safety assurance to increase safety culture awareness, and increased safety culture awareness can also increase sustainability.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.5
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• pp.467-478
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• 2024

The International Maritime Organization has adopted a strategy for reducing greenhouse gas emissions from international shipping, with enhanced targets to address ship-induced emissions. The liquid-hydrogen proton-exchange membrane fuel cell is promising for complying with such regulations. In general, ship design must adhere to the prescriptive rules of classification societies. However, increasing environmental regulations are enforcing the introduction of new fuels and systems, with the prescriptive rules lagging. Hence, we devise a method to verify new technologies by combining the hazard and operability study (HAZOP) and layer of protection analysis (LOPA) for a hydrogen fuel gas-supply system. The HAZOP allows us to identify hazardous scenarios, whereas the LOPA enables us to quantitatively complement the qualitative HAZOP results. The existing initiating event frequency and failure-on-demand probability of independent protection layers (IPLs) are identified. To determine the adequacy of the existing IPLs, we compare the estimated current mitigation with a risk-acceptance criterion. Additional IPLs are recommended when required to satisfy the risk criteria. Results show that HAZOP-LOPA can be potentially used to assess novel systems not yet adopted in the maritime sector.

• Korean Journal of Social Welfare Studies
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• v.48 no.2
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• pp.143-171
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• 2017

Along with the well-established evidence on the negative effect of social isolation on physical mental health and mortality, increasing attention has been paid to multi-dimensional nature of social isolation. In this study, the main effect and interaction effect of objective and subjective social isolation on heterogeneous age cohort related to the onset of dementia, which is becoming a social problem due to rapid aging of health issues, was examined through binary logistic regression analysis. Data came from the first wave of Korean Social Life, Health and Aging Project (KSHAP) (N= 814). Findings showed 1) in the young-old, objective isolation was a significant on the incidence of dementia, 2) in the old-old, subjective isolation increased the risk of dementia. In summary, the relative influence of objective and subjective social isolation related to the incidence of dementia varies depending on the young-old and old-old. On the other hand, the interaction effect of objective and subjective social isolation on dementia was not significant in both the young-old and old-old. Based on the findings, we discussed implications and suggestions for future research and relevant policy and program development(dementia-friendly communities) for ameliorating objective and subjective social isolation.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.4
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• pp.71-80
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• 2009

Although desire for living without hazardous damages grows these days, threats from natural disasters which we are currently exposed to are quiet different from what we have experienced. To cope with this changing situation, it is necessary to assess the characteristics of the natural disasters. Therefore, the main purpose of this research is to suggest a methodology to estimate the potential property loss and assess the flood risk using a regional regression analysis. Since the flood damage mainly consists of loss of lives and property damages, it is reasonable to express the results of a flood risk assessment with the loss of lives and the property damages that are vulnerable to flood. The regional regression analysis has been commonly used to find relationships between regional characteristics of a watershed and parameters of rainfall-runoff models or probability distribution models. In our research, however, this model is applied to estimate the potential flood damage as follows; 1) a nonlinear model between the flood damage and the hourly rainfall is found in gauged regions which have sufficient damage and rainfall data, and 2) a regression model is developed from the relationship between the coefficients of the nonlinear models and socio-economic indicators in the gauged regions. This method enables us to quantitatively analyze the impact of the regional indicators on the flood damage and to estimate the damage through the application of the regional regression model to ungauged regions which do not have sufficient data. Moreover the flood risk map is developed by Flood Vulnerability Index (FVI) which is equal to the ratio of the estimated flood damage to the total regional property. Comparing the results of this research with Potential Flood Damage (PFD) reported in the Long-term Korea National Water Resources Plan, the exports' mistaken opinions could affect the weighting procedure of PFD, but the proposed approach based on the regional regression would overcome the drawback of PFD. It was found that FVI is highly correlated with the past damage, while PFD does not reflect the regional vulnerabilities.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.27-40
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• 2022

Every year landslides cause serious casualties and property damages around the world. As the accurate prediction of landslides is important to reduce the fatalities and economic losses, various approaches have been developed to predict them. Prediction methods can be divided into landslide susceptibility analysis, landslide hazard analysis and landslide risk analysis according to the type of the conditioning factors, the predicted level of the landslide dangers, and whether the expected consequence cased by landslides were considered. Landslide susceptibility analyses are mainly based on the available landslide data and consequently, they predict the likelihood of landslide occurrence by considering factors that can induce landslides and analyzing the spatial distribution of these factors. Various qualitative and quantitative analysis techniques have been applied to landslide susceptibility analysis. Recently, quantitative susceptibility analyses have predominantly employed the physically based model due to high predictive capacity. This is because the physically based approaches use physical slope model to analyze slope stability regardless of prior landslide occurrence. This approach can also reproduce the physical processes governing landslide occurrence. This review examines physically based landslide susceptibility analysis approaches.