• Journal of Korean Society of Steel Construction
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• v.20 no.6
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• pp.751-759
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• 2008

In this study, the effect of an unsteady flow field around a body of aerostatic/aerodynamic forces were investigated using rectangular cylinders (B/D = 2, 3, 4, 5). Proper orthogonal decomposition (POD) was introduced to the analysis of the fluctuating pressure field that was measured on the stationary/oscillatory B/D=4 rectangular cylinder, and the characteristics of the proper functions with flow patterns were identified. In addition, the physical decoupling and interactions in the different co-existing flow patterns were investigated through POD. The comparison with the identified proper function associated with a particular flow pattern revealed that the Karman vortex is almost not affected by the separation bubble, but that the Karman vortex considerably interferes in the development of the separation bubble around the trailing edge. It can be considered that the Karman vortex induces the increment of the curvature of the substantial separated flow.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.163-168
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• 2011

In this paper, we proposed non-linear gamma curve algorithm for gamma correction. The previous non-linear gamma curve algorithm is generated by the least square polynomial using the Gauss-Jordan inverse matrix. However, the previous algorithm has some weak points. When calculating coefficients using inverse matrix of higher degree, occurred truncation errors. Also, only if input sample points are existed regular interval on 10-bit scale, the least square polynomial is accurately works. To compensate weak-points, we calculated accurate coefficients of polynomial using eigenvalue and orthogonal value of mat11x from singular value decomposition (SVD) and QR decomposition of vandemond matrix. Also, we used input data part segmentation, then we performed polynomial curve fitting and merged curve fitting results. When compared the previous method and proposed method using the mean square error (MSE) and the standard deviation (STD), the proposed segmented polynomial curve fitting is highly accuracy that MSE under the least significant bit (LSB) error range is approximately $10^{-9}$ and STD is about $10^{-5}$.