• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1509-1510
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• 2008

In this paper, we propose a robust adaptive controller for induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the high order neural networks(HONN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

• Communications of the Korean Mathematical Society
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• v.9 no.2
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• pp.439-448
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• 1994

It is known that the steepest descent(SD) method and the conjugate gradient(CG) method [1, 2, 5, 6] converge when these methods are applied to solve linear systems of the form Ax = b, where A is symmetric and positive definite. For some finite difference discretizations of elliptic problems, one gets positive definite matrices that are almost symmetric. Practically, the SD method and the CG method work for these matrices. However, the convergence of these methods is not guaranteed theoretically. The SD method is also called Orthores(1) in iterative method papers. Elman [4] states that the convergence proof for Orthores($\kappa$), with $\kappa$ a positive integer, is not heard. In this paper, we prove that the SD method and the CG method converge when the $\iota$$^2$ matrix norm of the non-symmetric part of a positive definite matrix is less than some value related to the smallest and the largest eigenvalues of the symmetric part of the given matrix.(omitted)

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.127-134
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• 2008

In this paper, we propose a robust adaptive backstepping control of induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time-varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the fuzzy neural network(FNN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.79-86
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• 2002

This paper proposes a new algorithm for estimating ARMA model parameters. In estimating ARMA model parameters, several methods such as generalized least square method, instrumental variable method have been developed. Among these methods, the utilization of a bootstrap type algorithm is known as one of the effective approach for the estimation, but there are cases that it does not converge. Hence, in this paper, making use of a cross correlation function and utilizing the relation of structural a priori knowledge, a new bootstrap algorithm is developed. By introducing theoretical relations, it became possible to remove terms, which is liable to include much noise. Therefore, this leads to robust parameter estimation. It is shown by numerical examples that using this algorithm, all simulation cases converge while only half cases succeeded with the previous one. As for the calculation time, judging from the fact that we got converged solutions, our proposed method is said to be superior as a whole.

• Journal of the Korean Institute of Rural Architecture
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• v.2 no.3
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• pp.77-84
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• 2000

Kurye-gun, which Hwaeomsa temple is located, has huge scale's geographical characteristics, such as mountains, rivers and open fields. This is really blessing area because of Som-jin river at the bottom of Ghiri mountain and open fields, which this situation is very difficult. The location of Hwaeomsa temple is an end of The Baek-Doo Mountains and very important spot(where influences to its geometric converge) of the theory of feng-shui. On exposure logic of the Korean traditional theory of feng-shui, the organization in Ga-Ram of Hwaeomsa temple is inconsistent with representative theory and analyzing system. So, this is one of successful examples with the theory of feng-shui because exhalation from the earth and water was organized well with accuracy.

• Journal of the Korean Institute of Navigation
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• v.24 no.4
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• pp.227-234
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• 2000

In general, neural networks are widely used for the category classification of multispectral images. Since the input multispectral images into neural networks we, however, low contrast images, neural networks converge very slowly and are of bad performance. To overcome this problem, we propose a new image enhancement method which consists of smoothing process, finding the main valley and enhancement process. In addition the enhanced images by the proposed method are used as the input of neural networks for the category classification. When the new category classification method is applied to multispectral LANDSAT TM images, we verified that the neural networks converge very lastly and that the overall category classification performance is improved.

• Journal of the Korean Mathematical Society
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• v.41 no.1
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• pp.1-20
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• 2004

Let A be a uniform algebra, and let $\phi$ be a self-map of the spectrum $M_A$ of A that induces a composition operator $C_{\phi}$, on A. It is shown that the image of $M_A$ under some iterate ${\phi}^n$ of \phi is hyperbolically bounded if and only if \phi has a finite number of attracting cycles to which the iterates of $\phi$ converge. On the other hand, the image of the spectrum of A under $\phi$ is not hyperbolically bounded if and only if there is a subspace of $A^{**}$ "almost" isometric to ${\ell}_{\infty}$ on which ${C_{\phi}}^{**}$ "almost" an isometry. A corollary of these characterizations is that if $C_{\phi}$ is weakly compact, and if the spectrum of A is connected, then $\phi$ has a unique fixed point, to which the iterates of $\phi$ converge. The corresponding theorem for compact composition operators was proved in 1980 by H. Kamowitz [17].

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.1095-1099
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• 2017

A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.997-1000
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• 2021

본 연구는 버스환승정보센터의 디지털기기에 마이크로 인터렉션을 적용하여 UI를 설계한다. UI를 설계하면서 디지털기기에 사용이 어려운 고령자의 특성을 물리적, 인지적 기준으로 분류하고 문제점을 파악하여 지금까지 연구되어온 타이포그래픽, 컬러 등의 그래픽적 요소가 아닌 마이크로인터렉션 효과를 적용하여 고령자에게 디지털기기의 사용성을 높이기 위한 UI를 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.972-975
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• 2021

최근 한국 여름 기후의 열대화 현상이 급속화 됨에 따라 잦은 장마와 태풍으로 인해 방제 약품이 씻겨나가 방제가 제대로 안되는 경우가 많아졌다. 이는 식물과 작물들이 병해에 약해지는 계기를 만들었다. 따라서 본 논문에서는 그 중 실내 농사가 어려운 감귤에 중점을 잡고 감귤에서 주로 나타나는 흑점 영상 인식에 대한 모델을 제안하였다. HSV 공간으로의 변환과 LBP 기법을 통해 간단하지만 인식률을 높일 수 있는 방안을 마련하고자 했다. 자원과 계산을 효율적으로 사용하기 위해 모델을 간략화 하였으며 추후 스마트팜의 연구에 도움이 될 수 있을 것이라 기대한다.