• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.519-527
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• 2003

Speech is much influenced by the existence of outliers which are introduced by such an unexpected happenings as additive background noise, change of speaker's utterance pattern and voice detection errors. These kinds of outliers may result in severe degradation of speaker recognition performance. In this paper, we proposed the GMM based on robust principal component analysis (RPCA-GMM) using M-estimation to solve the problems of both ouliers and high dimensionality of training feature vectors in speaker identification. Firstly, a new feature vector with reduced dimension is obtained by robust PCA obtained from M-estimation. The robust PCA transforms the original dimensional feature vector onto the reduced dimensional linear subspace that is spanned by the leading eigenvectors of the covariance matrix of feature vector. Secondly, the GMM with diagonal covariance matrix is obtained from these transformed feature vectors. We peformed speaker identification experiments to show the effectiveness of the proposed method. We compared the proposed method (RPCA-GMM) with transformed feature vectors to the PCA and the conventional GMM with diagonal matrix. Whenever the portion of outliers increases by every 2%, the proposed method maintains almost same speaker identification rate with 0.03% of little degradation, while the conventional GMM and the PCA shows much degradation of that by 0.65% and 0.55%, respectively This means that our method is more robust to the existence of outlier.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.12-15
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• 1996

An array often has faulty elements in real operation. The faulty elements, producing no output or highly reduced gain than other normal elements, cause an elevated sidelobe level and fail to reject the interference signals in an adaptive beamformer. In this paper we have presented the beamforming algorithm for arrays with faulty elements. In the ideal case, an autocorrelation matrix computed from array output data is the toeplitz. However, the inverse of the autocorrelation matrix computed from array with faulty elements can not be obtained due to deficient values of matrix. To overcome this problem, an adaptive beamforming algorithm using the average values of the diagonal terms of matrix is proposed. The computer simulations have been performed to study the performance of the presented method. We have been able to solve the degrees-of-freedom problem that is the drawback of the previous subaperture processing technique.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.315-323
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• 2011

This paper proposes two methods of estimating prior distribution to improve the performance of rapid speaker adaptation based on maximum a posteriori linear regression (MAPLR). In general, prior distribution of the transformation matrix used in MAPLR adaptation is estimated from all of the training speakers who are employed to construct the speaker-independent model, and it is applied identically to all new speakers. In this paper, we propose a method in which prior distribution is estimated from a group of reference speakers, selected using adaptation data, so that the acoustic characteristics of the selected reference speakers may be similar to that of the new speaker. Additionally, in MAPLR adaptation with block-diagonal transformation matrix, we propose a method in which the mean matrix and covariance matrix of prior distribution are estimated from two groups of transformation matrices obtained from the same training speakers, respectively. To evaluate the performance of the proposed methods, we examine word accuracy according to the number of adaptation words in the isolated word recognition task. Experimental results show that, for very limited adaptation data, statistically significant performance improvement is obtained in comparison with the conventional MAPLR adaptation.

• Journal of Korea Water Resources Association
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• v.31 no.4
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• pp.439-448
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• 1998

There are many methods to calculate steady-state flowrate in a large water distribution system. Linear method which analyzes continuity equations and energy equations simultaneously is most widely used. Though it is theoretically simple, when it is applied to a practical water distribution system, it produces a very sparse coefficient matrix and most of its diagonal elements are to be zero. This sparsity characteristic of coefficient matrix makes it difficult to analyze pipe flow using the linear method. In this study, a graph theory is introduced to water distribution system analysis in order to prevent from producing ill-conditioned coefficient matrix and the technique is developed to produce positive-definite matrix. To test applicability of developed method, this method is applied to 22 pipes and 142 pipes system located nearby Taegu city. The results obtained from these applications show that the method can calculate flowrate effectively without failure in converage. Thus it is expected that the method can analyze steady state flowrate and pressure in pipe network systems efficiently. Keywords : pipe flow analysis, graph theory, linear method.

• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.285-295
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• 2014

In the setting of semidenite linear complementarity problems on $S^n$, we focus on the Stein Transformation $S_A(X)\;:=X-AXA^T$, and show that $S_A$ is (strictly) monotone if and only if ${\nu}_r(UAU^T{\circ}\;UAU^T)$(<)${\leq}1$, for all orthogonal matrices U where ${\circ}$ is the Hadamard product and ${\nu}_r$ is the real numerical radius. In particular, we show that if ${\rho}(A)$ < 1 and ${\nu}_r(UAU^T{\circ}\;UAU^T){\leq}1$, then SDLCP($S_A$, Q) has a unique solution for all $Q{\in}S^n$. In an attempt to characterize the GUS-property of a nonmonotone $S_A$, we give an instance of a nonnormal $2{\times}2$ matrix A such that SDLCP($S_A$, Q) has a unique solution for Q either a diagonal or a symmetric positive or negative semidenite matrix. We show that this particular $S_A$ has the $P^{\prime}_2$-property.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.04a
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• pp.159-162
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• 2000

Interfacial and microfailure properties of carbon fiber/epoxy matrix composites were evaluated using both tensile fragmentation and compressive Broutman tests with acoustic emission (AE). Amino-silane and maleic anhydride polymeric coupling agents were used via the dipping and electrodeposition (ED), respectively. Both coupling agents exhibited higher improvements in interfacial shear strength (IFSS) under tensile tests than compressive cases. However, ED treatment showed higher IFSS improvement than dipping case under both tensile and compressive test. The typical microfailure modes including fiber break, matrix cracking, and interlayer failure were observed during tensile test, whereas the diagonal slippage in fiber ends was observed during compressive test. For both the untreated and treated cases AE distributions were separated well under tensile testing. On the other hand, AE distributions were rather closer under compressive tests because of the difference in failure energies between tensile and compressive loading. Under both loading conditions, fiber breaks occurred around just before and after yielding point. Maximum AE voltage fur the waveform of carbon or basalt fiber breakage under tensile tests exhibited much larger than those under compressive tests.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.05a
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• pp.258-262
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• 2001

The contact resistivity was correlated with IFSS and microfailure modes in conductive fiber/cement composites electro-pullout and AE. As IFSS increased, the number of AE signals increased and the contact resistivity increased latter to the infinity. In dual matrix composite (DMC) test and AE, the number of signals with high amplitude and energy in g]ass fiber composite is significantly larger than that of no-fiber composite. Many vertical and diagonal cracks were observed in glass fiber and no-fiber composite under tensile test, respectively. Electro-micromechanical technique and AE can be used efficiently for sensitive nondestructive (NDT) evaluation and to detect microfailure mechanisms in various conductive fibers reinforced brittle and nontransparent cement composites.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.3
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• pp.224-228
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• 2012

We have developed new materials that lead to methyl meth acrylate monomer and styrene monomer to using polymerization method. The materials have a powder form and show liquid behavior. We call the "Electronic Bead". An our experiment, a positive-charged particle has $TiO_2$, polymer and CCA(-), while a negative-charged particle consists of carbon black, polymer and CCA(+). The charged particles have electrical characteristic of white -10 uC/g and black 10 uC/g, respectively. Also, these particles have good fluidity by additive of nano-sized silica. Using these materials, we demonstrated prototype displays that have $320{\times}320$ array of pixels and 6-in-diagonal viewable image size, driven by passive-matrix addressing. The reflectivity shows about 30% even though our experiment is at the beginning point. Also, the panel has contrast ratio 6:1. We think there are many chances to improve reflectivity through modifying components of particle resin, mixture ratio of each particle, panel structure and so on.

• Korean Management Science Review
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• v.16 no.1
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• pp.157-171
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• 1999

In a increasingly competitive marketplace, the manufacturing companies have no choice but looking for ways to improve productivity to sustain their competitiveness and survive in the industry. Recently cellular manufacturing has been under discussion as an option to be easily implemented without burdensome capital investment. The objective of cellular manufacturing is to realize many aspects of efficiencies associated with mass production in the less repetitive job-shop production systems. The very first step for cellular manufacturing is to group the sets of parts having similar processing requirements into part families, and the equipment needed to process a particular part family into machine cells. The underlying problem to determine the part and machine assignments to each manufacturing cell is called the cell formation. The purpose of this study is to develop a clustering algorithm based on the neural network approach which overcomes the drawbacks of ART1 algorithm for cell formation problems. In this paper, a generalized learning vector quantization(GLVQ) algorithm was devised in order to transform a 0/1 part-machine assignment matrix into the matrix with diagonal blocks in such a way to increase clustering performance. Furthermore, an assignment problem model and a rearrangement procedure has been embedded to increase efficiency. The performance of the proposed algorithm has been evaluated using data sets adopted by prior studies on cell formation. The proposed algorithm dominates almost all the cell formation reported so far, based on the grouping index($\alpha$ = 0.2). Among 27 cell formation problems investigated, the result by the proposed algorithm was superior in 11, equal 15, and inferior only in 1.

• Journal of Internet Computing and Services
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• v.5 no.3
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• pp.57-62
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• 2004

In this paper, an efficient speaker identification based on robust vector quantizationprincipal component analysis (VQ-PCA) is proposed to solve the problems from outliers and high dimensionality of training feature vectors in speaker identification, Firstly, the proposed method partitions the data space into several disjoint regions by roust VQ based on M-estimation. Secondly, the robust PCA is obtained from the covariance matrix in each region. Finally, our method obtains the Gaussian Mixture model (GMM) for speaker from the transformed feature vectors with reduced dimension by the robust PCA in each region, Compared to the conventional GMM with diagonal covariance matrix, under the same performance, the proposed method gives faster results with less storage and, moreover, shows robust performance to outliers.