• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.8
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• pp.791-796
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• 2009

A hybrid iterative physical optics-method of moments(IPO-MoM) technique is presented for the analysis of jet engine structures which are both electrically large and complex. In this technique, the IPO method is used to analyze smooth inlet region and the MoM method is used to analyze electrically complex region inclusive of blades and hub. It is efficient and accurate by virtue of combining the respective merits of both methods. Numerical results are presented and validated through comparison with Mode-FDTD and measured results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.10
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• pp.1833-1840
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• 1992

In the diagnostic process for automobile, Neuro-Fuzzy technique was compared with the conventional diagnostic method for the verification of performance, and proto-type system was developed. For the utilities of the system, 1/3 octave filter(band-pass filter) and A/D converter were used for data acquisition and then data were analyzed using octave band processing and pattern recognition using hamming network algorithm. In order to raise the reliability of the diagnostic results by considering many operating variables and condition of automobile to be diagnosed, fuzzy inference technique was applied in combining several information. The validation of this diagnostic system was examined through computer simulation and experiment, and it showed an acceptable performance for diagnostic process.

• Journal of the Korea Computer Graphics Society
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• v.10 no.3
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• pp.52-60
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• 2004

This paper presents a physically based technique for simulating complex multiphase fluids. This work is motivated by the "stable fluids" method developed by Stam to handle gaseous fluids. We extend this technique to water, which calls for the development of methods for modeling multiphase fluids and suppressing dissipation. We construct a multiphase fluid formulation by combining the Navier-Stokes equations with the level set method. By adopting constrained interpolation profile (CIP)-based advection, we reduce the numerical dissipation and diffusion significantly. We further reduce the dissipation by converting potentially dissipative cells into droplets or bubbles that undergo Lagrangian motion. Due to the multiphase formulation, the proposed method properly simulates the interaction of water with surrounding air, instead of simulating water in a void space. Moreover. the introduction of the non-dissipative technique means that, in contrast 10 previous methods, the simulated water does not unnecessarily lose mass and its motion is not damped to an unphysical extent. Experiments showed that the proposed method is stable and runs fast. It is demonstrated that two-dimensional simulation runs in real-time.

• Journal of the Korea Computer Graphics Society
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• v.10 no.4
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• pp.13-21
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• 2004

This paper presents a physically based technique for simulating complex multiphase fluids. This work is motivated by the "stable fluids" method developed by Stam to handle gaseous fluids. We extend this technique to water, which calls for the development of methods for modeling multiphase fluids and suppressing dissipation. We construct a multiphase fluid formulation by combining the Navier-Stokes equations with the level set method. By adopting constrained interpolation profile (CIP)-based advection, we reduce the numerical dissipation and diffusion significantly. We further reduce the dissipation by converting potential1y dissipative cel1s into droplets or bubbles that undergo Lagrangian motion. Due to the multiphase formulation, the proposed method properly simulates the interaction of water with surrounding air, instead of simulating water in a void space. Moreover, the introduction of the non-dissipative technique means that, in contrast to previous methods, the simulated water does not unnecessarily lose mass and its motion is not damped to an unphysical extent. Experiments showed that the proposed method is stable and runs fast. It is demonstrated that two-dimensional simulation runs in real-time.

• Korean Journal of Acupuncture
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• v.25 no.1
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• pp.247-257
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• 2008

Objectives : The warm needling technique is the method in combining the effects of acupuncture needle with the effects of moxibustion. We need to standardize the characteristics of the warm needling technique in order to get more systematic and objective result in operation mechanism and effects and then get more clinical abilities in these fields. Methods : In this study, using of labview system on the warm needling technique we studied about measurement and comparison with partial temperature changes according to the position of ignition. Results & conclusion : When we measured the warm needling's partial temperature according to the position of ignition, the bottom ignition method got the higher result on the peak temperature measured at 2cm below the head than the apex ignition method.

• Journal of the Korea Society of Computer and Information
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• v.7 no.2
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• pp.73-78
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• 2002

Recognition system of noise processing technique. A method combining SNR normalization with RAS is considered as a noise Processing and the performance of the speech recognition system can be improved using other noise processing technique. Experiment of recognition system is the internal organs that using a general digital signal processor(TMS320C31). Recognition word set is composed of 60 command words for of Rce environment and order of computer. Simulation is considered as a colored noise of general environment. The results of experiment showed that the recognition word set gives 94.61% of efficiency of recognition at maximum in case of the combination of SNR normalization and spectral subtraction.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.109-117
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• 2008

In this study, a method predicting the displacement responseof structures from the measured dynamic strain signal is proposed by using a mode decomposition technique. Dynamic loadings including wind and seismic loadings could be exerted to the bridge. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. To overcome such a problem, a mode decomposition technique was used in this study. The measured strain signal is decomposed into each modal component by using the empirical mode decomposition(EMD) as one of mode decomposition techniques. Then, the decomposed strain signals on each modal component are transformed into the modal displacement components. And the corresponding mode shapes can be also estimated by using the proper orthogonal decomposition(POD) from the measured strain signal. Thus, total displacement response could be predicted from combining the modal displacement components.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.126-130
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion (FBFE) based on virus evolutionary genetic algorithm(VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter (EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FBFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by identifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.727-728
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• 2015

Nowadays many videos are created with motiongraphics which has new visual effects and technology. The technique try to find out the image models which maximally stimulate the memories to transfer new visual information. The image will be expressed various ways with combining graphics and real scene with the help of computer. With the advances of VFX, the real and graphic scenes are more naturally combined to make believe its real scene. In this paper the novel motiongraphic technique, which uses tracking data from camera, is proposed.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.568-581
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• 2015

Predicting locations of users with portable devices such as IP phones, smart-phones, iPads and iPods in public wireless local area networks (WLANs) plays a crucial role in location management and network resource allocation. Many techniques in machine learning and data mining, such as sequential pattern mining and clustering, have been widely used. However, these approaches have two deficiencies. First, because they are based on profiles of individual mobility behaviors, a sequential pattern technique may fail to predict new users or users with movement on novel paths. Second, using similar mobility behaviors in a cluster for predicting the movement of users may cause significant degradation in accuracy owing to indistinguishable regular movement and random movement. In this paper, we propose a novel fusion technique that utilizes mobility rules discovered from multiple similar users by combining clustering and sequential pattern mining. The proposed technique with two algorithms, named the clustering-based-sequential-pattern-mining (CSPM) and sequential-pattern-mining-based-clustering (SPMC), can deal with the lack of information in a personal profile and avoid some noise due to random movements by users. Experimental results show that our approach outperforms existing approaches in terms of efficiency and prediction accuracy.