• Mycobiology
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• v.45 no.2
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• pp.97-100
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• 2017

Endangered native plant habitats and populations are rapidly disappearing because of climate and environmental changes. As a representative, the abundance of the first-class endangered wild plant, Cypripedium japonicum, has been rapidly decreasing in Korea. The purpose of this study was to evaluate the distribution of rhizosphere and endophytic fungi on C. japonicum in its native habitat. A total of 440 rhizosphere and 79 endosphere fungi isolates were isolated and identified on the basis of their molecular characteristics. Sixty-five genera and 119 fungi species were identified in this study. The genus Trichoderma showed the highest abundance among both rhizosphere and endosphere fungi. Mortierella, Hypocrea, and Penicillium spp. were also relatively dominant species on C. japonicum. The community structures of rhizosphere and endosphere fungi were similar, but endosphere fungi showed greater diversity.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.744-746
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• 2003

A ZnO varistor with reference voltage 250V/mm was fabricated through the control of particle size in slurry and the variation of sintering conditions. It was found that to measure the flatness of the V-I characteristic curve in the small-current region and the flatness of the V-I characteristic curve in a large-current region was improved nonlinearity of the fabricated ZnO varistor. According to the IEC 60099-4 was measured the accelerated aging test and high current test of the distribution class surge varistor which is excellent in respect to the property of ZnO varistor.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.543-546
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• 1996

Recently, some research has been done to analyze the asymptotic behavior of queue length distribution in ATM (Asynchronous Transfer Mode) multiplexer. In this paper, we relate this asymptotic behavior with the asymptotic behavior of decreasing cell loss probability when the buffer capacity is increased. We find with reasonable assumptions that the asymptotic rate of queue length distribution is the same as that of decreasing cell loss probability. Even under different priority control schemes and traffic classes, we find that this asymptotic rate of the individual cell loss probability of each traffic class does not change. As a consequence, we propose the upper bound of cell loss probability of each traffic class when a priority control scheme is employed. This bound is computationally feasible in a real-time. The numerical examples will be provided to validate this finding.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1027-1039
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• 2005

Consider the problem of estimating a $p{\times}1$ mean vector $\theta(p\geq4)$ under the quadratic loss, based on a sample $X_1$, $X_2$, $\cdots$, $X_n$. We find a Lindley type decision rule which shrinks the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $\parallel\;{\theta}-\bar{{\theta}}1\;{\parallel}$ is restricted to a known interval, where $bar{{\theta}}=\frac{1}{p}\;\sum\limits_{i=1}^{p}{\theta}_i$ and 1 is the column vector of ones. In this case, we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.999-1004
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• 2015

In this paper, the study presents the development of 34kW class cryogenic induction motor using LNG Pump. Operating temperature of an induction motor using LNG Main Cargo Pump is at −163℃. Due to variation of the resistivity, these motor have different torque characteristics. So, it should design to considering the resistivity change. The most important consideration of induction machine operating is cryogenic temperature. If the temperature rise, LNG is vaporized. it is a major cause of pump failure. There are several causes of heat source like coreloss, hysterisysloss, copperloss. This paper analyzed the thermal distribution of the induction motor at rated speed operation.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.381-384
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• 2004

The goal of this study is to generate a landslide susceptibility map using GIS(geographic information system) based method. A simple and efficient algorithm is proposed to generate a landslide susceptibility map from DEM(digital elevation model) and existing maps. The categories of controlling factors for landslides, aspect of slope, soil, topographical index, landuse, vegetation are defined, because those factors are said to have relevance to landslide and are easy to obtain theirs sources. The weight value for landslide susceptibility is calculated from the density of the area of landslide blocks in each class. Finally, a map of susceptibility zones is produced using the weight value of all controlling factors, and then each susceptibility zone is evaluated by comparing with the distribution of each controlling factor class.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.1-9
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• 2014

Let X and $X_t$ denote the lifetime and the residual life at age t, respectively. X is said to be a NBUL (new better than used in Laplace transform order) random variable if $X_t$ is smaller than X in Laplace order, i.e., $X_t{\leq}_{LT}X$. We propose a new test statistics for testing exponentiality versus NBUL class of life distribution. The tests by Hollender and Proschan (1975) and the generalized Hollender and Proschan test by Ains and Mitra (2011) are considered as special cases of the our of test statistics. Our proposed test statistics is simple, consistent and asymptotically normal. Efficiency and powers of the test statistics for some commonly used distributions in reliability are discussed. Finally, real examples are presented to illustrate the theoretical results.

• Journal of Integrative Natural Science
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• v.10 no.1
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• pp.33-39
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• 2017

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-q{\geq}3)$, $q=rank(P_V)$ with a projection matrix $P_v$ under the quadratic loss, based on a sample $X_1$, $X_2$, ${\cdots}$, $X_n$. We find a James-Stein type decision rule which shrinks towards projection vector when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}{\theta}-P_V{\theta}{\parallel}$ is restricted to a known interval, where $P_V$ is an idempotent and projection matrix and rank $(P_V)=q$. In this case, we characterize a minimal complete class within the class of James-Stein type decision rules. We also characterize the subclass of James-Stein type decision rules that dominate the sample mean.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1670-1673
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• 2002

For pattern recognition on high-dimensional data, such as images, the dimensionality reduction as a preprocessing is effective. By dimensionality reduction, we can (1) reduce storage capacity or amount of calculation, and (2) avoid "the curse of dimensionality" and improve classification performance. Popular tools for dimensionality reduction are Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Independent Component Analysis (ICA) recently. Among them, only LDA takes the class labels into consideration. Nevertheless, it, has been reported that, the classification performance with ICA is better than that with LDA because LDA has restriction on the number of dimensions after reduction. To overcome this dilemma, we propose a new dimensionality reduction technique based on an information theoretic measure for difference of distribution. It takes the class labels into consideration and still it does not, have restriction on number of dimensions after reduction. Improvement of classification performance has been confirmed experimentally.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.258-267
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• 2013

New incremental learning algorithm using extended data expression, based on probabilistic compounding, is presented in this paper. Incremental learning algorithm generates an ensemble of weak classifiers and compounds these classifiers to a strong classifier, using a weighted majority voting, to improve classification performance. We introduce new probabilistic weighted majority voting founded on extended data expression. In this case class distribution of the output is used to compound classifiers. UChoo, a decision tree classifier for extended data expression, is used as a base classifier, as it allows obtaining extended output expression that defines class distribution of the output. Extended data expression and UChoo classifier are powerful techniques in classification and rule refinement problem. In this paper extended data expression is applied to obtain probabilistic results with probabilistic majority voting. To show performance advantages, new algorithm is compared with Learn++, an incremental ensemble-based algorithm.