• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.9-14
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• 2018

This study aims to investigate an importance of Author keyword with analysis the position of author keyword. An analysis was carried out on the position of author keyword. we examined an importance of Author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In the next stage, we performed analysis on correlation between network centrality measures and the position of keyword. As a result, degree centrality, closeness centrality, betweenness centrality, eigenvector centrality both has a high value in 4th author keyword order. eigenvector centrality was the comparatively effective method to separate of author keyword order method than other 3 centrality. Correlation analysis result shows that the network analysis value are increasing in order. This study has significance in that it was able to examine the author keyword behavior. Future research is needed to identify and supplement future situational factors, behavior, and psychology.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.33-40
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• 2006

This paper presents an efficient face recognition method using both first moment of image and eigenvector. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shitting to the centroid of face image. Eigenvector which are the basis images as face features, is extracted by principal component analysis(PCA). This is to improve the recognition performance by excluding the redundancy considering to second-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 60 face images(15 persons *4 scenes) of 320*243 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. In case of the 45 face images, the experimental results show that the recognition rate of the proposed methods is about 1.6 times and its the classification is about 5.6 times higher than conventional PCA without preprocessing. The city-block has been relatively achieved more an accurate classification than Euclidean or negative angle.

• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.279-284
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• 2017

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative time delay between two or more received signals for the direct signal must be determined. Although the GCC (Generalized Cross-Correlation) method is the most popular technique, an approach based on CCA (Canonical Correlation Analysis) was also proposed for the TDE (Time Delay Estimation). In this paper, we propose a new adaptive algorithm based on CCA in order to utilized the sparsity in the eigenvector of CCA based time delay estimator. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue with log-sum regularization in order to utilize the sparsity in the eigenvector. We have performed simulations for several SNR(signal to noise ratio)s, showing that the new CCA based algorithm can estimate the time delays more accurately than the conventional CCA and GCC based TDE algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1114-1119
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• 2002

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on 12-norm of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters for small order systems. In designing Kalman filters, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.313-318
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• 2001

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on $L_2-norm$ of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters. In designing Kalman filters for small order systems, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.10-10
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• 2000

Eigenstructure assignment is a typical method with the capability of the consideration of the specifications in time-domain in designing a 1]near control system. In general eigenstructure assignment such that all the desired eigenvalues are exactly assigned to the closed-loop system, the assignment of the eigenvectors is very restrictive. However if the arbitrary point in a certain area as an eigenvalue is allowed to be assigned t the closed-loop system, the assignment of the eigenvector corresponding to this eigenvalue can be much less restrictive. In this paper, the flexible eigenstructure assignment that can assign more closely the desired eigenvector to the closed-loop system by using an optimization technique is proposed.

• Wind and Structures
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• v.7 no.6
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• pp.359-372
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• 2004

Wind tunnel model studies were carried out to determine the wind load distribution on tributary areas near the gable-end of large, low-rise buildings with high pitch planar and curved roof shapes. Background pressure fluctuations on each tributary area are described by a series of uncorrelated modes given by the eigenvectors of the force covariance matrix. Analysis of eigenvalues shows that the dominant first mode contributes around 40% to the fluctuating pressures, and the eigenvector mode-shape generally follows the mean pressure distribution. The first mode contributes significantly to the fluctuating load effect, when its influence line is similar to the mode-shape. For such cases, the effective static pressure distribution closely follows the mean pressure distribution on the tributary area, and the quasi-static method would provide a good estimate of peak load effects.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.1-8
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• 1995

The practical problem of multi-attribute decision making are formed by the uncertain attribute that the attribute by the alternatives cannot be defined or judged crisphy but only as vague. In this case the final judgements are also represented by vague which have to be ordered to determine the optimal alternative. The problem is more complex if the evaluations of alternatives according to each attribute are expresed vague. This paper described the results of a study done to determine how well multi-attribute decision marking perform in helping a decision maker arrive at a preferred solution to a multi-attribute problem with vague attribute. Particular area of research has concentrated on the issue of combining quantitative and qualitative data supplied by estimation. Futher study considers some method for suitable evaluation of qualitative data.

• Computational Structural Engineering
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• v.9 no.4
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• pp.219-228
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• 1996

A method used for measuring the stiffness of hinging reinforced concrete frame structures is developed. The so called Stiffness Measure Method is used to evaluate the tangent stiffness of hinge regions while the structure is responding in nonlinear ranges. Eigenvector methods for nonlinear response have not been especially popular because of the need for regenerating eigenvectors as the time history proceeds. In the present work the eigenvectors sets and corresponding nonlinear state variables, i. e., the tangent stiffnesses of the hinge regions, are stored. There is an expectation that previously generated eigenvectors can be reused as the analysis proceeds. The stiffness measure is used to compare the current tangent stiffnesses of hinge regions with those of previously stored eigenvectors sets. Since eigenvector calculations are diminished the method is effective in reducing computational effort for reinforced concrete frame structures subjected to strong ground motions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.66-76
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• 2003

The arbitrary V-notched crack problem is considered. The general expressions for the stress components on this problem are obtained as explicit series forms composed of independent unknown coefficients which are denoted by coefficients of eigenvector. For this results eigenvalue equation is performed first through introducing complex stress functions and applying the traction free boundary conditions. Next solving this equation, eigenvalues and corresponding eigenvectors are obtained respectively, and finally inserting these results into stress components, the general equations are obtained. These results are also shown to be applicable to the symmetric V-notched crack or straight crack. It can be shown that this solutions are composed of the linear combination of Mode I and Mode II solutions which are obtained from different characteristic equations, respectively. Through performing asymptotic analysis for stresses, the stress intensity factor is given as a closed form equipped with the unknown coefficients of eigenvector. In order to calculate the unknown coefficients. based on these general explicit equations, numerical programming using the overdetermined boundary collocation method which is algorithmed originally by Carpenter is also worked out. As this programming requires the input data, the commercial FE analysis for stresses is performed. From this study, for some V-notched problems, unknown coefficients can be calculated numerically and also fracture parameters are determined.