• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.481-486
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• 2021

Machine learning algorithms adopt criterion function as a key component to measure the quality of their model derived from data. Cluster analysis also uses this function to rate the clustering result. All the criterion functions have in general certain types of favoritism in producing high quality clusters. These clusters are then described by attributes and their values. Category utility and partition utility play an important role in cluster analysis. These are fully analyzed in this research particularly in terms of how they are related to the favoritism in the final results. In this research, several data sets are selected and analyzed to show how different results are induced from these criterion functions.

• Korean Journal of Environment and Ecology
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• v.26 no.3
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• pp.412-425
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• 2012

This study investigated the actual vegetation and plant community structure of Geumsun valley and Weonjeok valley of Naejangsan(Mt.) National Park to provide the data for park management. As a result of analysis of actual vegetation, Quercus variabilis community(47.3%) and Quercus serrata community(17.0%) are widely distributed but Carpinus tschonoskii community(7.5%) and Zelkova serrata community(6.9%) are distributed in valley forests. Plant communities were divided into 6 communities of Fraxinus mandshurica, Carpinus tschonoskii, Carpinus tschonoskii-Platycarya strobilacea-Zelkova serrata, Zelkova serrata, deciduous broad-leaved mixture(Zelkova serrata-Lindera erythrocarpa-Acer palmatum), and Lindera erythrocarpa-Cornus walteri according to the analysis of TWINSPAN of classification using 20 plots($400m^2$). Geumseon valley is composed of boulder stone area of average slope $20^{\circ}$, and there were distributed Fraxinus mandshurica community of 86 years old, Carpinus tschonoskii community in age from 56 to 79, and Carpinus tschonoskii-Platycarya strobilacea-Zelkova serrata community in age from 48 to 71. Weonjeok valley is composed of boulder stone area of average slope $11^{\circ}$, and there were distributed Zelkova serrata community in age from 52 to 71, deciduous broad-leaved mixture community in age from 49 to 70, and Lindera erythrocarpa-Cornus walteri community in age from 43 to 51. Ecological succession of each community was predicted to maintain same state. The Shannon's species diversity showed from 0.8220(Fraxinus mandshurica community) to 1.3850(Carpinus tschonoskii community) per unit area of $400m^2$.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.195-201
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• 2008

본 연구에서는 고속도로와 같은 연속류 에서의 통행시간 군집화 현상을 연구하여 신뢰성 있는 단위 시간 당 구간 대표 통행시간을 구하는 전처리 방법을 제시하는데 목적이 있다. 현재까지는 단위시간 당 구간의 통행시간 대푯값으로 하나의 평균값(Mean), 최빈값(Mode), 또는 중앙값(Median)이 사용되었다. 이의 문제점은 운전자의 주행 습관(빠른 주행, 느린 주행), 휴게소 이용, 도로 정체 등 다양한 요인으로 인하여 차량일 구간 주행 속도 간 편차가 많아 현재 사용하는 1개의 대푯값으로는 전체 차량의 운행 특징을 정확히 표현하기가 곤란하다는 점이다. 이를 개선하기 위하여 본 연구에서는 군집 방법을 이용하여 차량군을 복수의 비슷한 군집으로 나누고 나누어진 그룹별로 통행시간 대푯값을 선정하는 방법을 제시하고 실험하여 이 방법이 효과적임을 증명하였다.

• Korean Journal of Environment and Ecology
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• v.19 no.2
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• pp.90-98
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• 2005

To investigate the vegetation structure of the Woraksan National Park, twenty-two plots were set up and surveyed. According to the analysis of classification by TWINSP AN, the communities were divided by six groups; Pinus densiflora-Quercus serrata, Q. mongolica-Q. serrata, Q. mongolica-Betula davueica, P. densiflora-Q. mongolica, Q. mongolica, Q. mongolica-Acer pseudosieboldianum. Successional sere of the forest vegetation in the surveyed area were proeeding from Pinus densiflora to Quercus serrata, Quercus monogolica in the canopy layer group and from Rhododendron Rhododendron schlippenbachii to Fraxinus sieboldiana and Acer pseudosieboldianum in the understory layer group. But Q. mongolica might be edaphic climax species in some area.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.67-77
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• 2017

The purpose of this study is to find convergence differences of academic burnout, career preparation behavior, and general characteristics of the students majoring in medical records according to each cluster of resilience, and draw a proper improvement plan. A self-administered questionnaire survey had been conducted and a total of 168 copies were analyzed. As a results Cluster analysis was conducted on three detailed categories of resilience and was classified into two clusters. Cluster1 was a group that had points higher than the average points of Korean in each one of three categories. Cluster2 had all of which were lower points than that. Cluster1 had higher points than cluster2 in terms of career preparation behavior, hobby, subjectively good health condition, extroverted personality, good academic records, satisfaction with school life, and study satisfaction ratio, but had lower points than cluster2 in terms of academic burnout. Therefore, positiveness enhancement education focused on cluster2 will improve total group resilience.

• Journal of The Korean Association For Science Education
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• v.25 no.5
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• pp.563-570
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• 2005

This study investigated the relationships among middle school students' understanding about the nature of scientific knowledge, conceptual understanding, and learning strategies. Grade 7 students (N=162) in Incheon completed the nature of scientific knowledge scales (NSKS) and a learning strategy questionnaire. After learning density by way of a CAl program, a conception test was administered. Results indicated that students' conceptual understanding and both deep and surface learning strategies were significantly correlated to their understanding about the nature of scientific knowledge. A cluster analysis was used to classify students on the basis of their deep and surface learning strategies. Three clusters of students with distinctive learning strategy patterns were found; high deep-low surface strategy (cluster 1), low deep-high surface strategy (cluster 2), and high deep-high surface strategy (cluster 3). One-way ANOVA results revealed that the scores of cluster 3 were significantly higher than those of the others in the NSKS and the conception test. Additionally, cluster 1 also performed better than cluster 2 in the conception test. Lastly, educational implications were discussed.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.572-587
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• 2008

The Self-organizing Feature Map(SOFM) that is one of unsupervised neural networks is a very powerful tool for data clustering and visualization in high-dimensional data sets. Although the SOFM has been applied in many engineering problems, it needs to cluster similar weights into one class on the trained SOFM as a post-processing, which is manually performed in many cases. The traditional clustering algorithms, such as t-means, on the trained SOFM however do not yield satisfactory results, especially when clusters have arbitrary shapes. This paper proposes automatic clustering on trained SOFM, which can deal with arbitrary cluster shapes and be globally optimized by graph cuts. When using the graph cuts, the graph must have two additional vertices, called terminals, and weights between the terminals and vertices of the graph are generally set based on data manually obtained by users. The Proposed method automatically sets the weights based on mode-seeking on a distance matrix. Experimental results demonstrated the effectiveness of the proposed method in texture segmentation. In the experimental results, the proposed method improved precision rates compared with previous traditional clustering algorithm, as the method can deal with arbitrary cluster shapes based on the graph-theoretic clustering.

• Korean Journal of Plant Resources
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• v.33 no.1
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• pp.1-14
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• 2020

This study was conducted to analyze community structure and species composition of Pinus densiflora for. erecta Stand in Mt. Cheonchuk (653 m). Field survey was carried out from June to September in 2013. 74 plots (20×20 m) were set up, 5 herb layer plots (3×3 m) were constructed for each plot, and there, Diameter at Breast Heigh t(DBH), height, environmental factor, annual growth were measured. Vascular plants were surveyed as following; 66 family, 165 genus, 211 species, 2 sub species, 29 variety, 6 form 248 taxa. Results of cluster analysis for P. densiflora for. erecta forest, 3 communities were divided into; Quercus mongolica (P-1), Quercus variabilis (P-2) and Quercus aliena-Stephanandra incisa (P-3). There were significant environmental factors that organic layer, annual growth, CEC, total total nitrogen, organic matter and pH for each community. As a result of DCA, P-1 and P-2 were distributed large range of environmental factors but relatively limited in P-3. Distributions of herb layer were affected by sand, cation exchange capacity, silt and total nitrogen. Results of MRPP test for herb layer communities, it was significantly analyzed (A=0.003, P<0.008). Species diversity index was highly recorded in P-3 and influenced by cation exchange capacity, total nitrogen, annual growth in consequence of NMS analysis.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.941-949
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• 2011

In this paper, 72 weather stations in Korea are clustered by the hierarchical agglomerative procedure based on the average linkage method. We compare our clusters and stations divided by mountain chains which are applied to study on the impact analysis of foodborne disease outbreak due to climate change.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.577-579
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• 2003

본 논문에서는 생체인식 분야 중 얼굴인식의 검색 정확성 향상 및 검색 시간을 단축하기 위한 단계로 인종별 얼굴영상 데이터베이스에 대한 군집화 기법을 연구하였다. 우선, 일반적으로 얼굴 및 이미지 검색에 사용되는 다양한 특징을 추출하고, 추출한 다차원의 특징 데이터들로부터 다 인종 얼굴 데이터를 유사한 인종별로 정확하게 군집화 하기 위해 최적의 특징벡터를 자동으로 선택 할 수 있는 방법을 제안하였다. 군집결과 분석을 위해 자기 조직화 지도 모형을 이용하였는데, 이는 2차원 분석 및 가시화에 유용하며, 학습 후 코드북벡터를 사용하여 유사한 의미간의 거리부터 검색할 수 있는 특징을 가지고 있다. 특징추출에 관한 실험결과 인종별 구분을 위한 특징벡터로는 웨이블릿 주파수 성분(lowpass 성분)과 CbCr 특징벡터가 인종별 군집화에 가장 유용한 특징으로 선택되었으며. 추출된 특징을 바탕으로 semantic map을 구성하여 제안방법의 효율성을 제시하였다.