• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.79-86
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• 2005

In this paper, we propose a new LINF(Linear Independent Non-negative Factorization) algorithm for real-time face recognition systea This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction Part we applied subtraction image, the detection of eye and mouth region , and normalization method, and then in the face recognition Part we used LINF in extracted face candidate region images. The existing recognition system using only PCA(Principal Component Analysis) showed low recognition rates, and it was hard in the recognition system using only LDA(Linear Discriminants Analysis) to apply LDA directly when the training set is small. To overcome these shortcomings, we reduced dimension as the matrix that had non-negative value to be different from former eigenfaces and then applied LDA to the matrix in the proposed system We have experimented using self-organized DAIJFace database and ORL database offered by AT(')T laboratory in Cambridge, U.K. to evaluate the performance of the proposed system. The experimental results showed that the proposed method outperformed PCA, LDA, ICA(Independent Component Analysis) and PLMA(PCA-based LDA mixture algorithm) method within the framework of recognition accuracy.

• Journal of Korean Academy of Nursing
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• v.29 no.6
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• pp.1365-1378
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• 1999

This study is a methodological research study to develop an instrument to measure in patients with cancer and to test the validity and reliability of the instrument. The research procedure was as follows : 1) The first step was to develop conceptual framework based on a comprehensive review of the literature and in-depth interviews with patients with cancer. This conceptual framework was organized in to three dimensions (the intrapersonal dimension, the significant-other and context related dimension, the transcendental dimension). Initially 59 items were adopted. 2) These items were analyzed through the index of content validity(CVI) and 53 items were selected which met more than 80% on the CVI. 3) The pretest was carried out with 87 patients with cancer. After the pretest results were analyzed by item analysis, 44 items were selected. A second test of content validity was conducted and 6 items were eliminated considering the 80% CVI. 4) To test for reliability and validity, data collection was done during the period from January 25, 1999, to February 26, 1999. The subjects for the test were 160 patients with cancer and 185 healthy persons. analysis, item analysis and multitrait-multimethod method to analyze validity. The findings are as follows : 1) The Cronbach's alpha coefficient for internal consistency was .92 for the total 38 items and .79, .82, .85, for the three dimensions in that order. 2) The item analysis was based on the corrected item to total correlation coefficient( .30 or more) and information about the alpha estimate if this item was dropped from the scale. 3) As a result of the initial factor analysis using principal component analysis and varimax rotation, one item was deleted because of factor complexity (indiscriminate factor loadings). In the secondary factor analysis, 7 factors with eigenvalue of more than 1.0 were extracted and these factors explained 56 percents of the total variance. The seven factors were labeled as 'family relationship', 'emotional condition', 'physical discomfort', 'meaning and goal of life', 'contextual stimuli', 'change of body image', 'guilt feelings'. 4) The convergence effect between this instrument and the life satisfaction scale was identified and there was significant positive correlation(r= .52, p= .00). The discriminant validity between this instrument and the depression scale(CES-D) was tested and there was significant negative correlation(r= -.50, p= .00). The instrument for accessing the suffering of patients with cancer developed in this study was identified as a tool with a high degree of reliability and validity. In this sense, this tool can be effectively utilized for assessment in caring for patients with cancer.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1001-1009
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• 2015

In Smart Grid, smart meter sends our electric signal data to the main server of power supply in real-time. However, the more efficient the management of power loads become, the more likely the user's pattern of usage leaks. This paper points out the threat of privacy and the need of security measures in smart device environment by showing that it's possible to identify the appliances and the specific usage patterns of users from the smart meter's data. Learning algorithm PCA is used to reduce the dimension of the feature space and k-NN Classifier to infer appliances and states of them. Accuracy is validated with 10-fold Cross Validation.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.78-78
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• 2015

Metamaterials, artificially structured nanomaterials, have enabled unprecedented phenomena such as invisibility cloaking and negative refraction. Especially, hyperbolic metamaterials also known as indefinite metamaterials have unique dispersion relation where the principal components of its permittivity tensors are not all with the same signs and magnitudes. Such extraordinary dispersion relation results in hyperbolic dispersion relations which lead to a number of interesting phenomena, such as super-resolution effect which transfers evanescent waves to propagating waves at its interface with normal materials and, the propagation of electromagnetic waves with very large wavevectors comparing they are evanescent waves and thus decay quickly in natural materials. In this abstract, I will focus discussing our efforts in achieving the unique optical property overcoming diffraction limit to achieve several extraordinary metamaterials and metadevices demonstration. First, I will present super-resolution imaging device called "hyperlens", which is the first experimental demonstration of near- to far-field imaging at visible light with resolution beyond the diffraction limit in two lateral dimensions. Second, I will show another unique application of metamaterials for miniaturizing optical cavity, a key component to make lasers, into the nanoscale for the first time. It shows the cavity array which successfully captured light in 20nm dimension and show very high figure of merit experimentally. Last, I will discuss the future direction of the hyperbolic metamaterial and outlook for the practical applications. I believe our efforts in sub-wavelength metamaterials having such extraordinary optical properties will lead to further advanced nanophotonics and nanooptics research.

• Journal of the Korean Institute of Navigation
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• v.24 no.3
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• pp.123-132
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• 2000

In order to improve the ship maneuverability, It is important to estimate precisely the hydrodynamic coefficients of added mass forces acting on a ship especially in shallow waters, and simple methods for predicting such hydrodynamic forces Is also very desirable. In the previous paper using 3-Dimension potential flow theory, it has been demonstrated that potential calculation is available to estimate added mass coefficients. The present work is aimed at the suggestion of the simplified formulas for predicting the translation and lateral motion of added mass coefficients in shallow water. So, 3-D potential flow theory is also used to calculate the added mass coefficients in deep and shallow waters for Series 60 model which has 5 different kinds of block coefficients (0.6-0.8), SR196 model and T/S HANNARA. After some series computation, simplified formulas for Predicting the added mass force in shallow waters is suggested based on the computation results of Series 60 model. The formulas consist of the combination of principal dimensions and the water depth; d/B, Cb, d/H. The predicted results are compared with the Computation results for SR196 model and T/S HANNARA. The precision of predicted results by simplified formulas are good enough for the practical use. (d/B : draft-Breadth ratio, d/H draft-Water depth ratio, Cb : Block coefficients).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1439-1446
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• 2011

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2551-2556
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• 2009

The principal operation of a ring laser gyroscope depends on the phase difference for the counter-propagating waves within a closed path. The reflection mirrors mounted on the resonator block form the traveling waves. Thus, the dimension accuracy of resonator block influences the traveling path of beam. In order to maintain the stable optical beam path in the ring resonator, the piezo-driven moveable mirror is adopted for the path length control under the thermal expansion or mechanical strain of resonator block. This paper presents the mathematical description of the elastic behavior of piezo-driven mirror. This description can be applied for the concept design of piezo-driven mirror.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.67-72
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• 2010

This paper presents biometrical driver verification system in car experiment through analysis of speech, and face information. We have used Mel-scale Frequency Cesptral Coefficients (MFCCs) for speaker verification using speech information. For face verification, face region is detected by AdaBoost algorithm and dimension-reduced feature vector is extracted by using principal component analysis only from face region. In this paper, we apply the extracted speech- and face feature vectors to an SVM kernel with Gaussian Mixture Models(GMM) supervector. The experimental results of the proposed approach show a clear improvement compared to a simple GMM or SVM approach.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.8
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• pp.992-999
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• 2011

The recent power add-on drive wheelchairs (PADWs) provide greater physical activity, are easier to transport, and may be an excellent alternative for the typical manual or electric wheelchairs. The development of in-wheel motor for a PADW is the principal issues. In this paper, design, implementation, and testing of the permanent magnet synchronous motor (PMSM) for a PADW are presented. To design output power and torque of the motor, the equation of motion has been investigated. The design parameters were calculated and the dimension and shape of the motor which was limited by the In-wheel mechanism of the PADW were done by applying FEM and optimal design technique. The prototype of the motor mentioned above was fabricated with precise machining and assembling. Then the motor tested on dynamometer and the measured results of the motor were verified by comparing the design results. The fabricated motor was 80 mm in length with a diameter of 110 mm and small enough to be attached the driving unit of the PADW.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1064-1073
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• 2015

In this study, we introduce the pedestrian detection system by using the feature of HOG-PCA and RBFNNs pattern classifier. HOG(Histogram of Oriented Gradient) feature is extracted from input image to identify and recognize a object. And a dimension is reduced for improving performance as well as processing speed by using PCA which is a typical dimensional reduction algorithm. So, the feature of HOG-PCA through the dimensional reduction by using PCA leads to the improvement of the detection rate. FCM clustering algorithm is used instead of gaussian function to apply the characteristic of input data as well and connection weight is used by polynomial expression such as constant, linear, quadratic and modified quadratic. Finally, INRIA person database known as one of the benchmark dataset used for pedestrian detection is applied for the performance evaluation of the proposed classifier. The experimental result of the proposed classifier are compared with those studied by Dalal.