• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.5
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• pp.459-467
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• 1992

This paper presents a new algorithm for the countermeasure to alleviate the line overloads due to contingency without shedding loads in a power system. This method for relieving the line overloads by line switching is based on obtaining the kine outage distribution factors-the linear sensitivity factors, which give the amount of change in the power flow of each line due to the removal of a line in a power system. There factors are made up of the elements of sparse bus reactance matrix and brach reactances. In this paper a fast algorithm and program is presented for obtaining only the required bus reactance elements which corresponds to a non-zero elements of bus admittance matrix, and elements of columns which correspond to two terminal buses of the overloaded(monitored) line. The proposed algorithm has been validated in tests on a 6-bus and the 30-bus test system.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.2
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• pp.1-9
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• 1985

In this study, two stage transfer line with limited repair capability is modeled to formulate optimal dynamic repair priority policy. The method of Markov Chains is used to analyze the analytical model of this line. An efficient algorithm is developed, utilizing the block tridiagonal structure of the transition probability matrix, to obtain the steady state probabilities and system performance measures, such as the steady state production rate of the line and the average in-process inventory in the interstage buffer.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.364-370
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• 2013

In the current paper, we propose a new modeling algorithm to analyze the coupling between an incident electromagnetic field (EMF) and a twisted conducting line, which is a kind of non-uniform line. Typically, analysis of external field coupling to a uniform transmission line (TL) is implemented by the Baum-Liu-Tesche (BLT) equation so that the induced load responses can be obtained. However, it is difficult to apply this method to the analysis of a twisted conducting line. To overcome this limitation, we used a chain matrix composed of ABCD parameters. The proposed algorithm expands the dimension of the previous chain matrix to consider the EMF coupling effectiveness of each twisted pair, which is then applied to multi-conductor transmission line (MTL) theory. In addition, we included a comparative study that involves the results of each method applied in the conventional BLT equation and new proposed algorithm in the uniform two-wire TL case to verify the proposed method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.2
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• pp.55-68
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• 2008

One of well known and much studied nonlinear matrix equations is the matrix polynomial which has the form $P(X)=A_0X^m+A_1X^{m-1}+{\cdots}+A_m$, where $A_0$, $A_1$, ${\cdots}$, $A_m$ and X are $n{\times}n$ complex matrices. Newton's method was introduced a useful tool for solving the equation P(X)=0. Here, we suggest an improved approach to solve each Newton step and consider how to incorporate line searches into Newton's method for solving the matrix polynomial. Finally, we give some numerical experiment to show that line searches reduce the number of iterations for convergence.

• Journal of the korean Society of Automotive Engineers
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• v.13 no.6
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• pp.90-100
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• 1991

This paper represents the analysis of the sheet drawing by applying the Matrix method to Hill's slip-line field for small reduction and indirect type slip-line field in case of large reduction. Results of the analysis represent the relation between the reduction ratio and the die wall pressure, mean drawing stress through rough die. The limitation on the use of this slip-line field is described. When the reduction ratio is given, the optimum die angle is analyzed in this paper.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.208-211
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• 2004

Landmark matching is one of an important algorithm for navigation of satellite images. This paper proposes a fast landmark matching algorithm using a MGLI (Moving Guide-Line Image). For searching the matched point between the landmark chip and a part of image, correlation matrix is used generally, but the full-sized correlation matrix has a drawback requiring plenty of time for matching point calculation. MGLI includes thick lines for fast calculation of correlation matrix. In the MGLI, width of the thick lines should be determined by satellite position changes and navigation error range. For the fast landmark matching, the MGLI provides guided line for a landmark chip we want to match, so that the proposed method should reduce candidate areas for correlation matrix calculation. This paper will show how much time is reduced in the proposed fast landmark matching algorithm compared to general ones.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1299-1301
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• 1999

This paper describes a initial screening methods for weak line selection using sensitivity matrix. The elements of sensitivity matrix for line suceptance have 1 or -1, 0. From this property of sensitivity matrix, the eigen-sensitivity for line suceptance can be computed very simply and selected weak line for small signal stability or transient stability. The proposed algorithm is applied to small signal stability of New England 39-bus system and also applied to voltage stability of New England 30-bus system too.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2657-2675
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• 2013

A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.795-802
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• 2001

The commutation and control in matrix converters is more complicated as in voltage source converters. Natural freewheeling paths do not exist and the theoretic absent storage elements result in a direct coupled system of load and line currents as well as voltages. The paper offers an overview about staggered commutation and control policies in matrix converters. Based on the knowledge about load current direction and the signs of the line to line input voltages different multi-step commutation policies were derived. This paper examines the application of that policies in the case of space vector modulation and direct control methods with the focus on the resulting effects to the reference output voltage deviation.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.595-601
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• 2003

In this paper we propose an on line training method for classification based on least squares support vector machine. Proposed method enables the computation cost to be reduced and the training to be peformed incrementally, With the incremental formulation of an inverse matrix in optimization problem, current information and new input data can be used for building the new inverse matrix for the estimation of the optimal bias and Lagrange multipliers, so the large scale matrix inversion operation can be avoided. Numerical examples are included which indicate the performance of proposed algorithm.