• Proceedings of the KAIS Fall Conference
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• 2003.06a
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• pp.253-255
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• 2003

Flash memory는 device 특성상 peripheral circuit을 구성하는 transistor의 종류가 다양하고, 이에 따른 각 transistor의 동작 전압 영역이 넓다. 이에 따라 설계 초기의 전기적 특성 스펙 절정을 위해서는, silicon 상에서 소자의 scale down에 따른 전기적 특성을 선 검증하는 과정이 필수적이었으며, 이로 인해 설계 및 소자 개발의 기간을 단축하기 어려웠다. 본 연구에서는 TCAD tool을 사용하여 silicon상에서의 제작 공정을 거치지 않고, 효과적으로 model parameter를 생성할 수 있도록 하는 방법을 제안하여. 전기적 특성 스펙 결정과 설계 단계의 시간 지연을 감소할 수 있도록 한다.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.2
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• pp.35-48
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• 2017

As the technology convergence paradigm emerges, the need for "CIA techniques" to analyze the mutual effects of technology is increasing. However, since the CIA input parameter estimation is difficult, the present study suggests a "CIA input parameter setting model" to alleviate the difficulty of CIA input parameter estimation. This paper is focused on the difference of measurement difficulty by each scale which expert's estimation behavior was defined as measurement activity quantifying the judgment of future technology. Therefore, this model is designed to estimate the input variable as a sequence or isometric scale that is relatively easy to measure, and then converts it into a probability value. The input parameter setting model of the CIA technique consists of three sub-models : 'probability value derivation model', 'influence estimation model', and 'impact value calculation model', in order to develop a series of models the Thurstone V model, Regression Analysis, etc has been used.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.99-109
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• 2009

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

• Bulletin of the Korean Mathematical Society
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• v.57 no.3
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• pp.751-762
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• 2020

We define the average of a set of continuous functions of two variables (surfaces) using the structure of the two-parameter Wiener space that constitutes a probability space. The average of a sample set in the two-parameter Wiener space is defined employing the two-parameter Wiener process, which provides the concept of distribution over the two-parameter Wiener space. The average defined in our work, called an average function, also turns out to be a continuous function which is very desirable. It is proved that the average function also lies within the range of the sample set. The average function can be applied to model 3D shapes, which are regarded as their boundaries (surfaces), and serve as the average shape of them.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1211-1222
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• 2017

In order to decrease the parameter sensitivity of deadbeat direct torque control (DB-DTC), an improved deadbeat direct torque control method for surface mounted permanent-magnet synchronous motor (SPMSM) drives is proposed. First, the track errors of the stator flux and torque that are caused by model parameter mismatch are analyzed. Then a sliding mode observer is designed, which is able to predict the d-q axis currents of the next control period for one-step delay compensation, and to simultaneously estimate the model parameter disturbance. The estimated disturbance of this observer is used to estimate the stator resistance offline. Then the estimated resistance is required to update the designed sliding-mode observer, which can be used to estimate the inductance and permanent-magnetic flux linkage online. In addition, the flux and torque estimation of the next control period, which is unaffected by the model parameter disturbance, is achieved by using predictive d-q axis currents and estimated parameters. Hence, a low parameter sensitivity DB-DTC method is developed. Simulation and experimental results show the validity of the proposed direct control method.

• Journal of Power System Engineering
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• v.12 no.2
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• pp.55-61
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• 2008

This paper discusses the advantages of using Fourier-based periodic excitation and of combining internal and external models in dynamic robot parameter identification. Internal models relate the joint torques or forces with the motion of the robot; external models relate the reaction forces and torques on the bedplate with the motion data. This combined model allows to combine joint torque/force and reaction torque/force measurements in one parameter estimation scheme. This combined model estimation will yield more accurate parameter estimates, and consequently better predictions of actuator torque, which is shown by means of a simulated experiment on a CRS A465 industrial robot.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2053-2061
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• 1994

The static and fatigue tensile tests have been conduted to predict the fatigue life of 8-harness satin woven and plain woven carbon/epoxy composite plates containing a circular hole. A fatigue residual strength degradation model, based on the assumption that the residual strength for unnotched specimen decreases monotonically, has been applied to predict statistically the fatigue life of materials used in this study. To determine the parameters(c, b and K) of the residual strength degradation model, the minimization technique and the maximum likelihood method are used. Agreement of the converted ultimate strength by using the minimization technique with the static ultimate strength is reasonably good. Therefore, the minimization technique is more adjustable in the determination of the parameter and the prediction of the fatigue life than the maximum likelihood method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.753-759
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• 2011

The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.555-560
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• 2010

One-dimensional approach to two-dimensional warranty data involves modeling us- age as a function of time. Iskandar (1993) suggests a simple linear model for usage. However, simple linear form of intensity function is of limited value to model the situa-tion where the intensity varies over time. In this study Weibull intensity is considered where the scale parameter is expressed in terms of different models. We will nd out how each parameter in the model a ects the warranty cost and which model gives a bigger number of failures within the two-dimensional warranty region.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.197-199
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• 2003

In this work, the Greitzer's B-parameter model is applied for analyzing the stall and surge characteristics. The four parameters in the model are highlighted in order to establish the influence of each parameter on the system. First of all, the governing equations of stall and surge behavior are solved numerically using fourth-order Runge-Kutta method. The Taguchi method is then used to analyze the results generated to obtain the extent of effects of the parameters on the system by varying the parameters in a series of combinations. Finally, a thorough analysis is carried out on the results generated from the Taguchi method and the graphs.