• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.460-467
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• 2006

Some large accidents in tunnels in recent years, such as Mont Blanc, Gotthard and Tauern tunnels, have lead to an increasing attention for tunnel safety and necessity of tool for quantitative risk assesment of road tunnel. And the purpose of this study is to develop the quantitative risk assesment tool for the application of road tunnel. The objectives of this paper are as follows : (1) analyze of traffic accident rates in tunnel, (2) make out scenario for fire accidents, (3) develop the evacuation model and FED calculation model, (4) Present the results from quantitative risk assesment for the model tunnel according with the fire heat release rates and distances of cross passage.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.53-63
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• 2017

Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.1
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• pp.121-132
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• 2018

Recent beauty trends focus on suitability to individual features. A personal color system is a recent aesthetic concept that influences color make up and coordination. However, a personal color concept has several weaknesses. For example, type classification is qualitative and not quantitative because its measuring system is a sensory test with no industry standard of personal color system. A quantitative personal color type classification model is the purpose of this study, which can be a solution to above problems. This model is a kind of mapping system in a 3D Cartesian coordinate system which has own axes, Value, Saturation, and Yellowness. The cheek color of the individual sample is also independent variable and personal color type is a dependent variable. In order to construct the model, this study conducted a colorimetric survey on a 993 sampling frequency of Korean women in their 20s and 30s. The significance of this study is as follows. First, through this study, personal color system is established on quantitative color space; in addition, the model has flexibility and scalability because it consisted of independent axis that allows for the inclusion of any other critical variable in the form of variable axis.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.239-247
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• 2014

For a sensitive survey in which the population is composed by several strata with quantitative attributes, we present an additive stratified quantitative attribute randomized response model which applied stratified random sampling instead of simple random sampling to the models of Himmelfarb-Edgell's additive quantitative attribute model and Gjestvang-Singh's. We also establish theoretical grounds to estimate the stratum mean of sensitive quantitative attributes as well as the over all mean. We deal with the proportional and optimal allocation problems in each suggested model and compare the relative efficiency of the suggested two models; subsequently, Himmelfarb-Edgell's model is more efficient than Gjestvang-Singh's model under the condition of stratified random sampling.

• Management Science and Financial Engineering
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• v.10 no.1
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• pp.25-41
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• 2004

There have been many studies to build a model that can help investors construct optimal portfolio. Most of the previous models, however, are based upon the path-breaking Markowitz model (1959) which is a quantitative model. One of the most important problems with that kind of quantitative model is that, in reality, most of the investors use not only quantitative, but also qualitative information when they select their optimal portfolio. Since collecting both types of information from the markets are time consuming and expensive, making a set of target assets smaller, without suffering heavy loss in the rate of return, would attract investors. To extract only desired assets among all available assets, we need knowledge that identifies investors' preference for the risk of the assets. This study suggests two-layer decision-making rules capable of identifying an investor's risk preference and an architecture applying them to a quantitative portfolio model based on risk and expected return. Our knowledge-based portfolio system is to build an investor's preference-oriented portfolio. The empirical tests using the data from Korean capital markets show the results that our model contributes significantly to the construction of a better portfolio in the perspective of an investor's benefit/cost ratio than that produced by the existing portfolio models.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.541-549
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• 2017

This research investigates the quantitative screening methods for the Grant Funding system and seeks for the efficient evaluation of a number of proposals. We search foreign cases of Grand Funding, but we found no appropriate model for using in Korea. Thus, we had to develope our own model for better screening. First, we analyse the existing evaluation system and find some problems and challenges. Second, we suggest a quantitative screening system for Grant Funding with a numeric model, and operates a tedious simulation by using the previous data and our suggested model. Third, we test the suggested model and find the optimal model by using simulation method The number of data analysed for simulation is larger than 200 thousands. Last, we suggest some brief policy implications based on the results in the paper.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.E2
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• pp.43-51
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• 2001

A report by the national research council in the United States suggested that many lung cancer deaths each year be associated with breathing radon in indoor air. Most of the indoor radon comes directly from soil beneath the basement of foundations. Recently, radon released from groundwater is found to contribute to the total inhalation risk from indoor air. This study presents the quantitative assessment of human exposures to radon released from the groundwater into indoor air. At first, a three-compartment model is developed to describe the transfer and distribution of radon released from groundwater in a house through showering, washing clothes, and flushing toilets. Then, to estimate a daily human exposure through inhalation of such radon for an adult. a physiologically-based pharmacokinetic(PBPK) model is developed. The use of a PBPK model for the inhaled radon could provide useful information regarding the distribution of radon among the organs of the human body. Indoor exposure patterns as input to the PBPK model are a more realistic situation associated with indoor radon pollution generated from a three-compartment model describing volatilization of radon from domestic water into household air. Combining the two models for inhaled radon in indoor air can be used to estimate a quantitative human exposure through the inhalation of indoor radon for adults based on two sets of exposure scenarios. The results obtained from the present study would help increase the quantitative understanding of risk assessment issues associated with the indoor radon released from groundwater.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.37-41
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• 2018

Process safety technology has developed from qualitative methods such as HAZOP (hazard and operability study) to semi-quantitative methods such as LOPA (layer of protection analysis), and quantitative methods are actively studied these days. Quantitative risk assessment (QRA) is often based on fault tree analysis (FTA). FTA is efficient, but difficult to apply when failure events are not independent of each other. This problem can be avoided using a Markov process (MP). MP requires definition of all possible states, and thus, generally, is more complicated than FTA. A method is proposed in this work that uses an MP model and a Weibull distribution model in order to construct a reliability model for multiple dependent failures. As a case study, a pressure safety valve (PSV) is considered, for which there are three kinds of failure, i.e. open failure, close failure, and gas tight failure. According to recently reported inspection results, open failure and close failure are dependent on each other. A reliability model for a PSV group is proposed in this work that is to reproduce these results. It is expected that the application of the proposed method can be expanded to QRA of various systems that have partially dependent multiple failure states.

• Structural Monitoring and Maintenance
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• v.10 no.2
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• pp.175-190
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• 2023

This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.206-207
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• 2022

Currently, safety accidents in construction area are managed regardless of the size. Therefore, the objective of this study is to conduct for developing the quantitative risk assessment according to large and small and medium-sized construction sites. The scope of this study is limited to the fall accidents which is the biggest accidents in the construction sites. the regression analysis was conducted based on the collected data. As a result, it was confirmed that there was a statistically significant difference between larce and small and medium-sized construction sites. This study is expected to be used as basic data for research on the development of a risk quantitative model for small and medium-sized construction sites in the future.