• 월간산업보건
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• s.267
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• pp.37-39
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• 2010

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.21-32
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• 2007

Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. However, fuel mapping is extremely difficult because fuel properties vary at spatial scales, change depending on the seasonal situations and are affected by the surrounding environment. Remote sensing has potential to reduce the uncertainty in mapping fuels and offers the best approach for improving our abilities. Especially, Hyperspectral sensor have a great potential for mapping vegetation properties because of their high spectral resolution. The objective of this paper is to evaluate the potential of mapping fuel properties using Hyperion hyperspectral remote sensing data acquired in April, 2002. Fuel properties are divided into four broad categories: 1) fuel moisture, 2) fuel green live biomass, 3) fuel condition and 4) fuel types. Fuel moisture and fuel green biomass were assessed using canopy moisture, derived from the expression of liquid water in the reflectance spectrum of plants. Fuel condition was assessed using endmember fractions from spectral mixture analysis (SMA). Fuel types were classified by fuel models based on the results of SMA. Although Hyperion imagery included a lot of sensor noise and poor performance in liquid water band, the overall results showed that Hyperion imagery have good potential for wildfire fuel mapping.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.240-255
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• 2014

Cloud computing has increasingly been drawing attention these days. Each big company in IT hurries to get a chunk of meat that promises to be a whopping market in the future. At the same time, information is always associated with security and risk problems. Nowadays, the handling of these risks is no longer just a technology problem, with a good deal of literature focusing on risk or security management and framework in the information system. In this paper, we find the specific business meaning of the BMIS model and try to apply and leverage this model to cloud risk. Through a previous study, we select and determine the causal risk factors in cloud service, which are also known as CSFs (Critical Success Factors) in information management. Subsequently, we distribute all selected CSFs into the BMIS model by mapping with ten principles in cloud risk. Finally, by using the leverage points, we try to leverage the model factors and aim to make a resource-optimized, dynamic, general risk control business model for cloud service providers.

• Fire Science and Engineering
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• v.8 no.1
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• pp.47-52
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• 1994

이 논문은 설계상의 안전 및 완전한 정량적 위험성 평가에 의해 맞추는 것이 가능한 여러가지 방법(QRA: Quantitative risk analysis)에 촛점을 두면서, 위험성 평가의 방법론의 간략한 개요를 소개하고 있다. QRA의 결과는 단독 위험 및 그룹 혹은 사회적 위험으로써 보통 소개된다. 계산된 단독 risk는 자주 단독 위험 graph(IRG : Individual risk graph)와 단독 위험등고선(IRC : Individual risk contours)의 형으로 나타낸다. IRG와 IRC는 예를 들면 다음과 같은 사고의 시나리오로 계산된다. : 여러가지 기상조건 하에서 2kg/s의 암모니아의 유출을 1800s로 한다. 이 예는 그래프가 곡선의 상승을 나타내는 것이 확실하다. 마지막으로, QRA는 예를 들어서 토지이용계획 등에 유용한 수단으로 될 수 있다고 할 수 있다. 한편 화학플랜트의 안전에 대해서는, 위험성 평가를 위해 다른 방법이 유효하며, 불가피하다.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10335-10337
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• 2015

Background: Gastric cancer is considered as the second most prevalent cancer in Iran. The present research sought to identify high risk clusters of gastric cancer with mapping using space-time scan statistics. Materials and Methods: The present research is of descriptive type. The required data were gathered from the registered cancer reports of Cancer Control Office in the Center for Non Communicable Disease of the Ministry of Health (MOH). The data were extracted at province level in the time span of 2004-9. Sat-Scan software was used to analyse the data and to identify high risk clusters. ArcGIS10 was utilized to map the distribution of gastric cancer and to demonstrate high risk clusters. Results: The most likely clusters were found in Ardabil, Gilan, Zanjan, East-Azerbaijan, Qazvin, West-Azerbaijan, Kurdistan, Hamadan, Tehran and Mazandaran between 2007 and 2009. It was statistically significant at the p-value below 0.05. Conclusions: High risk regions included Northern, West-North and central provinces, particularly Ardabil, Kurdistan, Mazandaran and Gilan. More screening tests are suggested to be conducted in high risk regions along with more frequent epidemiological studies to enact gastric cancer prevention programs.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.771-783
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• 2023

This study aims to compare the performance of each machine learning model for preparing a grid-based disaster risk map related to flooding in Jung-gu, Ulsan, for Typhoon Chaba which occurred in 2016. Dynamic data such as rainfall and river height, and static data such as building, population, and land cover data were used to conduct a risk analysis of flooding disasters. The data were constructed as 10 m-sized grid data based on the national point number, and a sample dataset was constructed using the risk value calculated for each grid as a dependent variable and the value of five influencing factors as an independent variable. The total number of sample datasets is 15,910, and the training, verification, and test datasets are randomly extracted at a 6:2:2 ratio to build a machine-learning model. Machine learning used random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) techniques, and prediction accuracy by the model was found to be excellent in the order of SVM (91.05%), RF (83.08%), and KNN (76.52%). As a result of deriving the priority of influencing factors through the RF model, it was confirmed that rainfall and river water levels greatly influenced the risk.

• The Journal of Engineering Geology
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• v.24 no.3
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• pp.343-351
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• 2014

Tunnel face mapping plays an important role in risk analysis and infrastructure support decisions during tunnel construction. In this study, a digital mapping system using a mobile device is employed instead of existing face-mapping methods that rely upon face mapping sheets. The mobile device is then connected to the main server in the field, where a tunnel-specific database is compiled automatically. This information provides real-time feedback on the tunnel face to construction personnel and engineers, thus allowing for rapid assessment of tunnel face stability and infrastructure needs. The Douglas-Peucker algorithm, among others, is employed to resolve problems arising from the detailed mapping and speed problem by data accumulation. This system is expected to raise program optimization through field verification and additional functional improvements.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1234-1245
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• 2018

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.1307-1316
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• 2009

In this case, powerfulness quorum of destruction side which we have expected are supposed general limit value for rock floor when retaining of earth on the section of rock floor in the urban area. For digging in the urban area, there are a lot of dislocations to be disadvantage for safety of digging ants. The displacement of the pondside didn't converged with the phase of the excavation. Also, the speed of displacement got higher than the percentages of risk in the construction. So, we put into operation Face mapping for checking special quality of dislocations which appear on the digging ants. This results were used to decide a destruction in the case of the final excavation by analyzing with other results. It was possible to know the unstable distribution of a fault line in Face Mapping and to get powerful lens of a surface of discontinuity by tests indoors and outdoors. The results were also used to make a solution. Therefore, It's a successful example using the Partial TopDown for stable digging. And it is important that Face Mapping have to be practiced for solving the uncertainty of ground organization when digging design in the urban city.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.132-144
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• 2014

Information always comes with security and risk problems. There is the saying that, "The tall tree catches much wind," and the risks from cloud services will absolutely be more varied and more severe. Nowadays, handling these risks is no longer just a technology problem. So far, a good deal of literature that focuses on risk or security management and frameworks in information systems has already been submitted. This paper analyzes the causal risk factors in cloud environments through critical success factors, from a business perspective. We then integrated these critical success factors into a business model for information security by mapping out 10 principles related to cloud risks. Thus, we were able to figure out which aspects should be given more consideration in the actual transactions of cloud services, and were able to make a business-level and general-risk control model for cloud computing.