• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.971-980
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• 2017

The varying coefficient regression model has gained lots of attention since it is capable to model dynamic changes of regression coefficients in many regression problems of science. In this paper we propose a varying coefficient regression model that effectively considers the errors on both input and response variables, which utilizes the kernel method in estimating the varying coefficient which is the unknown nonlinear function of smoothing variables. We provide a generalized cross validation method for choosing the hyper-parameters which affect the performance of the proposed model. The proposed method is evaluated through numerical studies.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.217-219
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• 2010

Spasticity is a motor disorder characterized by a velocity dependent increase in muscle tone with exaggerated tendon jerks, resulting from hyper-excitability of the stretch reflex. The aim of this study is to develop a portable system for quantifying the grade of spasticity which could calculate the biomechanical as well as neurophysiologic parameters, and for determining the relationship between the Tonic Stretch Reflex Threshold (TSRT) and Modified Ashworth Scale (MAS). Eleven patients with stroke participated in the study (6 males and 5 females, the average age of $64.5\pm16.0$ years). As a results, the mean and standard deviation values of the TSRT were $129.8\pm4.2$, $123.4\pm5.2$ and $119.1\pm2.6$ in the MAS 1, MAS 1+ and MAS 2 groups, respectively. Also, there was a negative correlation between the TSRT and MAS (rho=-0.72, p<0.05). This demonstrated that the TSRT could be made clinically available for the more objective and reliable evaluation of the spasticity, instead of using the conventional clinical scales and an isokinetic dynamometer.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.7
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• pp.814-820
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• 2011

It takes long time in numerical simulation because structural design for tire requires the nonlinear material property. Neural networks has been widely studied to engineering design to reduce numerical computation time. The numbers of hidden layer, hidden layer neuron and training data have been considered as the structural design variables of neural networks. In application of neural networks to optimize design, there are a few studies about arrangement method of input layer neurons. To investigate the effect of input layer neuron arrangement on neural networks, the variables of tire contour design and tension in bead area were assigned to inputs and output for neural networks respectively. Design variables arrangement in input layer were determined by main effect analysis. The number of hidden layer, the number of hidden layer neuron and the number of training data and so on have been considered as the structural design variables of neural networks. In application to optimization design problem of neural networks, there are few studies about arrangement method of input layer neurons. To investigate the effect of arrangement of input neurons on neural network learning tire contour design parameters and tension in bead area were assigned to neural input and output respectively. Design variables arrangement in input layer was determined by main effect analysis.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.217-234
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• 2018

Copulas are a tool for constructing multivariate distributions and formalizing the dependence structure between random variables. From copula literature review, there are a few asymmetric copulas available so far while data collected from the real world often exhibit asymmetric nature. This necessitates developing asymmetric copulas. In this study, we discuss a method to construct a new class of bivariate asymmetric copulas based on products of symmetric (sometimes asymmetric) copulas with powered arguments in order to determine if the proposed construction can offer an added value for modeling asymmetric bivariate data. With these newly constructed copulas, we investigate dependence properties and measure of association between random variables. In addition, the test of symmetry of data and the estimation of hyper-parameters by the maximum likelihood method are discussed. With two real example such as car rental data and economic indicators data, we perform the goodness-of-fit test of our proposed asymmetric copulas. For these data, some of the proposed models turned out to be successful whereas the existing copulas were mostly unsuccessful. The method of presented here can be useful in fields such as finance, climate and social science.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.18-23
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• 2006

The complex system synchronization methods improve based on synchronization theory; however, due to deeper level of complexity within complex system compared to that of chaos system, it is difficult to synchronize complex signals from complex system. In this paper, we proposed coupled-synchronization theory in the n-double scroll circuit and new embedding driven-synchronization theory, a method of accomplishing synchronization with only one parameter out of may parameters, in hyper-chaos circuit to apply synchronization in the complex system. By applying proposed synchronization method using computer simulation, we confirmed the accomplishment of superior synchronization in complex system.

• Computers and Concrete
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• v.21 no.1
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• pp.21-30
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• 2018

In this study, we analyze the behavior of concrete which contains zeolite and diatomite. In order to achieve the goal, we utilize expert system methods. The utilized methods are artificial neural network and adaptive network-based fuzzy inference systems. In this respect, we exploit seven different mixes of concrete. The concrete mixes contain zeolite, diatomite, mixture of zeolite and diatomite. All seven concrete mixes are exposed to 28, 56 and 90 days' compressive strength experiments with 63 specimens. The results of the compressive strength experiments are used as input data during the training and testing of expert system methods. In terms of artificial neural network and adaptive network-based fuzzy models, data format comprises seven input parameters, which are; the age of samples (days), amount of Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer. On the other hand, the output parameter is defined as the compressive strength of concrete. In the models, training and testing results have concluded that both expert system model yield thrilling medium to predict the compressive strength of concrete containing zeolite and diatomite.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1129-1134
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• 2016

This paper suggests a new method of finding regularization parameter for image restoration problems. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, unified Bayesian interpretation of Tikhonov regularization is introduced and applied to the image restoration problems. The relationship between Tikhonov regularization parameter and Bayesian hyper-parameters is established. Update formular for the regularization parameter using both maximum a posteriori(: MAP) and evidence frameworks is suggested. Experimental results show the effectiveness of the proposed method.

• Transactions of Materials Processing
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• v.21 no.8
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• pp.499-505
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• 2012

The fuel cell is a very promising power generation system combining the benefits of extremely low emissions, high efficiency, ease of maintenance and durability. In order to promote the commercialization of fuel cells, a flexible forming process, in which a hyper-elastic rubber is adopted as a medium to transmit forming pressure, is suggested as an efficient and cost effective manufacturing method for fuel cell bipolar plates. In this study, the ability of this flexible forming process to produce the micro channel arrays on metallic bipolar plates was first demonstrated experimentally. Then, a finite element (FE) model was built and validated through comparisons between simulated and experimental results. The effects of key process parameters on the forming performance such as applied load and punch velocity were investigated. As a result, appropriate process parameter values allowing high dimensional accuracy without failure were suggested.

• Biomolecules & Therapeutics
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• v.10 no.3
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• pp.202-207
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• 2002

The hepato-protective activity of the GODEX (Hepadif-s capsule) has been studied in the rats against $CCl_4$-ethanol induced liver toxicity. The rats were oral1y treated with $CCl_4$ (corn oil/ $CCl_4$ 1:1, 1 mg/kg). And one week passes, $CCl_4$(0.4 mg/kg) administered two times a week for 7 weeks. The drugs have been administered every two days for 4 weeks after $CCl_4$ injection. The experimental groups have consisted of the GODEX (250 mg/kg), Hepadif (200 mg/kg), DDB complex (DDB 50 mg/kg and garlic oil powder 50 mg/kg), DDB (50 mg/kg), and vehicle control respectively. There was a significant decrement on the serum level of aspartate aminotransferase (AST), alanine aminotransferase (ALT) and total bilirubin in all treated groups. Specially, ALT level of GODEX and Hepadif only treated groups was decreased c1early. Also, serum albumin level was significantly enhanced in GODEX treated group compared with control and DDB treated groups. In histological results, hepatocellular vacuolar degeneration, lobular restructure and necrosis of bile duct were severely showed in control. But other treated groups showed centerilobular degeneration and mild hyper-plasia. Hepadif or DDB has a effects of the recovery on serum parameters and structure ill liver injury. When it was compared GODEX to Hepadif alone or DDB complex or DDB, it suggested to have the best activity of the liver recovery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.529-536
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• 2007

Registration between image and object space is a fundamental step in photogrammetry and computer vision. Along with rapid development of sensors - multi/hyper spectral sensor, laser scanning sensor, radar sensor etc., the needs for registration between different sensors are ever increasing. There are two important considerations on different sensor registration. They are sensor invariant feature extraction and correspondence between them. Since point to point correspondence does not exist in image and laser scanning data, it is necessary to have higher entities for extraction and correspondence. This leads to modify first, existing mathematical and geometrical model which was suitable for point measurement to line measurements, second, matching scheme. In this research, linear feature is selected for sensor invariant features and matching entity. Linear features are incorporated into mathematical equation in the form of extended collinearity equation for registration problem known as photo resection which calculates exterior orientation parameters. The other emphasis is on the scheme of finding matched entities in the aide of RANSAC (RANdom SAmple Consensus) in the absence of correspondences. To relieve computational load which is a common problem in sampling theorem, deterministic sampling technique and selecting 4 line features from 4 sectors are applied.