• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.1982-1989
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• 2004

In photoelasticity, the directions of principal stresses are given by isoclinic fringe patterns. In this study, photoelastic theory is represented by Jones calculus and the photoelastic 8-step phase shifting method is described. A feasibility study using computer simulation is done to get isoclinics from photoelastic fringes of a circular disk under diametral compression. Fringe patterns of the disk are generated from the stress-optic law. The magnitudes of isoclinics obtained from the fringe patterns of computer simulation and experiment are compared with those of theory. The results are close between them. Then, the 8-step phase shifting method is applied to get distributions of isoclinics along the specified lines of a cuved beam plate under tensile load. Experimental results obtained from the phase shifting method were compared with those of finite element analysis (ANSYS). It is confirmed that measurement of isoclinic distributions is possible by use of photoelasitc phase shifting method.

• ETRI Journal
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• v.32 no.5
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• pp.831-834
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• 2010

This paper proposes a new joint channel coding algorithm based on principal component analysis. A conventional joint channel coder using passive downmixing undergoes a reduction of both the primary-to-ambient energy ratio (PAR) of the downmix signal and the panning gain ratio of the primary source. The proposed system preserves the PAR of the downmix signal by using active downmixing which reflects spatial characteristic. The proposed system also improves the accuracy of the panning gain ratio estimation. Computer simulations and subjective listening tests verify the performance of the proposed system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.3
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• pp.352-357
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• 2008

We present a space-time trellis coded OFDM system in slow fading channels. Generalized principal ratio combining (GPRC) is also analyzed theoretically in frequency domain. The analysis shows that the decoding metric of GPRC includes the metrics of maximum likelihood(ML) and PRC. The computer simulations with M-PSK modulation are obtained in frequency flat and frequency selective fading channels. The decoding complexity and simulation running times are also evaluated among the decoding schemes.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.21-26
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• 2018

As the large amount of data can be efficiently stored, the methods extracting meaningful features from big data has become important. Especially, the techniques of converting high- to low-dimensional data are crucial for the 'Data visualization'. In this study, principal component analysis (PCA; linear dimensionality reduction technique) and Isomap (non-linear dimensionality reduction technique) are introduced and applied to neural big data obtained by the functional magnetic resonance imaging (fMRI). First, we investigate how much the physical properties of stimuli are maintained after the dimensionality reduction processes. We moreover compared the amount of residual variance to quantitatively compare the amount of information that was not explained. As result, the dimensionality reduction using Isomap contains more information than the principal component analysis. Our results demonstrate that it is necessary to consider not only linear but also nonlinear characteristics in the big data analysis.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.49-56
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• 2014

In this paper, we propose a method for identifying hidden principal sentiments among large scale texts from documents, social data, internet and blogs by analyzing standard language, slangs, argots, abbreviations and emoticons in those words. The IRLBA(Implicitly Restarted Lanczos Bidiagonalization Algorithm) is used for principal component analysis with large scale sparse matrix. The proposed system consists of data acquisition, message analysis, sentiment evaluation, sentiment analysis and integration and result visualization modules. The suggested approaches would help to improve the accuracy and expand the application scope of sentiment analysis in social data.

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.113-118
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• 1996

Principal component analysis(PCA) is an essential technique for data compression and feature extraction, and has been widely used in statistical data analysis, communication theory, pattern recognition, and image processing. Oja(1992) found that a linear neuron with constrained Hebbian learning rule can extract the principal component by using stochastic gradient ascent method. In practice real data often contain some outliers. These outliers will significantly deteriorate the performances of the PCA algorithms. In order to make PCA robust, Xu & Yuille(1995) applied statistical physics to the problem of robust principal component analysis(RPCA). Devlin et.al(1981) obtained principal components by using techniques such as M-estimation. The propose of this paper is to investigate from the statistical point of view how Xu & Yuille's(1995) RPCA works under the same simulation condition as in Devlin et.al(1981).

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.598-600
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• 2001

DNA chip technology enables us to monitor thousands of gene expressions per sample simultaneously. Typically, DNA microarray data has at least several thousands of variables (genes) wish relatively smal1 number of samples. Thus feature (gene) selection by dimensionality reduction is necessary for efficient data analysis. In this paper we employ the partial least squares (PLS) method for gene selection and the principal component analysis (PCA) method for classification. The useful behavior of the PLS is verified by computer simulations.

• Journal of KIISE:Software and Applications
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• v.29 no.10
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• pp.747-754
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• 2002

In this paper, We propose a document thematic words extraction by using principal component analysis(PCA) which is one of the multivariate statistical methods. The proposed PCA model understands the flow of words in the document by using an eigenvalue and an eigenvector, and extracts thematic words. The proposed model is estimated by applying to document summarization. Experimental results using newspaper articles show that the proposed model is superior to the model using either word frequency or information retrieval thesaurus. We expect that the Proposed model can be applied to information retrieval , information extraction and document summarization.

• Food Science and Biotechnology
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• v.14 no.4
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• pp.554-557
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• 2005

As a device for taste sensation, an 8-channel taste evaluation system was prepared and applied for discriminant analysis of marketed liquor. The biomimetic polymer membranes for the system were prepared through a casting procedure by employing polyvinyl chloride, bis (2-ethylhexyl)sebacate as plasticizer and electroactive materials such as valinomycin in the ratio of 33:66:1, and were separately attached over the sensitive area of ion-selective electrodes to construct the corresponding taste sensor array. The sensor array in conjunction with a double junction reference electrode was connected to a high-input impedance amplifier and the amplified sensor signals were interfaced to a personal computer via an A/D converter. When the signal data from the sensor array for 3 groups of marketed liquor like Maesilju, Soju and beer were analyzed by principal component analysis after normalization, it was observed that the 1st, 2nd and 3rd principal component were responsible for most of the total data variance, and the analyzed liquor samples were discriminated well in 2 dimensional principal component planes composed of the 1st-2nd and the 1st-3rd principal component.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.154-157
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• 2001

Through this study we investigated the causes of bottom crack. We then redesigned petaloid bottom to prevent bottom crack. We examined the material property variations according to the stretch ratio of PET and analyzed stretches of bottom in blowing processes. We also performed crack test to observe a crack phenomena. The effective stress and maximum principal stress were examined by computer simulation. We concluded that the bottom crack occurs because of not only insufficient strength of material due to the insufficient stretch of PET but also coarse design of petaloid shape. The highest maximum principal stress occurred at valley in petaloid bottom of bottle and this strongly affected the crack in bottom. We redesigned petaloid shape to minimize maximum principal stress, and this result in increasing the crack resistance.