• Title/Summary/Keyword: cluster method

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A Study on Energy Efficiency for Cluster-based Routing Protocol (클러스터 기반 라우팅 프로토콜의 에너지 효율성에 관한 연구)

  • Lee, Won-Seok;Ahn, Tae-Won;Song, ChangYoung
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.3
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    • pp.163-169
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    • 2016
  • To establish the equitable distribution of total energy load, a representative cluster based routing protocol LEACH selects cluster heads randomly in accordance with the pre-determined probability every round. But because the current energy level of sensor nodes is not considered, if a sensor node which has little residual energy is elected as a cluster head, it can not live to fulfil the role of cluster head which has big energy load. As a result, the first time of death of a node is quickened and the service quality of WSN gets worse. In this regard we propose a new routing method that, by considering the current energy of a cluster head and the distance between cluster heads and a base station, selects the sub cluster head for saving the energy of a cluster head. Simulation results show that the first time of death of a node prolongs, more data arrive at the base station and the service quality of WSN improves.

An improved LEACH-C routing protocol considering the distance between the cluster head and the base station (클러스터 헤드와 기지국간의 거리를 고려한 향상된 LEACH-C 라우팅 프로토콜)

  • Kim, TaeHyeon;Park, Sea Young;Kwon, Oh Seok;Lee, Jong-Yong;Jung, Kye-Dong
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.2
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    • pp.373-377
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    • 2022
  • Wireless sensor networks are being used in various fields. Wireless sensor networks are applied in many areas, such as security, military detection, environmental management, industrial control, and home automation. There is a problem about the limit of energy that the sensor network basically has. In this paper, we propose the LEACH-CCBD (Low Energy Adaptive Clustering hierarchy - Centrailized with Cluster and Basestation Distance) algorithm that uses energy efficiently by improving network transmission based on LEACH-C among the representative routing protocols. The LEACH-CCBD algorithm is a method of assigning a cluster head to a cluster head by comparing the sum of the distance from the member node to the cluster distance and the distance from the cluster node to the base station with respect to the membership of the member nodes in the cluster when configuring the cluster. The proposed LEACH-CCBD used Matlab simulation to confirm the performance results for each protocol. As a result of the experiment, as the lifetime of the network increased, it was shown to be superior to the LEACH and LEACH-C algorithms.

An Improved Resampling Technique using Particle Density Information in FastSLAM (FastSLAM 에서 파티클의 밀도 정보를 사용하는 향상된 Resampling 기법)

  • Woo, Jong-Suk;Choi, Myoung-Hwan;Lee, Beom-Hee
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.6
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    • pp.619-625
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    • 2009
  • FastSLAM which uses the Rao-Blackwellized particle filter is one of the famous solutions to SLAM (Simultaneous Localization and Mapping) problem that estimates concurrently a robot's pose and surrounding environment. However, the particle depletion problem arises from the loss of the particle diversity in the resampling process of FastSLAM. Then, the performance of FastSLAM degenerates over the time. In this work, DIR (Density Information-based Resampling) technique is proposed to solve the particle depletion problem. First, the cluster is constructed based on the density of each particle, and the density of each cluster is computed. After that, the number of particles to be reserved in each cluster is determined using a linear method based on the distance between the highest density cluster and each cluster. Finally, the resampling process is performed by rejecting the particles which are not selected to be reserved in each cluster. The performance of the DIR proposed to solve the particle depletion problem in FastSLAM was verified in computer simulations, which significantly reduced both the RMS position error and the feature error.

DARK MATTER CONTENT IN GLOBULAR CLUSTER NGC 6397

  • Shin, Jihye;Kim, Sungsoo S.;Lee, Young-Wook
    • Journal of The Korean Astronomical Society
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    • v.46 no.4
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    • pp.173-181
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    • 2013
  • We trace the dynamical evolution of dark matter (DM) content in NGC 6397, one of the native Galactic globular clusters (GCs). The relatively strong tidal field (Galactocentric radius of ~ 6 kpc) and short relaxation timescale (~0.3 Gyr) of the cluster can cause a significant amount of DM particles to evaporate from the cluster in the Hubble time. Thus, the cluster can initially contain a non-negligible amount of DM. Using the most advanced Fokker-Planck (FP) method, we calculate the dynamical evolution of GCs for numerous initial conditions to determine the maximum initial DM content in NGC 6397 that matches the present-day brightness and velocity dispersion profiles of the cluster. We find that the maximum allowed initial DM mass is slightly less than the initial stellar mass in the cluster. Our findings imply that NGC 6397 did not initially contain a significant amount of DM, and is similar to that of NGC 2419, the remotest and the most massive Galactic GC.

A Composite Cluster Analysis Approach for Component Classification (컴포넌트 분류를 위한 복합 클러스터 분석 방법)

  • Lee, Sung-Koo
    • The KIPS Transactions:PartD
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    • v.14D no.1 s.111
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    • pp.89-96
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    • 2007
  • Various classification methods have been developed to reuse components. These classification methods enable the user to access the needed components quickly and easily. Conventional classification approaches include the following problems: a labor-intensive domain analysis effort to build a classification structure, the representation of the inter-component relationships, difficult to maintain as the domain evolves, and applied to a limited domain. In order to solve these problems, this paper describes a composite cluster analysis approach for component classification. The cluster analysis approach is a combination of a hierarchical cluster analysis method, which generates a stable clustering structure automatically, and a non-hierarchical cluster analysis concept, which classifies new components automatically. The clustering information generated from the proposed approach can support the domain analysis process.

Vegetation Structure of Peucedanum japonicum Thunb. Community in Southern Coast of Korea

  • Kim, Seong-Min;Shin, Dong-Il;Yoon, Seong-Tak;Song, Hong-Seon
    • Korean Journal of Medicinal Crop Science
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    • v.15 no.5
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    • pp.357-361
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    • 2007
  • This study was conducted to evaluate the vegetation structure of the Peucedanum japonicum community by the phytosociological method of floristic composition table and cluster analysis on the southern coast of Korea. The vegetation of the Peucedanum japonicum community was classified mainly into 2 communities such as the Miscanthus sinensis community and the Lysimachia mauritiana-Rosa wichuraiana community. The Carex boottiana and Sedum oryzifolium community were classified as the lower rank of Miscanthus sinensis community. On level 1 of the cluster analysis of plant species, they were classified into Lysimachia mauritiana and Rosa wichuraiana group, also Miscanthus sinensis, Carex boottiana and Sedum oryzifolium in Peucedanum japonicum community, which is similar to the community classification shown in the synoptic table. On level 1 of the cluster analysis of relev, inland coast with Jejudo was Lysimachia mauritiana and Rosa wichuraiana of group such as level 1 of the cluster analysis of plant species, and island coast with Geomundo was Miscanthus sinensis Carex boottiana and Sedum oryzifolium of group such as cluster analysis of plant species.

Evaluation of Shopping Items: Focused on Purchase of Foreign Tourists in South Korea

  • Jeong, Dong-Bin
    • East Asian Journal of Business Economics (EAJBE)
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    • v.7 no.2
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    • pp.21-30
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    • 2019
  • Purpose - In this work, we categorize the 21 shopping items which foreign tourists purchase in South Korea and monitor the level of dissimilarity (or similarity) between each item by utilizing distance matrix, and both hierarchical and k-means cluster analyses, respectively, based on several purpose of visit attributes in 2017. In addition, multidimensional scaling (MDS) method is applied for mining visual appearance of proximities among shopping items based on purpose of visit attributes. Research design and methodology - This study is carried out in 2017 by Ministry of Culture, Sports and Tourism and conduct a face-to-face survey of foreign tourists from 20 countries who purchase shopping items in South Korea. CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0 are used to perform this work. Results - We ascertain that 21 shopping items can be classified into five similar groups which have homogeneous traits by going through two-step cluster analysis. We can position homogeneous places of cluster and shopping items joining each cluster. Conclusions - We can relatively assess patterns and characteristics of each shopping item, come by useful information in activating shopping tour based on the actual state of recognition of foreign tourists and practically apply to each tourism industry on underlying results.

Clusters Analysis According to Causal Attribution in Patients with Cancer (암환자가 지각한 원인지각 차원별 동질집단 분석)

  • Ryu, Eun-Jung;Choi, So-Young;Choi, Kyung-Sook
    • Asian Oncology Nursing
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    • v.3 no.1
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    • pp.66-74
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    • 2003
  • Purpose: This study is designed to identify clusters according to the causal attribution that people make about the cancer and to determine influences of coping behavior and depression as output of causal attribution. Method: The subjects were 192 patients who had been diagnosed cancer one year ago and attended an outpatient clinic. For cancer patients to be classified homogenious groups according to causal attribution, cluster analysis of subjects' ratings on the Causal Dimension Scale was been made. Results: Cluster 1(n=71) had patients with having external, stable and uncontrollable attribution. Cluster 2(n =70) had patients with having unstable and external controllable attribution regarding cause of cancer. They were not important whether cause of cancer was self or other. Cluster 3(n=51) had patients with having internal, unstable and internal controllable attribution. Coping behaviors between cluster 1 and 3 were significant difference. However, depression was not significant difference among clusters. Conclusion: Based upon these results, it is recommended that the developing training program to be changed to the more positive attribution is necessary.

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An Integrated Watershed Environmental Assessment and Classification of the Mid-Nakdong River Region (낙동강 중류 지역의 통합적 유역환경평가 및 유형화)

  • Jung, Sung-Gwan;Park, Kyung-Hun
    • Journal of Environmental Impact Assessment
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    • v.13 no.3
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    • pp.137-151
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    • 2004
  • Many of today's environmental problems are regional in scope and their effects overlap and interact. The purpose of this paper is to developed a simple method for an integrated assessment of environmental conditions across the Mid-Nakdong River Region, by combining data on land use, impervious cover, roads, streams, riparian areas, forest patches, population, pollutant loadings, soil erosion and topography. A cluster analysis was used to identify groups of sub-watersheds with similar environmental characteristics. The mean value for each group was used to find watershed that may be more vulnerable to future environmental degradation. Watersheds in cluster I and II had high amount of forest, but the amount of riparian vegetation was low. Watersheds in cluster III, which located in the middle Geumho River and the main course of Nakdong River, had a greater proportion of their agriculture, a greater proportion of agriculture on steep slopes, and less forest adjacent to streams. Watersheds in cluster IV and V were in the most urbanized areas of the region. The principal adverse impacts for watersheds in this group were high scores for urban area, impervious cover, pollutant loadings, population density, forest fragmentation, and low amounts of forest and riparian forest cover. Notwithstanding the exploratory nature of cluster analysis, it appears to be a useful tool for grouping watersheds with similar environmental characteristics.

A Study on the Characteristics Analysis of Clusters by Tenants of Public Rental Housing (공공임대주택 입주가구의 군집별 특성분석에 대한 연구)

  • Nam, Young-Woo
    • Land and Housing Review
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    • v.11 no.2
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    • pp.25-32
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    • 2020
  • This study classified and analyzed characteristics of residents in public rental housing based on data from the 2018 Housing Survey. First, in order to classify the type of public rental housing resident, the criteria were derived through factor analysis based on the satisfaction evaluation index. Next, based on the factor value, the group was classified by type through cluster analysis, and the satisfaction, characteristics of residential households, and characteristics of rental housing types were analyzed for each cluster. As a result of factor analysis, evaluation of housing facilities, accessibility, and residential comfort was selected as the cluster classification criteria, and a total of four clusters were derived through cluster analysis. As a result of analyzing the characteristics of each cluster, it was found that there was a statistically significant difference in the level of residential satisfaction, characteristics of residents, and detailed types of rental housing. The results of this analysis are expected to be used to improve existing public rental housing or develop new types of rental housing to match the characteristics of residential housing for public rental housing. In addition, in the type integration of rental housing currently being promoted, it is necessary to develop a method of providing differentiated services in consideration of the characteristics of tenants as well as the integration of physical housing types.