• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1063-1073
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• 2015

In the long-term care insurance (LTCI) system, National Health Insurance Service (NHIS) provide counseling services for beneficiaries and their family caregivers, which help them use LTC services appropriately. The purpose of this study was to develop a Target Selection Model for the Counseling Services based on needs of beneficiaries and their family caregivers. To develope models, we used data set of total 2,000 beneficiaries and family caregivers who have used the long-term care services in their home in March 2013 and completed questionnaires. The Target Selection Model was established through various data-mining models such as logistic regression, gradient boosting, Lasso, decision-tree model, Ensemble, and Neural network. Lasso model was selected as the final model because of the stability, high performance and availability. Our results might improve the satisfaction and the efficiency for the NHIS counseling services.

• Journal of computational fluids engineering
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• v.6 no.4
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• pp.15-25
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• 2001

Numerical prediction of the diffusion controlled transition in a turbine gas pass is important because it can change the local heat transfer rate over a turbine blade as much as three times. In this study, the gas flow over turbine blade is simplified to the flat plate boundary layer, and an adaptive grid scheme redistributing grid points within the computation domain is proposed with a great emphasis on the construction of the grid control function. The function is sensitized to the second invariant of the mean strain tensor, its spatial gradient, and the interaction of pressure gradient and flow deformation. The transition process is assumed to be described with a κ-ε turbulence model. An elliptic solver is employed to integrate governing equations. Numerical results show that the proposed adaptive grid scheme is very effective in obtaining grid independent numerical solution with a very low grid number. It is expected that present scheme is helpful in predicting actual flow within a turbine to improve computation efficiency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.119-127
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• 1993

Recently, ADI scheme has been a most common tool for solving shallow water equation numerically. But ADI models of tidal flow is likely to cause so called ADI effect in such a region of the Yellow Sea which shows complex topography and has submarine canyons especially. To overcome this, a finite difference algorithm is developed which adopts fully implicit method and preconditioned conjugate gradient squared method. Applying the algorithm including simulation of intertidal zone to Sae-Man-Keum. velocity fields and flooding/drying phenomena are simulated well in spite of complex topography.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.523-528
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• 2004

This study proposed an anisotropic diffusion restoration fer image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.679-683
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• 2010

본 연구에서는 공간적 변수인 조도계수를 기지의 수위값을 이용하여 최적값을 결정하는 방법에 대해서 검토하고자 한다. 최적화 기법에 의한 조도계수는 기지의 수위값과 수치모의에 의한 결과 값의 전체 오차를 최소화하는 값으로 결정된다. 본 연구에서는 3가지 최적화 기법을 이용하였으며 가상 수로에 대해서 적용하였다. 수위계산은 표준축차법에 의해 수행하였으며 사용된 최적화 기법은 quasi-Newton 방법이다. 1차원 모형은 Matlab을 이용하여 표준축자법으로 구성하였으며 BFGS 기법, L-BFGS 기법, Steepest Gradient Descent 기법 등도 Matlab으로 구성하였다. 표준축차법은 조도계수가 입력되면 기지의 수위값과의 2-norm을 계산하도록 구성하였다. 계산 결과에 의하면 세가 기법 모두 20 23회 정도의 반복계산을 수행하고 값이 수렴되었는데, L-BFGS의 경우에는 정확하게 음수의 조도계수로 수렴하였으며, BFGS기법과 Steepest Gradient 기법의 경우에는 양의 값으로 정확하게 수렴하였다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.261-262
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• 2023

보행자 교통사고는 보행자와 운행 중인 차량 간 발생한 충돌사고로 도로 및 주변 환경 등에 영항을 받는다. 이 연구에서는 2018년부터 2022년까지 서울특별시에서 발생한 노인 보행자 교통사고 자료를 수집하여 보행자 교통사고의 사고 요인을 분석하였다. 분석에 있어서 고려된 연구모형은 랜덤포레스트, Gradient Boosting regression(GBR)이다. 분석 결과 서울특별시의 지리적 특성과 교통 통행 패턴을 반영하여 교통약자를 대상으로 하는 교통정책을 보완하고, 보행 안전을 강화하는 것이 필요하다.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.303-312
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• 2017

The central goal of Gamma Knife radiosurgery(GKRS) is to maximize the conformity of the prescription isodose surface, and to minimize the radiation effect of the normal tissue surrounding the target volume. There are the various kinds of indices related with the quality of treatment plans such as conformity index, coverage, selectivity, beam-on time, gradient index(GI), and conformity/gradient index(CGI). As the best treatment plan evaluation tool, we must check by all means conformity index, GI, and CGI among them. Specially, GI and CGI related with complication of healthy normal tissue is more indispensible than conformity index. Then author calculated and statistically analysed CGI, the newly defined conformity/gradient index as well as GI being applied widely using the treatment planning system Leksell GammaPlan(LGP) and the verification method Variable Ellipsoid Modeling Technique(VEMT). In the study 10 patients with intracranial lesion treated by GKRS were included. Author computed the indices from LGP and VEMT requiring only four parameters: the prescribed isodose volume, the volume with dose > 30%, the target volume, and the volume of half the prescription isodose. All data were analyzed by paired t-test, which is statistical method used to compare two different measurement techniques. No statistical significance in GI at 10 cases was observed between LGP and VEMT. Differences in GI ranged from -0.14 to 0.01. The newly defined gradient index calculated by two methods LGP and VEMT was not statistically significant either. Author did not find out the statistical difference for the prescribed isodose volume between LGP and VEMT. CGI as the evaluation index for determining the best treatment plan is not significant statistically also. Differences in CGI ranged from -4 to 3. Similarly newly defined Conformity/Gradient index for GKRS was also estimated as the metric for the evaluation of the treatment plans through statistical analysis. Statistical analyses demonstrated that VEMT was in excellent agreement with LGP when considering GI, new gradient index, CGI, and new CGI for evaluating the best plans of GKRS. Due to the application of the fast and easy evaluation tool through LGP and VEMT author hopes CGI and newly defined CGI as well as gradient indices will be widely used.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.1
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• pp.81-96
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• 2007

Nonlinear shoaling characteristics over surf zone are numerically investigated based on spatially averaged NavierStokes equation. We also test the validity of gradient model for turbulent stresses due to wave breaking using the data acquainted during SUPERTANK LABORATORY DATA COLLECTION PROJECT(Krauss et al., 1992). It turns out that the characteristics length scale of breaking induced current is not negligible, which firmly stands against ever popular gradient model, ${\kappa}-{\varepsilon}$ model, but favors Large Eddy Simulation with finer grid. Based on these observations, we model the residual stress of spatially averaged NavierStokes equation after Lagrangian Dynamic Smagorinsky(Meneveau et al., 1996). We numerically integrate newly proposed wave equations using SPH with Gaussian kernel function. Severely deformed water surface profile, free falling water particle, queuing splash after landing of water particle on the free surface and wave finger due to structured vortex on rear side of wave crest(Narayanaswamy and Dalrymple, 2002) are successfully duplicated in the numerical simulation of wave propagation over uniform slope beach, which so far have been regarded very difficult features to mimic in the computational fluid mechanics.

• Journal of Animal Science and Technology
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• v.46 no.2
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• pp.137-144
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• 2004

Algorithms for estimating breeding values on several categorical data by using latent variables with threshold conception were developed and showed. Thresholds on each categorical trait were estimated by Newton’s method via gradients and Hessian matrix. This algorithm was developed by way of expansion of bivariate analysis provided by Quaas(2001). Breeding values on latent variables of categorical traits and observations on linear traits were estimated by preconditioned conjugate gradient(PCG) method, which was known having a property of fast convergence. Example was shown by simulated data with two linear traits and a categorical trait with four categories(CE=calving ease) and a dichotomous trait(SB=Still Birth) in threshold animal mixed model(TAMM). Breeding value estimates in TAMM were compared to those in linear animal mixed model (LAMM). As results, correlation estimates of breeding values to parameters were 0.91${\sim}$0.92 on CE and 0.87${\sim}$0.89 on SB in TAMM and 0.72~0.84 on CE and 0.59~0.70 on SB in LAMM. As conclusion, PCG method for estimating breeding values on several categorical traits with linear traits were feasible in TAMM.