• 한방비만학회지
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• 제6권1호
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• pp.45-50
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• 2006

Objectives : The purpose of this study is to analyze the seven passions in terms of physical vector, and to understand the point of actions and directions. The result of this study will help us understand the aspect that the seven passions result in obesity and contribute in finding effective treatments. Methods : The characters of each seven passions were identified according to ${\ulcorner}$Hwangjenaekyung-Huangdineijing${\lrcorner}$. Results and Conclusions : 1. Each of the seven passions differs individually in physical characters in terms of points of actions and directions. 2. As the vector points of each seven passion work closely to digestive metabolism, and if the directions of vector clash into normal physiology, huge effects on obesity can be brought about. 3. Obesity, as a pathological situation, can be approached by canceling out all the vector elements of the seven passions. Here, the vector elements are basically regarded as the sources of obesity. 4. Psychological models of obesity can be applied for prevention and treatment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.196-201
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• 2008

Statistical learning theory has three analytical tools which are support vector machine, support vector regression, and support vector clustering for classification, regression, and clustering respectively. In general, their performances are good because they are constructed by convex optimization. But, there are some problems in the methods. One of the problems is the subjective determination of the parameters for kernel function and regularization by the arts of researchers. Also, the results of the learning machines are depended on the selected parameters. In this paper, we propose an efficient method for objective determination of the parameters of support vector clustering which is the clustering method of statistical learning theory. Using evolutionary algorithm and bootstrap method, we select the parameters of kernel function and regularization constant objectively. To verify improved performances of proposed research, we compare our method with established learning algorithms using the data sets form ucr machine learning repository and synthetic data.

• 자연과학논문집
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• 제11권1호
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• pp.11-14
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• 1999

군 G가 compact Lie군이며 $\rho$ : G $\rightarrow$ O(2)가 homomorphism일 때 군 G가 가환군이면 원위에서 실 G-vector bundle은 실 G-line bundle들의 Whitney 합이거나 G-plan bundle들의 Whitney 합과 isomorphic 하다는 것을 보였다.

• 충청수학회지
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• 제24권2호
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• pp.163-169
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• 2011

Recently, Kazmi and Khan [7] introduced a kind of equilibrium problem called generalized system (GS) with a single-valued bi-operator F. In this note, we aim at an extension of (GS) due to Kazmi and Khan [7] into a multi-valued circumstance. We consider a fairly general problem called the multi-valued quasi-generalized system (in short, MQGS). Based on the existence of 1-person game by Ding, Kim and Tan [5], we give a generalization of (GS) in the name of (MQGS) within the framework of Hausdorff topological vector spaces. As an application, we derive an existence result of the generalized vector quasi-variational inequality problem. This result leads to a multi-valued vector quasi-variational inequality extension of the strong vector variational inequality (SVVI) due to Fang and Huang [6] in a general Hausdorff topological vector space.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.422-432
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• 2019

A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.977-980
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• 2014

polyhedron promoter, vesicular stomatitis virus G (VSVG), polyA, cytomegalovirus (CMV) promoter, enhanced green fluorescent protein (EGFP), protein transduction domain (PTD) 유전자가 포함된 재조합 베큘로바이러스를 구축하였다. 본 재조합 베큘로바이러스 시스템은 인간 섬유아세포와 여러 가지 조직에 감염하여 시험하였고 재조합된 유전자의 전달과 유전자 발현을 대조 벡터시스템과 비교하였다. 본 연구의 결과로 제작된 재조합 베큘로바이러스 시스템은 유전자의 전달과 발현에 있어서 대조 벡터시스템 보다 더욱 효과적이고 안전적이었다.

• 호남수학학술지
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• 제45권2호
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• pp.300-315
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• 2023

In this article, we deal with the biharmonicity of a vector field X viewed as a map from a pseudo-Riemannian manifold (M, g) into its tangent bundle TM endowed with the Sasaki metric g_S. Precisely, we characterize those vector fields which are biharmonic maps, and find the relationship between them and biharmonic vector fields. Afterwards, we study the biharmonicity of left-invariant vector fields on the three dimensional Heisenberg group endowed with a left-invariant Lorentzian metric. Finally, we give examples of vector fields which are proper biharmonic maps on the Gödel universe.

• 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.

• 대한수학회지
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• 제37권1호
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• pp.1-19
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• 2000

We formulate a non-central limit theorem for non-linear functionals of stationary Gaussian vector processes with dependence.

• 대한전자공학회논문지SP
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• 제41권3호
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• pp.111-120
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• 2004

본 논문에서는 경계 영역에서의 색번짐 현상을 줄이기 위한 벡터 오차 확산법을 제안한다. 이러한 결점은 양자화 과정에서 생기는 큰 누적된 양자화 오차의 확산으로 인해서 발성하게 되며, 특히 색이 변하게 되는 영상의 경계 영역에서 특정 칼라띠를 형성하게된다. 따라서 이러한 결점을 줄이기 위해서 세안한 벡터 오차 확산 방법은 오차를 확산 받은 벡터와 8개의 기준색과의 벡터 크기 및 벡터 각을 비교함으로써, 큰 양자화 오차를 전체 중간조 처리 과정에서 제외한다. 먼저 오차가 보정된 벡터의 크기가 8개의 기준색보다 클 경우 양자화 오차를 확산시키지 않게 되며, 벡터 각이 클 경우에도 양자화 오차를 확산 시키지 않는다. 그러므로 제안한 방법은 각 채널의 상관관계를 고려한 벡터 칼라 공간상에서 중간조 처리를 함으로써 시각적으로 색이 향상된 결과를 얻을 수 있었고, 경계 부분에서의 색번짐 현상도 줄일 수 있었다.