• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.730-732
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• 2005

본 논문에서는 자율적인 다수의 에이전트들이 협력하여 미지의 공간을 탐사하는 실시간 그래프 탐색 알고리즘인 MADFS를 제안하고 그 효율성을 분석한다. 이 알고리즘은 깊이-우선 탐색(DFS)에 기초한 단일 에이전트 공간 탐사 알고리즘인 dFS-RTA* 와 DFS-PHA* 를 멀티 에이전트 환경에 적합하게 에이전트 간 정보공유 방식과 방문노드 선택전략을 설계하여 확장하였다. 본 논문에서는 대표적인 3차원 온라인 게임 환경인 Unreal Tournament 게임과 지능형 캐릭터 에이전트인 KGBot를 이용한 실험을 통해 알고리즘의 완전성과 효율성을 분석해본다.

• Journal of Korea Game Society
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• v.19 no.4
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• pp.5-14
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• 2019

This essay analyzes space in augmented reality games, and attempts to offer space analytic standards of mobile augmented reality games in regards to space in existing games. This article proposes categorizing criteria based on the following factors: Analysis of space in existing games, Jason Jerald's Three Virtual Space Horizon Categories, interaction between virtual world and real world, and Lavroff's Three deciding factors of reality perception in virtual reality. It is meaningful that the analysis criteria of the Augmented Reality game space is presented through this analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.798-801
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• 2014

여행 정보 시스템(ATIS), 교통 관리 시스템 (ITS) 등 궤적 기반 서비스에서, 서비스 품질을 향상시키기 위해서는 주어진 궤적 질의에 대한 정확한 주행시간을 예측하는 것이 필수적이다. 이를 위한 대표적인 공간 데이터 분석 기법으로는 데이터 분류에서 높은 정확도를 보장하는 규칙 기반 분류화 기법이 존재한다. 그러나 기존 규칙 기반 분류화 기법은 단일 컴퓨터 환경만을 고려하기 때문에, 대용량 공간 데이터 처리에 적합하지 않은 문제점이 존재한다. 이를 해결하기 위해, 본 연구에서는 맵리듀스 환경에서 규칙 기반 분류화를 이용한 궤적 데이터 주행 시간 예측 알고리즘을 개발하고자 한다. 제안하는 알고리즘은 첫째, 맵리듀스를 이용하여 대용량 공간 데이터를 병렬적으로 분석함으로써, 활용도 높은 궤적 데이터 규칙을 생성한다. 이를 통해 대용량 공간 데이터 기반의 규칙 생성 시간을 감소시킨다. 둘째, 그리드 구조 기반의 지도 데이터 분할을 통해, 사용자 질의처리 시 탐색 성능을 향상시킨다. 즉, 주행 시간 예측을 위한 규칙 그룹을 탐색 시 질의를 포함하는 그리드 셀만을 탐색하기 때문에, 질의처리 성능이 향상된다. 마지막으로 맵리듀스 구조에 적합한 질의처리 알고리즘을 설계하여, 효율적인 병렬 질의처리를 지원한다. 이를 위해 맵 함수에서는 선정된 그리드 셀에 대해, 질의에 포함된 도로 구간에서의 주행 시간을 병렬적으로 측정한다. 아울러 리듀스 함수에서는 출발 시간 및 구간별 주행 시간을 바탕으로 맵 함수의 결과를 병합함으로써, 최종 결과를 생성한다. 이를 통해 공간 빅데이터 분석을 통한 주행 시간 예측 기법의 처리 시간 및 결과 정확도를 향상시킨다.

• Education of Primary School Mathematics
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• v.25 no.1
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• pp.81-100
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• 2022

The purpose of this study is to develop a framework for analyzing the solution spaces of open-ended task and to explore their usefulness and applicability based on the analysis of solution spaces constructed by students. Based on literature reviews and previous studies, researchers developed a framework for analyzing solution spaces (OMR-framework) organized into subspaces of outcome spaces, method spaces, representation spaces which could be used in structurally analyzing students' solutions of open-ended tasks. In our research, we developed open-ended tasks which had various outcomes and methods that could be solved by using the concepts of factors and multiples and assigned the tasks to 181 elementary school fifth and sixth graders. As a result of analyzing the student's solution spaces by applying the OMR-framework, it was possible to systematically analyze the characteristics of students' understanding of the concept of factors and multiples and their approach to reversible and constructive thinking. In addition to formal mathematical representations, various informal representations constructed by students were also analyzed. It was revealed that each space(outcome, method, and representation) had a unique set of characteristics, but were closely interconnected to each other in the process. In conclusion, it can be said that method of analyzing solution spaces of open-ended tasks of this study are useful for systemizing and analyzing the solution spaces and are applicable to the analysis of the solutions of open-ended tasks.

• Spatial Information Research
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• v.9 no.2
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• pp.171-184
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• 2001

The nature of ill-defined planning problems makes expert systems difficult to acquire and represent knowledge for decision making in urban planning processes. In order to resolve these problems, a case-based reasoning method was applied to develop a spatial analysis system for urban planning. A case study was conducted in a residential land use planning process. The result of the study revealed the effectiveness of reasoning by the spatial analysis system and the possibility of its future application. More accumulation of information on other successful cases should be sought to yield better results

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.7
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• pp.625-630
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• 2009

In this paper, we introduce the analysis and counter-measure of signal distortion of search radar equipped on the ship. Using ShipEDF program, the search radar's main antenna and ship structures are modeled in the view of electromagnetism. Ray tracing method is used for analysis of the search radar's radiation patterns in free space and ship condition. From analyzed radiation patterns, we can conclude that the search radar's signal distortion is due to radiation pattern distortion. We also analyze the surface current distribution of the mast to propose the counter-measure to reduce electro-magnetic field reflection of mast.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.927-930
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• 2010

Recently, continuous k-nearest neighbor query(CkNN) which is defined as a query to find the nearest points of interest to all the points on a given path is widely used in the LBS(Location Based Service) and ITS(Intelligent Transportation System) applications. It is necessary to acquire results quickly in the above applications and be applicable to spatial network databases. This paper proposes a new method to search nearest POIs(Point Of Interest) for moving query objects on the spatial networks. The method produces a set of split points and their corresponding k-POIs as results. There is no order between the POIs. The analysis show that the proposed method outperforms the existing methods.

• Spatial Information Research
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• v.10 no.2
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• pp.185-199
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• 2002

The objective of this study is to investigate the suitable spatio-temporal analysis method considering the zoning effect of spatial analysis termed the modifiable areal unit problem(MAUP). In former studies of spatio-temporal analysis, there were disagreement between attribute data with spatial data, because of variation of administrative district aggregating attribute data. It is need to consider how the analysis zone effects spatial characteristics and spatio-temporal variation of urban region through land price variation analysis. This study considers MAUP through basic mesh system, which is composed of micro grid. Mesh system can solve disagreement of resolution between spatial data and attribute data.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.264-268
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• 2006

Graphplan 계획기에서 유래된 계획 그래프는 탐색에 매우 유용한 휴우리스틱을 손쉽게 얻을 수 있는 수단이다. 본 논문에서는 전향 상태 공간 계획방식을 정의한 뒤, 이 계획방식에 적용 가능한 계획 그래프 기반의 휴우리스틱 계산법들을 소개한다. 또 본 논문에서는 각 휴우리스틱 계산법이 갖는 특징을 정리하고 이들이 계획생성에 미치는 효과를 실험을 통해 비교, 분석해본다. 또한 이러한 전향 상태 공간 탐색 알고리즘과 휴우리스틱 계산법을 토대로 본 연구에서는 전향 상태 공간 계획기인 JPLAN을 구현하였고 그 구조에 대해 설명한다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2897-2907
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• 1998

The production-rule generation from training examples is a hard problem that has large space and many local optimal solutions. Many learning methods are proposed for production-rule generation and genetic algorithms is an alternative learning method. However, traditional genetic algorithms has been known to have an obstacle in converging at the global solution area and show poor efficiency of production-rules generated. In this paper, we propose a production-rule generating method which uses genetic algorithm learning. By analyzing optimal sub-solutions captured by genetic algorithm learning, our method takes advantage of its schema structure and thus generates relatively small rule set.