• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.245-258
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• 2005

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population outside the plant boundary due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR with 144 meteorological sequences were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence. This could provide valuable insights into areas for further research aiming at reducing the uncertainties.

• Korean Management Science Review
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• v.24 no.2
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• pp.143-155
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• 2007

The purpose of this paper is to develop a new method for information system sizing and selection based on a hybrid mixture of simulation and genetic algorithm, and to show its cost-effectiveness by applying it to a real world problem. To serve this purpose, we propose an operational model which identifies a set of system alternatives using simulation, and determines the optimal one using genetic algorithm. Specifically, with simulation, we generate probability distributions describing real data gathered from actual system, which can overcome the major weakness of the existing methodology that normally employs point estimates of the actual data and constant correction factors without theoretical rationale. We next search for the optimal combination of H/W, the number of CPUs, and S/W, which meets both of our business goals of incurring low TCO(total cost of ownership) and maintaining a good level of transaction processing performance. Experimental result shows the proposed method in this paper saves the cost while it preserves the system's capacity within allowable performance range.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.6
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• pp.103-111
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• 1995

Drought index calculation based on the principal hydrological parameters, such as rainfall and reservoir storage, can estimate the duration and intensity of drought in irrigation reservoirs. It is difficult to build up a drought criteria since the conditions change variously by the reliability of rainfall. Because of the increasing water demands, it is urgent to prepare a generalized positive countermeasure to overcome drought. Water demands can at calculated but the estimation of drought characteristics, and the effective water management method can be established. The purpose of this study is to obtain a drought index and build up a data-base on the reservoir basins for establishing the fundamental hydrological data-base. This Index can observe the behavior of the WSI(Water Supply Index) and the component indices. The results summarized through this study are as follows. 1. WSI value of zero does not correspond to 100% in average due to the skewness in the probability distributions. 2. WSI is not a linear index; that is, given change in terms of water volume or percentage of average does not result in a proportional change on the WSI scale. 3. WSI is not always between the reservoir and the rainfall index in magnitude. This is only true if the component indices are of opposite sign. If they are of the same sign, the SWSI will often have a mangitude greater than either of the component indices. This is easily understood, because the concurrence of extreme values of the same sign for the two components is rarer than the occurrence of extreme values for either of the two components individually.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.37-54
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• 2016

The methods for estimating the change of free energy in dissipative particle dynamics (DPD) are discussed on the basis of fluctuation theorems. Fluctuation theorems are tactics to evaluate free energy changes from non-equilibrium work distributions and have several forms, as proposed by Jarzynski, Crooks, and Bennett. The validity of these methods however, has been shown merely with the molecular dynamics or Langevin dynamics. In this study, the appropriate forms of fluctuation theorems for dissipative particle dynamics, which has similar structure to that of Langevin dynamics, are suggested using Liouville's theorem, and they are proved equivalent to original fluctuation theorems. Work distribution functions, which are probability distribution functions of works exerted on the system within the systematic change, are the basics of fluctuation theorems and their shapes are turned out to be dependent on the phase space trajectory of the change of the system. The reliability of Jarzynski and Crooks methods is highly dependent on the number of simulations to measure works and the shapes of the work distribution functions. Bennett method, however, can evaluate free energy changes even when Jarzynski and Crooks methods fail to do so.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.85-88
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• 2008

Damage from typhoon disaster can be mitigated by grasping and dealing with the damage promptly for the regions in typhoon track. What is this work, a technique to analyzed dangerousness of typhoon should be presupposed. This study estimated 10m level wind speed using 700hPa wind by typhoon, referring to GPS dropwindsonde study of Franklin(2003). For 700hPa wind, 30km resolution data of Regional Data Assimilation Prediction System(RDAPS) were used. For roughness length in estimating wind of 10m level, landuse data of USGS are employed. For 10m level wind speed of Typhoon Rusa in 2002, we sampled AWS point of $7.4\sim30km$ distant from typhoon center and compare them with observational data. The results show that the 10m level wind speed is the estimation of maximum wind speed which can appear in surface by typhoon and it cannot be compared with general hourly observational data. Wind load on domestic buildings relies on probability distributions of extreme wind speed. Hence, calculated 10m level wind speed is useful for estimating the damage structure from typhoon.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.2
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• pp.129-137
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• 2016

A colonoscopy is important because it detects the presence of polyps in the colon that can lead to colon cancer. How often one needs to repeat a colonoscopy may depend on various factors. The main purpose of this study is to determine personalized surveillance interval of colonoscopy based on characteristics of patients including their clinical information. The clustering analysis using a partitioning around medoids algorithm was conducted on 625 patients who had a medical examination at Korea University Anam Hospital and found several subgroups of patients. For each cluster, we then performed survival analysis that provides the probability of having polyps according to the number of days until next visit. The results of survival analysis indicated that different survival distributions exist among different patients' groups. We believe that the procedure proposed in this study can provide the patients with personalized medical information about how often they need to repeat a colonoscopy.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.95-102
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• 2013

This paper presents a stochastic driver behavior modeling framework which takes into account both individual and general driving characteristics as one aggregate model. Patterns of individual driving styles are modeled using a Dirichlet process mixture model, as a non-parametric Bayesian approach which automatically selects the optimal number of model components to fit sparse observations of each particular driver's behavior. In addition, general or background driving patterns are also captured with a Gaussian mixture model using a reasonably large amount of development data from several drivers. By combining both probability distributions, the aggregate driver-dependent model can better emphasize driving characteristics of each particular driver, while also backing off to exploit general driving behavior in cases of unseen/unmatched parameter spaces from individual training observations. The proposed driver behavior model was employed to anticipate pedal operation behavior during car-following maneuvers involving several drivers on the road. The experimental results showed advantages of the combined model over the model adaptation approach.

• Korean Journal of Remote Sensing
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• v.1 no.1
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• pp.5-27
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• 1985

A hill-sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimates of sample data for the first step of iterative unsupervised classification. The underlying assumption in this approach was that each cluster possessed a unimodal normal distribution. The key idea was that a clustering function proposed could distinguish elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill-sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with Landsat multispectral scanner (MSS) data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill-sliding clustering technique developed herein has the potential applicability to decomposition of any multivariate mixture distribution into a number of unimodal distributions when an appropriate diatribution function to the data set is employed.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.151-151
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• 2019

Because drought is a complex and stochastic phenomenon in nature, statistical approaches for drought assessment receive great attention for water resource planning and management. Generally drought characteristics such as severity, duration and intensity are modelled separately. This study aims to develop a relationship between drought characteristics using a bivariate copula model. To achieve the objective, we calculated the Standardized Precipitation Index (SPI) using rainfall data at 6 rain gauge stations for the period of 1961-1999 in Jehlum River Basin, Pakistan, and investigated the drought characteristics. Since there is a significant correlation between drought severity and duration, they are usually modeled using different marginal distributions and joint distribution function. Using exponential distribution for drought severity and log-logistic distribution for drought duration, the Galambos copula was recognized as best copula to model joint distribution of drought severity and duration based on the KS-statistic. Various return periods of drought were calculated to identify time interval of repeated drought events. The result of this study can provide useful information for effective water resource management and shows superiority against univariate drought analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.41-41
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• 2016

최근 다변량 확률모형을 이용한 빈도해석이 수문자료 등에 적용되면서 다양하게 연구되고 있으며 다변량 확률모형 중 copula 모형은 주변분포형에 대한 제약이 없어 여러 분야에 걸쳐 활발히 연구되고 있다. 강우자료는 기존 일변량 빈도해석을 수행하기 위하여 사용하던 block maxima 방법 대신 최소무강우시간(inter event time)을 통하여 강우사상을 추출하여 표본으로 사용한다. 또한 기후변화로 인한 강우량의 변화등에 대응하기 위하여 비정상성 Generalized Extreme Value(GEV)와 Gumbel 등의 확률분포형에 대한 연구도 많은 부분 이루어져 있다. 본 연구에서는, Archimedean copula 모형을 이용하여 이변량 확률모형을 구축하면서 여기에 사용되는 주변분포형에 정상성/비정상성 분포형을 적용하였다. 모형의 매개변수는 inference function for margin 방법을 이용하였으며 주변분포형으로는 정상성/비정상성 GEV, Gumbel 모형을 적용하였다. 결과로 정상성/비정상성 경향을 나타내는 지점을 구분하고 각 지점에 대한 정상성/비정상성 주변분포형을 적용한 이변량 확률분포형을 구하였다.