• Title/Summary/Keyword: CLUSTER 분석

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Differences between high school students' hope, grit, and school happiness by cluster type (일반고 학생 희망과 그릿의 군집유형별 학교행복의 차이)

  • Kim, Jin-Cheol;Kim, Chang-Gil
    • Journal of Industrial Convergence
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    • v.19 no.4
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    • pp.9-15
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    • 2021
  • The purpose of the study is to find out the difference between high school students' hopes and the school happiness of each cluster of grits. Method: 282 high students' responses were analyzed through correlation analysis and cluster analysis. Results: First, There is a positive correlation between hope and grit and school happiness. Second, Hope and Grit appeared in four clusters. School happiness had the highest "high psychological capital" group and the lowest "low psychological capital. Conclusion: It was discussed that the agency thinking and effort perseverance of grit should be reflected in the curriculum of general high schools. In addition, we propose to develop questionnaires for practical measurements.

Performance Analysis of a CFD code in the TeraCluster Parallel System (TeraCluster에서 CFD 코드의 병렬 성능 분석)

  • Cho K.W.;Lee S.Lee
    • 한국전산유체공학회:학술대회논문집
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    • 2000.10a
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    • pp.92-100
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    • 2000
  • At the end of 1999. the TeraCluster project has started in the KORDIC Supercomputer center to study PC clusters for parallel computing. The aim is to replace the Cray T3E with a new cluster system in 2002. The PC cluster without a fast network is well suited for applications which do not require large amount of global communications. Since CFD problems are not very communication intensive, whole test cluster may be efficiently used. As an example of practical CFD simulations. the flow past the ONERA M6 wing and the flow past infinite wing are simulated on a cluster of Linux workstations.

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Charaterization of Cities in Seoul Metropolitan Area by Cluster Analysis (군집분석을 이용한 수도권 도시의 유형화에 관한 연구)

  • Song, Min-Kyung;Chang, Hoon
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.1
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    • pp.83-88
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    • 2010
  • This paper has analyzed Seoul metropolitan area on the basis of cluster characteristics and it is to understand the traits of each clusters. In order to modelize the area, 10 different indicators were selected among components of a city such as population, activities, land and facilities. Also through principal component analysis, similar characteristics or congenialities of the variables were derived as a common factor. The result was organized by factor score from hierarchical clustering method and as a final result, metropolitan area was clustered into five areas.

Sushi Consumption Behavior of Koreans according to Food-related Lifestyle Type among Consumers (외식 소비자의 식생활 라이프스타일에 따른 초밥 소비행동 분석)

  • Lee, Kyung-Won;Chung, Hee-Chung;Cho, Mi-Sook
    • Journal of the Korean Society of Food Culture
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    • v.26 no.6
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    • pp.574-582
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    • 2011
  • The aim of this study was to classify Korean consumers based on their food-related lifestyle type, and to investigate the relationship between sushi consumption and food-related lifestyle type. Self-reported questionnaires were completed by 300 Korean adults. The SPSS 18.0 program was used to analyze the samples. Data was analyzed by frequency, descriptive factor, reliability, cluster analysis, ANOVA, and chi-square test. A factor analysis extracted four factors comprising foodrelated lifestyle, which we named Health-seeking (factor 1), Taste-seeking (factor 2), Convenience-seeking (factor 3), and Economy-seeking (factor 4). According to a cluster analysis based on those four factors, consumers were classified into three clusters. Cluster 1 was the Taste and Health-seeking cluster, Cluster 2 was the Convenience-seeking cluster, and Cluster 3 was the Passive Eating Habits cluster. The results also indicated that the selection attributes of each cluster were significantly different in terms of perception, the global state of sushi, sushi preference, frequency, companions, place of sushi consumption, and preference for different sushi sub-ingredients. Based on these results, consumer characteristics in the sushi market are discussed.

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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Cluster-Based Node Management Algorithm for Energy Consumption Monitoring in Wireless Mobile Ad Hoc Networks (무선 모바일 애드혹 네트워크상에서 에너지 소모 감시를 위한 클러스터 기반의 노드 관리 알고리즘)

  • Lee, Chong-Deuk
    • Journal of Digital Convergence
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    • v.14 no.9
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    • pp.309-315
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    • 2016
  • The node mobility in the wireless mobile network environment increases the energy consumption. This paper proposes a CNMA (cluster-based node management algorithm) to reduce the energy consumption caused by node mobility, and to prolong the life cycle for cluster member nodes. The proposed CNMA traces the mobility for nodes between cluster header and member, and it analyses the energy capacity as monitoring periodically their relationship. So, it makes a division and merges by analysing the state transition for nodes. This paper is to reduce the energy consumption due to the node mobility. The simulation results show that the proposed CNMA can efficiently control the energy consumption caused by mobility, and it can improve the energy cycle.

Research Trend Analysis on Practical Arts (Technology & Home Economics) Education Using Social Network Analysis (소셜 네트워크 분석(SNA)을 이용한 실과(기술·가정)교육 분야 연구 동향 분석)

  • Kim, Eun Jeung;Lee, Yoon-Jung;Kim, Jisun
    • Human Ecology Research
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    • v.56 no.6
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    • pp.603-617
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    • 2018
  • This study analyzed research trends in the field of Practical Arts (Technology & Home Economics) education. From 958 articles published between 2010 and 2018 in the Journal of Korean Practical Arts Education (JKPAE), Journal of Korean Home Economics Education Association (JHEEA), and Korean Journal of Technology Education Association (KJTEA), 958 keywords were extracted and analyzed using NetMiner 4. When the general network structure was analyzed, keywords such as practical arts education, curriculum, textbook, home economics education, and students were high in the degree centrality and closeness centrality, and textbook, practical arts education, curriculum, student, home economics education, and invention were high in the node betweenness centrality. The cluster analysis showed that a four-cluster solution was most appropriate: cluster 1, technology and experiential learning activities; cluster 2, curriculum studies and practical problem; cluster 3, relationships; and cluster 4, creativity and character education. The three journals showed differences in the knowledge network structure: The topics of JKPAE and JKHEEA focused on general content knowledge and curriculum, while the topics of KJTEA were spread across invention and creativity education, and curriculum studies.

User-Class based Service Acceptance Policy using Cluster Analysis (군집분석 (Cluster Analysis)을 활용한 사용자 등급 기반의 서비스 수락 정책)

  • Park Hea-Sook;Baik Doo-Kwon
    • The KIPS Transactions:PartD
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    • v.12D no.3 s.99
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    • pp.461-470
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    • 2005
  • This paper suggests a new policy for consolidating a company's profits by segregating the clients using the contents service and allocating the media server's resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) and profits through the cluster analysis of clients' data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.

Government Financial Support and Firm Performance: A Multilevel Analysis of the Moderating Effects of Firm and Cluster Characteristics (정부 자금지원과 기업 경영성과: 기업 및 클러스터 특성의 조절효과에 관한 다수준 분석)

  • Hee Jae Kim;Myung-Ho Chung
    • Journal of Industrial Convergence
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    • v.22 no.1
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    • pp.1-20
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    • 2024
  • Regarding the discourse on the correlation between governmental financial support and firm performance, much emphasis has been placed on the role of individual corporate characteristics as well as spatial features. However, there is a notable scarcity of empirical research examining the integrated impact of corporate and cluster characteristics on managerial performance. This study addresses this gap by empirically analyzing the financial and non-financial outcomes resulting from specific allocations of governmental financial support. Additionally, it explores corporate and cluster characteristics predicted to moderate the influence between governmental financial support and firm performance. The analysis employs a two-level hierarchical linear model (HLM) at individual and group levels. The data, reorganized based on business registration numbers at the firm and cluster levels, ultimately utilized panel data from 83,395 firms and 641 clusters. The research findings indicate that governmental financial support demonstrates a positive effect (+) on both sales and patents for firms, suggesting its effectiveness in complementing market failures. Results from the hierarchical linear model analysis show that when combined with human capital capacity, absorptive capacity, and cluster network density, governmental financial support exhibits significant positive effects on sales. This study contributes theoretical and practical insights by analyzing the relationship between governmental financial support and firm performance using a two-level hierarchical linear model. It highlights the role of corporate characteristics such as human capital and absorptive capacity, along with cluster characteristics like cluster network density, in moderating the effects of governmental financial support on firm performance.

An Analysis of Energy Efficient Cluster Ratio for Hierarchical Wireless Sensor Networks (계층적 센서네트워크에서 에너지 효율성을 위한 최적의 클러스터 비율 분석)

  • Jin, Zilong;Kim, Dae-Young;Cho, Jinsung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38B no.6
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    • pp.446-453
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    • 2013
  • Clustering schemes have been adopted as an efficient solution to prolong network lifetime and improve network scalability. In such clustering schemes cluster ratio is represented by the rate of the number of cluster heads and the number of total nodes, and affects the performance of clustering schemes. In this paper, we mathematically analyze an optimal clustering ratio in wireless sensor networks. We consider a multi-hop to one-hop transmission case and aim to provide the optimal cluster ratio to minimize the system hop-count and maximize packet reception ratio between nodes. We examine its performance through a set of simulations. The simulation results show that the proposed optimal cluster ratio effectively reduce transmission count and enhance energy efficiency in wireless sensor networks.