• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.147-150
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• 2012

While LDA is a supervised dimension reduction method which finds projective directions to maximize separability between classes, the performance of LDA is severely degraded when the number of labeled data is small. Recently semi-supervised dimension reduction methods have been proposed which utilize abundant unlabeled data and overcome the shortage of labeled data. However, matrix computation usually used in statistical dimension reduction methods becomes hindrance to make the utilization of a large number of unlabeled data difficult, and moreover too much information from unlabeled data may not so helpful compared to the increase of its processing time. In order to solve these problems, we propose an ensemble approach for semi-supervised dimension reduction. Extensive experimental results in text classification demonstrates the effectiveness of the proposed method.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.1
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• pp.12-22
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• 1994

Time evolution of linear water waves on a constant depth generated by a disturbance is analyzed by asymptotic methods; stationary phase, steepest descents and leading wave approximation. In order to verify the derived formulae of surface displacements for 1-D and 2-D waves. surface displacements are calculated and plotted from both the formulae and a numerical integration. The existing results for surface displacements are verified in which the leading amplitude of 1-D waves during the evolution decays as f- T/B, the rest of the wavetrain as t$^{-1}$ 2/ and the rest of the wavetrain of 2-D waves as t-1. But it is shown that the leading amplitude of 2-D waves decays as t 5/6 which is different from Kajiura's result t$^{-4}$ 3/.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.602-607
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• 2008

A technique for reliability-based design optimization(RBDO) is developed based on the Bayesian approach, which can deal with the epistemic uncertainty arising due to the limited number of data. Until recently, the conventional RBDO was implemented mostly by assuming the uncertainty as aleatory which means the statistical properties are completely known. In practice, however, this is not the case due to the insufficient data for estimating the statistical information, which makes the existing RBDO methods less useful. In this study, a Bayesian reliability is introduced to take account of the epistemic uncertainty, which is defined as the lower confidence bound of the probability distribution of the original reliability. In this case, the Bayesian reliability requires double loop of the conventional reliability analyses, which can be computationally expensive. Kriging based dimension reduction method(KDRM), which is a new efficient tool for the reliability analysis, is employed to this end. The proposed method is illustrated using a couple of numerical examples.

• Journal of the Korean Magnetics Society
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• v.25 no.6
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• pp.203-207
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• 2015

This paper introduces a probabilistic analysis method in order to analyze the effect of manufacturing tolerance on induction motor performance occurring in massive production. The univariate dimension reduction method is adapted to predict probabilistic characteristics of a performance function due to certain probabilistic distributions of design variables. Moreover, the sensitivity information on mean and variance of the performance function is estimated, and then the effect of randomness of individual design variables on the probability performance function is analyzed. The effectiveness and accuracy of the method is investigated with a mathematical model and an induction motor.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.88-88
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• 2020

수심평균 2차원 혼합모형은 하천환경에서 다양한 용존성 오염물질의 혼합현상을 모의하기 위해 널리 활용되어왔다. 2차원 혼합모형에서 분산계수는 하천의 전단 흐름에 의해 야기되는 오염물질의 퍼짐 현상을 표현하는 중요한 인자로서 작용하기 때문에 정교한 오염물질 혼합거동을 모의하기 위해서는 적합한 분산계수를 산정하는 것이 필수적이다. 분산계수를 실험적으로 산정하는 방법으로는 크게 모멘트법과 추적법으로 나뉘며, 비정상상태의 혼합거동에 대해 종방향 및 횡방향 분산계수를 동시에 산정할 수 있는 방법은 추적법 계열의 2차원 유관추적법(2D STRP)이 유일하다. 본 연구에서는 하천에 유입된 오염물질의 2차원 혼합해석을 위한 수치모형을 개발하였으며, 개발된 모형의 수치해를 바탕으로 다양한 Peclet 수의 범위에 대해 기존연구에서 제시된 2D STRP의 적용범위 및 성능을 정량적으로 분석하였다. 분석된 정보를 바탕으로 기존 2D STRP의 한계를 극복하기 위한 개선된 2차원 유관추적법(2D STRP-i)을 개발하고, 사행하천을 모형화한 실규모 하천실험시설에서 검증하였다. 기존 2D STRP의 성능평가 결과, Peclet 수가 낮은 조건일수록 농도분포의 예측 정확도가 감소하는 경향을 보였으며, 하안 경계에 도달하는 농도가 증가할수록 부정확한 결과를 초래하는 것으로 나타났다. 본 연구에서는 기존 2D STRP의 한계를 보완하여 더욱 정확한 분산계수를 산정하고자 하안 경계면 조건을 고려한 2차원 유관추적법(2D STRP-i)을 개발하였다. 2D STRP-i는 직교-곡선좌표계 기반의 2차원 이송-분산 방정식을 바탕으로 횡방향 유속분포 및 하안 경계조건을 고려할 수 있도록 개선되었다. 2D STRP-i는 공간적으로 상이한 이송효과 및 하안경계 조건을 적절히 반영함으로써 농도분포의 예측 정확도를 개선 시키는 것으로 평가되었으며, 하안경계면에서 농도가 증가하는 구간에서 기존 2D STRP의 결과와 비교하여 더욱 정확한 농도분포 및 분산계수를 제공하는 것으로 밝혀졌다.

• Journal of KIISE
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• v.45 no.1
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• pp.69-75
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• 2018

In the streaming data where data samples arrive sequentially in time, it is difficult to apply the dimension reduction method based on batch learning. Therefore an incremental dimension reduction method for the application to streaming data has been studied. In this paper, we propose an incremental linear discriminant analysis method using the least squared error solution. Instead of computing scatter matrices directly, the proposed method incrementally updates the projective direction for dimension reduction by using the information of a new incoming sample. The experimental results demonstrate that the proposed method is more efficient compared with previously proposed incremental dimension reduction methods.

• Korean Journal of Optics and Photonics
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• v.1 no.1
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• pp.12-15
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• 1990

Holospeckle interferometry, the combined technique of holographic interferometry and speckle photography, was applied to the measurement of 3-D contact deformation created by an indentor. This new tech$.$ nique makes possible to measure both in-plane and out-of-plane displacements from one photographic plate. In this study, the optical system based on image holography was set up. In order to enhance the size and the contrast of the speckle, a proper magnification and a low reference beam ratio was used as compared with the conventional holographic interferometry technique. This system shows the magnified and clear holographic interference fringe as well as Young's fringe patterns.tterns.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.275-280
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• 2008

A technique for reliability-based design optimization(RBDO) is developed based on the Bayesian approach, which can deal with the epistemic uncertainty arising due to the limited number of data. Until recently, the conventional REDO was implemented mostly by assuming the uncertainty as aleatory which means the statistical properties are completely known. In practice, however, this is not the case due to the insufficient data for estimating the statistical information, which makes the existing RBDO methods less useful. In this study, a Bayesian reliability is introduced to take account of the epistemic uncertainty, which is defined as the lower confidence bound of the probability distribution of the original reliability. In this case, the Bayesian reliability requires double loop of the conventional reliability analyses, which can be computationally expensive. Kriging based dimension reduction method(KDRM), which is a new efficient tool for the reliability analysis, is employed to this end. The proposed method is illustrated using a couple of numerical examples.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.664-668
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• 2008

본 연구에서는 비정상상태 자유수면 모의를 위해 2차원 유한체적법을 이용한 수치모형을 개발하였으며, 이론적인 해석해 및 수리실험을 통한 실측자료를 이용하여 검증하였다. 개발된 모형은 지배방정식으로 비선형 및 보존형 2차원 천수방정식(shallow water equation)을 이용하였으며, 동적메모리 할당 기능이 포함된 Fortran-90으로 코딩되었다. 또한 구조화된 격자 및 비구조화 격자 시스템에도 적용될 수 있도록 모형을 구성하였으며, 불규칙한 하상지형에 의해 수치진동을 감소시키기 위해 본 모형에 well-balanced HLLC 기법을 적용하였다. 모형의 적용성을 검증하기 위하여 1차원의 경우 젖은/마른 하상 조건하에서의 댐 붕괴파 문제와 하상이 변화하는 지형 구간을 통과할 때 발생되는 천이류에 대한 문제 그리고 시간에 따라 변화하는 수위와 지형 조건에서의 wetting & drying에 대한 문제에 적용하였으며, 2차원의 경우 전통적인 댐 붕괴파 문제 및 구조물에 미치는 댐 붕괴파의 영향에 대한 수리모형실험을 통한 실측자료를 이용하여 검증하였다. 검증결과 본 모형을 통해 계산된 수치해는 이론적인 해석해와 실측자료에 거의 정확히 일치하였으며, 향후 실제 하천 자료를 이용하여 모형의 현장 적용성을 검증할 것이다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.870-877
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• 2009

This study provides how the Dimension Reduction (DR) method as an efficient technique for reliability analysis can acquire its increased efficiency when it is applied to highly nonlinear problems. In the highly nonlinear engineering systems, 4N+1 (N: number of random variables) sampling is generally recognized to be appropriate. However, there exists uncertainty concerning the standard for judgment of non-linearity of the system as well as possibility of diverse degrees of non-linearity according to each of the random variables. In this regard, this study judged the linearity individually on each random variable after 2N+1 sampling. If high non-linearity appeared, 2 additional sampling was administered on each random variable to apply the DR method. The applications of the proposed sampling to the examples produced the constant results with increased efficiency.