• Communications for Statistical Applications and Methods
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• 제30권1호
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• pp.65-73
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• 2023

Contemporary biomedical data often involve an ill-posed problem owing to small sample size and large number of multi-collinear variables. Partial least squares (PLS) method could be a plausible alternative to an ill-conditioned ordinary least squares. However, in the case of a PLS model that includes a random-effect, how to deal with a random-effect or mixed effects remains a widely open question worth further investigation. In the present study, we propose a modified multivariate PLS method implementing mixed-effect model (PLSM). The advantage of PLSM is its versatility in handling serial longitudinal data or its ability for taking a randomeffect into account. We conduct simulations to investigate statistical properties of PLSM, and showcase its real clinical application to predict treatment outcome of esthetic surgical procedures of human faces. The proposed PLSM seemed to be particularly beneficial 1) when random-effect is conspicuous; 2) the number of predictors is relatively large compared to the sample size; 3) the multicollinearity is weak or moderate; and/or 4) the random error is considerable.

• Structural Engineering and Mechanics
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• 제81권1호
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• pp.103-115
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• 2022

The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

• 자원환경지질
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• 제18권3호
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• pp.217-224
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• 1985

Householder변환을 비저항반전 문제에 응용하여 해의 안전성을 조사하였다. 비저항탐사의 데이터를 해석할 때, 정규방정식을 통하여 지하구조모델을 구하는 종래의 비저항반전법은 수치적으로 불안정성을 야기시킬 경우가 간혹 있다. 이에 반하여 관측방정식의 해를 직접 구하는 Householder변환을 이용한 비저항반전법은 종래의 방법보다 수치적으로 더 안정하다. 본 논문에서는 Householder변환을 이용한 비저항반전법이 종래의 방법으로는 안정된 지하구조모델을 구할 수 없을 정도로 잡음이 포함된 이론적인 Schlumberger탐사 데이터의 경우에도 안정된 모델을 구할 수 있음을 보여 주었다.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.544-550
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• 2008

In this paper, an efficient positioning algorithm is proposed for a local positioning system using ultrasound and RF in WSN. The proposed positioning algorithm is the modified Savarese method where measurement noise characteristics are included as a weighting. Furthermore the ill-conditioned and the singularity problem occurred when all beacons are installed at the same height are removed. And the method is applicable to 2D positioning with 2 beacons only. The experiments with implemented system show the accurate seamless positioning less than 2cm error both static and dynamic experiments while the original Savarese method can not provide positions.

• 충청수학회지
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• 제25권2호
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• pp.367-377
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• 2012

The goal of the image restoration is to find a good approximation of the original image for the degraded image, the blurring matrix, and the statistics of the noise vector given. Fast truncated Lagrange (FTL) method has been proposed by G. Landi as a image restoration method for large-scale ill-conditioned BTTB linear systems([3]). We implemented FTL method for the image restoration problem with reflective boundary condition which gives better reconstructions of the unknown, the true image.

• 전기학회논문지
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• 제60권1호
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• pp.150-155
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• 2011

In an active noise control systems, an IIR filter may cause a problem in stability beacause of its poles. For IIR filter, its poles goes sometimes out of a unit circle in a z-plane in the transition state, where the adaptive algorithm converges to the optimum value, which causes the system to diverge. Fuzzy LMS algorithm has a better convergence property than conventional LMS algorithms, but is not applicable to IIR filter because of the reasons. Stabilized adaptive algorithm could be improves stability by moving the pole of IIR filer toward the origin forcibly in the transient state, and by introducing forgetting factor to maintain the optimum convergence when it reaches to the steady state. In this paper, We proposed stabilized adaptive fuzzy LMS algorithms with IIR filter structures, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithm.

• 한국측량학회지
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• 제31권6_2호
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• pp.577-583
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• 2013

Recently, massive archives of ground information imagery from new sensors have become available. To establish a functional relationship between the image and the ground space, sensor models are required. The rational functional model (RFM), which is used as an alternative to the rigorous sensor model, is an attractive option owing to its generality and simplicity. To determine the rational polynomial coefficients (RPC) in RFM, however, we encounter the problem of obtaining a stable solution. The design matrix for solutions is usually ill-conditioned in the experiments. To solve this unstable solution problem, regularization techniques are generally used. In this paper, we describe the effective determination of the optimal regularization parameter in the regularization technique during RPC derivation. A brief mathematical background of RFM is presented, followed by numerical approaches for effective determination of the optimal regularization parameter using the Euler Method. Experiments are performed assuming that a tilted aerial image is taken with a known rigorous sensor. To show the effectiveness, calculation time and RMSE between L-curve method and proposed method is compared.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.876-881
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• 2004

Finite element model updating is an inverse problem to identify and correct uncertain modeling parameters that leads to better predictions of the dynamic behavior of a target structure. Unlike other inverse problems, the restrictions on selecting parameters all: very high since the updated model should maintains its physical meaning. That is, only the regions with modeling errors should be parameterized. And the variations of the parameters should be kept small while the updated results give acceptable correlations with experimental data. To avoid an ill-conditioned numerical problem, the number of parameters should be kept as small as possible. Thus it is very difficult to select an adequate set of updating parameters which meet all these requirements. In this paper, the importance of updating parameter selection is illustrated through a case study, and an automated procedure to guide the parameter selection is suggested based on simple observations. The effectiveness of the suggested procedure is tested with two example problems, ones is a simulated case study and the other is a real engineering structure.

• 한국통신학회논문지
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• 제35권4C호
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• pp.386-394
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• 2010

본 논문에서는 다수의 사용자 각자가 다수의 수신 안테나를 가지고 하나의 기지국과 통신하는 다중 사용자 MIMO 시스템 환경에서, 사용자 간의 간섭을 제거하기 위한 적응적 coordinated Tx-Rx 빔형성 기법을 제안하였다. 기존의 coordinated Tx-Rx 빔형성 기법은 전송 순간의 채널 환경과는 상관없이 각 사용자에게 동일한 수의 데이터 스트림 수를 할당하여, 채널 환경이 좋지 않은 사용자에게도 같은 양의 데이터를 전송하는 비효율적인 문제가 있다. 제안된 적응적 coordinated Tx-Rx 빔형성 기법에서는 전송 순간의 채널 상태를 고려하여 사용자에게 적응적으로 데이터 스트림 수를 할당함으로써, 시스템 전반적인 BER 성능의 향상을 달성한다. 모의실험 결과는 제안된 coordinated Tx-Rx 빔형성 기법이 수신단에서 선형수신기법 사용을 가정한 경우에, target BER 10-2에서 기존의 coordinated Tx-Rx 빔형성 기법에 비하여 약 2.5dB정도의 성능을 향상시킴을 입증한다.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.266-272
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• 2021

In the pulsed electron beam generators, such as plasma focus devices and linear induction accelerators whose electron pulse width is in the range of nanosecond and less, as well as in cases where there is no direct access to electron beam, like runaway electrons in Tokamaks, measurement of the electron energy spectrum is a technical challenge. In such cases, the indirect measurement of the electron spectrum by using the bremsstrahlung radiation spectrum associated with it, is an appropriate solution. The problem with this method is that the matrix equation between the two spectrums is an ill-conditioned equation, which results in errors of the measured X-ray spectrum to be propagated with a large coefficient in the estimated electron spectrum. In this study, a method based on the neural network and the MCNP code is presented and evaluated to recover the electron spectrum from the X-ray generated by collision of the electron beam with a target. Multilayer perceptron network showed good accuracy in electron spectrum recovery, so that for the X-ray spectrum with errors of 3% and 10%, the network estimated the electron spectrum with an average standard error of 8% and 11%, on all of the energy intervals.