• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.73-83
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• 2017

In this paper, we discuss the differences between an ordinary B-tree and B-tree implemented by NTFS. There are lots of distinctions between the two B-tree, if not understand the distinctions fully, it is difficult to utilize and analyze artifacts of NTFS. Not much, actually, is known about the implementation of NTFS, especially B-tree index for directory management. Several items of B-tree features are performed that includes a node size, minimum number of children, root node without children, type of key, key sorting, type of pointer to child node, expansion and reduction of node, return of node. Furthermore, it is emphasized the fact that NTFS use B-tree structure not B+structure clearly.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.43-53
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• 2011

The many cities are changing in the city form where the person and nature are mixed. Namely, the government invests many expense in tree field of distance space for the change in the green city. In this paper, we design and implement a tree growth management system using PDA built in 13.56MHz RFID reader and CBD(Component Based Development) for ubiquitous computing environments. Our system provides history management to increase business efficiency for location coordinate of tree and history information of tree which using RFID, the RFlD tag is attaching the new tree and that is inputting GPS location information in PDA and provides tree information of tree by location coordinate to history management. Finally, we show from a performance analysis that our system achieves about 85% average tree read rate of RFID under test scenario environments.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.55-62
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• 2009

Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.12
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• pp.1063-1068
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• 2000

Water treeing in underground distribution power cable is not easy to observe by nondestructive method and it has very complex patterns. This study describes the principles and practices of a continuous observation of initiation and growth of tree in polymeric insulation material using an image measurement technique. Using this technique we could observe water tree and the growing process of electrical tree due to the water tree and the growing process of electrical tree due to the water tree. All of these growing process is analyzed quantitatively by image measurement program composed of borland c++. We fabricated the thin film type specimen to observe water tree easier and also the needle electrode was prepared by etching method using electrolytes. Initiation and the growth of three was observed somewhat different depending on the applied voltage and the water electrode. AgNO$_3$solution electrode accelerates the initiation and the growth of water tree, compared to those of distilled water electrode. The water and the electrical tree occurred by water tree has discontinuous growth characteristic.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.270-273
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• 2001

Electrical tree is studied widely by manufacture state of insulating material fare and blazing fire diagnosis system of use in phenomenon of part discharge that happen for main cause of dielectric breakdown of equipment for electric power. Use process that draw tree pattern here measuring above zero to study special quality of this electricity tree, real-time processing by image processing is proposed because reproduction of tree blazing fire process drops and pattern of tree is difficult correct quantification of tree growth by existent visual observation by involution. This research presents general process that need in image processing of tree blazing fire, and that remove various noises that happen in above zero by measuring electrical tree dividing background and complete view in measured above zero taking advantage of specially proposed complete view object abstraction techniques effectively and quantification of tree becomes easy naturally, can apply to dielectric breakdown estimate because can chase growth process of tree.

• Spatial Information Research
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• v.7 no.2
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• pp.271-282
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• 1999

In this paper, we derived an efficient indexing scheme, SJ tree, which handles multi-attribute data and spatial join operations efficiently. In addition, a number of algorithms for manipulating multi-attribute data are given , together with their computational and I/O complexity . Moreover , we how that SJ tree is a kind of generalized B-tree. This means that SJ-tree can be easily implemented on existing built-in B-tree in most storage managers in the sense that the structure of SJ tree is like that of B-tree. The spatial join operation with spatial output is benchmarked using R-tree, B-tree, K-D-B tree, and SJ tree. Results from the benchmark test indicate that SJ tree out performance other indexing schemes on spatial join with point data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.11a
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• pp.59-62
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• 1999

Inception and propagation of electrical tree and properties of Partial discharge(PD) pulses accompanying with tree as a function of needle tip radius in low density polyethylene were discussed. To study on these characteristics in different tip radius, we used specimens with needle-plane electrode system made of LDPE, observed inception and propagation of electrical tree by optical microscope with computer and investigated the characteristics of the phase resolved PD pulses accompanying with propagation of electrical tree. The PD quantities detected and analysed were PD magnitude, mean phase angle, average discharge, and the statistical characteristics of the PD pulses. As the tip radius ${\gamma}$ increases, tree inception stress E$\sub$i/ converges to constance value. This result suggests that tree inception stress E$\sub$i/ increases due to stress relaxation when the tip radius is small. Branch-type electrical tree was formed When E$\sub$i/ is 640-750[kV/mm]. bush-type electrical tree when E$\sub$i/ is 370∼400[kV/mm], branch-like electrical tree when E$\sub$i/ is 370-400[kV/mm].

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.11a
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• pp.207-208
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• 2001

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.1
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• pp.117-129
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• 2017

This research was conducted to construct a tree belt around Saemangeum reclaimed land using various planting methods and to analyze initial growth amount, to provide practical data to construct tree belt of various purposes. Tree species used in tree belt construction were Pinus thunbergii and Quercus serrata, and the main planting treatment methods used were categorized by existence of windy fence, mixed planting, and un-mixed planting. Growth amount analysis was conducted using ANOVA to compare growth amounts in different experimental groups and Duncan's multiple range test. Growth amount analysis results of tree belt by planting method showed that it is most statistically plausible to install 50% porous windy fence from the direction of wind and frost, followed by planting P. thunbergii and Q. serrata in areas that require mixed tree species tree belt around Saemangeum reclaimed land. In areas where un-mixed planting tree belt is required, it was appropriate to use P. thunbergii alone without a windy fence. Lastly, if the purpose of the tree belt is limited to rapid growth, it was most ideal to plant P. thunbergii alone (without windy fence) or install 50% porous windy fence from the direction of wind and frost, followed by planting P. thunbergii and Q. serrata. This research is based on initial growth amount of tree belt and there is a need for a long-term monitoring of tree belt growth to increase tree-planting success rate in establishing tree belt according to Saemangeum internal development.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.30-38
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• 2004

In many scientific and commercial applications such as Earth Observation System (EOSDIS) and mobile Phone services tracking a large number of clients, it is a daunting task to archive and index ever increasing volume of complex data that are continuously added to databases. To efficiently manage multidimensional data in scientific and data warehousing environments, R-tree based index structures have been widely used. In this paper, we propose a scalable technique called seeded clustering that allows us to maintain R-tree indexes by bulk insertion while keeping pace with high data arrival rates. Our approach uses a seed tree, which is copied from the top k levels of a target R-tree, to classify input data objects into clusters. We then build an R-tree for each of the clusters and insert the input R-trees into the target R-tree in bulk one at a time. We present detailed algorithms for the seeded clustering and bulk insertion as well as the results from our extensive experimental study. The experimental results show that the bulk insertion by seeded clustering outperforms the previously known methods in terms of insertion cost and the quality of target R-trees measured by their query performance.