• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.60-67
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• 1990

This paper proposes a model-based fault detection method for linear/nonlinear system having modelling errors, nonlinearities and measurement noise. The system model is represented by the unified operator [5] in order to apply to both the continuous-time and discrete-time problems. The fault detection method suggested here accounts for the effects of noise, model mismatch and nonlinearities. Modelling errors are depicted by additive forms and the nominal model denominator is fixed via prior experiments in order to quantify the nucertainty bound on the parameter estima-tion. The least square method is used to estimate the numerator parameters of the nominal model. performance than traditional methods.

• Environmental and Resource Economics Review
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• v.23 no.3
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• pp.473-496
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• 2014

This paper intends to test the non-linear relationship between $CO_2$ emissions and income by employing cointegration model of the time-varying income elasticity. We select France, UK, Italy, Japan, US, China, India, Mexico and Korea and use non-parametric time series analysis on each country in order to estimate its own effect of income on $CO_2$ emission. The main results indicate that the $CO_2$ emission-income elasticities vary over time and the income elasticities of the Annex I countries tend to be higher in absolute terms than those of developing countries. In addition, we find that emission-income elasticities decrease for Annex I countries over time, whereas those for developing countries increase.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.499-508
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• 2017

A new digital pre-distortion technique to linearize power amplifier (PA) is proposed for concurrent dual-band transmitters. In the conventional dual-band DPD techniques, two independent dual-feedback paths are required to compensate nonlinear cross-products between different bands as well as the nonlinear self-products of each band's own signal. However, it increases hardware complexity and expense. In this paper, we propose a new DPD method requiring only a single feedback path. In this new structure, the proposed technique first estimates the dual-band PA characteristics using the single feedback path. The DPD parameters are then extracted from the estimated PA characteristics. The DPD performance of the proposed method is validated through computer simulation. According to the results, the proposed technique can achieve comparable performance to the conventional two feedback DPD with significantly reduced hardware complexity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1207-1212
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• 2015

In this paper, we propose three-dimensional (3D) visualization and recognition techniques of micro-objects under photon-starved conditions using photon counting integral imaging microscopy. To capture high resolution 2D images with different perspectives in the proposed method, we use Synthetic Aperture Integral Imaging (SAII). Poisson distribution which is mathematical model of photon counting imaging system is used to extract photons from the images. To estimate 3D images with 2D photon counting images, the statistical estimation is used. Therefore, 3D images can be obtained and visualized without any damage under photon-starved conditions. In addition, 3D object recognition can be implemented using nonlinear correlation filters. To prove the usefulness of our technique, we implemented the optical experiment.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.2
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• pp.20-28
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• 1998

To accurately predict the motion of a submergible, the nonlinear structure of dynamic model should be selected and corresponding parameters should be estimated using model test. Providing the model structure, only the values of parameters are unknown and the estimation can thus be formulated as a standard least square problem. Unfortunately, the nonlinear model structure of submersibles is rarely known a prior and method of model structure determination from measurement data of model test should be developed and included as a vital part of the estimation procedure. In this study, the well-known linear least square algorithm for the analysis of model tests and a way to measure the goodness are reviewed, and the identification algorithm based on an orthogonal decomposition method of Gram-Schmidt is extended to combine structure selection and maneuvering coefficients estimation in a very simple and efficient manner. Finally, the efficiency of this algorithm is verified by using simulation and applying to the analysis of model test of a submerged body. As a result, it was verified that this combined method might be very erective in selecting the structure of dynamic model estimating the maneuvering coefficients from measurement fiat of model test.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.3
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• pp.339-346
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• 2018

A geological repository system consists of a disposal canister with packed spent fuel, buffer material, backfill material, and intact rock. The buffer is indispensable to assure the disposal safety of high-level radioactive waste. Since the heat generated from spent nuclear fuel in a disposal canister is released to the surrounding buffer materials, the thermal properties of the buffer material are very important in determining the entire disposal safety. Especially, since thermal expansion can cause thermal stress to the intact rock mass in the near-field, it is very important to evaluate thermal expansion characteristics of bentonite buffer materials. Therefore, this paper presents a thermal expansion coefficient prediction model of the Gyeongju bentonite buffer materials which is a Ca-bentonite produced in South Korea. The linear thermal expansion coefficient was measured considering heating rate, dry density and temperature variation using dilatometer equipment. Thermal expansion coefficient values of the Gyeongju bentonite buffer materials were $4.0{\sim}6.0{\times}10^{-6}/^{\circ}C$. Based on the experimental results, a non-linear regression model to predict the thermal expansion coefficient was suggested and fitted according to the dry density.

• The Journal of Engineering Geology
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• v.18 no.4
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• pp.359-369
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• 2008

For the design and effective management of underground storage caverns, preliminary investigation on the hydrogeologic parameters around caverns and analysis on the groundwater flow must be carried out. The data collection is very imporatnat task for the hydrogeologic design so various hydraulic tests have been performed. When analyzing the injection/fall off test data, existing graphical method to estimate the parameters in Theis' equation is widely used. However this method has some sources of error when estimating parameters by means of human faults. Therefore the method of estimating parameters by means of statistical methods such as regression type is evaluated as a useful tool. In this study, nonlinear regression analysis for the Theis' equation is suggested and applied to the estimation of parameters for the real field interference data around underground storage caverns. Damping parameter which reduce the iteration numbers and inhance the convergence is also introduced.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.371-381
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• 2000

In this paper, we describes smoothing spline in nonparametric regression and some asymptotic results for estimates of the regression cofficients in the parametric part were biased on semi parametric regression estimator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.996-1007
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• 1996

In this paper, a blind adaptation method for a decision feedback equalizer (DFE) is proposed to deal with nominimum phase channels. This equalizer is composed of a linear transversal filter and a prediction error filter which are trained separately using constant modulus and decision feedback prediction algorithms, respectively, during the learnign time. The proposed algorithm guaranetees the DFE to converge to a suboptimal point on the condition that a linear transversal of the proposed scheme is illustrated and the performance is compared with conventional blind equlization algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.172-174
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• 2003

화상평면내 미지호흡운동에 기인한 MRI 아티팩트를 제거하기 위한 후처리방법을 제안한다. 본 연구에서 호흡운동은 2차원의 선형확대축소운동으로 모델화 된다. 신체조직을 비압축성 유체모양의 물질로 가정할때, 화상위에서의 단위체적당 푸로톤 밀도는 일정하다고 가정한다. 사용한 모델에 따르면 호흡운동은 위상 오차와 비균일표본화 및 왜곡된 진폭변조를 MR 데이터에 부여한다. 운동 파라메타가 이미 알려져 있거나 추정 가능하다고 할 때, MRI 아티팩트를 제거하기 위하여 중첩법에 기초를 둔 재구성 알고리즘을 이용한다. 운동 파라매타가 미지인 경우 스팩트럼 이동법을 적용해서 호흡변동함수와 x 방향 확대계수 및 x 방향 확대중심을 추정한다. 다음으로 에너지 최소법을 이용해서 ｙ 방향 확대계수 및 ｙ 방향 확대중심을 추정한다. 시뮬레이션을 통해서 제안한 방법의 유효성을 확인한다.