• Title/Summary/Keyword: 시공간 클러스터

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Space-time cluster research of R&D industry in Seoul, Korea (서울시 R&D 산업체의 시공간 클러스터 분석)

  • Park, Sun-Young;Kim, Youngho
    • 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.

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Cancer cluster detection using scan statistic (스캔 통계량을 이용한 암 클러스터 탐색)

  • Han, Junhee;Lee, Minjung
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1193-1201
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    • 2016
  • In epidemiology or etiology, we are often interested in identifying areas of elevated risk, so called, hot spot or cluster. Many existing clustering methods only tend to a result if there exists any clustering pattern in study area. Recently, however, lots of newly introduced clustering methods can identify the location, size, and shape of clusters and test if the clusters are statistically significant as well. In this paper, one of most commonly used clustering methods, scan statistic, and its implementation SaTScan software, which is freely available, will be introduced. To exemplify the usage of SaTScan software, we used cancer data from the SEER program of National Cancer Institute of U.S.A.We aimed to help researchers and practitioners, who are interested in spatial cluster detection, using female lung cancer mortality data of the SEER program.

Prediction of Consumer Propensity to Purchase Using Geo-Lifestyle Clustering and Spatiotemporal Data Cube in GIS-Postal Marketing System (GIS-우편 마케팅 시스템에서 Geo-Lifestyle 군집화 및 시공간 데이터 큐브를 이용한 구매.소비 성향 예측)

  • Lee, Heon-Gyu;Choi, Yong-Hoon;Jung, Hoon;Park, Jong-Heung
    • Journal of Korea Spatial Information System Society
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    • v.11 no.4
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    • pp.74-84
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    • 2009
  • GIS based new postal marketing method is presented in this paper with spatiotemporal mining to cope with domestic mail volume decline and to strengthening competitiveness of postal business. Market segmentation technique for socialogy of population and spatiotemporal prediction of consumer propensity to purchase through spatiotemporal multi-dimensional analysis are suggested to provide meaningful and accurate marketing information with customers. Internal postal acceptance & external statistical data of local districts in the Seoul Metropolis are used for the evaluation of geo-lifestyle clustering and spatiotemporal cube mining. Successfully optimal 14 maketing clusters and spatiotemporal patterns are extracted for the prediction of consumer propensity to purchase.

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Design and Implementation of Disk-based Location Information Manager of GALIS (GALIS의 디스크 기반 위치 정보 관리기의 설계 및 구현)

  • 고영균;나연묵
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10b
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    • pp.85-87
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    • 2003
  • 최근 들어 이동통신 환경의 급격한 발달로 이를 활용한 위치기반 서비스에 대한 관심이 높아지고 있다. 효율적인 위치기반 서비스를 위해서는 실시간으로 위치를 변화시키는 이동객체에 대한 저장. 관리 및 질의를 담당할 수 있는 시공간 데이타베이스 관리 시스템의 존재가 필수적이다. 본 논문은 클러스터 기반 분산 컴퓨팅 구조를 바탕으로 제안된 시공간 데이타베이스 관리 시스템인 GALIS 구조 중에서 이동객체의 과거 위치 데이타를 디스크를 기반으로 저장 및 관리하는 노드인 LDP와 이동객체 데이터 생성기를 TMO 프로그래밍 스킴과 상용 데이타베이스 엔진을 사용하여 구현하였다. 제안 시스템은 대용량 이동객체의 효율적인 관리를 위한 실시간 엔진 개발에 활용될 수 있다.

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Spatio-temporal Analysis using Real-Time Data Processing for Wireless Sensor Networks (무선 센서 네트워크에서 실시간 데이터 처리를 이용한 시공간 분석)

  • Baek, Jeong-Ho;Mun, Young-Chae;Lee, Hong-Ro
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.6
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    • pp.688-692
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    • 2010
  • Wireless sensor network system collects and analyzes real-time data that have been requested by the many application nodes. This paper has constructed a sensor network cluster with various elements in the Gunsan City area of Jeollabuk-do, S.korea. The purpose of this paper is to utilize the constructed system in order to illustrate the real-time data in a diagram and analyze it to deduce the change ratio. The resulting analysis contents allow simple data interpretation by illustrating the data in change ratio by time, space, and motional directions. This analytical method will offer great benefit to those users using the wireless sensor network.

Cluster-based Continuous Object Prediction Algorithm for Energy Efficiency in Wireless Sensor Networks (무선 센서 네트워크에서 에너지 효율성을 위한 클러스터 기반의 연속 객체 예측 기법)

  • Lee, Wan-Seop;Hong, Hyung-Seop;Kim, Sang-Ha
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.8C
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    • pp.489-496
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    • 2011
  • Energy efficiency in wireless sensor networks is a principal issue to prolong applications to track the movement of the large-scale phenomena. It is a selective wakeup approach that is an effective way to save energy in the networks. However, most previous studies with the selective wakeup scheme are concentrated on individual objects such as intruders and tanks, and thus cannot be applied for tracking continuous objects such as wild fire and poison gas. This is because the continuous object is pretty flexible and volatile due to its sensitiveness to surrounding circumferences so that movable area cannot be estimated by the just spatiotemporal mechanism. Therefore, we propose a cluster-based algorithm for applying the efficient and more accurate technique to the continuous object tracking in enough dense sensor networks. Proposed algorithm wakes up the sensors in unit cluster where target objects may be diffused or shrunken. Moreover, our scheme is asynchronous because it does not need to calculate the next area at the same time.

Implementation of GALIS SLDS prototype for managing large volumes of location data (대용량 위치 데이타 관리를 위한 GALIS의 SLDS 프로토타입 구현)

  • 이운주;이준우;나연묵
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.46-48
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    • 2004
  • 최근의 위치 측위 기술과 무선 통신 기술의 발전에 따라 위치 기반 서비스에 대한 관심이 크게 증가하고 있다. 기존 연구의 단일 노드 기반 시스템으로는 휴대폰 사용자와 같은 대용량의 객체를 처리하는데 어려움이 있다. 본 논문에서는 대용량 이동 객체의 시공간 정보를 관리하기 위해 클러스터 기반 분산 컴퓨팅 구조로 제안된 GALIS(Gracefully Aging Location Information System)의 아키텍쳐 중 객체의 현재 위치 정보를 관리하는 SLDS(Short-term Location Data Subsystem)의 프로토 타입을 개발하였다. 본 논문에서 구현한 시스템은 메인 메모리 데이터 베이스를 사용하여 디스크 접근 시간이 없고 현재 정보와 과거 정보를 분리하여 빠른 검색이 가능하기 때문에 대용량 이동 객체를 관리하며 빠른 응답을 필요로 하는 상황에 효과적으로 대응할 수 있는 이점이 있다.

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Dentifying and Clustering the Flood Impacted Areas for Strategic Information Provision (전략적 정보제공을 위한 침수영향구역 클러스터링)

  • Park, Eun Mi;Bilal, Muhammad
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.100-109
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    • 2021
  • Flooding usually brings in disruptions and aggravated congestions to the roadway network. Hence, right information should be provided to road users to avoid the flood-impacted areas and for city officials to recover the network. However, the information about individual link congestion may not be conveyed to roadway users and city officials because too many links are congested at the same time. Therefore, more significant information may be desired, especially in a disastrous situation. This information may include 1) which places to avoid during flooding 2) which places are feasible to drive avoiding flooding. Hence, this paper aims to develop a framework to identify the flood-impacted areas in a roadway network and their criticality. Various impacted clusters and their spatiotemporal properties were identified with field data. From this data, roadway users can reroute their trips, and city officials can take the right actions to recover the affected areas. The information resulting from the developed framework would be significant enough for roadway users and city officials to cope with flooding.

A Spatial Statistical Method for Exploring Hotspots of House Price Volatility (부동산 가격변동 한스팟 탐색을 위한 공간통계기법)

  • Sohn, Hak-Gi;Park, Key-Ho
    • Journal of the Korean Geographical Society
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    • v.43 no.3
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    • pp.392-411
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    • 2008
  • The purpose of this paper is to develop a method for exploring hotspot patterns of house price volatility where there is a high fluctuation in price and homogeneity of direction of price volatility. These patterns are formed when the majority of householders in an area show an adaptive tendency in their decision making. This paper suggests a method that consists of two analytical parts. The first part uses spatial scan statistics to detect spatial clusters of houses with a positive range of price volatility. The second part utilizes local Moran's I to evaluate the homogeneity of direction of price volatility within each cluster. The method is applied to the areas of Gangnam-Gu, Seocho-Gu, and Songpa-Gu in Seoul from August to November of 2003; the Participatory Government of Korea designated these areas and this period as the most speculative. The results of the analysis show that the area around Gaepo-Dong was as a hotspot before the Government's anti-speculative 10.29 policy in 2003; the house prices in the same area stabilized in October, 2003 and the area was identified as a coldspot in December, 2003. This case study shows that the suggested method enables exploration of hotspot of house price volatility at micro spatial scales which had not been detected by visual analysis.

Real-Time Monitoring and Buffering Strategy of Moving Object Databases on Cluster-based Distributed Computing Architecture (클러스터 기반 분산 컴퓨팅 구조에서의 이동 객체 데이타베이스의 실시간 모니터링과 버퍼링 기법)

  • Kim, Sang-Woo;Jeon, Se-Gil;Park, Seung-Yong;Lee, Chung-Woo;Hwang, Jae-Il;Nah, Yun-Mook
    • Journal of Korea Spatial Information System Society
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    • v.8 no.2 s.17
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    • pp.75-89
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    • 2006
  • LBS (Location-Based Service) systems have become a serious subject for research and development since recent rapid advances in wireless communication technologies and position measurement technologies such as global positioning system. The architecture named the GALIS (Gracefully Aging Location Information System) has been suggested which is a cluster-based distributed computing system architecture to overcome performance losses and to efficiently handle a large volume of data, at least millions. The GALIS consists of SLDS and LLDS. The SLDS manages current location information of moving objects and the LLDS manages past location information of moving objects. In this thesis, we implement a monitoring technique for the GALIS prototype, to allow dynamic load balancing among multiple computing nodes by keeping track of the load of each node in real-time during the location data management and spatio-temporal query processing. We also propose a buffering technique which efficiently manages the query results having overlapped query regions to improve query processing performance of the GALIS. The proposed scheme reduces query processing time by eliminating unnecessary query execution on the overlapped regions with the previous queries.

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