• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.2
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• pp.68-76
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• 2001

The purpose of this study is to computerize street tree management using a CAD program in order to manage the drawing record of street trees systematically and concurrently. The configuration of this program is composed of Reference Data, Data Inquiry, and Cost Assessment. The Reference Data includes characteristics of trees, monthly managements records, damage by blight and insects and usage of pesticides. The Data Inquiry includes an individual search of the tree index, simple searches and multiple searches. The Cost Assessment includes two main components, the data input with labor cost, manure ocst and pesticide cost and the assesment of management cost for prevention of blight and insects, pruning and fertilization. The results of this study are as follows: 1) When there are practices such as transplanting and removing of street trees it is immediately updated with the various situation. By creating an in progress a tree management system, up to the date information can be given to the manager for decision making. 2) To identify individual tree at the site or in drawing, the street name and numbers were used instead of coordinates. Tree tags are attached to the street trees individually. It can make DB management simple and easy. 3) By doing simple or multiple search with constructed DB, data can be provided quickly. 4) The result of this type of search are useful in the assessment of management cost very useful in regards to items such as the pruning, pesticides scattering and fertilization. 5) By using the AutoCAD software and existing PC without purchasing new equipment, the cost of system implementation can be minimized.

• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.727-734
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• 1999

Let G be a connected graph of n vertices. The problem of finding a depth-first spanning tree of G is to find a connected subgraph of G with the n vertices and n-1 edges by depth-first-search. in this paper we propose an O(n) time algorithm to solve this problem on permutation graphs.

• Journal of Korea Multimedia Society
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• v.15 no.2
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• pp.215-225
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• 2012

In multimedia database, a multidimensional space-based indexing has been used to increase search efficiency. However, this method is inefficient in terms of ubiquity because it uses Euclidean distance as a scale of distance calculation. On the contrary, a metric space-based indexing method, in which metric axiom is prerequisite is widely available because a metric scale other than Euclidean distance could be used. This paper is attempted to propose a way of improving VP-tree, one of the metric space indexing methods. The VP-tree calculates the distance with an object which is ultimately linked to the a leaf node depending on the node fit for the search range from a root node and examines if it is appropriate with the search range. Because search speed decreases as the number of distance calculations at the leaf node increases, however, this paper has proposed a method which uses the latest interface on query object as the base point of trigonometric inequality for improvement after focusing on the trigonometric inequality-based range compression method in a leaf node. This improvement method would be able to narrow the search range and reduce the number of distance calculations. According to a system performance test using 10,000 video data, the new method reduced search time for similar videos by 5-12%, compared to a conventional method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.585-588
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• 2010

The prediction of user location within a building can be applied to many areas like visitor guiding. The existing methods for solving this problem consider limited number of locations a user visited in the past to predict the current location. It cannot model the complex movement patterns, and makes the system inefficient by modeling simple ones too detail. Also it causes prediction errors. In this paper, there is no restriction on the length of past movement patterns to consider for current location prediction. For this purpose, a modified search tree is used. The search tree is constructed to make exact matching as needed for location prediction. The search tree makes the efficient and accurate prediction possible.

• Journal of Korea Game Society
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• v.18 no.6
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• pp.59-68
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• 2018

In spite of its simple rule, Go is one of the most complex strategic board games in the field of Artificial Intelligence (AI). Monte-Carlo Tree Search (MCTS) is an algorithm with best-first tree search, and has used to implement computer Go. We try to find the most promising first move using MCTS for playing a Go game on a board of size smaller than $9{\times}9$ Go board. The experimental result reveals that MCTS prefers to place the first move at the center in case of odd-sized Go boards, and at the central in case of even-sized Go boards.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.119-122
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• 2003

This paper presents an efficient huffman decoding method based on the multiple branch technique. In the proposed search method, the internal node which does not contain a leaf node are removed for decrease the searching time and the memory consumption. The proposed search method gives 44％ of improved in searching time and 34％ of decreased in memory requirement compared to the binary search method.

• Journal of IKEEE
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• v.22 no.3
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• pp.850-853
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• 2018

In this paper, we propose a decoding method using a balanced binary tree and a canonical Huffman tree for efficient decoding of Huffman codes. The balanced binary tree scheme reduces the number of searches by lowering the height of the tree and binary search. However, constructing a tree based on the value of the code instead of frequency of symbol is a drawback of the balanced binary tree. In order to overcome these drawbacks, a balanced binary tree is reconstructed according to the occurrence probability of symbols at each level of the tree and binary search is performed for each level. We minimize the number of searches using a canonical Huffman tree to find level of code to avoid searching sequentially from the top level to bottom level.

• Journal of KIISE:Information Networking
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• v.36 no.1
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• pp.57-67
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• 2009

Packet forwarding in the Internet routers is to find out the longest prefix that matches the destination address of an input packet and to forward the input packet to the output port designated by the longest matched prefix. The IP address lookup is the key of the packet forwarding, and it is required to have efficient data structures and search algorithms to provide the high-speed lookup performance. In this paper, an efficient IP address lookup algorithm using binary search is investigated. Most of the existing binary search algorithms are not efficient in search performance since they do not provide a balanced search. The proposed binary search algorithm performs perfectly balanced binary search using switch pointers. The performance of the proposed algorithm is evaluated using actual backbone routing data and it is shown that the proposed algorithm provides very good search performance without increasing the memory amount storing the forwarding table. The proposed algorithm also provides very good scalability since it can be easily extended for multi-way search and for large forwarding tables

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.405-408
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• 2016

Games like Go, Chess, Janggi have helped to brain development of the people. These games are developed by computer program. And many algorithms have been developed to allow myself to play. The person winning chess program was developed in the 1990s. But game of go is too large number of cases. So it was considered impossible to win professional go player. However, with the use of MCTS(Monte Carlo Tree Search) and CNN(Convolutional Neural Network), the performance of the go algorithm is greatly improved. In this paper, using CNN and MCTS were proceeding development of go algorithm. Using the manual of go learning CNN look for the best position, MCTS calculates the win probability in the game to proceed with simulation. In addition, extract pattern information of go using existing manual of go, plans to improve speed and performance by using it. This method is showed a better performance than general go algorithm. Also if it is receiving sufficient computing power, it seems to be even more improved performance.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.345-353
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• 2019

Several studies have been proposed to improve storage space efficiency by expressing binary trie data structure as a linear binary bit string. Compact binary tree approach generated using one binary trie increases the key search time significantly as the binary bit string becomes very long as the size of the input key set increases. In order to reduce the key search range, a hierarchical compact binary tree technique that hierarchically expresses several small binary compact trees has been proposed. The search time increases proportionally with the number and length of binary bit streams. In this paper, we generate several binary compact trees represented by full binary tries hierarchically. The search performance is improved by allowing a path for the binary bit string corresponding to the search range to be determined through simple numeric conversion. Through the performance evaluation using the worst time and space complexity calculation, the proposed method showed the highest performance for retrieval and key insertion or deletion. In terms of space usage, the proposed method requires about 67% ~ 68% of space compared to the existing methods, showing the best space efficiency.