• Journal of the Korea Safety Management & Science
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• v.5 no.4
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• pp.257-266
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• 2003

3D Modeling Solution can reduce projecting error and also make possible to design visually, so that it can minimize human resources. On the other hand, it has defects of operating difficulties caused by too much complex function, thus it consequently prevent user from prompt handling. According to this paper, the developed party S/W will help that user can construct the parts easily, can let everybody use 3D modeling solution readily, and make fast development of new product. This software will carry out prompt development of new product and derive satisfaction of customers from high quality. Also, saving time and expense naturally raise competitive power in consequence.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.1-9
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• 2013

Accuracy of the 3-D model is essential in model-based camera tracking. However, 3-D object modeling requires dedicated and complicated procedures for precise modeling without any errors. Even if a 3-D model contains a certain level of errors, on the other hand, the tracking errors cause by the modeling errors can be different from its perceptual errors; thus, it is an important aspect that the camera tracking can be successful without precise 3-D modeling if the modeling errors are within the user's permissible range. In this paper, we analyze the tolerance of 3-D object modeling errors by comparing computational matching errors with perceptual matching errors through user evaluations, and also discuss permissible ranges of 3-D object modeling errors.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.5
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• pp.19-24
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• 2002

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.569-570
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• 2011

fault와 에러를 구분하여 정의한 후, 에러처리를 위한 시스템 상태를 fault, 에러, 회복, benign, mon1, mon2의 상세 상태로 분류하고, 이들 상태를 묘사해 줄 수 있는 추계적 페트리 네트를 이용하여 시스템 에러 처리를 모델링 한다. 시스템이 수십년이 지나면 궁극적으로 다운되는 비신뢰도를 모델로 부터 구할 수 있음을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.483-487
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• 1986

The LQG/LTR method is applied to the real servomechanism with the unknown modeling error and system noise variance Q$_{2}$. The equivalent discretized LQG controller is implemented on the 16-bit microcomputer and the experimental results show the improved stability and the satisfactory performance when the noise variance Q$_{2}$ is increased infinitly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.25-26
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.544-547
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• 1997

In this paper, we propose a dynamic localization method using a rotating sonar and a map. The proposed method is implemented by using extended Kalman filter. The state equation is based on the encoder propagation model and the encoder error model, and the measurement equation is a map-based measurement equation using a rotating sonar sensor. By utilizing sonar beam characteristics, map-based measurements are updated while AMR is moving continuously. By modeling and estimating systematic errors of a differential encoder, the position is successfully estimated even the interval of the map-based measurement. Monte-Carlo simulation shows that the proposed global position estimator has the performance of a few millimeter order in position error and of a few tenth degrees in heading error and of compensating systematic errors of the differential encoder well.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1155-1161
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• 2001

We propose an adaptive nonlinear control algorithm for high precision tracking and stabilization of LOS(Line-of-Sight). The friction parameters of the LOS gimbal are estimated by off-line evolutionary strategy and the friction is compensated by estimated friction compensator. Especially, as the nonlinear control input in a small tracking error zone is enlarged by the nonlinear function, the steady state error is significantly reduced. The proposed algorithm is a direct adaptive control method based on the Lyapunov stability theory, and its convergence is guaranteed under the limited modeling error or torque disturbance. The performance of the pro-posed algorithm is verified by computer simulation on the LOS gimbal model of a moving vehicle.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.24-32
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• 1996

A rigorous theory for modeling, analysis, optimum nonseparable filter bank in multidimensional M-band quantized subband codec are developed in this paper. Each pdf-optimized quantizer is modeled by a nonlinear gain-plus-additive uncorrelated noise and embedded into the subband structure. We then decompose the analysis/synthesis filter banks into their polyphase components and shift the down-and up-samplers to the right and left of the analysis/synthesis polyphase matrices respectively. Focusing on the slow clock rate signal between the samplers, we derive the exact expression for the output mean square quantization error by using spatial-invariant analysis. We show that this error can be represented by two uncorrelated components : a distortion component due to the quantizer gain, and a random noise component due to fictitious uncorrelated noise at the uantizer. This mean square error is then minimized subject to perfect reconstruction (PR) constraints and the total bit allocation for the entire filter bank. The algorithm gives filter coefficients and subband bit allocations. Numerical design example for the optimum nonseparable orthonormal filter bank is given with a quincunx subsampling lattice.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.199-204
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• 2006

Airborne LIDAR systems have been increasingly used for various applications as an effective surveying mean that can be complementary or alternative to the traditional one based on aerial photos. A LIDAR system is a multi-sensor system consisting of GPS, INS, and a laser scanner and hence the errors associated with the LIDAR data can be significantly affected by not only the errors associated with each individual sensor but also the errors involved in combining these sensors. The analysis about these errors have been performed by some researchers but yet insufficient so that the results can be critically contributed to performing accurate calibration of LIDAR data. In this study, we thus analyze these error sources, derive their mathematical models and perform the sensitivity analysis to assess how significantly each error affects the LIDAR data. The results from this sensitivity analysis in particular can be effectively used to determine the main parameters modelling the systematic errors associated with the LIDAR data for their calibration.