• Title/Summary/Keyword: cluster method

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A Clustering of Physical Fitness according to the Skeletal Maturation of Elementary School Students : Focused on Cluster Analysis (초등학생의 골성숙도에 따른 체력 군집화 : 군집분석 중심으로)

  • Kim, Dae-Hoon;Yoon, Hyoung-ki;Oh, Sei-Yi;Lee, Young-Jun;Cho, Seok-Yeon;Song, Dae-Sik;Seo, Dong-Nyeuck;Kim, Ju-Won;Na, Gyu-Min;Kim, Min-Jun;Oh, ․Kyung-A
    • Journal of the Korean Applied Science and Technology
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    • v.39 no.1
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    • pp.63-73
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    • 2022
  • The aim of this study was to cluster according to the bone age of elementary school students in order to analyze the physique, physical fitness, and skeletal maturation of each cluter group and to provide basic data for the balanced development of elementary school students through data analysis. The subjects of this study were 2243 students aged 8 to 13 years, and the skeletal maturation were calculated by applying them to the TW3 method score conversion table after the X-ray films were taken. A total of 2 components in physique were measured using a stadiometer(Hanebio, Korea, 2021) and the Inbody 270(Biospace, Korea, 2019), and a total of 7 components in physical fitness, which included muscular strength(Hand Grip Strength), balance(Bass Stick Test), agility(Plate Tapping), power(Standing Long Jump), flexibility(Sit&Reach), muscular endurance(Sit-Up), and cardiovascular endurance(Shuttle Run) were measured as well. K-Means clustering method, cross-tabulation analysis, and one-way variable analysis(ANOVA) were conducted for data processing using the SPSS PC/Program(Version 26.0) and Bristics Studio Tool, and it was considered significant at the level of p< .05. The results of this study may be summarized as follow. First, as a result of clustering using three components of skeletal maturation: retarded, normal, and advanced, cluster 1(Retarded) showed excellence in muscular strength, balance, and agility. cluster 2(Normal) showed poor flexibility, whereas cluster 3(Advanced) showed excellence in muscular strength. Second, as a result of analyzing the differences in physique according to the clustering of elementary school students by their individual characteristics, cluster 3(Advanced) showed excellence in height, weight, and body fat percentage. Third, as a result of analyzing the differences in physical fitness according to the clustering of elementary school students by their individual characteristics, cluster 3(Advanced) showed excellence in Hand Grip Strength(Left, Right), whereas cluster 1(Retarded) showed excellence in Bass Stick Test, and cluster 3(Advanced) showed excellence in Standing Long Jump.

Extending the Read Range of UHF Mobile RFID Readers: Arbitration Methods Based on Interference Estimation

  • Ahn, Si-Young;Park, Jun-Seok;Seong, Yeong Rak;Oh, Ha-Ryoung
    • Journal of Electrical Engineering and Technology
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    • v.9 no.6
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    • pp.2025-2035
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    • 2014
  • The read range of UHF mobile readers can be extended by a booster for mobile RFID readers (BoMR). But in an environment where multiple BoMRs are installed, the read success rate may be decreased due to signal interference. This paper proposes three arbitration methods based on interference estimation with the purpose of enhancing the read success rate. A central arbitration server manages global information in centralized arbitration method (CAM) without broadcast/multicast communication facility. In fully distributed arbitration method (FDAM), all the arbitration messages are broadcasted from a BoMR to every BoMR, and each BoMR decides with broadcasted global information. Events in FDAM are serialized naturally with broadcasted messages. Cluster Distributed Arbitration Method (CDAM) forms clusters with multicasted BoMRs and a selected BoMR acts as an arbiter in the cluster. Such effects as lengthened read range, improved the read success rates of readers can be obtained by the proposed methods without any hardware modification. In order to evaluate the arbitration methods, the RFID system is modeled by using the DEVS formalism and simulated by using the DEVSim++.

A novel clustering method for examining and analyzing the intellectual structure of a scholarly field (지적 구조 분석을 위한 새로운 클러스터링 기법에 관한 연구)

  • Lee, Jae-Yun
    • Journal of the Korean Society for information Management
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    • v.23 no.4 s.62
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    • pp.215-231
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    • 2006
  • Recently there are many bibliometric studies attempting to utilize Pathfinder networks(PFNets) for examining and analyzing the intellectual structure of a scholarly field. Pathfinder network scaling has many advantages over traditional multidimensional scaling, including its ability to represent local details as well as global intellectual structure. However there are some limitations in PFNets including very high time complexity. And Pathfinder network scaling cannot be combined with cluster analysis, which has been combined well with traditional multidimensional scaling method. In this paper, a new method named as Parallel Nearest Neighbor Clustering (PNNC) are proposed for complementing those weak points of PFNets. Comparing the clustering performance with traditional hierarchical agglomerative clustering methods shows that PNNC is not only a complement to PFNets but also a fast and powerful clustering method for organizing informations.

A GEE approach for the semiparametric accelerated lifetime model with multivariate interval-censored data

  • Maru Kim;Sangbum Choi
    • Communications for Statistical Applications and Methods
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    • v.30 no.4
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    • pp.389-402
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    • 2023
  • Multivariate or clustered failure time data often occur in many medical, epidemiological, and socio-economic studies when survival data are collected from several research centers. If the data are periodically observed as in a longitudinal study, survival times are often subject to various types of interval-censoring, creating multivariate interval-censored data. Then, the event times of interest may be correlated among individuals who come from the same cluster. In this article, we propose a unified linear regression method for analyzing multivariate interval-censored data. We consider a semiparametric multivariate accelerated failure time model as a statistical analysis tool and develop a generalized Buckley-James method to make inferences by imputing interval-censored observations with their conditional mean values. Since the study population consists of several heterogeneous clusters, where the subjects in the same cluster may be related, we propose a generalized estimating equations approach to accommodate potential dependence in clusters. Our simulation results confirm that the proposed estimator is robust to misspecification of working covariance matrix and statistical efficiency can increase when the working covariance structure is close to the truth. The proposed method is applied to the dataset from a diabetic retinopathy study.

A Comparison of Cluster Analyses and Clustering of Sensory Data on Hanwoo Bulls (군집분석 비교 및 한우 관능평가데이터 군집화)

  • Kim, Jae-Hee;Ko, Yoon-Sil
    • The Korean Journal of Applied Statistics
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    • v.22 no.4
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    • pp.745-758
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    • 2009
  • Cluster analysis is the automated search for groups of related observations in a data set. To group the observations into clusters many techniques has been proposed, and a variety measures aimed at validating the results of a cluster analysis have been suggested. In this paper, we compare complete linkage, Ward's method, K-means and model-based clustering and compute validity measures such as connectivity, Dunn Index and silhouette with simulated data from multivariate distributions. We also select a clustering algorithm and determine the number of clusters of Korean consumers based on Korean consumers' palatability scores for Hanwoo bull in BBQ cooking method.

Automatic Determination of Usenet News Groups from User Profile (사용자 프로파일에 기초한 유즈넷 뉴스그룹 자동 결정 방법)

  • Kim, Jong-Wan;Cho, Kyu-Cheol;Kim, Hee-Jae;Kim, Byeong-Man
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.2
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    • pp.142-149
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    • 2004
  • It is important to retrieve exact information coinciding with user's need from lots of Usenet news and filter desired information quickly. Differently from email system, we must previously register our interesting news group if we want to get the news information. However, it is not easy for a novice to decide which news group is relevant to his or her interests. In this work, we present a service classifying user preferred news groups among various news groups by the use of Kohonen network. We first extract candidate terms from example documents and then choose a number of representative keywords to be used in Kohonen network from them through fuzzy inference. From the observation of training patterns, we could find the sparsity problem that lots of keywords in training patterns are empty. Thus, a new method to train neural network through reduction of unnecessary dimensions by the statistical coefficient of determination is proposed in this paper. Experimental results show that the proposed method is superior to the method using every dimension in terms of cluster overlap defined by using within cluster distance and between cluster distance.

Connection-Degree Based Search and Replication in Mobile Ad Hoc Networks (모바일 애드-혹 네트워크에서 연결차수 기반 탐색 및 복제 기법)

  • Kang, Eun-Young;Im, Yong-Soon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.5
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    • pp.187-195
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    • 2008
  • In MANET, it is important to efficiently manage data objects and traffic to improve network throughput and response time. This paper proposes a connection-degree based data object search and replication scheme in mobile ad-hoc networks. In this method, information about the path data object providers is stored at the cache of a cluster header at which lots of queries arrive, so that, to reduce the load of the cluster header, replicas can be created at its neighboring nodes. The method proposes an algorithm that picks up a cluster header among mobile nodes and makes it possible to search for and utilize adaptive and up-to-date information in MANET. The method is expected to be effective since it enables access to data objects in spite of broken links among mobile nodes with an enhancement in network response time of searching and a decrease in communication costs. The efficiency of this system was verified via simulation.

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The Spatial Location Analysis of Rural Village and Amenity Resources (농촌마을 공간특성과 어메니티자원의 입지분석)

  • Choi, Young-Wan;Kim, Young-Joo
    • Journal of Korean Society of Rural Planning
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    • v.19 no.1
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    • pp.81-90
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    • 2013
  • The aim of the research was to analyze a correlation between rural villages and a space of amenity resources in order to provide objective basic data for rural renewal planning in the future. 15 villages were selected to analyze amenity resources. A Space Syntax Method(SSM) was used to analyze a spacial structure of each village and location characteristics of amenity resources. Finally, Statistical Package for the Social Sciences(SPSS) was used for a cluster analysis. The results of spacial analysis showed that the MeanDepth of rural villages was 4.482 and Global Integration Value(GInteg) was 0.956. Relatively, a depth was lower and GInteg was higher, compared to other villages. Rural villages were easily recognized and accessible by outsiders, compared to mountain and fishing villages. In the case of rural villages, the MeanDepth of amenity resources was low and GInteg was high in the results of cluster analysis using a nonhierachical method. Results indicated that an access was easy and amenity resources were closely located each other. However, the deviation of each village was great in mountain villages. This research suggests that an effective maintenance of road network for improving accessibility would be given priority in an undeveloped farming and fishing villages' renewal. Especially, using a spacial analysis in village renewal planning process can improve accessibility and maximize an utilization of public facilities and amenity resources.