• 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 the Economic Geographical Society of Korea
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• v.16 no.1
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• pp.1-16
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• 2013

This study investigates the spatial distribution characteristics of Korean fashion industries during the last decade, in which the economic geography of fashion industries has changed dynamically with economic globalization and "thus resulted in increased" demand "of" diversification. In particular, this study examines the spatial distribution patterns of fashion industries in the Seoul metropolitan area where fashion industries are highly agglomerated. For the purpose, this study applies Moran's I Index of spatial autocorrelation analysis for seven functional sectors of fashion industries related to fashion production. The global and local agglomeration patterns are examined for each functional sector. The results clarify the distinction in the spatial agglomeration patterns among the seven functional sectors of fashion industries in the Seoul Metropolitan area. Logit models are developed to examine the interrelationships among functional sectors in their spatial agglomeration distribution patterns. By conducting binary logistic regression analysis, we find out how the spatial agglomeration of each functional sector is related to the others.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.75-86
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• 2007

The subjects were fifteen dong at downtown of Busan. LQ index and cluster analysis were used to research space functions of downtown in both years, that is to say, 2000 and 2005. At the analysis of LQ index in 2000, the secondary industries were specialized at traditional markets as well as large-scaled commercial districts, while the tertiary industries were done at financial business districts. LQ index in 2005 did not make change mostly comparing with the one in 2000: But, main businesses at downtown that belonged to the tertiary industries rapidly dwindled at old downtown to make appearance at Seomyeon of new downtown. Main businesses at old downtown in the past moved to new downtown to dwindle main functions at old downtown. The cluster analysis was done by using LQ index to classify into three clusters. The first cluster was old downtown that functions of downtown dwindle, and the second cluster was residence area, and the third cluster was the area where space function at downtown was very much active. The findings were as follow: Firstly, various kinds of urban regeneration plans should be made to control dwindling of old downtown and to establish comprehensive and systematic plans on new downtown. Secondly, downtown space functions could be placed depending upon specialization of each industry so that industries being suitable to the area should be introduced to construct development base.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.3
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• pp.35-46
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• 2013

In order to develop an accurate analytical model for domestic electricity demand forecasting, we propose a prediction method of the electric power demand pattern by combining SMO classification techniques and a dimension reduction conceptualized subspace clustering techniques suitable for high-dimensional data cluster analysis. In terms of electricity demand pattern prediction, hourly electricity load patterns and the demographic and geographic characteristics can be analyzed by integrating the wireless load monitoring data as well as sub-regional unit of census information. There are composed of a total of 18 characteristics clusters in the prediction result for the sub-regional demand pattern by using census information and power load of Seoul metropolitan area. The power demand pattern prediction accuracy was approximately 85%.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.261-262
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• 2016

교통사고의 발생요인에는 다양한 원인들이 있지만 본 연구에서는 공간적으로 접근하여 사고유형별 분포특성을 도출하기 위해 공간적 자기상관성 분석을 수행하였다. 논문에서는 2012년부터 2014년까지 울산광역시에서 발생된 교통사고를 대상으로 분석을 수행하였다. 그 결과 울산시 전체 교통사고 약 53%는 안전운전불이행이며 다음으로는 안전거리미확보, 신호위반 순으로 나타났다. 밀도분석 결과는 사고유형별로 분포가 차이가 있었으며 안전운전불이행의 경우 가장 큰 군집은 중심시가지인 달동과 삼산동 중심에 나타났으며 중앙선침범은 도시의 중심부 보다는 면지역에 넓게 퍼져서 발생되었으며 산업단지가 있는 동구지역에 군집이 크게 나타났다. 따라서 읍면동별 공간적 특성을 파악하기 위해 Moran's I분석과 LISA분석을 수행한 결과 안전운전불이행, 안전거리미확보, 신호위반, 교차로운행방해 모두 중심시가지인 신정동, 달동, 삼산동이 공간적 자기상관성이 높았으며 중앙선침범의 경우 밀도분석 결과와 마찬가지로 중심시가지 이외에 읍면 지역도 자기상관성이 더 높게 나타났다. 이를 통해 사고유형별 공간의존성 및 이질성을 파악하여 교통사고 다발지역을 도출하고 이를 토대로 지역특성에 맞는 저감 대책 마련에 활용되고자 한다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.138-143
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• 2009

본 논문에서는 감성 공간에서 mean shift clustering과 user feedback을 이용하여 영상 검색 결과를 개선하기 위한 시스템을 제안한다. 제안된 시스템은 사용자 인터페이스, 감성 공간 변환, 검색결과 순위 재지정(re-ranking)으로 구성된다. 사용자 인터페이스는 텍스트 형태의 질의 입력과 감성 어휘 선택에 따른 user feedback에 의해 개선된 검색결과를 보인다. 사용된 감성 어휘는 고바야시가 정의한 romantic, natural, casual, elegant, chic, classic, dandy, modern 등의 8개 어휘를 사용한다. 감성 공간 변환 단계에서는 입력된 질의에 따라 웹 영상 검색 엔진(Yahoo)에 의해 검색된 결과 영상들에 대해 컬러와 패턴정보의 특징을 추출하고, 이를 입력으로 하는 8개의 각 감성별 분류기에 의해 각 영상은 8차원 감성 공간으로의 특징 벡터로 변환된다. 이때 감성 공간으로 변환된 특징 벡터들은 mean shift clustering을 통해 군집화 되고, 그 결과로써 대표 클러스터를 찾게 된다. 검색결과 순위 재지정 단계에서는 user feedback 유무에 따라 대표 클러스터의 평균 벡터와 user feedback에 의해 생성된 사용자 감성 벡터에 의해 검색 결과를 개선할 수 있다. 이때 각 기준에 따라 유사도가 결정되고 검색결과 순위가 재지정 된다 제안된 시스템의 성능을 검증하기 위해 7개의 질의의 각 400장, 총 2,800장에 대한 Yahoo 검색 결과와 제안된 시스템을 개선된 검색 결과를 비교하였다.

• Korean Journal of Remote Sensing
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• v.19 no.2
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• pp.135-147
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• 2003

This study used the multistage hierarchical clustering image classification to analyze the satellite images for the land-cover types of an area in the Korean peninsula. The multistage algorithm consists of two stages. The first stage performs region-growing segmentation by employing a hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous, and finally the whole image space is segmented into sub-regions where adjacent regions have different physical properties. Without spatial constraints for merging, the second stage clusters the segments resulting from the previous stage. The image classification of hierarchical clustering, which merges step-by step two small groups into one large one based on the hierarchical structure of digital imagery, generates a hierarchical tree of the relation between the classified regions. The experimental results show that the hierarchical tree has the detailed information on the hierarchical structure of land-use and more detailed spectral information is required for the correct analysis of land-cover types.

• 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.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.2
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• pp.175-191
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• 2008

In the early stage of industrial development, most of software companies were agglomerated at the CBD(Central Business Districts) in Seoul. However, the spatial distribution pattern of Korean Software industry has been changed according to the propagation of broadband, the change in rents, the governmental policy for industrial districts. In this research, using the software year book at 1997 and 2007, the emerging new pattern was analyzed using spatial clustering analysis. As a results of research, the spatial distribution was expanded in morphological changes. However, it was found that there was not a significant difference in a degree of accumulation. In the aspect of behavioral movement of companies, they tend to be relocated from the CBD to urban fringes and their movement is related to the product life cycle in selecting the clustered place.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.2
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• pp.292-303
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• 2012

The main purpose of this study is to analyze R&D networks and spatial implications in Qingdao consumer electronics industry agglomeration in China. The characteristics of R&D networks in Qindao consumer electronic industry are as follows. There is a cluster central around large enterprises led by the government and their subcontracting enterprises. However, the degree of collaborative networks in intra-firm, inter-firm, firm-research institutes(including university lab.) is relatively low. Therefore, Large enterprises in Qingdao has stimulated research collaborations with firms and research institutes located in other regions rather than within region. It is likely to show that R&D networks of consumer electronics industry has not been stimulated in Qingdao. Therefore, collaborative R&D networks among firms, research institutes and governments should be stimulated to build regional innovation systems central around consumer electronics industry in Qingdao.