• Journal of the Korean Society of Mechanical Technology
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• v.13 no.3
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• pp.73-79
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• 2011

In this study, an analytical realization of end-milling system was introduced using recursive parametric modeling analysis. Also, the numerical mode analysis of end-milling system with different conditions was performed systematically. In this regard, a recursive least square modelling algorithm and the natural mode for real part and imaginary one was discussed. This recursive approach (RLSM) can be adopted for on-line end-milling identification. After experimental practice of the end-milling, the end-milling force was obtained and it was used for the calculation of FRF (Frequency response function) and mode analysis. Also the FRF was analysed for the prediction of a end-milling system using recursive algorithm.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.485-493
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• 2019

The parametric array phenomenon refers to the generation of a high directivity low frequency wave from a small size radiation plate using the nonlinearity of the medium. In order to improve the usability of parametric array, the beam steering method of low frequency wave is researched, and the beam steering phenomenon is predicted easily using the PD (product directivity) model. However, the PD model can only be applied to Gaussian sources under quasi-linear conditions. Also, the prediction accuracy of low frequency wave beam width is poor. In this paper, a method for predicting the beam steering characteristics of a parametric array that can overcome the limitation of the PD model is investigated. For this purpose, the numerical analysis algorithm of the KZK (Khokhlov-Zabolotskaya-Kuzentsov) equation widely used for parametric array phenomenon prediction is improved. Thus, the beam steering characteristics are calculated by applying the electrical beam steering condition and comparing experimental results. As a result, the numerical analysis using the modified KZK equation algorithm in this study confirms that the beam steering phenomenon can be predicted even in a parametric array source that does not correspond to the quasi-linear condition.

• Computational Structural Engineering
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• v.5 no.1
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• pp.109-118
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• 1992

Lateral bracing has long been used in design practice to enhance the carrying capacity of the lateral buckling of the beam. Many factors, critically important to lateral bracing performance, do not appear in design formulas. Some of these factors are discussed in this study for the application to short I - beams under repeated loadings through parametric studies with an analytical model : the brace location along the length of the beam, the height of the bracing above the shear center of the beam, and the strength and stiffness of the brace. The parametric studies are carried out using a propped cantilever arrangement, and also using a geometrically (fully) nonlinear beam model for the brace as well as the beam to capture the system buckling. An idealized bracing system is configured to restrain lateral motion, but not rotation. A multiaxial cyclic plasticity model is also implemented to better represent cyclic metal plasticity in conjunction with a consistent return mapping algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.9
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• pp.952-958
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• 2014

In this paper, we propose a parametric sparse recovery algorithm(SRA) applied to a radar signal model, based on the compressive sensing(CS), for the ISAR(Inverse Synthetic Aperture Radar) image reconstruction from an incomplete radar-cross-section(RCS) data and for the estimation of rotation rate of a target. As the SRA, the iteratively-reweighted-least-square(IRLS) is combined with the radar signal model including chirp components with unknown chirp rate in the cross-range direction. In addition, the particle swarm optimization(PSO) technique is considered for searching correct parameters related to the rotation rate. Therefore, the parametric SRA based on the IRLS can reconstruct ISAR image and estimate the rotation rate of a target efficiently, although there exists missing data in observed RCS data samples. The performance of the proposed method in terms of image entropy is also compared with that of the traditional interpolation methods for the incomplete RCS data.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.231-236
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• 2014

The transit time of contrast agents and the parameters of time-intensity curves in ultrasonography are important factors to diagnose various diseases of a digestive organ. We have implemented an automatic parametric imaging method to overcome the difficulty of the diagnosis by naked eyes. However, the micro-bubble noise and the respiratory motions may degrade the reliability of the parameter images. In this paper, we introduce an optimization technique based on MRF(Markov Random Field) model to enhance the quality of the parameter images, and present an image tracking algorithm to compensate the image distortion by respiratory motions. A method to extract the respiration periods from the ultrasound image sequence has been developed. We have implemented the ROI(Region of Interest) tracking algorithm using the dynamic weights and a momentum factor based on these periods. An energy function is defined for the Gibbs sampler of the image enhancement method. Through the experiments using the data to diagnose liver lesions, we have shown that the proposed method improves the quality of the parametric images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1013-1022
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• 2003

This paper implemented the real-time object tracking algorithm that extracts and tracks the moving object adaptively to input frame sequence by using non-parametric image processing method and Kalman filter-based dynamic AR(2) process method. By applying non-parametric image processing to input frames, the moving object was extracted from the background adaptively to diverse environmental conditions. And the movement of object was able to be adaptively estimated and tracked by modeling the various movement of object as dynamic AR(2) process and estimating based on the Kalman filter the parameters of AR(2) process dynamically changing along time. The experiments of the implemented object tracking system showed that the proposed method tracked the moving object as more approximately as the estimation error became about l/2.5∼1/50 of one of the traditional tracking method based on linear Kalman filter.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.303-308
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• 1989

A new estimationn mothod of single-EP(evoked potential) using adaptive algorithm and paralnetrlc model is proposed. Since the EEG(eletroencephalogram) signal is stationary in short time interval the AR(autoregressive) parameters of the EEG are estimated by the Burg algorithm using the EEG of prestimulus interval. After stimulus, the single-EP is estimated by adaptive algorithm. The validity of this method is verified by the simulation for generated auditory single-EP based on parametric model.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2092-2095
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• 2003

In this paper, we propose an algorithm to extract rectangular object area such 3s Data Matrix two-dimensional barcode using edge tracing-based linear feature detection. Hough transform is usually employed to detect lines of edge map. However, it requires parametric image space, and does not find the location of end points of the detected lines. Our algorithm detects end points of the detected lines using edge tracing and extracts object area using its shape information.

• The Pure and Applied Mathematics
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• v.14 no.3
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• pp.191-196
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• 2007

The main components in the generalized Mandelbrot sets are under a theoretical investigation for their parametric boundary equations. Using the boundary geometries, a fast construction algorithm is introduced for the generalized Mandelbrot set. This fast algorithm definitely reduces the construction CPU time in comparison with the naive algorithm. Its graphic implementation displays the mysterious and beautiful fractal sets.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.35-53
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• 1994

Orthographic views ore traditionally used for engineering drawings. This paper presents a methodology for 3D parametric design using orthographic views. The parametric design technique, which is used to design 2D orthographic views, is based on production rules. In the production rule-base, several view interrelation rules and over 50 geometric rules are included. An efficient algorithm is also developed to expedite the reasoning process. For 3D object construction from orthographic views, the approach known as bottom-up geometrical approach is used. The approach consists of 4 steps : 1) generation of wire-frame, 2) construction of face from wire frame, 3) formation of 3D subobjects from faces, and 4) construction of final 3D objects. Curvilinear solids as well as planar solids can be constructed. A method of converting existing 2D CAD data to parametric 3D CAD data is also presented.