• Kyungpook Mathematical Journal
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• v.48 no.2
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• pp.241-254
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• 2008

We define the crosscap number of a 2-component link as the minimum of the first Betti numbers of connected, non-orientable surfaces bounding the link. We discuss some properties of the crosscap numbers of 2-component links.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.390-395
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• 2005

Sunspots are dark areas that grow and decay on the lowest level of the sun that is visible from the Earth. Shot-term predictions of solar activity are essential to help plan missions and to design satellites that will survive for their useful lifetimes. This paper presents a parallel-structure fuzzy system(PSFS) for prediction of sunspot number time series. The PSFS consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedding dimension determines the number of inputs of each component fuzzy system and a time delay decides the interval of inputs of the time series. According to the embedding dimension and the time delay, the component fuzzy system takes various input-output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems in order to reduce error accumulation effect.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.8
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• pp.2572-2592
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• 1996

A low-Reynolds-number second moment turbulence closure was developed with the aid of DNS data. Model coefficients of nonlinear return to isotropy term were derived by use of Cayley-Hamilton theorem and two component turbulence limit condition as the functions of invariances of anisotropy and turbulent Reynolds number. Launder and Tselepidakis' cubic mean pressure strain model was modified to fit the predicted pressure-strain components to the DNS data. Two component turbulence limit condition was the precondition to be satisfied in developing the second moment turbulence closure for the realizable Reynolds stress prediction. But the satisfactions of Reynolds stress level and pressure-strain level of each component were compromised because the satisfaction of both levels was impossible.

• Journal of the Korean Applied Science and Technology
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• v.22 no.3
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• pp.241-249
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• 2005

This experiment extracted the natural green-tea using ethanol and obtained the refined oil component after filterated green-tea extract. This study tested the antimicrobial effect as characteristics experiment, and analyzed refined oil component with pH-meter and GC/MS. In the result of this experiment, it obtained the next conclusions. In the first result of extraction experiment, it could know that extraction ratio of refined oil component appeared about 9.0%. In the second result of characteristics experiment, it could certificate that in case of increasing the refined oil component in concentration of 100ppm and above, and according to passage of cultivation time, the number of S-aureus and E-coli in microbe decreased less and less. But in case of blank test not adding the refined oil component, the number of microbe increased more and more. In these phenomena, it could certificate that refined oil component of green-tea appeared antimicrobial effect against microbe. In the third result of instrumental analysis, refined oil component of green-tea appeared about 7.6 in 1% distilled water solution with pH-meter, and the aromatic components of benzene, bonyl acetate, campene, ${\alpha},{\beta},{\gamma}$-pinnene etcs from refined oil component of green-tea was detected with GC/MS.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.387-395
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• 2000

Circular consecutive-k-out-of-n:F system when the failure of component is dependent is studied. We assume that the failure of a component in the system increase the failure rate of the survivor which is working just before the failed component. In this case, a mean time to failure (MTTF), a average failure number of the system, and the expected cost per unit time are obtained. Then the minimum number of consecutive failed components to cause system failure to minimize the expected cost per unit time is determined as searching paths to system failure. And various numerical examples are studied.

• 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 Korean Institute of Industrial Engineers
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• v.26 no.2
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• pp.128-135
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• 2000

This paper considers a consecutive k-out-of-n:F system when the failure of a component in the system induces higher failure rate of the preceding survivor. The reliability, mean time to failure(MTTF), and average failure number of a consecutive k-out-of-n:F system are obtained, when the failure of a component increases the failure rate of the survivor which is working just before the failed component. Then the optimal number of consecutive failed components to minimize this long run average cost rate can be obtained. An example is considered to calculate the reliability, MTTF and average failure number of the system. And two procedures that find the optimal number of consecutive failed components are studied. Then, various cases of system parameters are also studied.

• Journal of the military operations research society of Korea
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• v.7 no.2
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• pp.43-62
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• 1981

Computational expressions for point availability and average availability of a system of components each of which is subject to random failures and has random restoration times are determined. Each component is assumed to have a fixed number of spares such that where all spares are exhausted no restoration can take place. These expressions are useful in deciding PL and ASL in the military logistic applications. Given a fixed length of mission duration and finite number of spares, a system may not be available at the end of a mission due to lack of spares. The probability distribution of system down time due to lack of spares is determined as a function of number of spares and mission duration.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.307-316
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• 2004

Principal Component Regression(PCR) and Partial Least Squares Regression(PLSR) are the two most popular regression techniques in chemometrics. In the field of chemometrics usually the number of regressor variables greatly exceeds the number of observation. So we have to reduce the number of regressors to avoid the identifiability problem. In this paper we compare PCR and PLSR techniques combined with various robust regression methods including regression depth estimation. We compare the efficiency, goodness-of-fit and robustness of each estimators under several contamination schemes.