• Korean Journal of Child Education & Care
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• v.17 no.1
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• pp.75-98
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• 2017

This study examined the possibility of clustering using 5-year-old children's basic learning ability and mothers' achievement expectation anxiety, and compared the impact of the children's self-regulation ability and mothers' learning involvement for each cluster. The subjects were 239 children (120 boys & 119 girls) aged 5 and attending 9 kindergartens in Seoul, Gyeonggi and Incheon, and also their mothers. The collected data were analyzed using non-hierarchical (K-means) cluster analysis and multivariate logistic regression analysis. The findings of this study were as follows. First, the mother-child pairs were classified into four clusters of 'high learning ability-high expectation anxiety', 'high learning ability-low expectation anxiety', 'low learning ability-low expectation anxiety', or 'low learning ability-high expectation anxiety'group. Second, the level of child's self-monitoring, self-control, and mother's respect and love were significantly higher in the 'high learning ability-low expectations anxiety' group than the 'low learning ability-high expectation anxiety' group. Also, pressure for academic achievement was higher in the 'high learning ability-high expectation anxiety' group than the 'low learning ability-low expectations anxiety' group. Third, child's self-monitoring, mother's pressure for academic achievement, home learning activities, and respect/love for child predicted the clustering using children's basic learning ability and mothers' achievement expectation anxiety.

• Journal of the Korea Computer Graphics Society
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• v.10 no.2
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• pp.42-50
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• 2004

캐릭터 애니메이션 기술의 발달로 가상공간에 애니메이트되는 캐릭터의 수가 점점 증가되고 있으며, 캐릭터 자체 골격구조의 관절 개수와 캐릭터를 덮고 있는 메쉬의 폴리곤 개수도 점점 증가하는 추세이다. 따라서, 실시간 가상환경에서 다수의 캐릭터를 전처리 과정 없이 시뮬레이션할 경우 전체 군중시스템 성능의 저하가 예상된다. 본 논문에서는, 이러한 문제점을 해결하기 위해 모션 다단계(motion level-of-detail) 기법을 제시한다. 모션 단순화 기법은 캐릭터의 움직임을 제어하는 골격(관절)구조와 캐릭터의 형태를 시각적으로 표현하는 기하(메쉬)구조를 단순화 하는 방법으로 기존 동작과 단순화된 동작의 차이를 최소화 한다. 골격구조 단순화를 위한 JPC(joint posture clustering)방법은 특정 관절의 연속된 모션 시퀀스에서의 유사 자세 집단을 추출하여 하나의 자세로 표현하는 방법으로, 모션의 특성에 따라 동적으로 관절을 단순화하여 관절 시뮬레이션 시간을 줄이는 방법이다. JPC방법은 골격구조가 시간에 따라 동적으로 변형되기 때문에 골격구조의 계층구조를 재 구축할 시간이 필요하지만, 기존 동작과 유사성을 잃지 않는 단순화된 동작 생성이 가능하다. 유사 자세 집단을 추출하기 위해 전체 모션 시퀀스에서 관절의 프레임간 자세 차이를 수식화하여 테이블 형태로 구성하고 이를 통해 기존 동작의 유사성을 잃지 않으며 관절의 단순화 율을 최대화 할 수 있는 알고리즘을 제시한다. 또한, 실시간 군중 환경의 성능을 더욱 향상시키기 위해 시간에 따라 변형되는 캐릭터 메쉬의 단순화 기법을 적용한다. 실험결과 모션 다단계 기법은 실시간 군중환경에서 캐릭터의 수가 많고 복잡한 골격구조와 기하구조로 구성된 관절 궤적의 변화가 심하지 않은 동작에 대해 특히 효율적이다.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.39-51
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• 2012

Cluster analysis has proven to be a useful tool for investigating the association structure among genes and samples in a microarray data set. We applied several cluster validation measures to evaluate the performance of clustering algorithms for analyzing microarray gene expression data, including hierarchical clustering, K-means, PAM, SOM and model-based clustering. The available validation measures fall into the three general categories of internal, stability and biological. The performance of clustering algorithms is evaluated using simulated and SRBCT microarray data. Our results from simulated data show that nearly every methods have good results with same result as the number of classes in the original data. For the SRBCT data the best choice for the number of clusters is less clear than the simulated data. It appeared that PAM, SOM, model-based method showed similar results to simulated data under Silhouette with of internal measure as well as PAM and model-based method under biological measure, while model-based clustering has the best value of stability measure.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.293-296
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• 2000

본 논문에서는 주제어 인식에 기반한 문서영상의 검색 및 색인 시스템에 적용하기 위한 단어 단위 분한 시스템을 제안한다. 제안 시스템은 영상 전처리, 문서 구조 분석을 통해 추출된 텍스트 영역을 입력으로 단어 단위 분할을 수행하는데, 텍스트 영역에 대해 텍스트 라인을 분할하고 분할된 텍스트 라인을 단어 단위로 분할하는 계층적 접근 방법을 사용한다. 텍스트라인 분할은 수평 방향 투영 프로파일을 적용하여 분할 지점을 구한다. 그리고 단어 분할은 연결요소들을 추출한 후 연결요소간의 gap 정보를 구하고, gap 군집화 기법을 사용하여 단어 단위 분한 지점을 구한다. 이때 단어 단위 분할의 성능을 저하시키는 특수기호에 대해서는 휴리스틱 정보를 이용하여 검출한다. 제안 시스템의 성능 평가는 50개의 텍스트 영역에 적용하여 99.83%의 정확도를 얻을 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.335-338
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• 2016

최근 디지털 정보들은 각종 매체에 저장되어 다양하게 활용되고 있다. 그 중 범죄관련 비정형데이터의 분석과 활용은 범죄수사에 유용한 자료로 활용될 수 있다. 그러나 기존의 범죄통계 자료의 분석 및 활용은 정형데이터를 이용한 제한적 접근에 그치고 있다. 따라서, 본 논문은 수사 자료 중 처리되지 못한 비정형데이터를 분석, 저장, 처리하여, 수사 자료로 활용할 수 있도록 정형데이터화 함으로 범죄 프로파일링에 도움이 될 것으로 기대된다.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.783-791
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• 2013

There are sixteen indicators of "College Information" found on the website of College Information Disclosure Center. Among these indicators, the current study examined an enrollment rate and an employment rate based on health insurance coverage, and focused on twenty-four universities in Daegu and Gyeongbuk area. The universities were classified into groups by the enrollment rate and employment rate. This study investigated the characteristics pertaining to those different groups. Hierarchical cluster analysis and support vector cluster analysis were conducted in order to analyze the characteristics of the groups statistically.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.1-8
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• 1998

Clustered microcalcifications on X-ray mammograms are an important sign for early detection of breast cancer. This paper proposes a computer-aided diagnosis method for the detection of clustered microcalcifications and marking their locations on digitized mammograms. The proposed detection method consists of the region of interest (ROI) selection, the film-artifact removal, the surrounding texture analysis method for the detection of clustered microcalcifications, which is based on the second-order histogram in two nested surrounding regions on the current pixel. This paper also describes the effectiveness of the proposed film-artifact removal filter in terms of the classification performance with the receiver operating-characteristics(ROC) analysis. A three-layer backpropagation neural network is employed as a classifier. The appropriate marking for the locations of clustered microcalcifications can be used to alert radiologists to locations of suspicious lesions.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.17-30
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• 2000

In this paper, we propose an efficient algorithm to produce 3-D surface model from a set of range data, based on NURBS (Non-Uniform Rational B-Splines) surface fitting technique. It is assumed that the range data is initially unorganized and scattered 3-D points, while their connectivity is also unknown. The proposed algorithm consists of three steps: initial model approximation, hierarchical representation, and construction of the NURBS patch network. The mitral model is approximated by polyhedral and triangular model using K-means clustering technique Then, the initial model is represented by hierarchically decomposed tree structure. Based on this, $G^1$ continuous NURBS patch network is constructed efficiently. The computational complexity as well as the modeling error is much reduced by means of hierarchical decomposition and precise approximation of the NURBS control mesh Experimental results show that the initial model as well as the NURBS patch network are constructed automatically, while the modeling error is observed to be negligible.

• Journal of Korea Water Resources Association
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• v.42 no.2
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• pp.149-160
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• 2009

The objective of this study is to suggest parameter regionalization scheme which is integrated two multivariate statistical methods: principal components analysis(PCA) and hierarchical cluster analysis(HCA). This technique is to apply semi-distributed rainfall-runoff model on ungauged catchments. 7 catchment characteristics (area, mean altitude, mean slope, ratio of forest, water content at saturation, field capacity and wilting point) are estimated for 109 mid-sized sub-basins. The first two components from PCA results account for 82.11% of the total variance in the dataset. Component 1 is related to the location of the catchments relevant to the altitude and Component 2 is connected with the area of these. 103 ungauged catchments are clustered using HCA as the following 6 groups: Goesan 23, Andong 6, Imha 5, Hapcheon 21, Yongdam 4, Seomjin 44. SWAT model is used to simulate runoff and the parameters of the model on the 6 gauged basins are estimated. The model parameters were regionalized for Soyang, Chungju and Daecheong dam basins which are assumed as ungauged ones. The model efficiency coefficients of the simulated inflows for these three dams were at least 0.8. These results also mean that goodness of fit is high to the observed inflows. This research will contribute to estimate and analyze hydrologic components on the ungauged catchments.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.103-111
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• 2011

Clustering methods is divided into hierarchical clustering, partitioning clustering, and more. If the amount of documents is huge, it takes too much time to cluster them in hierarchical clustering. In this paper we deal with K-Means algorithm that is one of partitioning clustering and is adequate to cluster so many documents rapidly and easily. We propose the new method of selecting initial seeds in K-Means algorithm. In this method, the initial seeds have been selected that are positioned as far away from each other as possible.