• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2167-2172
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• 2015

Due to the recent progress in information technology, demand for video imaging devices such as displays has grown. In general, images experience deterioration during the process of transmission due to various reasons. Many studies have boon undertaken on ways o reduce such noise. This paper6 suggests an algorithm that makes a judgment on the noise in order to remove the salt & pepper noise and replaces original pixels if they are non-noise while processing noise according to its density. The suggested algorithm shows a high PSNR of 30.49[dB] for Goldhill images that had been damaged of a high density salt & pepper noise(P = 60%), Compared to the exising CWMF, SWMF, and A-TMF, there were improvements by 17.74[dB], 11.52[dB], and 13.76[dB], respectively.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.33-35
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• 2006

배전 독립사업부제 도입 및 분산전원의 출현으로 배전계통은 계획 및 운영에 있어서도 변화가 일어 날 것이다. 예로, 기존의 방사상 구조의 배전 계통은 분산 전원의 출현으로 부분적인 그물망 구조로 변형될 수 있으며, 사업 구역이나 사업 지역으로 나누어진 배전계통에서는 서로 다른 관리 체제 하에서 운영이 필요하기 때문에 각 배전회사간의 정보 공유 문제가 발생할 수도 있다. 이러한 문제를 해결하기 위해 분화된 배전 계통의 특성을 고려하여 송전계통과 같이 전체 시스템에 대해 조류 계산하지 않고 배전 계통을 몇 개의 영역으로 나누고 다른 영역과의 경계 정보만을 이용하여 자신의 영역에 대한 조류 계산을 수행하는 알고리즘을 제안하였다. 이런 특성을 최대한 반영한 각 영역의 조류 계산은 분산 전원의 투입으로 인한 양방향 조류가 발생하게 되므로 그물망 구조로 된 구역과 기존의 방사상 구조로 된 영역으로 구분할 수 있다. 본 논문에서는 구역 특성에 맞고 배전 계통에 적용 가능한 알고리즘으로 먼저 분리 구역별 조류 계산을 수행한 후 그 다음 경계치 교환으로 배전 계통 전체의 조류 계산을 수행하는 알고리즘을 제안한다. 즉 방사상 구조 영역에서는 back/forward sweep 방법으로 수행하고 그물망 구조 영역에서는 Full Newton-Raphson 방법으로 구분하여 영역의 특성에 맞게 수행하였다.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.181-183
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• 2003

본 연구에서는 현재 국내-외 논문을 참조하여 배전계통에 적용된 조류계산 알고리즘의 적용사례를 조사하였다. 배전계통에 적용된 조류계산알고리즘은 Power Summation Method와 Current Summation Method가 있다. 배전계통은 선로의 구조가 거의 대부분 방사상으로 성되어 있기 때문에 Newton Raphson, Gauss Seidel, Fast Decoupled 방법을 그대로 사용하기는 문제가 있다. 그래서 DistFlow, Forward/Backward sweeping 법 등이 주로 사용되어 왔다. 그러나 미래의 계통은 현재와는 또 다른 Topology로 방사상과 루프가 혼합된 형태로 다르게 구성되어야 할 것이다. 이러한 상황에서 미래의 배전계통에 대하여 적용 가능한 알고리즘을 전망하고져 한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1281-1286
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• 2003

A line search algorithm to increase a convergence in Newton's method is developed and applied to nonlinear finite element analysis. The algorithm is based on the slack line search theory which is an efficient algorithm to determine initial acceleration coefficient, variable backtracking algorithm proposed by some researchers, and convergence criterion based on residual norm. Also, it is capable of avoiding exceptional diverging conditions. Developed program is tested in metal forming simulation such as forging and ring rolling. Numerical result shows the validity of the algorithm for a highly nonlinear system .

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.95-102
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• 2005

The Newton-Raphson iterative algorithm for finding a floating point reciprocal which is widely used for a floating point division, calculates the reciprocal by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the reciprocal of a floating point number F, the algorithm repeats the following operations: '$'X_{i+1}=X=X_i*(2-e_r-F*X_i),\;i\in\{0,\;1,\;2,...n-1\}'$ with the initial value $'X_0=\frac{1}{F}{\pm}e_0'$. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than $'e_r=2^{-p}'$. The value of p is 27 for the single precision floating point, and 57 for the double precision floating point. Let $'X_i=\frac{1}{F}+e_i{'}$, these is $'X_{i+1}=\frac{1}{F}-e_{i+1},\;where\;{'}e_{i+1}, is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to $'\frac{1}{F}{'}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal tables $(X_0=\frac{1}{F}{\pm}e_0)$ with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal unit. Also, it can be used to construct optimized approximate reciprocal tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia scientific computing, etc.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.1
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• pp.27-48
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• 1984

This study is conserned with the optimization of reinforced concrete frames using limit state design theory. Formulations of the optimal design for reinforced concrete frame based on the limit state theory turn out to be the nonlinear programming problems which have to deal with the required steel area, the width and effective height of the beam and column section and the moment reduction factor as the design variables. The objective function is formulated as the total construction cost which considers the costs of steel, concrete and forming for the reinforced concrete frames, and the basic constraints are imposed upon both ultimate and serviciability limit state concepts. Also, the stress blocks assumpted in CP110 and Hognestad et al. theory are applied to analysis an ultimate resistant section force for the ultimate limit state and only the criteria of CP110 are used for serviciability limit state. The optimized technique which is applied to solve the nonlinear programming problems for the optimization of reinforced concrete frames is SUMT utilizing the modified Newton-Raphson method. This algorithm is used to test for the two reinforced concrete frames, and then is compared and analysized with the numerical results of reference(10) to examine its convergence, applicability and stability under the same conditions. The results of this study are discussed about the economy comparision of the optimal values for CP110 and Hognestad et al., and the applicability, stability, convergence and validity of this algorithm used herein through the numerical analyses.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.200-208
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• 2003

This paper proposes a separation and feature extraction of image signals using the independent component analysis(ICA) based on neural networks of efficient learning rule. The proposed learning rule is a hybrid fixed-point(FP) algorithm based on secant method and momentum. Secant method is applied to improve the performance by simplifying the 1st-order derivative computation for optimizing the objective function, which is to minimize the mutual informations of the independent components. The momentum is applied for high-speed convergence by restraining the oscillation in the process of converging to the optimal solution. The proposed algorithm has been applied to the composite images generated by random mixing matrix from the 10 images of $512\times512$-pixel. The simulation results show that the proposed algorithm has better performances of the separation speed and rate than those using the FP algorithm based on Newton and secant method. The proposed algorithm has been also applied to extract the features using a 3 set of 10,000 image patches from the 10 fingerprints of $256\times256$-pixel and the front and the rear paper money of $480\times225$-pixel, respectively, The simulation results show that the proposed algorithm has also better extraction speed than those using the another methods. Especially, the 160 basis vectors(features) of $16\times16$-pixel show the local features which have the characteristics of spatial frequency and oriented edges in the images.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.336-341
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• 2004

This paper proposes an independent component analysis(ICA) of the fixed-point (FP) algorithm based on secant method and the kurtosis. The FP algorithm based on secant method is applied to improve the analysis speed and performance by simplifying the calculation process of the complex derivative in Newton method, the kurtosis is applied to cluster the components. The proposed ICA has been applied to the problems for separating the 6-mixed signals of 500 samples and 8-mixed images of $512{\times}512$ pixels, respectively. The experimental results show that the proposed ICA has always a fixed analysis sequence. The result can be solved the limit of conventional ICA based on secant method which has a variable sequence depending on the running of algorithm. Especially, the proposed ICA can be used for classifying and identifying the signals or the images.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.4
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• pp.447-459
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• 2013

Many problems need to be solved before vision systems can actually be applied in industry, such as the precision of the kinematics model of the robot control algorithm based on visual information, active compensation of the camera's focal length and orientation during the movement of the robot, and understanding the mapping of the physical 3-D space into 2-D camera coordinates. An algorithm is proposed to enable robot to move actively even if the relative positions between the camera and the robot is unknown. To solve the correction problem, this study proposes vision system model with six camera parameters. To develop the robot vision control algorithm, the N-R and EKF methods are applied to the vision system model. Finally, the position accuracy and processing time of the two algorithms developed based based on the EKF and the N-R methods are compared experimentally by making the robot perform slender bar placement task.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.247-256
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• 2004

This paper presents an efficient collision detection algorithm the performance of which is independent of animation speed. Most of the previous collision detection algorithms are incremental and discrete methods, which find out the neighborhood of the extreme vertex at the previous time instance in order to get an extreme vertex at each time instance. However, if an object collides with another one with a high torque, then the angular speed becomes faster. Hence, the candidate by the incremental algorithms may be farther from the real extreme vertex at this time instance. Therefore, the worst time complexity nay be $O(n^2)$, where n is the number of faces. Moreover, the total time complexity of incremental algorithms is dependent on the time step size of animation because a smaller time step yields more frequent evaluation of Euclidean distance. In this paper, we propose a new method to overcome these drawbacks. We construct a spherical extreme vertex diagram on Gauss Sphere, which has geometric properties, and then generate the distance function of a polyhedron and a plane by using this diagram. In order to efficiently compute the exact collision time, we apply the interval Newton method to the distance function.