• The Journal of Natural Sciences
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• v.18 no.1
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• pp.91-97
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• 2007

The Korean name "Bizooki" tree was named by the shape of winter bud which is like a slim bow. There are four scientific names in the tree which are Cleyera japonica Thunberg, Cleyera ochnacea DC, Sakakia ochnacea Nakai, and Ternstroemia gymnanthera. And the English name are Japanese Ternstroemia and Japanese Cleyera. "Bizooki" tree has planted at Buddhist temples in Japan for the ritual. The best result of stem cutting in "Bizooki" tree, 100 percent of rooting, could be accomplished in July when cuttings were done on the mixture-soil containing the same rates by volume of vermiculite, peatmoss and perlite with cuts processed with IBA 1,000 mg/l under the circumstances that 70% of shade, plastic mulching, and mist were conditioned.

• Kyungpook Mathematical Journal
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• v.22 no.1
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• pp.113-115
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• 1982

• Journal of Life Science
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• v.9 no.2
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• pp.176-181
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• 1999

In order to understand molecular phylogenetics of silkworm (Bombyx mori), we analyzed the sequences of BmoMAR isolated from Bomhyx mori that is partial coding gene of transposase of mariner-like element(MLE). By pairwise comparing nucleotide sequences of BmoMAR with ten previously reported insect MLEs accessed in GeneBank, the average genetic distance was estimated to be 0.4840. The phylogenetics tree constructed from nine insect species except for human MLE(Hsmarl) by UPGMA method indicated that MLEs are divided into three clusters, and Drosophila mariutiana was independently subgrouped. Bombyx mori(BmoMAR) was subgrouped with microcaddishfly (Orthotrichia cristata), webworm(Atteva punctella), almond moth(Ephestia cautella), Hyalopora cecropia which we lepidoptera. Phylogenetics tree according to UPGMA principle, on the basis of informative nucleotide sequences of nine insect MLEs, indicated that Bombyx mori was more closely related to microcaddishfly(Orthotrichia cristata) and webworm (Atteva punctella) of lepidoptera. We suggest that insect MLEs are a useful key for studying molecular phylogenetics among intra species of insects.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.208-212
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• 1998

This paper suggests the method to recognize the various defect patterns of cold mill strip using binary decision tree constructed by genetic algorithm automatically. In case of classifying the complex the complex patterns with high similarity like the defect patterns of cold mill strip, the selection of the optimal feature set and the structure of recognizer is important for high recognition rate. In this paper genetic algorithm is used to select a subset of the suitable features at each node in binary decision tree. The feature subset of maximum fitness is chosen and the patterns are classified into two classes by linear decision function. After this process is repeated at each node until all the patterns are classified respectively into individual classes. In this way , binary decision tree classifier is constructed automatically. After construction binary decision tree, the final recognizer is accomplished by the learning process of neural network using a set of standard p tterns at each node. In this paper, binary decision tree classifier is applied to recognition of the defect patterns of cold mill strip and the experimental results are given to show the usefulness of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.98-103
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• 2000

This paper suggests a method to recognize the various defect patterns of a cold mill strip using a binary decision tree automatically constructed by a genetic algorithm(GA). In classifying complex patterns with high similarity like the defect patterns of a cold mill stirp, the selection of an optimal feature set and an appropriate recognizer is important to achieve high recognition rate. In this paper a GA is used to select a subset of the suitable features at each node in the binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes using a linear decision function. This process is repeated at each node until all the patterns are classified into individual classes. In this way, the classifier using the binary decision tree is constructed automatically. After constructing the binary decision tree, the final recognizer is accomplished by having neural network learning sits of standard patterns at each node. In this paper, the classifier using the binary decision tree is applied to the recognition of defect patterns of a cold mill strip, and the experimental results are given to demonstrate the usefulness of the proposed scheme.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.169-181
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• 2008

Because moving objects usually move on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. But, because FNR-tree and MON-tree are stored by the unit of the moving object's segment, they can't support the whole moving objects' trajectory. In this paper, we propose an efficient trajectory index structure, named Trajectory of Moving objects on Network Tree(TMN Tree), for moving objects. For this, we divide moving object data into spatial and temporal attribute, and preserve moving objects' trajectory. Then, we design index structure which supports not only range query but trajectory query. In addition, we divide user queries into spatio-temporal area based trajectory query, similar-trajectory query, and k-nearest neighbor query. We propose query processing algorithms to support them. Finally, we show that our trajectory index structure outperforms existing tree structures like FNR-Tree and MON-Tree.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.840-849
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• 2013

This paper presents a statistical approach to analyze electrical tree inception voltage, electrical tree breakdown voltage and tree breakdown time of unsaturated polyester resin subjected to AC voltage. The aim of this work was to show that Weibull and lognormal distribution may not be the most suitable distributions for analysis of electrical treeing data. In this paper, an investigation of statistical distributions of electrical tree inception voltage, electrical tree breakdown voltage and breakdown time data was performed on 108 leaf-like specimen samples. Revelations from the test results showed that Johnson SB distribution is the best fit for electrical tree inception voltage and tree breakdown time data while electrical tree breakdown voltage data is best suited with Wakeby distribution. The fitting step was performed by means of Anderson-Darling (AD) Goodness-of-fit test (GOF). Based on the fitting results of tree inception voltage, tree breakdown time and tree breakdown voltage data, Johnson SB and Wakeby exhibit the lowest error value respectively compared to Weibull and lognormal.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.157-159
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• 2007

The conventional hard disk has been the dominant database storage system for over 25 years. Recently, hybrid systems which incorporate the advantages of flash memory into the conventional hard disks are considered to be the next dominant storage systems to support databases for desktops and server computers. Their features are satisfying the requirements like enhanced data I/O, energy consumption and reduced boot time, and they are sufficient to hybrid storage systems as major database storages. However, we need to improve traditional index node management schemes based on B-Tree due to the relatively slow characteristics of hard disk operations, as compared to flash memory. In order to achieve this goal, we propose a new index node management scheme called FNC-Tree. FNC-Tree-based index node management enhanced search and update performance by caching data objects in unused free area of flash leaf nodes to reduce slow hard disk I/Os in index access processes.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.696-703
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• 2017

In this paper, we show how to design based on solving Sudoku problem that is one of the NP-complete problems like Go. We show how to use greedy method which can minimize depth based on tree expansion and how to apply heuristic algorithm for pruning unnecessary branches. As a result of measuring the performance of the proposed method for solving of Sudoku problems, this method can reduce the number of function call required for solving compared with the method of heuristic algorithm or recursive method, also this method is able to reduce the 46~64 depth rather than simply expanding the tree and is able to pruning unnecessary branches. Therefore, we could see that it can reduce the number of leaf nodes required for the calculation to 6 to 34.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.516-522
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• 2020

Water trees can cause considerable damage to the performance of underground cables. Theymay formwithin the dielectric used in buried or water-immersed high voltage cables. They grow in a bush-like or tree-like form, often taking decades before causing damage to a cable's performance. They are usually found on very old underground cables, often in an inaccessible place. It is costly and time-consuming to detect watertrees in underground cables. Tree detection technology, including mathematical modeling,can reduce the maintenance cost and time necessary for detecting these trees.To simulate detection of water trees in this study, a mathematical model ofan XLPE cable and a water tree were developed. The complex water tree structure was simplified, based on two identified patterns of aventedtree. A Matlab simulation was performed to calculate and analyze the capacitance and resistance of a cable insulation layer,based on growth of a watertree. Capacitance size increased about 0.025×10^-13[Farads/mm] compared to normal when the tree area of the cable was advanced to 95% of the insulation layer. The resistance value decreased by about 0.5×10¹⁶[ohm/m]. These changesand changesshowninaBurkes paper physical modeling simulation are similar.The value of mathematical modeling for detecting water trees and damage to underground cables has been demonstrated.