• International conference on construction engineering and project management
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• 2011.02a
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• pp.107-110
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• 2011

The key role in safety management is to identify any possible hazard before it occurs by identifying any possible risk factors which are critical to risk assessment. This planning/assessment process is considered to be tedious and requires a lot of attention due to the following reasons: firstly, falsework (temporary structures) in construction projects is fundamentally important. However, the installation and dismantling of those facilities are one of the high risk activities in the job sites. Secondly, temporary facilities are generally not clearly delineated on the building drawings. It is our strong belief that safety tools have to be simple and convenient enough for the jobsite people to manage them easily and be flexible for any occasions to be occurred at various degrees. In order to develop the safety assessment system, this research utilizes the BIM technology and collects important information by importing data from BIM models and use it in the planning stage.

• The KIPS Transactions:PartC
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• v.12C no.7 s.103
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• pp.989-998
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• 2005

Information systems are today becoming larger and mostly broadband-networked. This exposes them at a higher risk of intrusions and hacking than ever before. Of the technologies developed to meet information system security needs, risk analysis is currently one of the most actively researched areas. Meanwhile, due to the extreme diversity of assets and complexity of network structure, there is a limit to the level of accuracy which can be achieved by an analysis tool in the assessment of risk run by an information system. Also, the results of a risk assessment are most oftennot up-to-date due to the changing nature of security threats. By the time an evaluation and associated set of solutions are ready, the nature and level of vulnerabilities and threats have evolved and increased, making them obsolete. Accordingly, what is needed is a risk analysis tool capable of assessing threats and propagation of damage, at the same time as security solutions are being identified. To do that, the information system must be simplified, and intrusion data must be diagrammed using a modeling technique this paper, we propose a modeling technique information systems to enable security risk analysis, using SPICE and Petri-net, and conduct simulations of risk analysis on a number of case studies.

• Proceedings of the Korea Environmental Mutagen Society Conference
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• 2002.05a
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• pp.137-137
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• 2002

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.51-62
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• 2022

This study suggests a design of predictive modeling for a hospital fall risk based on inpatients' posture. Inpatient's profile, medical history, and body measurement data along with basic information about a bed they use, were used to predict a fall risk and suggest an algorithm to determine the level of risk. Fall risk prediction is largely divided into two parts: a real-time fall risk evaluation and a qualitative fall risk exposure assessment, which is mostly based on the inpatient's profile. The former is carried out by recognizing an inpatient's posture in bed and extracting rule-based information to measure fall risk while the latter is conducted by medical staff who examines an inpatient's health status related to hospital fall risk and assesses the level of risk exposure. The inpatient fall risk is determined using a sigmoid function with recognized inpatient posture information, body measurement data and qualitative risk assessment results combined. The procedure and prediction model suggested in this study is expected to significantly contribute to tailored services for inpatients and help ensure hospital fall prevention and inpatient safety.

• Journal of Food Hygiene and Safety
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• v.15 no.3
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• pp.267-270
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• 2000

This study was designed to predict the risk of a hazard chemical, vinyl chloride, by applying dose-response assessment that are one of the major process in practicing risk assessment. After extrapolating from the high dose exposure of vinyl chloride based upon animal carcinogenic data to the low dose exposed to human using several mathematical models, we calculated the cancer potency factors as well as virtually safe dose and the resulted values were compared. This process will provide the new insight to assess the risk of a chemical accurately imposed to human in the future.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.119-136
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• 1996

The evaluation of risk level or possibility of traffic accidents is a fundamental task in reducing the dangers associated with current transportation system. However, due to the lack of data and basic researches for identifying such factors, evaluations so far have been undertaken by only the experts who can use their judgements well in this regard. Here comes the motivation this thesis to evaluate such risk level more or less in an automatic manner. The purpose of this thesis is to test the fuzzy-logic theory in evaluating the risk level of traffic accidents. In modeling the process of expert's logical inference of risk level determination, only the geometric features have been considered for the simplicity of the modeling. They are the visibility of road surface, horizontal alignment, vertical grade, diverging point, and the location of pedestrain crossing. At the same time, among some inference methods, fuzzy composition inference method has been employed as a back-bone inference mechanism. In calibration, the proposed model used four sites' data. After that, using calibrated model, six sites' risk levels have been identified. The results of the six sites' outcomes were quite similar to those of real world other than some errors caused by the enforcement of the model's output. But it seems that this kind of errors can be overcome in the future if some other factors such as driver characteristics, traffic environment, and traffic control conditions have been considered. Futhermore, the application of site's specific time series data would produce better results.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.164-164
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• 2023

This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.

• East Asian mathematical journal
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• v.36 no.1
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• pp.55-60
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• 2020

We study a probabilistic approach for valuing an exchange option with default risk. The structural model of Klein [6] is used for modeling default risk. Under the structural model, we derive the closed-form pricing formula of the exchange option with default risk. Specifically, we provide the pricing formula of the option with the bivariate normal cumulative function via a change of measure technique and a multidimensional Girsanov's theorem.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.645-648
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• 2008

This study provides considerations for quantitative risk assessment of landslide on GIS technology. It shows how the landslide possibility analysis is linked by GIS modeling to provide loss estimation tools for landslide hazards in support of socio-economic loss reduction efforts. Those risk assessment results can deliver factual damage situation prediction to policy making for the landslide damage mitigation.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.207-215
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• 2009

Recently, the research of the analysis of the crime spatial is increased by using the computer information technology and GIS (Geometric Information System) in order to prevent the urban crime so as to increase the urbanization rate. In this paper, a probability map formed by the raster is organized by the quantification of crime risk per the cell using the region property of the urban spatial information in the static environment. Also, a map of the risk probability is constructed based on the relative risk by the region property, the relative risk by the facility, the relative risk by the woody plant and the river, and so on. And, this integrated risk probability map is calculated by averaging the individual cell risk applied to the climatic influence and the seasonal factor. And, a probability map of the overall risk is generated by the interpretation key of the crime occurrence relative risk index, and so, this information is applied to the probability map quantifying the occurrence crime pattern. And so, in this paper, a methodology of the modeling and the simulation that this crime risk probability map is modified according to the passage of time are proposed.