• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.23-29
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• 2015

In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.

• 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.

• Journal of the Korean Geographical Society
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• v.39 no.3
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• pp.457-472
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• 2004

The purpose of this study is to analyze spatial patterns of traffic accidents and to investigate spatial relations among neighboring spatial objects by applying GIS and spatial data mining methods. This study investigated traffic accident data in Kangnam-gu, Seoul, as a case study. As a result, four clusters were emerged based on individual attributes of traffic accidents. Each cluster showed distinctive properties. In spatial associations between individual attributes of traffic accidents and neighboring spatial objects, there were many rules according to concept hierarchy and definition of spatial relations. Although all rules were not be interesting and significant, they could be a clue to investigate more.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.419-422
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• 2005

본 논문은 미지의 공간 그래프에 대한 실시간 최단 경로 탐색 알고리즘인 $RTA{\ast}$ 알고리즘과 $PHA{\ast}$ 알고리즘을 소개하고, 예제 그래프를 통해 이들의 특성을 설명한다. 또 3차원 온라인 게임 환경인 언리얼 토너먼트(Unreal Tournament) 게임과 Gamebots 시스템을 이용하여 두 알고리즘 간의 탐색 최적성과 효율성을 비교하였다. 이 실험을 통하여 $PHA{\ast}$ 알고리즘은 언제나 최선의 경로를 탐색하지만 이동경로가 많고, 시간이 많이 걸릴 수 있으며, $RTA{\ast}$는 최적의 경로 혹은 차선 경로를 빠른 시간 내에 탐색함을 확인 하였다. 따라서 이러한 특성을 바탕으로 주어진 탐색 환경의 조건에 따라 두 알고리즘을 선택적으로 적용함으로써 보다 높은 효과를 얻을 수 것으로 기대한다.

• Journal of the Korean Regional Science Association
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• v.37 no.2
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• pp.63-82
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• 2021

This study aims to explore how manufacturing start-up activities from 2000 to 2018 have changed spatially and to predict changes in distribution patterns of future start-up activities. For the analysis, the Census on Establishments microdata from 2000 to 2018 were used, and the manufacturing industry was classified into four detailed industrial groups according to the 40 manufacturing standards presented by the Korea Institute for Industrial Economics and Trade's ISTANS. According to the results, start-up activities in industries that require high technology levels are concentrated in southern Gyeonggi region, and other start-up activities are concentrated outside of the metropolitan area. When the distribution change from 2018 to 2036, extending the trend from 2000 to 2018, it was confirmed that there was a high possibility of a rise in the hierarchy in the future in regions adjacent to regions where start-up activities occur. This study aimed to provide implications for regional policies related to fostering start-ups and creating jobs by dynamically analyzing the location pattern of manufacturing start-ups, which is a major source of job creation.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.67-81
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• 2006

The present study suggests an analytical method to overcome the spatial problems that traditional hedonic methods have. The concept of overlapping neighborhoods is introduced in order to solve the problems of global parameter estimate methods that treat the whole city by the gross. Moreover, a 3rd party program for the tight coupling of GIS and statistics is developed in order to explore hedonic methods efficiently. By using these, this study analyses the spatial variation of location variables that affect the real estate price. The results show that the influences of urban centers do not reach to the whole city, but only to the catchment areas of them. And the coefficients of location variables are different depending on the space. The tight coupling of GIS and statistics offers a powerful tool in analysing the real estate price efficiently.

• 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.

• 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 the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.492-511
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• 2013

According to IASB(International Accounting Standards Board), R&D(Research and Development) is defined as a tertiary sector industry combining research and development. Many studies investigated R&D industry clusters in the form of high-tech cluster(Coe et al., 2007). However, these studies only generalized various spatial cluster of R&D industries. In particular, the studies could not considers cluster formation process over time lacking statistical significance in space-time perspectives. This study, therefore, indicates the limitation of recent R&D cluster literature which only considers either time or space. In addition, this study explores space-time clusters in R&D industry together with textile and cloth industry for comparison. Discovering the existence and location of clusters, this study utilized space-time K function and space-time scan statistics. The result shows that R&D industry presents significant clusters only in spatial dimension. No significant clusters were found in space-time dimension. However, textile and clothing industry presents significant clusters in both spatial and space-time dimensions.