• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.905-912
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• 2009

We propose a doubly penalized kernel machine (DPKM) which uses heteroscedastic location-scale model as basic model and estimates both mean and volatility functions simultaneously by kernel machines. We also present the model selection method which employs the generalized approximate cross validation techniques for choosing the hyperparameters which affect the performance of DPKM. Artificial examples are provided to indicate the usefulness of DPKM for the mean and volatility functions estimation.

• Kyungpook Mathematical Journal
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• v.60 no.4
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• pp.753-765
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• 2020

Smoking is one of the main causes of health problems and continues to be one of the world's most significant health challenges. In this paper, we use the multi-step Adomian decomposition method (MSADM) to obtain approximate analytical solutions for a mathematical fractional model of the evolution of the smoking habit. The proposed MSADM scheme is only a simple modification of the Adomian decomposition method (ADM), in which ADM is treated algorithmically with a sequence of small intervals (i.e. time step) for finding accurate approximate solutions to the corresponding problems. A comparative study between the new algorithm and the classical Runge-Kutta method is presented in the case of integer-order derivatives. The solutions obtained are also presented graphically. The results reveal that the method is effective and convenient for solving linear and nonlinear differential equations of fractional order.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.325-332
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• 1994

In this paper, a method is proposed to detect the endocardial contour of the left ventricle using the Hough transform with a weighted model and edge information from the 2D echocardiogram. The implementation of this method is as follows: first, an approximate model detection algorithm was implemented in order to detect the approximate endocardium model and the model center, then we constructed a weighted model with the detected model. Next, we found automatically the cavity center of the left ventricle performing the Hough transform which used the weighted model, and then we detected the endocardial contour using weighted model and edge image.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.314-320
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• 2011

In this work, optimization of two-stage shock absorption system for lunar lander has been carried out. Because of complexity of impact phenomena of shock absorption system, a 1-D constitutive model is proposed to describe the behavior of shock absorption system. Quadratic polynomial regression meta-model is constructed by using a commercial software ABAQUS with the proposed 1-D constitutive model, and sequential approximate optimization of two-stage shock absorption system has been carried out along with the constructed meta-model. Through the optimization, it is verified that landing impact force on lunar lander can be considerably reduced by changing the cell size and foil thickness of honeycomb structure in two-stage shock absorption system.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.16-26
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• 1997

China is one of the few countries where natural disaster strike frequently and cause heavy damage. In this paper, we mathematically develop two models to assess fuzzy risk of natural disaster in China. One is to assess the risk based on database of historical disaster effects by using information diffusion method relevant in fuzzy information analysis. In another model, we give an overview over advanced method to calculate the risk of release, exposure and consequence assessent, where information distribution technique is used to calculate basic fuzzy relationships showing historical experience of natural disasters, and fuzzy approximate inference is employed to study loss risk based on these basic relationships. We also present an examples to show how to use the first model. Result show that the model is effective for natural disaster risk assessment.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1858-1859
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• 2006

This paper presents a new fuzzy-neural-network based interacting multiple model (FNNBIMM) algorithm for tracking a maneuvering target. To effectively handle the unknown target acceleration, this paper regards it as additional noise, time-varying variance to target model. Each sub model characterized by the variance of the overall process noise, which is obtained on the basis of each acceleration interval. Since it is hard to approximate this time-varying variance adaptively owing to the unknown acceleration, the FNN is utilized to precisely approximate this time-varying variance. The gradient descendant method is utilized to optimize each FNN. To show the feasibility of the proposed algorithm, a numerical example is provided.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.199-205
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• 2010

The research proposes the three-factor random measurement models for estimating the precision about operator, part, tool, and various measurement environments. The combined model with crossed and nested factors is developed to analyze the approximate F test by degrees of freedom given by Satterthwaite and point estimation of precisions from expected mean square. The model developed in this paper can be extended to the three useful models according to the type of nested designs. The study also provides the three-step procedures to evaluate the measurement precisions using three indexes such as SNR(Signal-To-Noise Ratio), R&R TR(Reproducibility&Repeatability-To-Total Precision Ratio), and PTR(Precision-To-Tolerance Ratio), The procedures include the identification of resolution, the improvement of R&R reduction, and the evaluation of precision effect.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.209-216
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• 2015

Quantile regression models with covariate measurement errors have received a great deal of attention in both the theoretical and the applied statistical literature. A lot of effort has been devoted to develop effective estimation methods for such quantile regression models. In this paper we propose the partially linear support vector orthogonal quantile regression model in the presence of covariate measurement errors. We also provide a generalized approximate cross-validation method for choosing the hyperparameters and the ratios of the error variances which affect the performance of the proposed model. The proposed model is evaluated through simulations.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.6 no.4
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• pp.453-462
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• 1994

An unsteady quasi one-dimensional model of momentum, heat and mass transfer in a falling film of a vertical plate absorber which is cooled by air was developed using the integral method. Energy conservation of the absorber wall is considered in the model. The model can predict absorption rate, film thickness and mean velocity as well as concentration and temperature profiles. Predictions of steady state temperature and concentration profiles for LiBr/water system for constant wall temperature condition are in good agreement with the two-dimensional finite difference method solutions. Effects of operating conditions, such as convective heat transfer coefficient between the cooling air and the absorber wall, cooling air temperature and film thickness at inlet, on absorption rate of water vapor into LiBr/water solution were shown.

• Journal of KSNVE
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• v.8 no.3
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• pp.533-541
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• 1998

Recently, optical disk drives are increasingly demanded to have higher speed as well as high information density, especially for applications like CD ROM drives. To this end, improvement of their optical pickup structure and control is recognized the very challenging issue. In this paper, the pickup is first analytically modelled in a plane to describe its coupled auto-focusing and auto-tracking motions. Subsequently, the model is linearized and combined with actuator dynamics for the auto-focusing system. With its unmeasurable parameters being estimated based on experimental data, an approximate I-DOF linear model is obtained neglecting the coupling term. To design the high speed and robust positional servo controller realistic design specifications are addressed, and H control method is employed based on the approximate model. Finally, taking the pickup in a commerical high speed CD ROM drive as an example performance of the designed controller is verified through realtime experiments.