• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.398-406
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• 2009

This study intends to provide support for tourism industry to establish marketing strategies for selling the travel products on which it should focus on more by examining the difference on selection of travel product attributes by tourism action. This research utilized cluster analysis and ANOVA. The cluster analysis identified four cluster: logical tourism, weak conspicious tourism, value tourism, conspicuous and value tourism. ANOVA analysis showed that four cluster were different in terms of tourism action such as transportation accommodation facilities, tourist attractions, shopping and meals except for travel service, entertainment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.565-573
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• 2008

The behavior-based decentralized approach is considered for multi-UAV formation flight. It is assumed that each UAV has its own mission of flying to a specified region, while the distances between UAVs should be maintained. These two requirements may conflict with each other. To design the controller, coupled dynamics approach is applied to multi-UAVs with an assumption that each UAV can communicate with each other to share the state-information. Control gain matrices are optimized to acquire better performances of formation flying. To validate the proposed control approach, numerical simulation is performed for the waypoint-passing mission of multi-UAVs.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.557-565
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• 2021

This study was attempted to identify differences in self-esteem and grit in adolescents depending on the type of parenting attitude. Among the Korea Children Youth Panel Survey conducted by National Youth Policy Institute, the data of 2,438 first-year middle school students in 2018 year were analyzed. The collected data were analyzed using hierarchical cluster analysis and k-mean cluster analysis. As a result, the adolescent's perceived parenting attitude was classified into four types: 'passive affection acceptance', 'active affection acceptance', 'authoritarian inconsistency', and 'lack of affection rejection'. Also, there were significant differences in self-esteem and the degree of grit among the four clusters of parenting attitudes. Both self-esteem and grit were highest in the "active affection acceptance" group 2. In the future, differentiated parental education is needed for each cluster to improve self-esteem and grit of adolescents, and this study can be used as a basic data for the development of educational programs.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.381-393
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• 2002

K-modes algorithm and ROCK(RObust Clustering using linKs) algorithm we useful clustering methods for large categorical data. In the paper, we investigate these algorithms and propose improved algorithms of them to correct their weakness. A simulation study shows that the proposed algorithms could increase the performance of data clustering.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.969-977
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• 2021

We cluster the electricity consumption of households in A-apartment in Seoul, Korea using Hierarchical K-means clustering algorithm. The data is recorded from the advanced metering infrastructure (AMI), and we focus on the electricity consumption during evening weekdays in summer. Compare to the conventional clustering algorithms, Hierarchical K-means clustering algorithm is recently applied to the electricity usage data, and it can identify usage patterns while reducing dimension. We apply Hierarchical K-means algorithm to the AMI data, and compare the results based on the various clustering validity indexes. The results show that the electricity usage patterns are well-identified, and it is expected to be utilized as a major basis for future applications in various fields.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1337-1340
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• 2015

분광 군집화 기술은 Non-convex 군집에 대해 타 군집화 기술에 비해 강건하여 다양한 분야에서 활용되고 있다. 본 논문에서는 다중 뷰 데이터의 특성을 반영한 새로운 분광 군집화 기술을 제안한다. 제안한 방법은 협업학습의 접근 방법을 적용하되, 다수의 뷰가 서로 간에 가지는 독립성의 정도를 반영하여 유사도 그래프를 구축하고, 구축된 그래프를 기반으로 분광 군집화를 수행한다. 이를 통해 뷰들간 서로 다른 정보 요구를 그래프에 반영함으로써 군집화 성능을 높인다. 세 개의 뷰를 가정한 가상의 데이터에서 제안한 방법은 기존 방법에 비해 최대 8.25%, 높은 성능을 보였다.

• Journal of The Korean Association For Science Education
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• v.42 no.6
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• pp.611-619
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• 2022

The purpose of this study is to explore the possibility of applying big data analysis to provide appropriate feedback to students using evaluation data in science education at a time when interest in educational data mining has recently increased in education. In this study, we use the evaluation data of 2,576 students who took 24 questions of the national assessment of educational achievement. And we use K-means cluster analysis as a method of unsupervised machine learning for clustering. As a result of clustering, students were divided into six clusters. The middle-ranking students are divided into various clusters when compared to upper or lower ranks. According to the results of the cluster analysis, the most important factor influencing clusterization is academic achievement, and each cluster shows different characteristics in terms of content domains, subject competencies, and affective characteristics. Learning motivation is important among the affective domains in the lower-ranking achievement cluster, and scientific inquiry and problem-solving competency, as well as scientific communication competency have a major influence in terms of subject competencies. In the content domain, achievement of motion and energy and matter are important factors to distinguish the characteristics of the cluster. As a result, we can provide students with customized feedback for learning based on the characteristics of each cluster. We discuss implications of these results for science education, such as the possibility of using this study results, balanced learning by content domains, enhancement of subject competency, and improvement of scientific attitude.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.316-318
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• 2019

Recently, healthy life has become an issue in an aging society, and the number of people who have been interested in continuous health care for better life is increasing. In this paper, we implemented a personalized recommendation systm to provide convenient healthcare management for user. The PHR (Personal Health Record) of user could be stored in the server along with health related information such as lifestyle, disease, and physical condition. The users could be classified into similar clusters according to the PHR profile in order to provide healthcare contents to the users who had similar PHR profile. K-Means clustering was applied to generate clusters based on PHR profile and ACDT(Ant Colony Decision Tree) algorithm was used to provide personalised recommendation of health information stored in knowledge base. The app system developed in this paper is useful for users to perform healthcare themselves by providing information on serious diseases and lifestyle habits to be improved according to the clusters classified by PHR profile.

• Korean Journal of Environment and Ecology
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• v.10 no.2
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• pp.240-250
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• 1997

To investigate the structure and the conservation strategy of natural forest at Soch'ongbong-Taech'ongbong Area in Soraksan , 36 plots (20m*20) set up with random sampling method. Three groups - Quercus mongolica- Abies holophylla community, Acer mandshuricum- Abies nebhrolepis community, Abies holophylla-Ulmus laciniata-were classified by cluster analysis. High positive correlations were proved between Ulmus laciniata and Carpinus cordata; Tripterygium regelii and Syringa reticulata var. mandshurica ; Tripterygium regelii and Rhodo- dendron brachycarpum ; Carpinus cordata and Rhododenron mucronulatm; Wergela subsessilis and Rhododenron nucronulatum and High negative correlations were proved between Rhododen- dron schippenbachii and Euonymus macroptera; Betula ermani and Acer pseudo-sieboldianum, Tilia amurensis, Magnolia sieboldii, Betula costata ; Pinus pumila and Pinus koraiensis. Species diversity(H') of investigated area was calculated 0.8393~1.3431.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.373-387
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• 2021

In this study, the impact of clustered groundwater usage facilities and the proper amount of groundwater usage in the Daejeong-Hangyeong watershed of Jeju island were evaluated based on the data-driven analysis methods. As the applied data, groundwater level data; the corresponding precipitation data; the groundwater usage amount data (Jeoji, Geumak, Seogwang, and English-education city facilities) were used. The results show that the Geumak usage facility has a large influence centering on the corresponding location; the Seogwang usage facility affects on the downstream area; the English-education usage facility has a great impact around the upstream of the location; the Jeoji usage facility shows an influence around the up- and down-streams of the location. Overall, the influence of operating the clustered groundwater usage facilities in the watershed is prolonged to approximately 5km. Additionally, the appropriate groundwater usage amount to maintain the groundwater base-level was analyzed corresponding to the precipitation. Considering the recent precipitation pattern, there is a need to limit the current amount of groundwater usage to 80%. With increasing the precipitation by 100mm, additional groundwater development of approximately 1,500m³-1,900m³ would be reasonable. All the results of the developed data-driven estimation model can be used as useful information for sustainable groundwater development in the Daejeong-Hangyeong watershed of Jeju island.