• Title/Summary/Keyword: CLUSTER 분석

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Differences in Leisure Type of Temporary stay -in overseas Lay over by Segmentation of Flight Attendant's Life Style (항공사 객실승무원의 라이프스타일과 일시적 해외 체제 시 여가 유형)

  • Oh, Seon-Mi;Cho, Ju-Eun
    • The Journal of the Korea Contents Association
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    • v.12 no.7
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    • pp.425-436
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    • 2012
  • This research aims to investigate the life-style and types of leisure experienced among airline flight attendants during temporary stays abroad. In this study 2 hypotheses based on literature reviews were employed. Questionnaires were also developed based on data collected from previous studies. Subjects of the study were focused on flight attendants in Legacy Airlines. Factor analysis and reliability coefficients were used to examine the internal consistency among variables. Seven dimensions of leisure, which are cultural experience, pursuit of success, social orientation, humanity, pursuit of fashion, shopping preferences and health-orientation were identified from factor analysis. Three dimensions of leisure, which include type of rest, type of sports, and activity of tourists, were identified from factor analysis accordingly. Lifestyle factors were extracted from a result of cluster analysis, cluster 1- Passive lifestyle, Active lifestyle community type 2, and Cluster 3 analyzed Self-satisfied lifestyle types. Airline cabin crew workers involved in the life style analysis can make good use of leisure time.

Cluster analysis of companies introducing smart factory based on 6-domain smart factory maturity assessment model (6-도메인 스마트팩토리 성숙도 평가 모델 기반 도입기업 군집분석)

  • Jeong, Doorheon;Ahn, Junghyun;Choi, Sanghyun
    • Journal of the Korea Convergence Society
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    • v.11 no.9
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    • pp.219-227
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    • 2020
  • Smart Factory is one of the fastest developing and changing fourth industrial revolution fields. In particular, the degree of introduction and maturity level in the smart factory is an important part. In this paper, a cluster analysis of companies introduced smart factory was performed based on a new maturity assessment model. The 68% of 193 companies surveyed were at the basic level, with only 21% being the middle one. Most SMEs cited lack of funds as the main reason for not entering the middle one. As a result of the cluster analysis, it was found that all clusters had similar patterns but grouped into one of three levels of high, middle, and low depending on maturity level of smart factory operation, and process domain had the highest maturity and data domain was lowest among the 6 domains. Through this, analysis of more specific and quantified maturity levels can be performed using 6-domain smart factory maturity evaluation model.

The Assessment of Patient Satisfaction in Accordance with Hospital Patients Food Service Cluster Groups (병원입원환자의 서비스. 영양관리. 식단 만족 요인집단에 따른 만족도 분석)

  • 장은재;김혜진;홍완수
    • Korean Journal of Community Nutrition
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    • v.5 no.1
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    • pp.83-91
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    • 2000
  • The aims of this study are to evaluate the quality of hospital food services and the evaluate the quality in selected hospitals trough the use of the questionnaires. A survey of 30 hospital food and nutrition service department was undertaken and detailed information was collected from each, including, surveys of 1, 016 patient. Statistical data analysis was completed using the SAS/win 6.11 package for descriptive analysis, t-test X$^2$-test ANOVA principal component analysis , and cluster analysis and cluster analysis. In the case of patient satisfaction with hospital food and food services, overall satisfaction scores of male and female were 3.54 and 3.45 showing higher levels than the average score(3.00) The aspect of the food and food service which received the lowest ratings by patients was 'meal rounding while dining'. After conduction of factor analysis of variables affecting the patients meal satisfaction 3 groups including the 'menu satisfaction factor', 'service satisfaction factor ' and 'nutrition management satisfaction factor ' were selected. 3 clusters were categorized by the 'service cluster' 'nutrition management cluster', 'men cluster', and 'menu nutrition service cluster' after conducting a cluster analysis with influencing variables affecting patients meal satisfaction. The overview results of patient satisfaction by cluster were : in the case of the service group, such factors as taste, portion size, dealing with complaints while dining meal rounding while dining should be managed with caution In case of the nutrition management group, such factors as taste, portion size, temperature of the food intake, and dependence on hospital food should be managed with care, In the case of the menu groups, such factors as punctuality of meal times, contaminated substances in meals and serving mistakes, cleanliness of dishes, kindness of the server meal rounding while dining should by particularly managed with importance.

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Cluster Label-based ZigBee Mesh Routing Protocol (클러스터 라벨 기반의 지그비 메쉬 라우팅 프로토콜)

  • Lee, Kwang-Koog;Kim, Seong-Hoon;Park, Hong-Seong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.11A
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    • pp.1164-1172
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    • 2007
  • To solve scalability problem in the ZigBee Network, this paper presents a new mesh routing protocol for ZigBee, called ZigBee Cluster Label (ZiCL). ZiCL divides the ZigBee network into one or more logical clusters and then assigns a unique Cluster Label to each cluster so that it discovers a route of a destination node based on Cluster Label. When a node collects new Cluster Label information of a destination node according to discovery based on Cluster Label, ZiCL encourages nodes with the same Cluster Label to share the information. Consequen tly, it contributes on reducing numerical potential route discoveries and improving network performances such as routing overhead, end-to-end delay, and packet delivery ratio. Simulation results using NS-2 show ZiCL performs well.

An Empirical Investigation on the Dynamic Relationships among the Critical Factors Influencing on the High-tech Cluster Formation and Its Sustainable Growth (첨단산업클러스터 형성요인들간의 인과관계분석)

  • Kwoun, Sung-Taeck;Kim, Sang-Wook
    • Korean System Dynamics Review
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    • v.7 no.2
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    • pp.133-148
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    • 2006
  • This study suggests a Causal Loop Diagram(CLD) of causality mechanism which are integrating matters of localization, networking, embeddedness & institutional thickness and collective learning. These five factors(localization, networking, embeddedness & institutional thickness, collective learning, innovative synergy) have been studied and proofed Also this study suggest a model of industry cluster based on holistic and global system thinking rather than local and linear thinking.

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Regional Analysis of Precipitation using Mean Annual Precipitation and Cluster Methods (연강수량 및 클러스터 기법에 의한 강수의 지역화 분석(수공))

  • 이순혁;맹승진;류경식;지호근
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2000.10a
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    • pp.397-404
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    • 2000
  • A total of 65 rain gauges with Automatic Weather Station(AWS) were used to regional analysis of precipitation. Nine cluster regions were identified using geographical locations, maximum, mean, standard deviation of 1 day maximum rainfalls, mean annual precipitation and rainfall of rainy season in Korea. The mean annual precipitation, geographical locations, and the synoptic generating mechanisms were used to identify th five climatological homogeneous regions in Korea. Number of final regions by mean annual precipitation and cluster methods divided into five regions in Korea.

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An Analysis of the Characteristics of Companies introducing Smart Factory System Using Data Mining Technique (데이터 마이닝 기법을 활용한 스마트팩토리 도입 기업의 특성 분석)

  • Oh, Jeong-yoon;Choi, Sang-hyun
    • Journal of the Korea Convergence Society
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    • v.9 no.5
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    • pp.179-189
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    • 2018
  • Currently, research on smart factories is steadily being carried out in terms of implementation strategies and considerations in construction. Various studies have not been conducted on companies that introduced smart factories. This study conducted a questionnaire survey for SMEs applying the basic stage of smart factory. And the cluster analysis was conducted to examine the characteristics of the company. In addition, we conducted Decision Tree and Naive Bay to examine how the characteristics of a company are derived and compare the results. As a result of the cluster analysis, it was confirmed that the group was divided into the high satisfaction group and the low satisfaction group. The decision tree and the Naive Bay analysis showed that the higher satisfaction group has high productivity.

The Spatial Characteristics of Network in Zhongguancun Cluster - Focus on the Corporate Activities - (중관촌(中關村) 클러스터 네트워크의 공간적 특성 - 기업 활동을 중심으로 -)

  • Zhan, Jun
    • Journal of the Korean association of regional geographers
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    • v.18 no.3
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    • pp.298-309
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    • 2012
  • This paper studies the characteristics of the network of the Zhongguancun Cluster, the most representative innovative cluster of the high-tech industry in China at present. For this study, Zhongguancun Cluster was the first high-tech cluster created in China in 1988, the current Zhongguancun Cluster plays a leading role in the development of the high-tech industry in China. In addition, the Zhongguancun Cluster has attracted global attention and helped elevate China as a key region in terms of research development in relation to the high-tech industry. With regard to the spatial characteristics of the network belonging to the companies in Zhongguancun Cluster, purchase and producer services and information and R&D network have a strong tendency to be local, while on the other hand the product sales network has a strong tendency to be non-local. It is because the political support supplied by the government, institutional base that provides high-tech companies, producer services and information regarding producer services is relatively well prepared and managed in Zhongguancun Cluster. The spatial characteristics of the R&D network have a very strong local character is due to the location of the Zhongguancun Cluster where companies, universities and research centers with outstanding research development capacity as well as various support organizations for technology innovation within the cluster are included. On the other hand, because the high-tech products produced in this area are sold all across China as well as in foreign countries, the product sales network has a strong non-local character. Strengthening the local network in terms of the main agents of the cluster is the most important aspect in order to develop a certain industrial cluster into an innovative cluster. In this respect, if the Zhongguancun Cluster is seen from the perspective of a network, it has a basic network foundation. However, to strengthen international competitiveness, not only the local network but also the international network should be strengthened.

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Investigating Online Learning Types Based on self-regulated learning in Online Software Education: Applying Hierarchical Cluster Analysis (온라인 소프트웨어 교육에서 학습자의 자기조절학습 관련 특성에 기반한 온라인 학습 유형 분석: 계층적 군집 분석 기법을 활용하여)

  • Han, Jeongyun;Lee, Sunghye
    • The Journal of Korean Association of Computer Education
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    • v.22 no.5
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    • pp.51-65
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    • 2019
  • This study aims to provide educational implications for more strategic online software education by the types of online learning according to learners' self-regulated learning characteristics in the online software education environment and examining the characteristics of each type. For this, variables related to self-regulated learning characteristic were extracted from the log data of 809 students participating in the online software learning program of K University, and then analyzed using hierarchical cluster analysis. Based on hierarchical cluster analysis learner clusters according to the characteristics of self-regulated learning were derived and the differences between learners' learning characteristics and learning results according to cluster types were examined. As a result, the types of self-regulated learning of online software learners were classified as 'high level self-regulated learning type (group 1)', 'medium level self-regulated learning type (group 2)', and 'low level self-regulated learning type (group 3)'. The achievement level was found to be highest in 'high-level self-regulated learning type (group 1)' and 'low-level self-regulated learning type (group 3)' was the lowest. Based on these results, the implications for effective online software education were suggested.

Current Research Trends in Entrepreneurship Based on Topic Modeling and Keyword Co-occurrence Analysis: 2002~2021 (토픽모델링과 동시출현단어 분석을 이용한 기업가정신에 대한 연구동향 분석: 2002~2021)

  • Jang, Sung Hee
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.3
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    • pp.245-256
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    • 2022
  • The purpose of this study is to provide comprehensive insights on the current research trends in entrepreneurship based on topic modeling and keyword co-occurrence analysis. This study queried Web of Science database with 'entrepreneurship' and collected 14,953 research articles between 2002 and 2021. The study used R program for topic modeling and VOSviewer program for keyword co-occurrence analysis. The results of this study are as follows. First, as a result of keyword co-occurrence analysis, 5 clusters divided: entrepreneurship and innovation cluster, entrepreneurship education cluster, social entrepreneurship and sustainability cluster, enterprise performance cluster, and knowledge and technology transfer cluster. Second, as a result of the topic modeling analysis, 12 topics found: start-up environment and economic development, international entrepreneurship, venture capital, government policy and support, social entrepreneurship, management-related issues, regional city planning and development, entrepreneurship research, and entrepreneurial intention. Finally, the study identified two hot topics(venture capital and entrepreneurship intention) and a cold topic(international entrepreneurship). The results of this study are useful to understand current research trends in entrepreneurship research and provide insights into research of entrepreneurship.