• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.893-900
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• 2007

This paper suggests an algorithm that improves the disadvantages of the Dijkstra algorithm that is commonly used in GPS navigation system, searching for the shortest path. Dijkstra algorithm, first of all, requires much memory for the performance of the algorithm. It has to carry out number of node minus 1, since it determines the shortest path from all the nodes in the graph, starting from the first node. Therefore, Dijkstra algorithm might not be able to provide the information on every second, searching for the shortest path between the roads of the congested city and the destination. In order to solve these problems, this paper chooses a method of searching a number of nodes at once by means of choosing the shortest path of all the path nodes (select of minimum weight arc in-degree and out-degree), excluding the departure and destination nodes, and of choosing all the arcs that coincide with the shortest path of the path nodes, from all the node outgoing arcs starting from the departure node. On applying the suggested algorithm to 14 various digraphs, we succeeded to search the shortest path. In addition, the result was obtained at the speed of 2 to 3 times faster than that of Dijkstra algorithm, and the memory required was less than that of Dijkstra algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.493-498
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• 2004

A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.32-39
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• 2009

In this thesis, design effective elimination interference algorithm of ICS repeat system for repeater that improve frequency efficiency. Gennerally, LMS Algorithm apply to ICS repeat system. Error convergence speed and accuracy of LMS Algorithm are influenced by reference signal. For improve LMS Algorithm, suggest Adaptive searching channel estimate algorithm. For using channel characteristic, adaptive searching channel estimate algorithm make reference signal similar interference signal by convolution operation and complement LMS algorithm demerit. For make channel similar pratical channel, apply Jake's Rayleigh multi-path model. LMS algorithm and suggested adaptive searching channel estimate algorithm that have 16 taps apply to ICS repeat system under Rayleigh multi-path channel, so simulate with MATLAB. According to simulate, ICS repeat system with LMS algorithm show -40 dB mean square error convergent after 110 datas iteration and ICS repeat system with adaptive searching channel estimate algorithm show -80 dB mean square en-or convergent after 120 datas iteration. Analyze simulation result, suggested adaptive searching channel estimate algorithm show 40 dB accuracy than LMS algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.11-21
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• 2015

In order to achieve success in ground operations, searching for moving targets is one of critical factors. Usually, the system of searching for adversary ground moving targets has complex properties which includes target's moving characteristics, camouflage level, terrain, weather, available search time window, distance between target and searcher, moving speed, target's tactics, etc. The purpose of this paper is to present a practical quantitative method for effectively searching for infiltrated moving targets considering aforementioned complex properties. Based upon search theories, this paper consists of two parts. One is infiltration route analysis, through terrain and mobility analysis. The other is building dynamic probability maps through Monte Carlo simulation to determine the prioritized searching area for moving targets. This study primarily considers ground moving targets' moving pattern. These move by foot and because terrain has a great effect on the target's movement, they generally travel along a constrained path. With the ideas based on the terrain's effect, this study deliberately performed terrain and mobility analysis and built a constrained path. In addition, dynamic probability maps taking terrain condition and a target's moving speed into consideration is proposed. This analysis is considerably distinct from other existing studies using supposed transition probability for searching moving targets. A case study is performed to validate the effectiveness and usefulness of our methodology. Also, this study suggests that the proposed approach can be used for searching for infiltrated ground moving target within critical time window. The proposed method could be used not only to assist a searcher's mission planning, but also to support the tactical commander's timely decision making ability and ensure the operations' success.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.843-851
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• 2007

• 한국ITS학회:학술대회논문집
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• 2004.11a
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• pp.349-354
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• 2004

• Journal of Korea Game Society
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• v.9 no.4
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• pp.81-88
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• 2009

In this paper, I suggested a way for searching a path of the intelligent character in an action game by using a genetic algorithm. This realized the algorithm which enables not only to chose the nearest path but also to search the optimum path by using genetic algorithm. In this case, if the codes of chromosomes are applied as they are, a lot of lethal genes could occur. In order to solve such a problem, I used a splicing method, one of the DNA's behavior characteristics. The intelligent character searched out a optimum pass as well as a shortcut path with one treatment by using the characteristic of a genetic algorithm which generates multiple candidate solutions in the search process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.87-90
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• 2008

Dynamic Heuristic(DH) is not fixed data and is dynamically modified using transferred real time road data from server In this paper, we propose path-finding algorithm with Maximum Speed Dynamic Heuristic (DH-MAX) and do an experiment. The DH-MAX is to be used the highest speed as DH, in real map divided by same sire. And proposed algorithm searches path using the priority searching only of the fixed data, but also the highest speed with real time information. In the performance test, the quality of path is enhanced but the cost of searching is increased than $A^*$ algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1986-1992
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• 2009

A user often searches a data by inputting a variant such as the abbreviation or substring of a word, or a misspelled word. The simple approach to the searching for variants is to build a variants dictionary. However, it entails enormous cost and time and can not handle variants by misspelling. Approximate searching, searching by approximate string matching, is a good approach to the searching. A problem in the approach is that it cannot handle variants by abbreviations. This paper propose a method for searching various variants including abbreviations and misspelled words, by using the trie indexing. First, this paper shows a variant matching method with the calculation of path weighted-metric. In addition, it provides variant searching algorithm to reduce the search time.

• Korean Management Science Review
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• v.18 no.1
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• pp.105-118
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• 2001

The common shortest path problem is to find the shortest route between two specified nodes in a transportation network with only one traffic mode. The public transportation network with multiple traffic mode is a more realistic representation of the transportation system in the real world, but it is difficult for the conventional shortest path algorithms to deal with. The genetic algorithm (GA) is applied to solve this problem. The objective function is to minimize the sum of total service time and total transfer time. The individual description, the coding rule and the genetic operators are proposed for this problem.