• Title/Summary/Keyword: i-vector

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Study on Distortion Ratio Calculation of Park's Vector Pattern for Diagnosis of Stator Winding Fault of Induction Motor (유도전동기의 고정자 권선고장 진단을 위한 팍스벡터 패턴의 왜곡률 연산에 대한 연구)

  • Yang, Chul-Oh;Park, Kyu-Nam;Song, Myung-Hyun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.4
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    • pp.643-649
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    • 2012
  • The diagnosis technique of stator winding faults based on Motor Current Signature Analysis(MCSA) was suggested. Park's vector pattern, the circle that is drawn by d-q transformed currents($i_d$, $i_q$), is widely used for stator winding faults detection. The current Distortion Ratio(DR), defined by the ratio of max axis and min axis of ellipse of Park's vector's pattern, was more simple and powerful method than the Park's vector pattern. In this study, a calculation method of distortion ratio of Park's vector pattern was suggested for auto diagnosis of stator winding short fault and usefulness of suggested calculation method of distortion ratio was verified through simulation using LabVIEW program.

Modifying linearly non-separable support vector machine binary classifier to account for the centroid mean vector

  • Mubarak Al-Shukeili;Ronald Wesonga
    • Communications for Statistical Applications and Methods
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    • v.30 no.3
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    • pp.245-258
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    • 2023
  • This study proposes a modification to the objective function of the support vector machine for the linearly non-separable case of a binary classifier yi ∈ {-1, 1}. The modification takes into account the position of each data item xi from its corresponding class centroid. The resulting optimization function involves the centroid mean vector, and the spread of data besides the support vectors, which should be minimized by the choice of hyper-plane β. Theoretical assumptions have been tested to derive an optimal separable hyperplane that yields the minimal misclassification rate. The proposed method has been evaluated using simulation studies and real-life COVID-19 patient outcome hospitalization data. Results show that the proposed method performs better than the classical linear SVM classifier as the sample size increases and is preferred in the presence of correlations among predictors as well as among extreme values.

2-TYPE HYPERSURFACES SATISFYING ⟨Δx, x - x0⟩ = const.

  • Jang, Changrim
    • East Asian mathematical journal
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    • v.34 no.5
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    • pp.643-649
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    • 2018
  • Let M be a connected n-dimensional submanifold of a Euclidean space $E^{n+k}$ equipped with the induced metric and ${\Delta}$ its Laplacian. If the position vector x of M is decomposed as a sum of three vectors $x=x_1+x_2+x_0$ where two vectors $x_1$ and $x_2$ are non-constant eigenvectors of the Laplacian, i.e., ${\Delta}x_i={\lambda}_ix_i$, i = 1, 2 (${\lambda}_i{\in}R$) and $x_0$ is a constant vector, then, M is called a 2-type submanifold. In this paper we proved that a connected 2-type hypersurface M in $E^{n+1}$ whose postion vector x satisfies ${\langle}{\Delta}x,x-x_0{\rangle}=c$ for a constant c, where ${\langle}$, ${\rangle}$ is the usual inner product in $E^{n+1}$, is of null 2-type and has constant mean curvature and scalar curvature.

A Note on the Small-Sample Calibration

  • So, Beong-Soo
    • Journal of Korean Society for Quality Management
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    • v.22 no.2
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    • pp.89-97
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    • 1994
  • We consider the linear calibration model: $y_1={\alpha}+{\beta}x_i+{\sigma}{\varepsilon}_i$, i = 1, ${\cdots}$, n, $y={\alpha}+{\beta}x+{\sigma}{\varepsilon}$ where ($y_1$, ${\cdots}$, $y_n$, y) stands for an observation vector, {$x_i$} fixed design vector, (${\alpha}$, ${\beta}$) vector of regression parameters, x unknown true value of interest and {${\varepsilon}_i$}, ${\varepsilon}$ are mutually uncorrelated measurement errors with zero mean and unit variance but otherwise unknown distributions. On the basis of simple small-sample low-noise approximation, we introduce a new method of comparing the mean squared errors of the various competing estimators of the true value x for finite sample size n. Then we show that a class of estimators including the classical and the inverse estimators are consistent and first-order efficient within the class of all regular consistent estimators irrespective of type of measurement errors.

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Short utterance speaker verification using PLDA model adaptation and data augmentation (PLDA 모델 적응과 데이터 증강을 이용한 짧은 발화 화자검증)

  • Yoon, Sung-Wook;Kwon, Oh-Wook
    • Phonetics and Speech Sciences
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    • v.9 no.2
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    • pp.85-94
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    • 2017
  • Conventional speaker verification systems using time delay neural network, identity vector and probabilistic linear discriminant analysis (TDNN-Ivector-PLDA) are known to be very effective for verifying long-duration speech utterances. However, when test utterances are of short duration, duration mismatch between enrollment and test utterances significantly degrades the performance of TDNN-Ivector-PLDA systems. To compensate for the I-vector mismatch between long and short utterances, this paper proposes to use probabilistic linear discriminant analysis (PLDA) model adaptation with augmented data. A PLDA model is trained on vast amount of speech data, most of which have long duration. Then, the PLDA model is adapted with the I-vectors obtained from short-utterance data which are augmented by using vocal tract length perturbation (VTLP). In computer experiments using the NIST SRE 2008 database, the proposed method is shown to achieve significantly better performance than the conventional TDNN-Ivector-PLDA systems when there exists duration mismatch between enrollment and test utterances.

Construction of New Transfer Vector of Nuclear Polyhedrosis Virus of the Silkworm, Bombyx mori (누에 핵다각체병 바이러스를 이용한 새로운 전이 벡터의 제작)

  • 우수동;김우진;진병래;강석권
    • Journal of Sericultural and Entomological Science
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    • v.37 no.1
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    • pp.46-51
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    • 1995
  • In order to develope baculovirus expression vector system, we constructed new transfer vector of nuclear polyhedrosis virus of the silkworm, Bombyx mori. The promoter region containing only adenine of translation start codon of polyhedrin gene was cloned by polymerase chain reaction technique. And the 5' and 3' leader regions of polyhedrin gene was sequentially cloned. The polyhedrin coding gene was deleted from the +2 to the +597 position. As the result, we constructed new transfer vector which has EcoRI, SacI and KpnI sites for the cloning sites of foreign gene. New transfer vector was named as pBmKSKl. Escherichia coli $\beta$-galactosidase gene as foreign gene was inserted into pBmKSKl, under the control of the polyhedrin promoter and expressed in B. mori cells. The result showed that the new transfer vector pBmKSK1 is functional.

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GORENSTEIN SEQUENCES OF HIGH SOCLE DEGREES

  • Park, Jung Pil;Shin, Yong-Su
    • Journal of the Korean Mathematical Society
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    • v.59 no.1
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    • pp.71-85
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    • 2022
  • In [4], the authors showed that if an h-vector (h0, h1, …, he) with h1 = 4e - 4 and hi ≤ h1 is a Gorenstein sequence, then h1 = hi for every 1 ≤ i ≤ e - 1 and e ≥ 6. In this paper, we show that if an h-vector (h0, h1, …, he) with h1 = 4e - 4, h2 = 4e - 3, and hi ≤ h2 is a Gorenstein sequence, then h2 = hi for every 2 ≤ i ≤ e - 2 and e ≥ 7. We also propose an open question that if an h-vector (h0, h1, …, he) with h1 = 4e - 4, 4e - 3 < h2 ≤ (h1)(1)|+1+1, and h2 ≤ hi is a Gorenstein sequence, then h2 = hi for every 2 ≤ i ≤ e - 2 and e ≥ 6.

Classification of Power Quality Disturbances Using Feature Vector Combination and Neural Networks (특징벡터 결합과 신경회로망을 이용한 전력외란 식별)

  • Nam, Sang-Won
    • Proceedings of the KIEE Conference
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    • 1997.11a
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    • pp.671-674
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    • 1997
  • The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FIT, DWT(Discrete Wavelet Transform), and Fisher's criterion are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 10-class power quality disturbances are also provided.

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The Analysis on Vector Control Characteristics of LIM Using Finite Element Method (FEM을 이용한 선형유도 전동기의 벡터제어 특성 해석)

  • Im, D.H.;Kwon, B.I.;Lee, J.H.;Woo, K.I.;Kim, C.E.
    • Proceedings of the KIEE Conference
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    • 1995.07a
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    • pp.3-5
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    • 1995
  • For a linear induction motor(LIM), the constants of each phase are different due to the structure. In this paper, a vector control analysis method of a LIM taking into consideration its asymmetrical constants are proposed. And, in order to prove the propriety of proposed vector control method and to analyze the dynamic characteristics of LIM's vector control, FEM taking into account of movement and using stator tapped winding is used in the analysis region. So, It is confirmed that the proposed asymetrical constants vector control theory and simulation method of mixing with FEM is appropriate to dynamic characteristics analysis of LIM.

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GENERALIZATIONS OF ISERMANN'S RESULTS IN VECTOR OPTIMIZATION

  • Lee, Gue-Myung
    • Bulletin of the Korean Mathematical Society
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    • v.30 no.1
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    • pp.1-7
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    • 1993
  • Vector optimization problems consist of two or more objective functions and constraints. Optimization entails obtaining efficient solutions. Geoffrion [3] introduced the definition of the properly efficient solution in order to eliminate efficient solutions causing unbounded trade-offs between objective functions. In 1974, Isermann [7] obtained a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with linear constraints and showed that every efficient solution is a properly efficient solution. Since then, many authors [1, 2, 4, 5, 6] have extended the Isermann's results. In particular, Gulati and Islam [4] derived a necessary and sufficient condition for an efficient solution of a linear vector optimization problem with nonlinear constraints, under certain assumptions. In this paper, we consider the following nonlinear vector optimization problem (NVOP): (Fig.) where for each i, f$_{i}$ is a differentiable function from R$^{n}$ into R and g is a differentiable function from R$^{n}$ into R$^{m}$ .

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