• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.134-143
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• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.

• Korean Journal of Human Ecology
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• v.18 no.4
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• pp.857-867
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• 2009

The purpose of this study was to examine the relationships among principal's transformational and transactional leadership, subjective quality of life of teacher, and organizational commitment of teacher in kindergarten and day care center based on the survey data from 203 teachers working in kindergarten and day care center in Kyoungbuk province. The collected data were analyzed by Simple Regression, Multiple Regression in SPSS Win program(15.0 version). The main results of this study were as follows. First, principal's transformational and transactional leadership each exerted positive effects on teacher's subjective quality of life and organizational commitment. Second, teacher's subjective quality of life had a positive influence on organizational commitment. Finally, each effect of principal's transformational and transactional leadership on teacher's organizational commitment was mediated by teacher's subjective quality of life.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.329-336
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• 2006

In this paper, we propose a method of significant term extraction within a document. The technique used is Principal Component Analysis(PCA) which is one of the multivariate analysis methods. PCA can sufficiently use term-term relationships within a document by term-term correlations. We use a correlation matrix instead of a covariance matrix between terms for performing PCA. We also try to find out thresholds of both the number of components to be selected and correlation coefficients between selected components and terms. The experimental results on 283 Korean newspaper articles show that the condition of the first six components with correlation coefficients of |0.4| is the best for extracting sentence based on the significant selected terms.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.129-135
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• 2005

Representative observations are useful to express explicitly the distributional variation of the data by a few selected observations corresponding to the quantiles in the univariate situation. Jones and Rice(1992) extended it to the multidimensional case by the principal component based method. This study introduces a modified version of Jones and Rice exploiting the self-consistency of principal components in expressing the chosen observation vectors. Compared to that of Jones and Rice, the suggested method tends to provide with less susceptible representative observations to the sampling variation of the data and the resulted vectors benefits from the self-consistency.

• Elastomers and Composites
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• v.38 no.4
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• pp.354-362
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• 2003

The use of a petaloid design for the bottom of carbonated poly(ethylene terephthalate)(PET) bottles is widely spread. This study investigated the causes of bottom cracks. The tensile yield stress variations of PET according to the crystallinity and stretch ratio were examined, then the stretch ratio and strength in the bottom area of a blown bottle were analyzed. A crack test was also performed to observe the cracking phenomena. The distribution of the effective stress and maximum principal stress were both examined using computer simulation to seek the influence of the bottom design on crack. It was concluded that the bottom cracks occurred because of inadequate material strength due to the insufficient stretching of PET, plus the coarse design of a petaloid bottom. The stretch ratio at the bottom during bottle blowing should be higher than the strain hardening point of PET to produce enhanced mechanical strength. The cracks in the bottom of the PET bottles occurred through crazing below the yield stress. The maximum principal stress was higher in the valleys of the petaloid bottom than in the rest bottom area, and the maximum principal stress had a strong effect on the cracks.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.143-154
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• 2017

A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

• Journal of the Korea Concrete Institute
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• v.11 no.4
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• pp.55-62
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• 1999

When stress is beyond elastic limit or cracks occur in a reinforced concrete member subjected to axial force and biaxial bending, curvature about each principal axis of uncracked section is influenced by axial force and bending moments about both major and minor principal axes. It is mainly due to the translation and rotation of principal axes of the cross section after cracking. Recently, by considering these effects, a numerical method predicting the behavior of concrete columns subjected to axial force and biaxial bending was proposed. In this study, in order to verify the proposed numerical method and investigate the effects of cracking on the behavior of reinforced concrete columns, a series of tests were carried out for 16 tied reinforced concrete columns with 100×100 mm square and 200×100 mm rectangular sections under various loading conditions. The angle between the direction of eccentricity and the major principal axis of uncracked section were 0, 30, 40° for the square section and 0, 30, 45, 60, 90° for the rectangular section, respectively. A comparison between numerical predictions and test results shows good agreements in ultimate loads, axial force-lateral deflection relations, and lateral deflection trajectories. It is also found, in this limited investigation, that the ACI's moment magnifier method is conservative in both uniaxial and biaxial loading conditions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.143-151
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• 2015

In this paper, we investigate how the power consumption of a heat pump dryer depends on various factors in the drying process by analyzing variables that affect the power consumption. Since there are in general many variables that affect the power consumption, for a feasible analysis, we utilize the principal component analysis to reduce the number of variables (or dimensionality) to two or three. We find that the first component is correlated positively to the entrance temperature of various devices such as compressor, expander, evaporator, and the second, negatively to condenser. We then model the power consumption as a multiple regression with two and/or three transformed variables of the selected principal components. We find that fitted value from the multiple regression explains 80~90% of the observed value of the power consumption. This results can be applied to a more elaborate control of the power consumption in the heat pump dryer.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.885-893
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• 2015

It is important to improve the forecasting accuracy of one-year-ahead seasonal factors in order to produce seasonally adjusted series of the following year. In this paper, seasonal factors of 8 monthly Korean economic time series are examined and forecast based on the functional principal component regression. One-year-ahead forecasts of seasonal factors from the functional principal component regression are compared with other forecasting methods based on mean absolute error (MAE) and mean absolute percentage error (MAPE). Forecasting seasonal factors via the functional principal component regression performs better than other comparable methods.

• Journal of Mechanical Science and Technology
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• v.19 no.7
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• pp.1432-1440
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• 2005

High-temperature rupture behavior of 5083-Al alloy was tested for failure at 548K under multiaxial stress conditions: uniaxial tension using smooth bar specimens, biaxial shearing using double shear bar specimens, and triaxial tension using notched bar specimens. Rupture times were compared for uniaxial, biaxial, and triaxial stress conditions with respect to the maximum principal stress, the von Mises effective stress, and the principal facet stress. The results indicate that the von Mises effective and principal facet stresses give good correlation for the material investigated, and these parameters can predict creep life data under the multiaxial stress states with the rupture data obtained from specimens under the uniaxial stress. The results suggest that the creep rupture of this alloy under the testing condition is controlled by cavitation coupled with highly localized deformation process, such as grain boundary sliding. It is also conceivable that strain softening controls the highly localized deformation modes which result in cavitation damage in controlling rupture time of this alloy.