• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.165-168
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• 2004

This paper propose a target tracker using phase correlation. The tracker consist of a pre-processing module, a translation estimation module based on phase correlation, a fine motion estimation module applied when confidence rate could not fulfill a threshold value and a reference image update module. The fine motion estimation module measure the shift, rotation and scale of input image compared to reference using Fourier-Mellin transform. Proposed tracker was tested its accuracy and robustness using some real indoor and outdoor image sequences.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.877-884
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• 2012

Phase I trials determine the maximum tolerated dose(MTD) and the recommended dose(RD) for subsequent Phase II trials. In this paper, a MTD estimation method applied to a biased coin design is proposed for Phase I Clinical Trials. The suggested MTD estimation method is compared to the SM3 method and the NM method (Lee and Kim, 2012) using a Monte Carlo simulation study.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.10
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• pp.1-7
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• 2010

A new frequency offset estimation algorithm for chirp spread spectrum based on matched filter is proposed. Generally, the differential phase between successive symbols is used for the conventional frequency offset estimation algorithm. However, if the conventional frequency offset estimation algorithm is used for CSS, phase ambiguity arises because of long symbol duration and guard time. The phase ambiguity causes performance degradation of matched filter since the received signal is corrupted by the integer frequency offset. In this paper, we propose a new frequency offset estimation algorithm which separates integer and fractional frequency offset estimation for removing the phase ambiguity. The proposed algorithm estimates the integer frequency offset by using differential phase between matched filtering results of sub-chirps and successive symbols. Then, the fractional frequency offset is estimated by using the differential phase between successive symbols Simulation results show that the proposed algorithm well removes the phase ambiguity, and have almost same estimation performance compared with conventional one when there is not the phase ambiguity.

• International Journal of Contents
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• v.1 no.1
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• pp.1-5
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• 2005

This paper presents the development and application of electrical resistance imaging techniques for the visualization of two-phase flow fields. Two algorithms, the so-called the mesh grouping and the boundary estimation, are described for potential applications of electrical resistance tomography (ERT) and results from extensive numerical simulations are also presented. In the electrical resistance imaging for two-phase flows, numerical meshes fairly belonging to each phase can be grouped to improve the reconstruction performance. In many cases, the detection of phase boundary is a key subject and a mathematical model to estimate phase boundary can be formulated in a different manner. Our results indicated that the mesh grouping algorithm is effective to enhance computational performance and image quality, and boundary estimation algorithm to determine the phase boundary directly.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.403-410
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• 2023

Two-Phase sampling, which was first introduced by Neyman (1938), has various applications in different forms. Variance estimation for two-phase sampling has been an important research topic because conventional variance estimators used in most softwares are not working. In this paper, we considered a variance estimation for two-phase sampling in which stratified two-stage cluster sampling designs are used in both phases. By defining a conditionally unbiased estimator of an approximate variance estimator, which is calculable when all elements in the first phase sample are observed, we propose an explicit form of variance estimator of the double expanded estimator for a two-phase sample. A small simulation study shows the proposed variance estimator has a negligible bias with small variance. The suggested variance estimator is also applicable to other linear estimators of the population total or mean if appropriate residuals are defined.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.360-364
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• 2009

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase induction machine using genetic algorithm. The parameter estimation procedure is based on the steady-state phase current versus slip and input power versus slip characteristics. The propose estimation algorithm is of non-linear kind based on selection in genetic algorithm. The machine parameters are obtained as the solution of a minimization of objective function by genetic algorithm. Simulation shows good performance of the propose procedures.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.697-700
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• 2000

This paper introduces a new rotor position estimation algorithm for the SRM based on the magnetizing curves of aligned and unaligned rotor positions. The flux linkage is calculated by the measured data from phase voltage and phase current and the calculated data are used as the input of magnetizing profiles for rotor position detection. Each of the magnetizing profiles consisted of the methods using the neural network and fuzzy algorithm And also the optima phase is selected by phase selector. To demonstrate the promise of this approach the proposed rotor position estimation algorithms are verified by the experiment results or variable spee range.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1067-1075
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• 2016

This paper presents an adaptive observer-based approach to estimate voltage parameters, including frequency, amplitude, and phase angle, for single-phase power systems. In contrast to most existing estimation methods of grid voltage parameters, in this study, grid voltage is treated as a dynamic system related to an unknown grid frequency. Based on adaptive observer theory, a full-order adaptive observer is proposed to estimate voltage parameters. A Lyapunov function-based argument is employed to ensure that the proposed estimation method of voltage parameters has zero steady-state error, even when frequency varies or phase angle jumps significantly. Meanwhile, a reduced-order adaptive observer is designed as the simplified version of the proposed full-order observer. Compared with the frequency-adaptive virtual flux estimation, the proposed adaptive observers exhibit better dynamic response to track the actual grid voltage frequency, amplitude, and phase angle. Simulations and experiments have been conducted to validate the effectiveness of the proposed observers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6C
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• pp.453-461
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• 2012

This paper proposes an improved phase estimation method for AM(Amplitude Modulation) range measurement system. The previous phase estimation method induces errors by Doppler shift of a moving target. The proposed method compensates phase estimation error through the ADC(Adaptive Doppler Correction) to take the Doppler shift, thus can improve distance measurement accuracy. When compared with the previous method through simulation results, the Doppler shift compensation and accuracy are improved by 94.7% and 50%, respectively. Target distance error in an acoustic tank is estimated to be 7.7cm, which confirms that the proposed method can be used to estimate the distance in the marine environment.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.115-121
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• 2007

Phase contrast imaging in atomic force microscopy showed a promise as an effective tool for better understanding of micromechanical properties of surfaces at nano scale. A qualitative estimation model for phase contrast images obtained with a tapping mode AFM was developed. This investigation demonstrated the high efficiency of combined analysis of topography and phase contrast images for characterizing nanosurfaces. Phase contrast images allowed estimation of relative stiffness(elastic modulus) of the sample surface. The phase contrast images revealed a significant inhomogeneity of the nano scale worn surfaces. Phase contrast images are also capable of revealing the formation of tribofilms.