• 전기학회논문지
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• 제61권4호
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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.

• Communications for Statistical Applications and Methods
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• 제30권3호
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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 y_i ∈ {-1, 1}. The modification takes into account the position of each data item x_i 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.

• East Asian mathematical journal
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• 제34권5호
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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.

• 품질경영학회지
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• 제22권2호
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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.

• 말소리와 음성과학
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• 제9권2호
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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.

• 한국잠사곤충학회지
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• 제37권1호
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• pp.46-51
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• 1995

국내 분리주의 BmNPV를 이용하여 유용 단백질을 생산할 수 있는 새로운 전이벡터의 제작과 외내 유전자의 발현에 대한 연구결과는 다음과 같다. 1. PCR 기법에 의하여 다각체 단백질 유전자의 ＋1 - －194에 해당하는 promoter 부위를 증폭하고 클로닝 하였다. 2. 다각체 단백질 유전子의 5' 및 3'의 leader 부위를 promoter 부위와 함께 단계적으로 클로닝하여 전이벡터를 완성하였다. 3. 완성된 전이벡터는 pBmKSK1으로 명명하였으며, 염기서열 결정을 통하여 다각체 단백질 유전자의 ＋2 부터 ＋597까지 제거되고 외내 유전자의 클로닝 sites로 EcoRI, KpnI과 SacI을 가짐을 확인하였다. 4. 외래 유전자로서 E. coli의 $\beta$-galactosidase 유전자를 pBmKSKl에 클로닝하고 누에 세포주에 전이시킨 후, X-gal 염색 및 SDS-PAGE에 의하여 pB- mKSKl이 제 기능을 수행함을 확인하였다.

• 대한수학회지
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• 제59권1호
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• pp.71-85
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• 2022

In [4], the authors showed that if an h-vector (h₀, h₁, …, h_e) with h₁ = 4e - 4 and h_i ≤ h₁ is a Gorenstein sequence, then h₁ = h_i for every 1 ≤ i ≤ e - 1 and e ≥ 6. In th_is paper, we show that if an h-vector (h₀, h₁, …, h_e) with h₁ = 4e - 4, h₂ = 4e - 3, and h_i ≤ h₂ is a Gorenstein sequence, then h₂ = h_i for every 2 ≤ i ≤ e - 2 and e ≥ 7. We also propose an open question that if an h-vector (h₀, h₁, …, h_e) with h₁ = 4e - 4, 4e - 3 < h₂ ≤ (h₁)₍₁₎|⁺¹₊₁, and h₂ ≤ h_i is a Gorenstein sequence, then h₂ = h_i for every 2 ≤ i ≤ e - 2 and e ≥ 6.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 A
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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.

• 대한수학회보
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• 제30권1호
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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$^{m}$ .