• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.963-977
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• 2011

PCA(Principal Component Analysis) is a well-studied statistical technique and an important tool for handling multivariate data. Although many algorithms exist for PCA, most of them are unsuitable for real time applications or high dimensional problems. Since it is desirable to avoid extensive matrix operations in such cases, alternative solutions are required to calculate the eigenvalues and eigenvectors of the sample covariance matrix. Erdogmus et al. (2004) proposed Recursive PCA(RPCA), which is a fast adaptive on-line solution for PCA, based on the first order perturbation theory. It facilitates the real-time implementation of PCA by recursively approximating updated eigenvalues and eigenvectors. However, the performance of the RPCA method becomes questionable as the size of newly-added data increases. In this paper, we modified the RPCA method by taking advantage of the mathematical relation of eigenvalues and eigenvectors of sample covariance matrix. We compared the performance of the proposed algorithm with that of RPCA, and found that the accuracy of the proposed method remarkably improved.

• Speech Sciences
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• v.10 no.4
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• pp.201-219
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• 2003

Background: The perceptual assessment is generally performed by the voice specialist. The objective evaluation is performed in a voice laboratory. Research in voice laboratories has generated a variety of different objective tests and parameters. The perceptual evaluation is one of the most controversial topics in voice research. Review of literature reveals a wide variety of rating scales and reliability data fluctuating from study to study. Unfortunately, there is no widely accepted valid method for classifying voice disorders and assessing outcome after voice treatment. Objectives: The goals of this research were to identify important objective acoustic parameters of vocal quality, and to establish an objective and quantitative correlate of the perceived vocal quality. Materials and Methods : We evaluated the voice analyzed data from 122 dysphonic patients and 20 normal volunteers. A computerized speech lab. 4300B(CSL) was used to carry out the analysis of each voice sample. Results: Three dysphonia severity indices(DSI) were created using discriminant analysis. DSI is based on the weighted combination of the following selected set of acoustic parameters: absolute jitter(Jita in us), smoothed pitch period perturbation (sPPQ in %), amplitude perturbation quotient(APQ in %), soft phonation index(SPI), average fundamental frequency(Fo in Hz), lowest fundamental frequency(Flo in Hz), and smoothed amplitude perturbation quotient(sAPQ in %). The DSI, being the discriminating rule calculated by the logistic regression, consists of three equation based on statistically significant acoustic parameters. Three DSI were created to reflects best the degree of hoarseness as expressed by G from the GRBAS scale. The more positive this DSI is for a patient, the worse the vocal quality. The more it is negative, the better it is. The effect of sex is included implicitly in the DSI-1 and DSI-2, so that a separate DSI-1 and DSI-2 for males and females need not be used. The DSI is objective because no perceptual input is required for its calculation. Conculsion : This research demonstrates that the voice function values calculated from three different multivariate objective dysphonia severity indices are significantly associated with subjective voice assessments. These multivariate objective dysphonia severity indices may be appropriate for use in clinical trials and outcomes research on treatment effectiveness for voice disorders.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.675-680
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• 2016

The development of various mobile devices and mobile platform technology has led to a steady increase in the number of online social network (OSN) users. OSN users are free to communicate and share information through activities such as social networking, but this causes a new, user privacy issue. Various distributed OSN architectures are introduced to address the user privacy concern, however, users do not obtain technically perfect control over their data. In this study, the control rights of OSN user are maintained by using personal data storage (PDS). We propose a technique to improve data privacy protection that involves making a group with the user's friend by generating and providing fake text data based on user's real text data. Fake text data is generated based on the user's word sensitivity value, so that the user's friends can receive the user's differential data. As a result, we propose a system architecture that solves possible problems in the tradeoff between service utility and user privacy in OSN.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.127-134
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• 1997

A method is proposed for the choice of the number of principal components in principal component regression based on the predicted error sum of squares. To do this, we approximately evaluate that statistic using a linear approximation based on the perturbation expansion. In this paper, we apply the proposed method to various data sets and discuss some properties in choosing the number of principal components in principal component regression.

• Journal of the Korean Magnetic Resonance Society
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• v.22 no.3
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• pp.46-53
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• 2018

NMR-based metabolomics needs various knowledge to elucidate metabolic perturbation such as NMR experiments, NMR spectrum processing, raw data processing, metabolite identification, statistical analysis, and metabolic pathway analysis regarding technical aspects. Among them, some concepts of raw data processing and multivariate analysis are not easy to understand but are important to correctly interpret metabolic profile. This article introduces NMR spectrum processing, raw data processing, and multivariate analysis.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.163-172
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• 1999

We propose a cross-validatory method for the choice of the number of principal components in principal component regression based on the magnitudes of correlations with y. There are two different manners in choosing principal components, one is the order of eigenvalues(Shin and Moon, 1997) and the other is that of correlations with y. We apply our method to various data sets and compare results of those two methods.

• Journal of KSNVE
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• v.8 no.6
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• pp.1069-1077
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• 1998

A dynamic model of turbo compressor having helical gear pairs is developed. The model accounts for the shaft and bearing flexibilities, gyroscopic effects and the force couplings among the transverse, torsion. and axial motions due to gearings. For the mode analysis of turbo compressor, a transfer matrix method is used. The excitation sources caused by the mass unbalances of the rotors and misalignment of the shafts, the transmitted errors of the gearings. and the vane passing frequencies of the Impeller are studied qualitatively. By introducing the perturbation method, the generated forcing frequencies are defined and devided into three groups. With the field data, two critical speeds are analytically found and the corresponding modal characteristics are examined.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.3
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• pp.398-404
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• 2013

The simulation of the ballistic trajectory of penetrator into the spaced multi-layer RC targets is very important to predict the hitting condition in subsequent target. Because of perturbation by lateral load of penetrator caused by asymmetric hitting position between penetrator and steel bar reinforcement, penetrator rotates and deviates from the straight path. Therefore, penetration capability of penetrator is decreased in the subsequent targets. This paper presents the result of the penetration of steel-bar-reinforced concrete target by using the explicit finite element code LS-DYNA. A series of computations is performed and compared to experimental data and the computed results are in good agreement with the experimental results over a wide range of velocities. And then we conduct the simulation according to various RC target hitting condition and impact velocities.

• Journal of Astronomy and Space Sciences
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• v.30 no.1
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• pp.33-41
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• 2013

Various features of the existing perturbations in the Earth's spin rotation are investigated for the recent and most reliable data by spectral analysis, filtering, and comparison with idealized model. First, theory of Earth's spin rotational perturbation is briefly re-derived in the Earth-fixed coordinate frame. By spectral windowings, different periodic components of the length of day perturbation are separated, and their characters and excitations are discussed. Different periodic components of polar motion are acquired similarly and described with further discussion of their excitations. Causes of the long time trends of both the length of day and polar motion are discussed. Three possible causes are considered for the newly discovered 490-day period component in the polar motion.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.112-115
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• 2001

Eigenvalue perturbation theory of augmented system matrix(AMEP) is a useful tool in the analysis and design of large scale power systems. This paper describes the application results of AMEP algorithm with respect to all controller parameter of KEPCO systems. AMEP for interarea and local mode can be used for turning controller parameter, and verifying system data and linear model of controller.