• Title/Summary/Keyword: Spatial Clustering

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Design and Implementation of Load Balancing Method for Efficient Spatial Query Processing in Clustering Environment (클러스터링 환경에서 효율적인 공간 질의 처리를 위한 로드 밸런싱 기법의 설계 및 구현)

  • 김종훈;이찬구;정현민;정미영;배영호
    • Journal of Korea Multimedia Society
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    • v.6 no.3
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    • pp.384-396
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    • 2003
  • Hybrid query processing method is used for preventing server overload that is created by heavy user connection in Web GIS. In Hybrid query processing method, both server and client participate in spatial query processing. But, Hybrid query processing method is restricted in scalability of server and it can't be fundamentally solution for server overload. So, it is necessary for Web GIS to be brought in web clustering technique. In this thesis, we propose load-balancing method that uses proximity of query region. In this paper, we create tile groups that have relation each tile in same group is very close, and forward client request to the server that can have maximum rate of buffer reuse with considering characteristic of spatial query. With out load balancing method, buffet in server is optimized for exploring spatial index tree and increase rate of buffer reuse, so it can be reduced amount of disk access and increase system performance.

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Spatial Typification based on Heat Balance for Improving Thermal Environment in Seoul (열수지를 활용한 서울시 열환경 개선을 위한 공간 유형화)

  • Kwon, You Jin;Ahn, Saekyul;Lee, Dong Kun;Yoon, Eun Joo;Sung, Sunyong;Lee, Kiseung
    • Journal of Korea Planning Association
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    • v.53 no.7
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    • pp.109-126
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    • 2018
  • The purpose of this study is to identify the spatial types for thermal environment improvement considering heat flux and its spatial context through empirical orthodox formulas. First, k-means clustering was used to classify values of three kinds of heat flux - latent, sensible and storage heat. Next, from the k-means clustering, we defined a type of thermal environment (type LHL) where improvement is needed for more comfortable and pleasant thermal environment in the city, among the eight types. Lastly, we compared and analyzed the characteristics of each classified thermal environmental types based on land cover types. From the study, we found that the ratio of impervious surfaces, roads, and buildings of the type LHL is higher than those of the type HLH (relatively thermal comfort environment). In order to improve the thermal environment, the following contents are proposed to urban planners and designers depending on the results of the study. a) Increase the green zone rate by 10% to reduce sensible heat; b) Reduce the percentage of impermeable surfaces and roads by 10% ; c) Latent heat increases when water and green spaces are expanded. This study will help to establish a minimum criterion for a land cover rate for the improvement of the urban thermal environment and a standard index for the thermal environmental improvement can be derived.

A Study on Clustering Representative Color of Natural Environment of Korean Peninsula for Optimal Camouflage Pattern Design (최적 위장무늬 디자인을 위한 한반도 자연환경 대표 색상 군집화 연구)

  • Chun, Sungkuk;Kim, Hoemin;Yoon, Seon Kyu;Yun, Jeongrok;Kim, Un Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.315-316
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    • 2019
  • 전투복, 군용 천막 등에 사용되는 위장무늬는 군 작전 수행 시 주변 환경의 색상, 패턴을 모사하여 개인병사 및 무기체계의 위장 기능을 극대화하고, 이를 통해 아군의 생명과 시설피해를 최소화하기 위한 목적으로 사용된다. 특히 최근 들어 군의 작전환경과 임무가 복잡하고 다양해짐에 따라, 작전환경에 대한 데이터의 취득 및 정량적 분석을 통해 전장 환경에 최적화된 위장무늬 패턴 및 색상 추출에 대한 연구의 필요성이 증대되고 있다. 본 논문에서는 한반도 자연환경 영상에 대한 자기 조직화 지도(SOM, Self-organizing Map) 기반의 한반도 자연환경 대표 색상 군집화 연구 방법에 대해 서술한다. 이를 위해 한반도 내 위도를 고려한 장소에서 시간별, 계절별 자연환경 영상 수집을 진행하며, 수집된 영상 내 다수의 화소의 군집화를 위해 2차원 SOM을 활용한다. 영상 내 각 화소의 색상 값에 대한 SOM의 학습 시, RGB공간상의 색차/색상 인지 왜곡을 피하기 위하여 CIEDE2000 색차 식을 통해 군집화를 진행한다. 실험결과에서는 온라인상으로 수집한 여름 및 가을철 대표 색상 군집화 결과와, 현재까지 수집된 계절별 자연환경 사진 내 6억 7648개 화소에 대한 대표 색상 군집화 결과를 보여준다.

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A Study on the Influence of Commercial Facility Diversity on the Formation of Consumption Centre: Application of Spatial Regression Models (상업시설의 다양성이 소비중심지 형성에 미치는 영향에 관한 연구: 공간회귀모형의 적용)

  • Sul-Hee Kim;Heung-Soon Kim
    • Land and Housing Review
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    • v.15 no.1
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    • pp.57-75
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    • 2024
  • To create dynamic and bustling urban environments, a diverse array of commercial facilities is indispensable. These facilities are recognised as pivotal in attracting and accommodating a larger floating population, thereby suggesting that a greater diversity of commercial establishments fosters heightened consumer expenditure. With this premise, our study endeavours to explore the influence of commercial facility diversity on the Consumer Centre Index. Focused on the temporal context of 2021 and the spatial context of Seoul, our analysis utilizes the Consumer Centre Index, derived from Kernel Density analysis, as the dependent variable. Independent variables encompass factors reflecting commercial attributes and urban characteristics. Employing spatial regression analysis at the administrative district level, we discern that the clustering of similar industries exerts a more pronounced positive effect on consumer activation compared to the clustering of disparate industries. Additionally, the findings underscore the importance of concentrating industries that bolster consumer activation. Anticipated outcomes of this study include insights beneficial for optimizing commercial facility location policies within the consumer market.

Detection of Moving Objects in Crowded Scenes using Trajectory Clustering via Conditional Random Fields Framework (Conditional Random Fields 구조에서 궤적군집화를 이용한 혼잡 영상의 이동 객체 검출)

  • Kim, Hyeong-Ki;Lee, Gwang-Gook;Kim, Whoi-Yul
    • Journal of Korea Multimedia Society
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    • v.13 no.8
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    • pp.1128-1141
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    • 2010
  • This paper proposes a method of moving object detection in crowded scene using clustered trajectory. Unlike previous appearance based approaches, the proposed method employes motion information only to isolate moving objects. In the proposed method, feature points are extracted from input frames first and then feature tracking is followed to create feature trajectories. Based on an assumption that feature points originated from the same objects shows similar motion as the object moves, the proposed method detects moving objects by clustering trajectories of similar motions. For this purpose an energy function based on spatial proximity, motion coherence, and temporal continuity is defined to measure the similarity between two trajectories and the clustering is achieved by minimizing the energy function in CRFs (conditional random fields). Compared to previous methods, which are unable to separate falsely merged trajectories during the clustering process, the proposed method is able to rearrange the falsely merged trajectories during iteration because the clustering is solved my energy minimization in CRFs. Experiment results with three different crowded scenes show about 94% detection rate with 7% false alarm rate.

The Pattern Segmentation of 3D Image Information Using FCM (FCM을 이용한 3차원 영상 정보의 패턴 분할)

  • Kim Eun-Seok;Joo Ki-See
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.5
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    • pp.871-876
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    • 2006
  • In this thesis, to accurately measure 3D face information using the spatial encoding patterns, the new algorithm to segment the pattern images from initial face pattern image is proposed. If the obtained images is non-homogeneous texture and ambiguous boundary pattern, the pattern segmentation is very difficult. Furthermore. the non-encoded areas by accumulated error are occurred. In this thesis, the FCM(fuzzy c-means) clustering method is proposed to enhance the robust encoding and segmentation rate under non-homogeneous texture and ambiguous boundary pattern. The initial parameters for experiment such as clustering class number, maximum repetition number, and error tolerance are set with 2, 100, 0.0001 respectively. The proposed pattern segmentation method increased 8-20% segmentation rate with conventional binary segmentation methods.

Chaff Echo Detecting and Removing Method using Naive Bayesian Network (나이브 베이지안 네트워크를 이용한 채프에코 탐지 및 제거 방법)

  • Lee, Hansoo;Yu, Jungwon;Park, Jichul;Kim, Sungshin
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.10
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    • pp.901-906
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    • 2013
  • Chaff is a kind of matter spreading atmosphere with the purpose of preventing aircraft from detecting by radar. The chaff is commonly composed of small aluminum pieces, metallized glass fiber, or other lightweight strips which consists of reflecting materials. The chaff usually appears on the radar images as narrow bands shape of highly reflective echoes. And the chaff echo has similar characteristics to precipitation echo, and it interrupts weather forecasting process and makes forecasting accuracy low. In this paper, the chaff echo recognizing and removing method is suggested using Bayesian network. After converting coordinates from spherical to Cartesian in UF (Universal Format) radar data file, the characteristics of echoes are extracted by spatial and temporal clustering. And using the data, as a result of spatial and temporal clustering, a classification process for analyzing is performed. Finally, the inference system using Bayesian network is applied. As a result of experiments with actual radar data in real chaff echo appearing case, it is confirmed that Bayesian network can distinguish between chaff echo and non-chaff echo.

Advanced Improvement for Frequent Pattern Mining using Bit-Clustering (비트 클러스터링을 이용한 빈발 패턴 탐사의 성능 개선 방안)

  • Kim, Eui-Chan;Kim, Kye-Hyun;Lee, Chul-Yong;Park, Eun-Ji
    • Journal of Korea Spatial Information System Society
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    • v.9 no.1
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    • pp.105-115
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    • 2007
  • Data mining extracts interesting knowledge from a large database. Among numerous data mining techniques, research work is primarily concentrated on clustering and association rules. The clustering technique of the active research topics mainly deals with analyzing spatial and attribute data. And, the technique of association rules deals with identifying frequent patterns. There was an advanced apriori algorithm using an existing bit-clustering algorithm. In an effort to identify an alternative algorithm to improve apriori, we investigated FP-Growth and discussed the possibility of adopting bit-clustering as the alternative method to solve the problems with FP-Growth. FP-Growth using bit-clustering demonstrated better performance than the existing method. We used chess data in our experiments. Chess data were used in the pattern mining evaluation. We made a creation of FP-Tree with different minimum support values. In the case of high minimum support values, similar results that the existing techniques demonstrated were obtained. In other cases, however, the performance of the technique proposed in this paper showed better results in comparison with the existing technique. As a result, the technique proposed in this paper was considered to lead to higher performance. In addition, the method to apply bit-clustering to GML data was proposed.

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The Changes in the Quality of Life Measure of the Seoul Metropolitan Area (수도권 삶의 질 지수 변동에 관한 연구)

  • Lee, Se-Hyung;Chang, Hoon;Rho, Jin-A
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.1
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    • pp.29-37
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    • 2011
  • The purpose of this research is to measure Quality of Life indices using Factor Analysis and Principle Component Analysis and to analyze the spatial patterns of Quality of life distribution in the Seoul Metropolitan Area in terms of spatial association using spatial statistics and spatial exploratory technique. In order to check the degree of clustering, this study used spatial autocorrelation indices, global Moran's I index. In addition, local scale analysis was conducted using Moran Scatterplot and Local Moran's I to identify the spatial association pattern and the high Quality of life. The analysis based on global statics showed that, in the Seoul Metropolitan Area, QoL Indices had been distributed with positive spatial association. According to the local spatial statistics, the general tendency of clustering H-H clusters which were mainly concentrated on the Seoul, L-H clusters were concentrated on the Kyunggi-Do and L-L Clusters showed the regional extent of lagging behind. However, in case of H-H, L-H Clusters they had been spread out in the Newtown as population increase.

Spatial Pattern Analysis for Distribution of Migratory Insect Pests at Paddy Field in Jeolla-province (전라도 지역 논벼에서 비래해충 개체군 분포의 공간패턴분석)

  • Park, Taechul;Choe, Hojeong;Jeong, Hyoujin;Jang, Hojung;Kim, Kwang Ho;Park, Jung-Joon
    • Korean journal of applied entomology
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    • v.57 no.4
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    • pp.361-372
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    • 2018
  • Migratory insect pest populations migrate from the southern China to Korea through jet streams. In Korea, 5 major migratory insect species are important, i.e. Nilaparvata lugens, Sogatella furcifera, Laodelphax striatellus, Cnaphalocrocis medinalis and Mythimma separate, which are damages to the major crops, rice. This study was conducted from late July 2016 to early September 2016 and from July 2017 to August 2017 in rice paddy of Jeolla-province. C. medinalis and M. separata collected using pheromone traps, while N. lugens, S. furcifera and L. striatellus collected using 3 methods (visual surveys, sweeping surveys, sticky traps). SADIE (Spatial Analysis by Distance IndicEs) among geostatistics was used to analyze migratory insect pests. SADIE was used to analyze spatial distribution and index of aggregation $I_a$, index of clustering $V_i$, $V_j$ were used to investigate the spatial distribution. Also, the clustering indices were mapped as red-blue plot. C. medinalis and M. separata showed different distribution based on SADIE spatial aggregation analysis and red-blue plot analysis. Initial spatial distributions of L. striatellus and other planthoppers were differed for sampling location and time.