• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.1-9
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• 2004

This study concentrates on the upwind schemes for convergence acceleration of the multigrid method for the Navier-Stokes equations. Comparative study of the upwind schemes in the Fourier space has been performed to identify why the second-order upwind scheme with enlarged stencil can be preconditioned better than the classical second-order upwind scheme. The full-coarsening multigrid method with implicit preconditioned multistage scheme has been implemented for verification of analysis. Numerical simulations on the inviscid and turbulent flows with the Spalart-Allmaras turbulent model have been performed. The results showed consistent trend with the analysis.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.3
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• pp.237-244
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• 2016

This paper presents a nonlinear Moving Least Squares(MLS) difference method for material nonlinearity problem. The MLS difference method, which employs strong formulation involving the fast derivative approximation, discretizes governing partial differential equation based on a node model. However, the conventional MLS difference method cannot explicitly handle constitutive equation since it solves solid mechanics problems by using the Navier's equation that unifies unknowns into one variable, displacement. In this study, a double derivative approximation is devised to treat the constitutive equation of inelastic material in the framework of strong formulation; in fact, it manipulates the first order derivative approximation two times. The equilibrium equation described by the divergence of stress tensor is directly discretized and is linearized by the Newton method; as a result, an iterative procedure is developed to find convergent solution. Stresses and internal variables are calculated and updated by the return mapping algorithm. Effectiveness and stability of the iterative procedure is improved by using algorithmic tangent modulus. The consistency of the double derivative approximation was shown by the reproducing property test. Also, accuracy and stability of the procedure were verified by analyzing inelastic beam under incremental tensile loading.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.25-36
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• 2008

In this paper, we present a robust hand recognition approach to sudden illumination changes. The proposed approach constructs a background model with respect to hue and hue gradient in HSI color space and extracts a foreground hand region from an input image using the background subtraction method. Eighteen features are defined for a hand pose and multi-class SVM(Support Vector Machine) approach is applied to learn and classify hand poses based on eighteen features. The proposed approach robustly extracts the contour of a hand with variations in illumination by applying the hue gradient into the background subtraction. A hand pose is defined by two Eigen values which are normalized by the size of OBB(Object-Oriented Bounding Box), and sixteen feature values which represent the number of hand contour points included in each subrange of OBB. We compared the RGB-based background subtraction, hue-based background subtraction and the proposed approach with sudden illumination changes and proved the robustness of the proposed approach. In the experiment, we built a hand pose training model from 2,700 sample hand images of six subjects which represent nine numerical numbers from one to nine. Our implementation result shows 92.6% of successful recognition rate for 1,620 hand images with various lighting condition using the training model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.16-22
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• 2011

This paper presents the multi-object tracking approach using the background difference and particle filtering by monte carlo sampling. We apply particle filters based on probabilistic importance sampling to multi-object independently. We formulate the object observation model by the histogram distribution using color information and the object dynaminc model for the object motion information. Our approach does not increase computational complexity and derive stable performance. We implement the whole Bayesian maximum likelihood framework and describes robust methods coping with the real-world object tracking situation by the observation and transition model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.3
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• pp.241-245
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• 2008

The characteristics of temperature profile around human body with heating life vest at sea were investigated in this paper. Especially, the temperature profile of human body was numerically calculated by finite difference method with Mathcad. The main parameters were seasonal mean sea water temperature, heating amount and heating duration time of heating life vest. In this paper, the boundary layer was composed by the difference matters, and the thermal conductivity was calculated with an adjacent cells using thermal resistance method. It was clarified that the body temperature was kept highly and the risk of death from hypothermia was reduced by wearing heating life vest.

• Journal of the Korean Society of Propulsion Engineers
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• v.6 no.4
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• pp.7-13
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• 2002

In this study, the mathematical model on the various complicated levels of the viscous liquid flows in the symmetric channel with the complicated shape was introduced and the assumptions applied to the simplified model was proposed. To analyse the steady cavitation flow, axis transform of physical region to non-dimensional region was performed, and multigrid were generated. Using this model, the steady cavitation flow was calculated, and good coincidence between experiment and calculation was achieved.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.4
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• pp.75-80
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• 2001

In this paper, we propose a new chaotic synchronization algorithm of using HVPM(Hyperchaotic Volume Preserving Maps) model. The proposed chaotic equation, that is, HVPM model which consists of three dimensional discrete-time simultaneous difference equations and shows uniquely random chaotic attractor using nonlinear maps and modulus function. Pecora and Carrol have recently shown that it is possible to synchronize a chaotic system by sending a signal from the drive chaotic system to the response subsystem. We proposed coupled synchronization algorithm in order to accomplish discrete time hyperchaotic HVPM signals. In the numerical results, two hyperchaotic signals are coupled and driven for accomplishing to the chaotic synchronization systems. And it is demonstrated that HVPM signals have shown the chaotic behavior and chaotic coupled synchronization.

• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2001.05a
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• pp.307-308
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• 2001

축제식 양식장 호지의 노령화를 방지하기 위해 수차를 이용하여 호지에 폭기 및 순환작용을 활성화하여 수질과 저질을 개선하는 방법이 널리 사용되고 있다. 본 연구에서는 이차원 수심적분 Reynolds 방정식을 지배방정식으로 하였고 이를 유한차분식으로 이산화한 수치모형(PDM)을 개발하였다. PDM은 수차 1대에 의한 유속발생에 적용하여 수차로부터 l0m 거리마다 층별 유속을 측정한 자료와 비교하여 검증하였다. (중략)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.407-409
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• 2015

In this paper, a hardware implementation of MOD(Moving Object Detection) algorithm is described, which is based GMM(Gaussian Mixture Model) and background subtraction. The EGML(Effective Gaussian Mixture Learning) is used to model and update background. Some approximations of EGML calculations are applied to reduce hardware complexity, and pipelining technique is used to improve operating speed. Gaussian parameters are adjustable according to various environment conditions to achieve better MOD performance. MOD processor is verified by using FPGA-in-the-loop verification, and it can operate with 109 MHz clock frequency on XC5VSX95T FPGA device.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.268-271
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• 2016

In video sequences, foreground object detection being composed of a background model and a background subtraction is an important part of diverse computer vision applications. However, object detection might fail in sudden illumination changes. In this letter, an illumination-robust background detection is proposed to address this problem. The method can provide quick adaption to current illumination condition using two background models with different adaption rates. Since the proposed method is a non-parametric approach, experimental results show that the proposed algorithm outperforms several state-of-art non-parametric approaches and provides low computational cost.