• Journal of the Korean association of regional geographers
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• v.6 no.3
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• pp.169-184
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• 2000

Industrial clusters and their boundaries are identified by factor and hot spot analyses for the greater Cincinnati metropolitan area in USA. While traditional input-output approach identified aspatial industrial clusters, this study combines traditional approach with GIS techniques to identify their boundaries. Combining the results of input-output industrial clusters with the leading industries groups, we have identified five leading industry clusters. They are food (20), chemicals (28), metal manufacturing (32), metal products (33), and machinery (35). We also used hot spot analysis to visualize each industry cluster on the research area by using Arcview software. Determining the degree to which such industries are associated spatially and their spatial delimitation may be an additional approach to measuring the efficiency of the spatial organization of an economy. It is hoped that the industrial clusters and industrial spatial clusters approaches may also proved the basis for the development of new models of the spatial arrangement of industry at a level more aggregated than that of the single plant or firm.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.21-28
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• 2008

In MCDA (Multi-Criteria Decision Analysis) based on GIS, building the CM(Criteria Map) which represents the space phenomenon properly is important process to deduce precise and efficient site analysis result. The CM using administrative district data is widely used for site analysis process. But, there are not enough studies on site analysis using dasymetric mapping technique. For MCDA, this study suggests building the CM by using dasymetric mapping technique, which re-assigns the social-economic attribute value to more detail space unit. The suggested method is used for industrial site analysis. The criteria map for workforce and criteria map for the distance to the city were built and criteria map which represents attribute's space distribution pattern is documented. The criteria map is successfully applied to multi-criteria decision making process and eventually the analysis result of proposed suitable industrial site is derived.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.141-156
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• 2023

This study aims to improve understanding of freight movement, crucial for logistics facility investment and policy making. It addresses the limitations of traditional freight truck traffic data, aggregated only at city and county levels, by developing a new methodology. This method uses trip chain data for more detailed, facility-level analysis of freight truck movements. It employs DTG (Digital Tachograph) data to identify individual truck visit locations and creates H3 system-based polygons to represent these visits spatially. The study also involves an algorithm to dynamically determine the optimal spatial resolution of these polygons. Tested nationally, the approach resulted in polygons with 81.26% spatial fit and 14.8% error rate, offering insights into freight characteristics and enabling clustering based on traffic chain characteristics of freight trucks and visited facility types.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.464-469
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• 2013

After city of Busan has been entered to the aging society in 2000, the city has the highest aging rate among 7 representative cities in 2011. Moreover, while entire population and number of average household are decreasing, over 65 years old of elderly population is rapidly increasing. So, it is possible to enter the super-aged society, where aging rate would be about 20% after 2020. The purpose of this study is that older housing-related analysis is consisted of dong-unit, and this led microscopic analysis has become necessary. Surveys from 2000 through 2010, census aggregate (output area) unit of spatial analysis was conducted. Take advantages of this, aging population and area, soaring area, high-density areas, such as the region of interest were primary extracted, and microscopic location and spatial distribution patterns were analyzed. Upon analysis, aging population is concentrated in the city and adjacent area, the highlands, and 10 years of increasing rate was more than 30 times in certain aggregate. Regarding the characteristic of these areas, the original city center, Busan, especially concentrated and intensified in aging population. Also, 2000 to 2010, the overall distribution pattern of Busan has identified aging population that is increasingly being distributed. This is the result, which is confronted with previous research result. Entering a super aged-society for the future is accordance with migration of social costs and improve the quality of life of elderly. And this could be the basic information to use the spatial dimension for the corresponding.

• Journal of the Korean Institute of Rural Architecture
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• v.23 no.2
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• pp.9-16
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• 2021

The purpose of this study is to maintain the existing characteristics of the city by utilizing the physical decline status and floating population in small and medium cities residential areas. In addition, it intends to present the direction of flexible urban regeneration and maintenance by reflecting regional characteristics and current status. A total of three data were used in this study. Building data, floating population data, and census output area data were used. Building data and floating population data were classified into five classes. The graded data were joined to the census output area data and analyzed by overlapping the two data. As a result of analysis of 17 residential areas in 5 small and medium cities in Jeollanam-do, 4 types, 2 management models, and 4 indicators could be presented by grade and regional characteristics. This study is meaningful in that it is possible to plan regionally customized urban regeneration/maintenance management plans and projects through the typology of the current status and characteristics of the region, which is an important step in the bottom-up form.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1386-1396
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• 2009

Most decision support functions of spatial data warehouse rely on the OLAP operations upon a spatial cube. Meanwhile, higher performance is always guaranteed by indexing the cube, which stores huge amount of pre-aggregated information. Hierarchical Dwarf was proposed as a solution, which can be taken as an extension of the Dwarf, a compressed index for cube structures. However, it does not consider the spatial dimension and even aggregates incorrectly if there are redundant values at the lower levels. OLAP-favored Searching was proposed as a spatial hierarchy based OLAP operation, which employs the advantages of R-tree. Although it supports aggregating functions well against specified areas, it ignores the operations on the spatial dimensions. In this paper, an indexing approach, which aims at utilizing the concept hierarchy of the spatial cube for decision support, is proposed. The index consists of concept hierarchy trees of all dimensions, which are linked according to the tuples stored in the fact table. It saves storage cost by preventing identical trees from being created redundantly. Also, it reduces the OLAP operation cost by integrating the spatial and aspatial dimensions in the virtual concept hierarchy.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.1443-1446
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• 2001

본 논문에서는 5개 이동통신 사업자 식별을 위한 사용자 에이전트와 개인휴대전화를 이용한 유 무선인터넷 통합서버에 의해 각 이동통신사업자를 경유한 유선 포털사이트 또는 특정 사이트(URL 접속)에 직접 접속하여 WAP 또는 ME를 동시에 지원할 수 있는 NT 또는 LINUX 통합서버를 구축한다. 이로서 휴대전화를 이용한 입학관리시스템, 휴대전화를 이용한 만성질환자의 원격 진료시스템, 휴대전화를 이용한 방송 순위집계 시스템과 사용자 참여방법, 시청률 및 여론조사, 무선성경 검색 등의 다양한 컨텐츠의 개발이 용이하고, LINUX/UNIX, NT 서버구축이 단순함으로서 이동전화의 장점인 휴대성으로 시간과 공간의 제약을 벗어나 다양한 무선 인터넷 검색이 가능해 질 것이다.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.445-448
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• 2009

DSS 응용들의 대용량 집계 데이터 집중 시스템에서는 효율적이고 즉각적인 의사결정 지원을 위한 근사 질의응답의 연구가 필요하다. 따라서 본 연구에서는 FCM 클러스터링 기법과 ANFIS을 이용한 기법을 제안한다. 제안된 기법은 다차원 데이터 큐브의 데이터 특성을 가지며 질의에 대한 근사적인 응답을 제공할 수 있는 모델을 생성한다. 제안된 기법을 통해 학습된 모델은 기존의 기법보다 근사 질의응답의 정확성이 향상되었음을 비교 실험을 통하여 확인한다. 따라서 제안된 기법은 기존의 기법보다 저장 공간과 시간을 줄일 수 있으며 또한 근사 응답의 정확도를 향상시킬 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.46-48
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• 2003

최근 시공간 데이타에 대한 OLAP연산 효율을 증가시키기 위한 여러 가지 연구들이 행하여지고 있다. 이들 연구의 대부분은 다중트리구조에 기반하고 있다. 다중트리구조는 공간차원을 색인하기 위한 하나의 R-tree와 시간차원을 색인하기 위한 다수의 B-tree로 이루어져 있다. 하지만, 이러한 다중트리구조는 높은 유지비용과 불충분한 질의 처리 효율로 인해 현실적으로 시공간 OLAP연산에 적용하기에는 어려운 점이 있다. 본 논문에서는 이러한 문제를 근본적으로 개선하기 위한 접근 방법으로서 힐버트큐브(Hilbert Cube, H-Cube)를 제안하고 있다. H-Cube는 집계질의(aggregation query) 처리 효율을 높이기 위해 힐버트 곡선을 이용하여 셀들에게 완전순서(total-order)를 부여하고 있으며, 아울러 전통적인 누적합(prefix-sum) 기법을 함께 적용하고 있다. H-Cube는 적응적이며, 완전순서화되어 있으며, 또한 누적합을 이용한 셀 기반의 색인구조이다. 본 논문에서는 H-Cube의 성능 평가를 위해서 다양한 실험을 하였으며, 그 결과로서 유지비용과 질의 처리 효율성면 모두에서 다중트리구조보다 높은 성능 향상이 있음을 보인다.