• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.95-101
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• 2015

To accurately extract absolute distance information from a self-mixing interferometry (SMI) signal, in this paper we propose an approach based on a particle swarm optimization (PSO) algorithm instead of frequency estimation for absolute distance. The algorithm is utilized to search for the global minimum of the fitness function that is established from the self-mixing signal to find out the actual distance. A resolution superior to $25{\mu}m$ in the range from 3 to 20 cm is obtained by experimental measurement, and the results demonstrate the superiority of the proposed approach in comparison with interpolated FFT. The influence of different external feedback strength parameters and different inertia weights in the algorithm is discussed as well.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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• pp.254-261
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• 2003

In mold and die shops, NC machining process mainly affects the quality of the machined surface and the manufacturing time of molds and dies. The estimation of NC machining time is a prerequisite to measure the machining productivity and to generate a process schedule, which generally includes the process sequence and the completion time of each process. It is required to take into account dynamic characteristics in the estimation, such as the ac/deceleration of NC machine controllers. Intensive observations at start and end points of NC blocks show that a minimum feedrate, a key variable in a machining time model, has a close relation to a block distance, an angle between blocks, and a command feedrate. Thus, this study addresses regression models for the minimum feedrate estimation on short and long NC blocks considering these parameters. Furthermore, machining time estimation models by the four types of feedrate behaviors are suggested based on the estimated minimum feedrate. To show the validity of the proposed machining time model, the study compares the estimated with the actual machining time in the sculptured surface machining of several mold dies.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.149-167
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• 2005

The minimum disparity estimators introduced by Lindsay and Basu (1994) are studied empirically. An extensive simulation in this paper provides a location estimate of the small sample and supplies empirical evidence of the estimator performance for the univariate contaminated normal model. Empirical results show that the minimum generalized negative exponential disparity estimator (MGNEDE) obtains high efficiency for small sample sizes and dominates the maximum likelihood estimator (MLE) and the minimum blended weight Hellinger distance estimator (MBWHDE) with respect to efficiency at the contaminated model.

• Bulletin of the Korean Mathematical Society
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• v.47 no.5
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• pp.889-905
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• 2010

In this paper, a distribution free approach to the parameter estimation of a simple bilinear model with periodic coefficients is presented. The proposed method relies on minimum distance estimator based on the autocovariances of the squared process. Consistency and asymptotic normality of the estimator, as well as hypotheses testing, are derived. Numerical experiments on simulated data sets are presented to highlight the theoretical results.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.349-360
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• 1995

This paper deals with the robustness properties of the minimum disparity estimation in linear regression models. The estimators defined as statistical quantities whcih minimize the blended weight Hellinger distance between a weighted kernel density estimator of the residuals and a smoothed model density of the residuals. It is shown that if the weights of the density estimator are appropriately chosen, the estimates of the regression parameters are robust.

• Journal of Navigation and Port Research
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• v.38 no.6
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• pp.561-565
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• 2014

This paper is mainly concerned with the interaction effects between two vessels and sidewall with a mound. Experimental study on hydrodynamic forces between ship and sidewall with a mound was already shown in the previous paper, measured by varying the distances between ship and sidewall. The ship maneuvering simulation was conducted to find out the minimum safe distance between vessels, which is needed to avoid sea accident in confined waters. From the inspection of this investigation, it indicates the following result. When and if one vessel passes the other vessel through the proximity of sidewall with a mound, the spacing between two vessels is needed for the velocity ratio of 1.2, compared to the case of 1.5. Also, for the case of ship-size estimation, the ship maneuvering motion is more affected by interaction effects for the overtaken small vessel, compared to the overtaking large vessel.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.320-324
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• 2015

Mutual coupling between antenna elements of a linear microstrip patch antenna array positioned along the H-plane including the effect of edge reflections is investigated. Simple formulas are presented for the estimation of the grounded dielectric substrate size with minimum mutual coupling. The substrate sizes calculated by these formulas are in good agreement with those obtained by the full-wave simulation and experimental measurement. The substrate size with minimum mutual coupling is a function of the effective dielectric constant for surface waves and the distance between the antenna centers. The substrate size with minimum mutual coupling decreases as the effective dielectric constant for surface waves on a finite grounded dielectric substrate increases.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.8-13
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• 2023

We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.711-717
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• 2007

Location information will become increasingly important for future Pervasive Computing applications. Location tracking system of a moving device can be classified into two types of architectures: an active mobile architecture and a passive mobile architecture. In the former, a mobile device actively transmits signals for estimating distances to listeners. In the latter, a mobile device listens signals from beacons passively. Although the passive architecture such as Cricket location system is inexpensive, easy to set up, and safe, it is less precise than the active one. In this paper, we present a passive location system using Cricket Mote sensors which use RF and ultrasonic signals to estimate distances. In order to improve accuracy of the passive system, the transmission speed of ultrasound was compensated according to air temperature at the moment. Upper and lower bounds of a distance estimation were set up through measuring minimum and maximum distances that ultrasonic signal can reach to. Distance estimations beyond the upper and the lower bounds were filtered off as errors in our scheme. With collecting distance estimation data at various locations and comparing each distance estimation with real distance respectively, we proposed an equation to compensate the deviation at each point. Equations for proposed algorithm were derived to calculate relative coordinates of a moving device. At indoor and outdoor tests, average location error and average location tracking period were 3.5 cm and 0.5 second, respectively, which outperformed Cricket location system of MIT.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.599-604
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• 2013

Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.