• Journal of Applied Reliability
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• v.1 no.1
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• pp.17-33
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• 2001

The characteristics of Weibull distribution are investigated as a function of shape parameter. The statistical estimation methods of the shape parameter and statistical comparison methods of two or more shape parameters are studied. Assuming Weibull distribution, statistical analysis of bending-strength data of alumina titanium carbide ceramic matrix composites machined two different methods are performed.

• Journal of the Korean Ceramic Society
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• v.34 no.12
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• pp.1205-1212
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• 1997

The matrices which consisted of SiC whisker, PES(polyesterasulfone) as a binder, span 80(sorbitan monooleate) as a surfactant, TPP(triphenyl phosphate) as a plasticizer and dichloromethane as a solvent, have been prepared by the various methods such as tape casting, rolling, tape cast-coating and roll-coating method. The fuel cells of single stack type using these matrices are characterized by ac impedance spectroscopy and cyclic voltammetry technique. A fuel cell using a matrix prepared by the tape cast-coating method shows the best performance of 466.34 mA/$\textrm{cm}^2$ at 0.6V because it has the lowest polarization resistance at the interface between electrodes and a matrix due to the largest three phase contact region of gases, catalyst and electrolyte.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.457-469
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• 2007

Many procedures are available to identify a single outlier or an isolated influential point in linear regression and logistic regression. But the detection of influential points or multiple outliers is more difficult, owing to masking and swamping problems. The multiple outlier detection methods for logistic regression have not been studied from the points of direct procedure yet. In this paper we consider the direct methods for logistic regression by extending the $Pe\tilde{n}a$ and Yohai (1995) influence matrix algorithm. We define the influence matrix in logistic regression by using Cook's distance in logistic regression, and test multiple outliers by using the mean shift model. To show accuracy of the proposed multiple outlier detection algorithm, we simulate artificial data including multiple outliers with masking and swamping.

• International Journal of Contents
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• v.11 no.2
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• pp.1-8
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• 2015

In this paper, we describe a novel method for document layout analysis that is based on a Fuzzy Energy Matrix (FEM). A FEM is a two-dimensional matrix that contains the likelihood of text and non-text and is generated through the use of Fuzzy theory. The key idea is to define an Energy map for the document to categorize text and non-text. The proposed mechanism is designed for execution with a low-resolution document image, and hence our method has a fast processing speed. The proposed method has been tested on public ICDAR 2009 datasets to conduct a comparison against other state-of-the-art methods, and it was also tested with Korean documents. The results of the experiment indicate that this scheme achieves superior segmentation accuracy, in terms of both precision and recall, and also requires less time for computation than other state-of-the-art document image analysis methods.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.734-736
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• 1996

This paper presents a method of calculating a selective number of eigenvalues in power systems, which are rightmost, or are largest modulus. The modified Arnoldi method in conjunction with implicit shift OR-algorithm is used to calculate the rightmost eigenvalues. Algorithm requires neither a prior knowledge of the specified shifts nor the calculation of inverse matrix. The key advantage of the algorithm is its ability to converge to the wanted eigenvalues at once. The method is compared with the modified Arnoldi method combined with S-matrix transformation, where the eigenvalues having the largest modulus are to be determined. The two methods are applied to the reduced Kansai system. Convergence characteristics and performances are compared. Results show that both methods are robust and has good convergence properties. However, the implicit shift OR method is seen to be faster than the S-matrix method under the same condition.

• Structural Engineering and Mechanics
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• v.82 no.4
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• pp.503-515
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• 2022

The multi-rigid-body matrix method (MRBMM) is a generalized modeling method for obtaining the displacements, forces, and dynamic characteristics of a compliant mechanism without performing inner-force analysis. The method discretizes a compliant mechanism of any type into flexure hinges and rigid bodies by implementing a multi-body mass-spring model using coordinate transformations in a matrix form. However, in this method, the deformations of bodies that are assumed to be rigid are inherently omitted. Consequently, it may yield erroneous results in certain mechanisms. In this paper, we present a multi-compliant-body matrix-method (MCBMM) that considers a rigid body as a compliant element, while retaining the generalized framework of the MRBMM. In the MCBMM, a rigid body in the MRBMM is segmented into a certain number of body nodes and flexure hinges. The proposed method was verified using two examples: the first (an XY positioning stage) demonstrated that the MCBMM outperforms the MRBMM in estimating the static deformation and dynamic mode. In the second example (a bridge-type displacement amplification mechanism), the MCBMM estimated the displacement amplification ratio more accurately than several previously proposed modeling methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.85-91
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• 2008

When a large sparse matrix is calculated for a horizontal geodetic network adjustment, it needs to go through the process of matrix reordering for the efficiency of time and space. In this study, several reordering methods for sparse matrix were tested, using Sparse Matrix Manipulation System(SMMS) program, total processing time and Fill-in number produced in factorization process were measured and compared. As a result, Minimum Degree(MD) and Mutiple Minimum Degree(MMD), which are based on Minimum Degree are better than Gibbs-Poole-Stockmeyer(GPS) and Reverse Cuthill-Mckee(RCM), which are based on Minimum Bandwidth. However, the method of the best efficiency can be changed dependent on distribution of non-zero elements in a matrix. This finding could be applied to heighten the efficiency of time and storage space for national datum readjustment and other large geodetic network adjustment.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.653-657
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• 2005

Eigenstructure of a spatial design matrix of Matheron's variogram estimator in $R^1$ is derived. It is shown that the spatial design matrix in $R^1$ with n/2$\le$h < n has a nice spectral decomposition. The mean, variance, and covariance of this estimator are obtained using the eigenvalues of a spatial design matrix. We also found that the lower bound and the upper bound of the normalized Matheron's variogram estimator.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.173-176
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• 1987

This paper presents a simple factorization of the Hadamard matrix which is used to develop a fast algorithm for the Hadamard transform. This matrix decomposition is of the kronecker products of identity matrices and successively lower order Hadamard matrices. This following shows how the Kronecker product can be mathematically defined and efficiently implemented using a factorization matrix methods.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.317-329
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• 2010

In recent years, many sparse estimation methods, also known as compressed sensing, have been developed. However, most of these methods presume that the measurement matrix is completely known. We develop a new blind maximum likelihood method-the expectation-sparse-maximization (ESpaM) algorithm-for models where the measurement matrix is the product of one unknown and one known matrix. This method is a variant of the expectation-maximization algorithm to deal with the resulting problem that the maximization step is no longer unique. The ESpaM algorithm is justified theoretically. We present as well numerical results for two concrete examples of blind channel identification in digital communications, a doubly-selective channel model and linear time invariant sparse channel model.