• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.57-62
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• 2003

Among the procedure of automatic fingerprint recognition, binary code is important for the optimum thinning and singular point extraction while reserving the fingerprint image data. Binarization is to convert gray scale images into 0s and 255s values. For this conversion, you should set up the proper threshold value not to lose fingerprint image data. In this paper, we suggest the method to extract the standard threshold in real-time from fingerprint images entered by applying artificial intelligent methods in the binary code procedure. We show improved features while comparing the experiment results with the existing methods.

• International Journal of Contents
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• v.10 no.2
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• pp.47-58
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• 2014

Physiological signals provide important clues in the diagnosis and prediction of disease. Analyzing these signals is important in health and medicine. In particular, data preprocessing for physiological signal analysis is a vital issue because missing values, noise, and outliers may degrade the analysis performance. In this paper, we propose PhysioCover, a system that can recover missing values of physiological signals that were monitored in real time. PhysioCover integrates a gradual method and EM-based Principle Component Analysis (PCA). This approach can (1) more readily recover long- and short-term missing data than existing methods, such as traditional EM-based PCA, linear interpolation, 5-average and Missing Value Singular Value Decomposition (MSVD), (2) more effectively detect hidden variables than PCA and Independent component analysis (ICA), and (3) offer fast computation time through real-time processing. Experimental results with the physiological data of an intensive care unit show that the proposed method assigns more accurate missing values than previous methods.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.456-459
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• 2007

This study was performed for improving the Environmental Conservation Value Assessment Map (ECVAM) of National Land in Korea. The ECVAM items are composed of legal assessment and environmental/ecological assessment. An assessment method applied to ECVAM is basically an overlay method for environmental/ecological assessment items. The purpose of this study is to offer complement items of the ECVAM by examining assessment items. For this, our study was preceded as follows; In this study we assessed the ECVAM by 4 kinds of method. Method I is Comparing overlapping areas of each assessment items Grade 1, 2 and Permission of each assessment items'duplication, Method 2 is Grade 1, 2 areas by only singular assessment items, Method 3 is Only Grade 1 areas of Method 2 and Method 4 is Only Grade 2 areas of Method 2. As results, Method1 showed 93.4% of diameter Grade II(standard for stability), forest diameter item was accounted for 99.9% by Method 2, Method 3 showed 95.7% of forest diameter and forest density was accounted for 66.4% by Method 4. From now on, this study will contribute to reduce the complexity in the process of manufacturing ECVAM of National Land, and to raise the pliability in the process of managing and updating this map.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.37-48
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• 2020

Purpose - This study empirically investigates whether the risk property included in fat-tails of return distributions is systematic or unsystematic based on the devised statistical methods. Design/methodology/approach - This study devised empirical designs based on two traditional methods: principal component analysis (PCA) and the testing method of portfolio diversification effect. The fatness of the tails in return distributions is quantitatively measured by statistical probability. Findings - According to the results, the risk property in the fat-tails of return distributions has the economic meanings of eigenvalues having a value greater than 1 through PCA, and also systematic risk that cannot be removed through portfolio diversification. In other words, the fat-tails of return distributions have the properties of the common factors, which may explain the changes of stock returns. Meanwhile, the fatness of the tails in the portfolio return distributions shows the asymmetric relationship of common factors on the tails of return distributions. The negative tail in the portfolio return distribution has a much closer relation with the property of common factors, compared to the positive tail. Research implications or Originality - This empirical evidence may complement the existing studies related to tail risk which is utilized in pricing models as a common factor.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.159-165
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• 2005

This paper designs observers for matrix second-order linear systems on the basis of generalized eigenstructure assignment via unified parametric approach. It is shown that the problem is closely related with a type of so-called generalized matrix second-order Sylvester matrix equations. Through establishing two general parametric solutions to this type of matrix equations, two unified complete parametric methods for the proposed observer design problem are presented. Both methods give simple complete parametric expressions for the observer gain matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows eigenvalues of the error system to be set undetermined and sought via certain optimization procedures. A spring-mass system is utilized to show the effect of the proposed approaches.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.75-77
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• 1999

정보추천 시스템은 사용자가 어떤 정보를 선호하는지를 식별함으로써 산재한 정보 중에서 적절한 정보만을 제공하는 것을 목표로 한다. 이러한 정보추천 시스템에서 사용되는 정보여과 기술에는 내용기반 여과와 협력적 여과가 있다. 기존의 협력적 정보여과 기술은 선호도를 적게 제시한 사용자에게 정보를 추천하기 어렵고, 동일한 상품 정보에 대해서 사용자의 평가가 없을 경우 사용자간의 유사성을 판단하기 어려운 단점이 있다. 본 논문은 SVD (Singular Value Decomposition)를 통해 사용자 프로파일을 정량화함으로써 사용자 선호도 행렬로부터 숨어있는 의미정보를 추출하여 동일한 정보에 대해 선호도를 평가해야 한다는 단점을 극복한다. 이때, 사용자 프로파일 벡터를 비감독 학습 알고리즘인 SOM (Self0Organizing Map)으로 클러스터링하여 사용자를 분류하고, 정보추천은 사용자 그룹간에서 이루어지며 Pearson correlation 알고리즘을 이용한다. 기존의 방법과 비교한 결과, 제안한 방법이 새로운 사용자에 대해서도 적절한 정보를 추천할 수 있음을 볼 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.984-994
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• 2010

Pose variation is a critical problem in face recognition. Three-dimensional(3D) face recognition techniques have been proposed, as 3D data contains depth information that may allow problems of pose variation to be handled more effectively than with 2D face recognition methods. This paper proposes a pose-normalized 3D face modeling method that translates and rotates any pose angle to a frontal pose using a plane fitting method by Singular Value Decomposition(SVD). First, we reconstruct 3D face data with stereo vision method. Second, nose peak point is estimated by depth information and then the angle of pose is estimated by a facial plane fitting algorithm using four facial features. Next, using the estimated pose angle, the 3D face is translated and rotated to a frontal pose. To demonstrate the effectiveness of the proposed method, we designed 2D and 3D face recognition experiments. The experimental results show that the performance of the normalized 3D face recognition method is superior to that of an un-normalized 3D face recognition method for overcoming the problems of pose variation.

• ETRI Journal
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• v.29 no.2
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• pp.237-239
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• 2007

Interference from IEEE 802.11a systems affects ultra-wideband (UWB) systems significantly. In this letter, we suggest a novel narrow-band interference (NBI) suppression technique based on the singular value decomposition (SVD) algorithm in time-hopping pulse amplitude modulation (TH-PAM) UWB systems. The SVD algorithm is used to approximate the interference which then is subtracted from the received signals. In contrast to the conventional notch filter and rake receiver, our method is more effective and the receiver complexity can be greatly reduced.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.199-204
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• 2002

This paper is concerned with H$_{\infty}$ controller design methods for descriptor systems with and without time-varying delays in state and control input. The sufficient condition for the existence of an H$_{\infty}$ controller and the controller design method are presented by linear matrix inequality (LMI), singular value decomposition, Schur complements, and changes of variables. Since the obtained sufficient condition can be changed to an LMI form by proper manipulations, all solutions including controller gain can be obtained at the same time. Moreover, it is shown that robust H$_{\infty}$ controller design problem for parameter uncertain descriptor systems with time-varying delays in state and control input can be solvable using the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1650-1654
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• 2004

This paper presents how it is effective to use many features for improving the speed and the accuracy of the visual servo systems. Some rank conditions which relate the image Jacobian and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm Robot manipulator made in Samsung Electronic Co. Ltd.