• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.59-71
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• 2013

The lack of sufficient flood data being kept across Korea has made it difficult to assess reliable estimates of the design flood while relatively sufficient rainfall data are available. In this regard, a rainfall simulation based derivation technique of flood frequency curve has been proposed in some of studies. The main issues in deriving the flood frequency curve is to develop the rainfall simulation model that is able to effectively reproduce extreme rainfall. Also the rainfall-runoff modeling that can convey uncertainties associated with model parameters needs to be developed. This study proposes a systematic approach to fully consider rainfallrunoff related uncertainties by coupling a piecewise Kernel-Pareto based multisite daily rainfall generation model and Bayesian HEC-1 model. The proposed model was applied to generate runoff ensemble at Daechung Dam watershed, and the flood frequency curve was successfully derived. It was confirmed that the proposed model is very promising in estimating design floods given a rigorous comparison with existing approaches.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.197-211
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• 2018

We conducted this research to examine how well regional housing prices are suited to use as an alternative to conventional census-based regional deprivation indices in health and medical geography studies. To examine the relative performance of mean regional housing prices compared to conventional census-based regional deprivation indices, we compared several multilevel logistic regression models, where the first level was individuals and the second was health districts in the Seoul Metropolitan Area (SMA) in Korea, for the sake of adjusting the regional clustering tendency of unknown factors. In these models, we predicted two dichotomous variables that represented individuals' after-lunch tooth brushing behavior and use of dental floss by individual characteristics and regional indices. Then, we compared the relative predictive performance of the models using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The results from the estimations showed that mean regional housing prices and census-based deprivation indices were correlated with the two types of dental health behavior in a statistical sense. The results also revealed that the model with mean regional housing prices showed smaller AIC and BIC compared with other models with conventional census-based deprivation indices. These results imply that it is possible for housing prices summarized using aerial units to be used as an alternative to conventional census-based deprivation indices when the census variables employed cannot properly reflect the characteristics of the aerial units.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.684-691
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• 2006

As many functionalities such as cameras and MP3 players are converged to mobile phones, more intuitive and interesting interaction methods are essential. In this paper, we present applications and their enabling technologies for gesture interactive cell phones. They employ gesture recognition and real-time shake detection algorithm for supporting motion-based user interface and entertainment applications respectively. The gesture recognition algorithm classifies users' movement into one of predefined gestures by modeling basic components of acceleration signals and their relationships. The recognition performance is further enhanced by discriminating frequently confusing classes with support vector machines. The shake detection algorithm detects in real time the exact motion moment when the phone is shaken significantly by utilizing variance and mean of acceleration signals. The gesture interaction algorithms show reliable performance for commercialization; with 100 novice users, the average recognition rate was 96.9% on 11 gestures (digits 1-9, O, X) and users' movements were detected in real time. We have applied the motion understanding technologies to Samsung cell phones in Korean, American, Chinese and European markets since May 2005.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.191-193
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• 2014

The aim of this study was to examine the trend of ovary cancer incidence from 1999 to 2010 in China and predict the burden up to 2020. Crude incidence, age specific incidence and age-adjusted incidence rates were calculated. Joinpoint regression was performed to obtain estimated annual percentages and Bayesian age-period-cohort modeling was used to predict the incidence rate until the year 2020. In China, the crude rate of ovary cancer was 7.91/100,000 and the age-adjusted rate was 5.35/100,000 overall during period 1999-2010. The rates in urban regions were higher than in rural regions. A significant rising trend during 1999-2006 was followed by a drop during 2006-2010 in age-adjusted rates for urban females. In contrast, constant rise was observed in rural women. The decrease in ovary cancer of urban areas tended to be restricted to women aged 50 years and younger. In contrast, increases of ovary cancer in rural areas appeared in virtually all age groups. Although the age-adjusted incidence rate for ovary cancer was predicted to be reduced after year 2011, the crude rate was likely to be relative stable up to 2020. The burden of ovary cancer in China will continue to be relative stable due to the aging population.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.390-397
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• 2003

A three-dimensional (3D) inversion technique has been developed for interpretation of magnetotelluric (MT) data. The inversion method is based on the linearized least-squares (Gauss-Newton) method with smoothness regularization. In addition to the underground 3D resistivity distribution, static shifts are also treated as unknown parameters in the inversion. The forward modeling is by the staggered-grid finite difference method. A Bayesian criterion ABle is applied to search the optimum trade-off among the minimization of the data misfit, model roughness and static shifts. The method has been applied to several MT datasets obtained at geothermal fields in Japan and other Asian countries. In this paper, two examples will be discussed: one is the data at the Ogiri geothermal area, southwestern Japan, and the other is at the Pohang low-enthalpy geothermal field, southeastern Korea. The inversion of the Ogiri data has been performed stably, resulting in a good fitting between the observed and computed apparent resistivities and phases. The recovered 3D resistivity structure is generally similar to the two-dimensional (2D) inversion models, although the deeper portion of the 3D model seems to be more realistic than that of the 2D model. The 3D model is also in a good agreement with the geological model of the geothermal reservoirs. 3D interpretation of the Pohang MT data is still preliminary. Although the fitting to the observed data is very good, the preliminary 3D model is not reliable enough because the station coverage is not sufficient for a 3D inversion.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1133-1140
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• 2013

A computer model is a useful tool that provides solution via physical modeling instead of expensive testing. In reality, however, it often does not agree with the experimental data owing to simplifying assumption and unknown or uncertain input parameters. In this study, a Bayesian approach is proposed to calibrate the computer model in a probabilistic manner using the measured data. The elasto-plastic analysis of a pyrotechnically actuated device (PAD) is employed to demonstrate this approach, which is a component that delivers high power in remote environments by the combustion of a self-contained energy source. A simple mathematical model that quickly evaluates the performance is developed. Unknown input parameters are calibrated conditional on the experimental data using the Markov Chain Monte Carlo algorithm, which is a modern computational statistics method. Finally, the results are applied to determine the reliability of the PAD.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.139-145
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• 2006

This paper develops pedestrian fatality models capable of producing the probability of pedestrian fatality in collision between vehicles and pedestrians. Probabilistic neural network (PNN) and binary logistic regression (BLR) ave employed in modeling pedestrian fatality pedestrian age, vehicle type, and collision speed obtained from reconstructing collected accidents are used as independent variables in fatality models. One of the nice features of this study is that an iterative sampling technique is used to construct various training and test datasets for the purpose of better performance comparison Statistical comparison considering the variation of model Performances is conducted. The results show that the PNN-based fatality model outperforms the BLR-based model. The models developed in this study that allow us to predict the pedestrian fatality would be useful tools for supporting the derivation of various safety Policies and technologies to enhance Pedestrian safety.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.94-99
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• 2015

With the recent machine learning paradigm of using nonparametric Bayesian statistics and statistical inference based on random sampling, the Dirichlet distribution finds many uses in a variety of graphical models. It is a multivariate generalization of the gamma distribution and is defined on a continuous (K-1)-simplex. This paper presents a sampling method for a Dirichlet distribution for the problem of dividing an integer X into a sequence of K integers which sum to X. The target samples in our problem are all positive integer vectors when multiplied by a given X. They must be sampled from the correspondingly gridded simplex. In this paper we develop a Markov Chain Monte Carlo (MCMC) proposal distribution for the neighborhood grid points on the simplex and then present the complete algorithm based on the Metropolis-Hastings algorithm. The proposed algorithm can be used for the Markov model, HMM, and Semi-Markov model for accurate state-duration modeling. It can also be used for the Gamma-Dirichlet HMM to model q the global-local duration distributions.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1119-1131
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• 2016

The Neyman-Scott Rectangular Pulses Model (NSRPM) is mainly used to construct hourly rainfall series. This model uses a modest number of parameters to represent the rainfall processes and underlying physical phenomena, such as the arrival of storms or rain cells. In NSRPM, the method of moments has often been used because it is difficult to know the distribution of rainfall intensity. Recently, approximated likelihood function for NSRPM has been introduced. In this paper, we propose a hierarchical model for applying a spatial structure to the NSRPM parameters using the approximated likelihood function. The proposed method is applied to summer hourly precipitation data observed at 59 weather stations (Korea Meteorological Administration) from 1973 to 2011.

• YAKHAK HOEJI
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• v.39 no.2
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• pp.103-112
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• 1995

Population pharmacokinetics for gentamicin were compared with 24 American patients (16 male and 8 female) and 16 Korean-American appendicitis patients(12 male and 4 female). Two to six blood specimens were collected from all patients at the following times: just before a regularly scheduled infusion and at 1/2 hour after the end of a 1/2 hour infusion. Nonparametric expected maximum(NPEM) algorithm for population modeling was used. The estimated parameters were the elimination rate constant(K), the slope of the relationship between K versus creatinine clearance(KS), the apparent volume of distribution(V), the slope of the relationship between V versus weight(VS), gentamicin clearance(CL) and the slope of the relationship between CL versus creatinine clearance and the VS(CS). The output includes a 3-dimensional plot of the joint probability density function(PDF), two marginal PDF, means, medians, modes, variance, skewness, kurtosis, and CV%. The mean K(KS) were 0.424$\pm$0.139(0.00429$\pm$0.00164) and 0.411$\pm$0.135 hr$^{-1}$ (0.00475$\pm$0.00180[hr.mL/min/1.73m$^{2}]^{-1}$) for American and Korean-American populations, respectively. The mean V(VS) were not different at 15.6$\pm$4.77(0.233$\pm$0.0526) and 15.1$\pm$3.84L(0.239$\pm$0.0492 L/kg) for American and Korean-American populations, respectively (P>0.2). The mean CL (CS) were 6.28$\pm$1.85(0.0634$\pm$0.0191) and 5.70$\pm$1.77 L/hr(0.0701$\pm$0.0215 L/kg[hr.mL/min/1.73m$^{2}$)] for American and Korean-American populations, respectively. There are no differences in gentamicin pharmacokinetics between American and Korean-American Appendicitis patients.