• Publications of The Korean Astronomical Society
• /
• v.32 no.1
• /
• pp.209-211
• /
• 2017

We performed Principle Component Analysis (PCA) over 264 galaxies in the IRAS Revised Bright Galaxy Sample (Sanders et al., 2003) using 12, 25, 60 and $100{\mu}m$ flux data observed by IRAS and 9, 18, 65, 90 and $140{\mu}m$ flux data observed by AKARI. We found that (i)the first principle component was largely contributed by infrared to visible flux ratio, (ii)the second principal component was largely contributed by the flux ratio between IRAS and AKARI, (iii)the third principle component was largely contributed by infrared colors.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.9
• /
• pp.1547-1553
• /
• 2008

This paper presents a method that generates various facial expressions of vector graphic character by using the simplified principle component vector. First, we analyze principle components to the nine facial expression(astonished, delighted, etc.) redefined based on Russell's internal emotion state. From this, we find principle component vector having the biggest effect on the character's facial feature and expression and generate the facial expression by using that. Also we create natural intermediate characters and expressions by interpolating weighting values to character's feature and expression. We can save memory space considerably, and create intermediate expressions with a small computation. Hence the performance of character generation system can be considerably improved in web, mobile service and game that real time control is required.

• Structural Engineering and Mechanics
• /
• v.54 no.2
• /
• pp.379-392
• /
• 2015

A number of acceleration-based damage detection methods have been developed but they have not been widely applied in engineering practices because the acceleration response is insensitive to minor damage of civil structures. In this article, a damage detection approach using the long-gauge strain sensing technology and the principle component analysis technology is proposed. The Long gauge FBG sensor has its special merit for damage detection by measuring the averaged strain over a long-gauge length, and it can be connected each other to make a distributed sensor network for monitoring the large-scale civil infrastructure. A new damage index is defined by performing the principle component analyses of the long-gauge strains measured from the intact and damaged structures respectively. Advantages of the long gauge sensing and the principle component analysis technologies guarantee the effectiveness for structural damage localization. Examples of a simple supported beam and a steel stringer bridge have been investigated to illustrate the successful applications of the proposed method for structural damage detection.

• Proceedings of the Korea Contents Association Conference
• /
• 2003.11a
• /
• pp.213-217
• /
• 2003

In this paper, we analysize the noise robustness of MLPs(Multilayer perceptrons). Also, as a preprocessing stage of MLPs to improve noise robustness, we consider the ICA(independent component analysis) and PCA(principle component analysis). After analyzing the noise redunction effect using PCA or ICA, we verify the noise robustness of MLPs through handwritten-digit recognition simulations.

• Korean Journal of Applied Biomechanics
• /
• v.25 no.2
• /
• pp.157-165
• /
• 2015

Object : The goals of this research were to make Performance Enhanced Model(PE) taken the largest performance index (PI) through artificial variation of principle components calculated by principle component analysis for trial data, and to verify the effect through comparing kinematic factors between trial data (Raw) and PE. Method : Ten subjects (5 men, 5 women) were recruited and 80% of their maximal record was considered. The PI is a regression equation. In order to develop PE, we extracted Principle components from trial position data (by Principle Components Analysis (PCA)). Before PCA, we made 17 position data to 3 row matrix according to components. We calculated 3 eigen value (principle components) through PCA. And except Y (medial-lateral direction) component (because motion of Y component is small), principle components of X (anterior-posterior direction) and Z (vertical direction) components were changed as following. Changed principle components = principle components + principle components ${\times}$ k. After changing the each principle component, we reconstructed position data using the changed principle components and calculated performance index (PI). A Paired t-test was used to compare Raw data and Performance Enhanced Model data. The level of statistical significance was set at $p{\leq}0.05$. Result : The PI was significantly increased about 12.9kg at PE ($101.92{\pm}6.25$) when compared to the Raw data ($91.29{\pm}7.10$). It means that performance can be increased by optimizing 3D positions. The difference of kinematic factors as follows : the movement distance of the bar from start to lock out was significantly larger (about 1cm) for PE, the width of anterior-posterior bar position in full phase was significantly wider (about 1.3cm) for PE and the horizontal displacement toward the weightlifter after beginning of descent from maximal height was significantly greater (about 0.4cm) for PE. Additionally, the minimum knee angle in the 2-pull phase was significantly smaller (approximately 2.7cm) for the PE compared to that of the Raw. PE was decided at proximal position from the Raw (origin point (0,0)) of PC variation). Conclusion : PI was decided at proximal position from the Raw (origin point (0,0)) of PC variation). This means that Performance Enhanced Model was decided by similar motion to the Raw without a great change. Therefore, weightlifters could be accept Performance Enhanced Model easily, comfortably and without large stress. The Performance Enhance Model can provide training direction for athletes to improve their weightlifting records.

• International Commerce and Information Review
• /
• v.12 no.4
• /
• pp.279-302
• /
• 2010

A better selection model on management innovative enterprises is needed since the Korean government provides multi benefits to those selected enterprises. However, the selection model's propriety is suspicious because of the shortage of consideration of assessment items. In particular, the most important two assessment items, strategy and performance are suspected of multicollinearity because of high correlation scores. No consideration on multicollinearity among those items leads to erroneous selection which doubly counts the same components with different item names. The principle component analysis is applied to factor out the uncorrelated items. Using the resulted principle components, the new estimations are carried out. The comparison between estimated results from using principle components and non principle components shows that the present selection model overly considers the performance items compared to the real effect of items, which is a result of multicollinearity between performance and strategy.

• International Journal of Advanced Culture Technology
• /
• v.6 no.3
• /
• pp.142-150
• /
• 2018

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the edge orientation histogram and principle component analysis. By using the detected object region as a recognition input image, in this paper the object recognition method combined with principle component analysis and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input object image, this method computes the eigenspace through principle component analysis and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the object recognition is performed by inputting the multi-layer neural network.

• Journal of Pharmacopuncture
• /
• v.15 no.4
• /
• pp.42-51
• /
• 2012

Objectives: This study used the basic principle of Oriental medicine, the sovereign, minister, assistant and courier principle (君臣佐使論) to investigate the effects of the component of ONGABO, which is composed of Ginseng Radix (Red Ginseng), Angelica Gigantis Radix, Schisandrae Fructus, Cuscuta Semen and Curcumae tuber on the viability of HepG2 cells. Methods: Single and mixed extracts of the component of ONGABO were prepared by lypohilizing powder of Red Ginseng (6-year root from Kanghwa), Angelica Gigantis Radix, Schisandrae Fructus, Cuscuta Semen, Curcumae Tuber (from Omniherb Co., Ltd., Korea) at the laboratory of herbal medicine in Woosuk University and were eluted after being macerated with 100% ethanol for three days. The cell viability of HepG2 was determined by using an absorptiometric analysis with PrestoBlue (Invitrogen) reagent after the plate had been incubated for 48 hours. All of the experiments were repeated three times to obtain the average value and standard deviation. The statistical analysis was done and the correlation factor was obtained by using Microsoft Office Excel 2007 and Origin 6.0 software. Results: Although Ginseng Radix (Red Ginseng) and Schisandrae Fructus did not enhance the viability of HepG2 cells, they were shown to provide protection of those cells. On the other hand, Angelica Gigantis Radix decreased the viability of HepG2 cells significantly, Cuscuta Semen and Curcumae Tuber had a small or no effect on the viability of HepG2 cells. Conclusions: In the sovereign, minister, assistant and courier principle (君臣佐使論), Ginseng Radix (Red Ginseng) corresponds to the sovereign component because it provides cell protection effects, Angelica Gigantis Radix corresponds to minister medicinal because it kills cells, Schisandrae Fructus corresponds to the assistant medicinal to help red ginseng having cell protect effects. Cuscuta Semen and Curcumae Tuber correspond to the courier medicinal having no effect in cell viability in HepG2. We hope this study provides motivation for advanced research on the sovereign, minister, assistant and courier principle.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.1C
• /
• pp.65-71
• /
• 2004

We improved the MLLR speaker adaptation algorithm with reduction of the order of HMM parameters using PCA(Principle Component Analysis) or ICA(Independent Component Analysis). To find a smaller set of variables with less redundancy, we adapt PCA(principal component analysis) and ICA(independent component analysis) that would give as good a representation as possible, minimize the correlations between data elements, and remove the axis with less covariance or higher-order statistical independencies. Ordinary MLLR algorithm needs more than 30 seconds adaptation data to represent higher word recognition rate of SD(Speaker Dependent) models than of SI(Speaker Independent) models, whereas proposed algorithm needs just more than 10 seconds adaptation data. 10 components for ICA and PCA represent similar performance with 36 components for ordinary MLLR framework. So, compared with ordinary MLLR algorithm, the amount of total computation requested in speaker adaptation is reduced by about 1/167 in proposed MLLR algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.2
• /
• pp.99-107
• /
• 2009

This paper presents an enhanced hybrid model based on Independent Component Analysis(ICA) in order to features of numeric characters in license plates. ICA which is used only in high dimensional statistical features doesn't consider statistical features in low dimension and correlation between numeric characters. To overcome the drawbacks of ICA, we propose an improved ICA with the hybrid model using both Principle Component Analysis(PCA) and Linear Discriminant Analysis(LDA). Experiment results show that the proposed model has a superior performance in feature extraction and recognition compared with ICA only as well as other hybrid models.