• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2699-2701
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• 2000

This paper presents the Runge-Kutta neural networks(RKNN's) using the Runge-Kutta approximation method and the orthogonal function for control of unknown dynamical systems described by ordinary differencial equations in high accuracy. These subnetworks of RKNN's are based on orthogonal function. Computer simulations show the usefulness of the proposed scheme.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.98-104
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• 2009

The objective of this paper is to investigate the effect of factors on the dynamic stiffness variation of boring bar. The experiment was carried out by Taguchi Method and Orthogonal array table. The results indicate that overhang was found out to be dominant factor with 95% confident intervals and feed rate and depth of cut were insignificant. In addition, analysis of loss function shows that loss value increased sharply from 3D to 4D(D is a shank diameter). Consequently, there is critical point which changes property of dynamic stiffness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.145-154
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• 2000

In this paper we proposed the orthogonal neural network(ONN) to control and identify the unknown controlled system. The proposed ONN used the buffer layer in front of the hidden layer and the hidden layer used the sigmoid function and its derivative a derived RBF that is a derivative of the sigmoid function. In order to verify the property of the proposed, it is examined by simulation results of the Narendra model. Controlled system is composed of ONN and confirmed its usefulness through simulation and experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.8 s.185
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• pp.119-126
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• 2006

Kriging model is widely used as design DACE(analysis and computer experiments) model in the field of engineering design to accomplish computationally feasible design optimization. In this paper, the optimization of gate valve was performed using Kriging based approximation model. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. In addition, we describe the definition, the prediction function and the algorithm of Kriging method and examine the accuracy of Kriging by using validation method.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.50-57
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• 2003

In this study, the structural optimal design was applied to the girder of over head crane. The optimization was carried out using ANSYS code fur the deadweight of girder, especially focused on the thickness of its upper, lower, reinforced and side plates. The weight could be reduced up to around 15% with constraints of its deformation, stress and buckling strength. The structural safety was also verified by the buckling analysis of its panel structure. It might be thought to be very useful to design the conventional structures fur the weight save through the structural optimization. The objective function and restricted function were estimated by the orthogonal array, and the sensitivity analysis of design variable fur that was operated.

• Communications of the Korean Mathematical Society
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• v.15 no.2
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• pp.285-308
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• 2000

We generalize bi-orthogonal (non-orthogona) MRA to frame MRA in which the family of integer translates of a scaling func-tion forms a frame for the initial ladder space V0. We investigate the internal structure of frame MRA and establish the existence of a dual scaling function, and show that, unlike bi-orthogonal MRA, there ex-ists a frame MRA that has no (frame) 'wavelet'. Then we prove the existence of a dual wavelet under the assumption of the existence of a wavelet and present easy sufficient conditions for the existence of a wavelet. Finally we give a new proof of an equivalent condition for the translates of a function in L2(R) to be a frame of its closed linear span.

• Interaction and multiscale mechanics
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• v.3 no.2
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• pp.123-143
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• 2010

The essential idea of the element-free Galerkin method (EFG) is that moving least-squares (MLS) approximation are used for the trial and test functions with the variational principle (weak form). By using the weighted orthogonal basis function to construct the MLS interpolants, we derive the formulae for an improved element-free Galerkin (IEFG) method for solving three-dimensional problems in linear elasticity. There are fewer coefficients in improved moving least-squares (IMLS) approximation than in MLS approximation. Also fewer nodes are selected in the entire domain with the IEFG method than is the case with the conventional EFG method. In this paper, we selected a few example problems to demonstrate the applicability of the method.

• Proceedings of the KSRS Conference
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• v.2
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• pp.913-916
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• 2006

Spatial distribution, seasonal and interannual variability of chlorophyll a concentration in Okhotsk Sea from SeaWiFS data between 2001 and 2004 were describe. An Empirical Orthogonal Function method was applied for analysis data. The ten modes described about 85% of total variance. Two maxima were defined - more intensive in spring and weaker in autumn. The first mode showed zones with chlorophyll a concentration during maximum bloom. The second mode specified timing of spring bloom in various regions in Okhotsk Sea. Analysis of SeaWiFS data indicated connection between highest chlorophyll a concentration and sea surface temperature limits during spring bloom. Similar relation was not found during fall bloom.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.4 s.346
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• pp.39-43
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• 2006

In this contribution, the achievable performance of orthogonal multicarrier DS-CDMA systems employing synchronous uplink transmissions is investigated. The bit error ratio (BER) performance is analyzed under dispersive Rayleigh multipath fading conditions as a function of the number of users.

• Journal of applied mathematics & informatics
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• v.6 no.2
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• pp.669-684
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• 1999

We are interested in the problem of fitting a curve to a set of points in the plane in such a way that the sum of the squares of the orthogonal distances to given data points ins minimized. In[1] the prob-lem of fitting circles and ellipses was considered and numerically solved with general purpose methods. Especially in [2] H. Spath proposed a special purpose algorithm (Spath's ODF) for parabolas y-b=$c($\chi$-a)^2$ and for rotated ones. In this paper we present another parabola fitting algorithm which is slightly different from Spath's ODF. Our algorithm is mainly based on the steepest descent provedure with the view of en-suring the convergence of the corresponding quadratic function Q(u) to a local minimum. Numerical examples are given.