• Title/Summary/Keyword: Spatial Clusters

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Data Correlation-Based Clustering Algorithm in Wireless Sensor Networks

  • Yeo, Myung-Ho;Seo, Dong-Min;Yoo, Jae-Soo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.3 no.3
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    • pp.331-343
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    • 2009
  • Many types of sensor data exhibit strong correlation in both space and time. Both temporal and spatial suppressions provide opportunities for reducing the energy cost of sensor data collection. Unfortunately, existing clustering algorithms are difficult to utilize the spatial or temporal opportunities, because they just organize clusters based on the distribution of sensor nodes or the network topology but not on the correlation of sensor data. In this paper, we propose a novel clustering algorithm based on the correlation of sensor data. We modify the advertisement sub-phase and TDMA schedule scheme to organize clusters by adjacent sensor nodes which have similar readings. Also, we propose a spatio-temporal suppression scheme for our clustering algorithm. In order to show the superiority of our clustering algorithm, we compare it with the existing suppression algorithms in terms of the lifetime of the sensor network and the size of data which have been collected in the base station. As a result, our experimental results show that the size of data is reduced and the whole network lifetime is prolonged.

Recent Spatial and Temporal Trends of Malaria in Korea

  • Kim, Yeong Hoon;Ahn, Hye-Jin;Kim, Dongjae;Hong, Sung-Jong;Kim, Tong-Soo;Nam, Ho-Woo
    • Parasites, Hosts and Diseases
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    • v.59 no.6
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    • pp.585-593
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    • 2021
  • This study was done to provide an analytical overview on the latest malaria infection clusters by evaluating temporal trends during 2010-2019 in Korea. Incheon was the most likely cluster (MLC) for all cases of malaria during the total period. MLCs for P. falciparum, vivax, malariae, ovale, and clinically diagnosed malaria without parasitological confirmation were Jeollanam-do, Incheon, Gangwon-do, Gyeongsangnam-do, and Jeollabuk-do, respectively. Malaria was decreasing in most significant clusters, but Gwangju showed an increase for all cases of malaria, P. vivax and clinically diagnosed cases. Malaria overall, P. falciparum and P. vivax seem to be under control thanks to aggressive health measures. This study might provide a sound scientific basis for future control measures against malaria in Korea.

Identifying the Optimal Number of Homogeneous Regions for Regional Frequency Analysis Using Self-Organizing Map (자기조직화지도를 활용한 동일강수지역 최적군집수 분석)

  • Kim, Hyun Uk;Sohn, Chul;Han, Sang-Ok
    • Spatial Information Research
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    • v.20 no.6
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    • pp.13-21
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    • 2012
  • In this study, homogeneous regions for regional frequency analysis were identified using rainfall data from 61 observation points in Korea. The used data were gathered from 1980 to 2010. Self organizing map and K-means clustering based on Davies-Bouldin Index were used to make clusters showing similar rainfall patterns and to decide the optimum number of the homogeneous regions. The results from this analysis showed that the 61 observation points can be optimally grouped into 6 geographical clusters. Finally, the 61 observations points grouped into 6 clusters were mapped regionally using Thiessen polygon method.

A Study on the Preference for the Way of Composing the Unit Plan for Apartment Houses by Lifestyle (라이프스타일에 따른 공동주택 단위평면 공간구성방식에 관한 선호도 조사.연구)

  • Jun, Su-Young;Park, Seung-Hwan;Kim, Sung-Hwa;Choi, Moo-Hyuck
    • Journal of the Korean housing association
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    • v.17 no.5
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    • pp.147-157
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    • 2006
  • A study on Composing Unit Spaces of Apartment Houses according to the Differentiation in Lifestyle by survey on preferences. The purpose of this study is to propose composition models of unit spaces for 85m2 net area apartment houses by lifestyle types. This study set up a hypothesis that there is a critical divergence of preferences in composition types of unit spaces according to lifestyle. To prove the hypothesis, investigation on variable floor plans of apartments to extract spatial composition types of units and questionnaire survey on lifestyleand preferences for composition types were implemented. To extract several factors regarding, characteristics of lifestyle, factor analysis, was implemented for each variable. Cluster analysis was conducted to cluster interviewees by similarity of lifestyle. To identify and define how each factor reacts, ANOVA and cross tabulation analysis between factors and clusters were used. The type of spatial composition was analyzed by plane characteristic, spatial relation and spatial usability on the basis of apartment plate type. As a result, lifestyle was divided into three types: reasonable lifestyle, trend-seeking lifestyle and conservative lifestyle. As, the result of investigating characteristics for the type of spatial composition according to the type of lifestyle, preferred types and main districts were different. Therefore, the hypothesis was proved.

Optimizing the maximum reported cluster size for normal-based spatial scan statistics

  • Yoo, Haerin;Jung, Inkyung
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.373-383
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    • 2018
  • The spatial scan statistic is a widely used method to detect spatial clusters. The method imposes a large number of scanning windows with pre-defined shapes and varying sizes on the entire study region. The likelihood ratio test statistic comparing inside versus outside each window is then calculated and the window with the maximum value of test statistic becomes the most likely cluster. The results of cluster detection respond sensitively to the shape and the maximum size of scanning windows. The shape of scanning window has been extensively studied; however, there has been relatively little attention on the maximum scanning window size (MSWS) or maximum reported cluster size (MRCS). The Gini coefficient has recently been proposed by Han et al. (International Journal of Health Geographics, 15, 27, 2016) as a powerful tool to determine the optimal value of MRCS for the Poisson-based spatial scan statistic. In this paper, we apply the Gini coefficient to normal-based spatial scan statistics. Through a simulation study, we evaluate the performance of the proposed method. We illustrate the method using a real data example of female colorectal cancer incidence rates in South Korea for the year 2009.

Performance Evaluation of Spatial Clustering Method using Regular Grid (균등 격자를 이용한 공간 클러스터링 기법의 성능 평가)

  • 문상호
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.468-471
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    • 2003
  • In this paper, experimental tests are performed to evaluate the efficiency of spatial clustering method using regular grid that is proposed in our recent research. In details, we estimate the execution time for finding clusters varying spatial objects on sample data sets with various distributions and perform experimental tests varying threshold value on a data set. We also compare the running time of cluster generating algorithm with that of cluster merging algorithm per each test.

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A Clustering Method for Optimizing Spatial Locality (공간국부성을 최적화하는 클러스터링 방법)

  • 김홍기
    • Journal of KIISE:Databases
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    • v.31 no.2
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    • pp.83-90
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    • 2004
  • In this paper, we study the CCD(Clustering with Circular Distance) and the COD(Clustering with Obstructed Distance) problems to be considered when objects are being clustered in a circularly search space and a search space with the presence of obstacles. We also propose a now clustering algorithm for clustering efficiently objects that the insertion or the deletion is occurring frequently in multi-dimensional search space. The distance function for solving the CCD and COD Problems is defined in the Proposed clustering algorithm. This algorithm is included a clustering method to create clusters that have a high spatial locality by minimum computation time.

Hybrid Diversity-Beamforming Technique for Outage Probability Minimization in Spatially Correlated Channels

  • Kwon, Ho-Joong;Lee, Byeong-Gi
    • Journal of Communications and Networks
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    • v.9 no.3
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    • pp.274-281
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    • 2007
  • In this paper, we present a hybrid multi-antenna technique that can minimize the outage probability by combining the diversity and beamforming techniques. The hybrid technique clusters the transmission antennas into multiple groups and exploit diversity among different groups and beamforming within each group. We analyze the performance of the resulting hybrid technique for an arbitrary correlation among the transmission antennas. Through the performance analysis, we derive a closed-form expression of the outage probability for the hybrid technique. This enables to optimize the antenna grouping for the given spatial correlation. We show through numerical results that the hybrid technique can balance the trade-offs between diversity and beamforming according to the spatial correlation and that the optimally designed hybrid technique yields a much lower outage probability than the diversity or beamforming technique does in partially correlated fading channels.

An Analysis of Relocation of SW Industries using GIS Flow Map (GIS 흐름도 기법에 의한 소프트웨어 기업 이동의 동태적 분석)

  • Choi, Jun-Young;Oh, Kyu-Shik
    • Spatial Information Research
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    • v.18 no.3
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    • pp.41-52
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    • 2010
  • This paper analyzed the interregional flow changes of software (SW) industries using a GIS Flow Map. Employment data for SW enterprise headquarters from 1999 until 2008 were constructed according to the Origin-Destination Matrix, and were mapped and analyzed using the Flow Mapper and ArcGIS Flow Data Model. From the result we can identify the decentralization of interregional flow in SW industries and recognize the possibilities of the larger SW enterprises' employment, the higher locational footlooseness. The GIS Flow Map was identified as useful tool for researching growth, decline and spatial movement of industrial clusters that experience business relocation. This method can be applied to understand and visualize urban spatial changes.

Spatial Changes in Work Capacity for Occupations Vulnerable to Heat Stress: Potential Regional Impacts From Global Climate Change

  • Kim, Donghyun;Lee, Junbeom
    • Safety and Health at Work
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    • v.11 no.1
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    • pp.1-9
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    • 2020
  • Background: As the impact of climate change intensifies, exposure to heat stress will grow, leading to a loss of work capacity for vulnerable occupations and affecting individual labor decisions. This study estimates the future work capacity under the Representative Concentration Pathways 8.5 scenario and discusses its regional impacts on the occupational structure in the Republic of Korea. Methods: The data utilized for this study constitute the local wet bulb globe temperature from the Korea Meteorological Administration and information from the Korean Working Condition Survey from the Occupational Safety and Health Research Institute of Korea. Using these data, we classify the occupations vulnerable to heat stress and estimate future changes in work capacity at the local scale, considering the occupational structure. We then identify the spatial cluster of diminishing work capacity using exploratory spatial data analysis. Results: Our findings indicate that 52 occupations are at risk of heat stress, including machine operators and elementary laborers working in the construction, welding, metal, and mining industries. Moreover, spatial clusters with diminished work capacity appear in southwest Korea. Conclusion: Although previous studies investigated the work capacity associated with heat stress in terms of climatic impact, this study quantifies the local impacts due to the global risk of climate change. The results suggest the need for mainstreaming an adaptation policy related to work capacity in regional development strategies.