• Title/Summary/Keyword: 군집성

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A Comparative Study using Bibliometric Analysis Method on the Reformed Theology and Evangelicalism (개혁신학과 복음주의에 관한 계량서지학적 비교 연구)

  • Yoo, Yeong Jun;Lee, Jae Yun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.29 no.3
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    • pp.41-63
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    • 2018
  • This study aimed at analyzing journals and index terms, authors of the reformed theology and evangelicalism, neutral theological position by using bibliometrical analyzing methods. The analyzing methods are average linkage and neighbor centralities, profile cosine similarities. Especially, when analyzing the relationship between authors, we interpreted the research topic by finding the key shared index terms between the authors. In the journal analysis results, 9 journals were largely clustered together in the two clusters of the reformed theology and evangelicalism, but Presbyterian Theological Quarterly that is thought to be a reformed journal was clustered in evangelical cluster. In the index terms analysis results of the clusters, the reformed theology and evangelicalism were key words representing the two clusters. In the authors' analysis results, we had 9 clusters and the Presbyterian theologian studying the reformed theology had the four clusters and the non-Presbyterian theologian had the 5 clusters. Therefore, we consistently had the two clusters of the reformed theology and evangelicalism in all the analysis of the journals and the index terms, the authors.

Diversity of Arbuscular Mycorrhizal Fungi in Rhizospheres of Camellia japonica and Neighboring Plants Inhabiting Wando of Korea (전남 완도에 서식하는 동백나무와 그 주변 식물의 근권에 분포하는 수지상균근균의 다양성)

  • Lee, Eun-Hwa;Ka, Kang-Hyeon;Eom, Ahn-Heum
    • The Korean Journal of Mycology
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    • v.42 no.1
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    • pp.34-39
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    • 2014
  • In this study, the community structures of arbuscular mycorrhizal fungi (AMF) in rhizospheres of Camellia japonica and neighboring woody plants in Wando, Korea were investigated. Rhizospheres of C. japonica and other woody plants were dominated by the same species, Acaulospora mellea, but Shannon's index, species richness and total spore numbers of the AMF communities were higher in non-C. japonica than in neighboring plants. Regardless of host plant species, the frequency of A. mellea was significantly high comparing with other AMF species. The community similarity of AMF within C. japonica was significantly higher than between C. japonica and neighboring plants or neighboring plants (p<0.005). Results showed that AM fungal communities in rhizospheres of C. japonica have unique community structure and are different from that of neighboring host plants, suggesting that community structure of AMF could be influenced by host plant species.

Table Clustering Using Inter-schema Association (스키마간 연관성을 이용한 테이블 군집화 기법)

  • 조순이;이도헌
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.85-87
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    • 2001
  • 업무 데이터 분석을 통한 종합적인 의사결정을 지원할 수 있도록 데이터웨어하우스, OLAP, 데이터마이닝을 적용하려는 기업의 요구가 많아졌다. 그래서 기초 데이터의 이해, 선별, 수집, 가공, 정제가 매우 중요한 과정이나 테이블명 및 속성명이 표준화되어있지 않고 코드나 시스템 카탈로그와 같은 기본 데이터는 부정확하고 부족하다. 본 논문에서는 거의 스키마 정보에만 의존하여 테이블의 의미적 연관성에 근거한 유사한 특성을 가진 집단끼리 분류하는 대략적인 군집분석 방법을 제안한다. 질의 수행시 사용자가 설정한 임계 거리에 ㄸ라 관련된 군집만 검색함으로써 신속한 응답시간을 보장하고, 분석시점에서 다양한 질의에 유연하게 대처할 수 있다는 장점이 있다. 또한 실제 데이터에 본 연구를 적용하여 산출한 군집결과와 사람이 매뉴얼하게 그룹핑한 군집결과와 비교한다.

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군집행태가 정보기술도입에 미치는 영향

  • 박상혁;강태경;장철웅
    • Proceedings of the Korea Association of Information Systems Conference
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    • 2005.12a
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    • pp.435-440
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    • 2005
  • 정보기술 도입과 관련된 주류 이론은 혁신확산이론과 기술수용모델이다. 특히 기술수용모델은 도입의사결정자가 합리적 사고를 한다는 전제가 이론 기저에 깔려 있다. 하지만, 실제 현실세계에서는 유행과 집단의식 등에 의해 정보기술을 도입하는 경우가 많다. ERP가 유행이면, 무조건 쫓아서 ERP를 도입하고, KM이 유행이면 또한 쫓아서 KM을 도입하는 현상이 보편적으로 일어나고 있다. 이러한 행태를 군집 행태라 한다. 군집행태는 정보에 대한 비대칭성이 커서 사람들이 느끼는 정보의 불확실성이 큰 경우에 사람들이 보이는 행태 중의 하나이다. 어느 한 사람이 특정한 행동을 하면 다른 사람들도 그를 따라 집단적으로 동일한 행동을 하는 것을 말한다. 그 사람이 왜 그러한 행동을 하는지를 알고 따라하는 것이 아니다. 그가 자신이 모르는 무엇인가를 알고 있다고 믿고 우선 따라 하는 것이 상책이라고 생각하는 것이다. 본 연구에서는 정보기술의 도입과 관련된 군집행태에 영향을 주는 요인을 찾아내고자 한다.

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Characteristics of Distribution of Phytoplankton Communities in Three Estuarial Lakes of the Yeongsan River (영산강 하구역에 위치한 세 호수의 식물플랑크톤 군집 분포 특성)

  • Cho, Hyeon Jin;Na, Jeong Eun;Lee, Gun Ju;Lee, Hak Young
    • Korean Journal of Ecology and Environment
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    • v.54 no.4
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    • pp.291-302
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    • 2021
  • The phytoplankton community in the estuarine system is affected by changes of physicochemical factors easily. The present study analyzed phytoplankton community distribution and similarity, in addition to exploring factors influencing variations in phytoplankton community structure in three lakes located in the Yeongsan River estuary from March 2014 to November 2017. We carried out non-multidimensional scaling (NMDS) and random forest analysis (RF) for comparing the pattern of phytoplankton distribution and the relationship between phytoplankton distribution and environmental variables. Similarity Percentage (SIMPER) and Analysis of Similarity (ANOSIM) were performed to figure out the similarity of phytoplankton community at each site of three lakes. From NMDS, Phytoplankton community distribution differed between Yeongsan and Gumho lakes, and the factors influencing the distribution of phytoplankton communities across the three lakes were water temperature, dissolved oxygen, total nitrogen (T-N), nitrate-N (NO3-N), and conductivity. NO3-N was a key factor influencing phytoplankton community structure in the three lakes based on RF. A total of 24 species were identified as indicator species in the three lakes studied, with the highest species numbers observed in Yeongsan Lake (13) and the lowest observed in Yeongam Lake (2). According to SIMPER and ANOSIM results, the phytoplankton community in Yeongsan and Yeongam lakes were similar, and they differed from those in Gumho Lake. In addition, the phytoplankton community structure varied across the study sites in the three lakes, indicating that water channels across the lakes a minor influence phytoplankton community distribution.

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.

A New Similarity Measure for Categorical Attribute-Based Clustering (범주형 속성 기반 군집화를 위한 새로운 유사 측도)

  • Kim, Min;Jeon, Joo-Hyuk;Woo, Kyung-Gu;Kim, Myoung-Ho
    • Journal of KIISE:Databases
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    • v.37 no.2
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    • pp.71-81
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    • 2010
  • The problem of finding clusters is widely used in numerous applications, such as pattern recognition, image analysis, market analysis. The important factors that decide cluster quality are the similarity measure and the number of attributes. Similarity measures should be defined with respect to the data types. Existing similarity measures are well applicable to numerical attribute values. However, those measures do not work well when the data is described by categorical attributes, that is, when no inherent similarity measure between values. In high dimensional spaces, conventional clustering algorithms tend to break down because of sparsity of data points. To overcome this difficulty, a subspace clustering approach has been proposed. It is based on the observation that different clusters may exist in different subspaces. In this paper, we propose a new similarity measure for clustering of high dimensional categorical data. The measure is defined based on the fact that a good clustering is one where each cluster should have certain information that can distinguish it with other clusters. We also try to capture on the attribute dependencies. This study is meaningful because there has been no method to use both of them. Experimental results on real datasets show clusters obtained by our proposed similarity measure are good enough with respect to clustering accuracy.

Plant Community Structure Analysis in Noinbong area of Odaesan National Park (오대산 국립공원 노인봉지역 식물군집구조분석)

  • 최송현;권전오;민성환
    • Korean Journal of Environment and Ecology
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    • v.9 no.2
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    • pp.156-165
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    • 1996
  • To investigate the forest structure and to suggest the management of vegetation landscape in Noinbong area, Pdaesan National Pa, twelve plots were set up and surveyed. According to the acalysis of classification by TWINSPAN, the community was divided by two groups of Carpinus laxiflora - Quercus mongolica community and the other is Betula costata - schmidtii - C. laxiflora community. It was found out that the successional stage of Noinbong forests was climax and introduced-climax by the analysis of species structure, similarity index and species diversity. The number of individuals was about 120~130 and species was 17 per 100m$^{2}$. Through the analysis of basal area and DBH class distribution, it was estimated that C. laxiflora, B. costata, and B. schmidtii will be clmax species instead of Q. mongolica in tree layer, and in the subtree layer, Acer pseudo-sieboldianum will be dominant species.

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A clutter reduction algorithm based on clustering for active sonar systems (능동소나 시스템을 위한 군집화 기반의 클러터 제거 기법)

  • Kwak, ChulHyun;Cheong, Myoung Jun;Ahn, Jae-Kyun
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.2
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    • pp.149-157
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    • 2016
  • In this paper, we propose a new clutter reduction algorithm, which rejects heavy clutter density in shallow water environments, based on a clustering method. At first, it applies the density-based clustering to active sonar measurements by considering speed of targets, pulse repetition intervals, etc. We assume clustered measurements as target candidates and remove noise, which is a set of unclustered measurements. After clustering, we classify target and clutter measurements by the validation check method. We evaluate the performance of the proposed algorithm on synthetic data and sea-trial data. The results demonstrate that the proposed algorithm provides significantly better performances to reduce clutter than the conventional algorithm.

Clustering of Gene Expression Data by using SOM and Hierarchical Clustering (자기 조직화 지도와 계층적 군집화를 이용한 유전자 발현 데이터 군집화 기법)

  • 박창범;이동환;이성환
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10b
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    • pp.784-786
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    • 2003
  • 본 논문에서는 유전자 발현 데이터를 분석하는데 있어서 자기 조직화 지도와 계층적 군집화 기법을 상호 보완적으로 사용하여 사용자가 보다 직관적으로 군집화 결과를 해석할 수 있는 방법을 제안한다. 제안된 방법을 사용하면 빠른 처리 속도로 대용량 데이터 처리에 적합한 자기 조직화 지도의 장점을 살릴 수 있으며 계층적 군집화의 장점인 가시화 기능을 이용하여 자기 조직화 지도의 단점인 군집 경계에 대한 불명확성을 해소하여 군집화 결과를 사용자가 쉽게 이해하고 직관적으로 해석할 수 있도록 도와준다. 본 논문에서 제안된 방법의 효용성을 검증하기 위해 세 종류의 데이터를 사용하여 실험을 수행한 결과 제안된 방법이 기존 방법에 비해 더 나은 성능을 보이는 것을 확인할 수 있었다.

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