• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.569-578
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• 2020

Various graph clustering methods have been introduced to identify communities in social or biological networks. This paper studies the entropy-based and the Markov chain-based methods in clustering the undirected graph. We examine the performance of two clustering methods with conventional methods based on quality measures of clustering. For the real applications, we collect the mathematical subject classification (MSC) codes of research papers from published mathematical databases and construct the weighted code-to-document matrix for applying graph clustering methods. We pursue to group MSC codes into the same cluster if the corresponding MSC codes appear in many papers simultaneously. We compare the MSC clustering results based on the several assessment measures and conclude that the Markov chain-based method is suitable for clustering the MSC codes.

• 대한치과교정학회지
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• 제21권1호
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• pp.113-130
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• 1991

This study was undertaken to investigate soft tissue profile changes by orthodontic treatment in female patients. Traditional cephalometric appraisal yields data of dubious scientific value, the soft tissue profile forms were evaluated by finite element method. The subject was divided into three groups according to Angle's classification and each group was composed of 25 female patients averaged aged 12-14 years at the start of treatment. The changes in soft tissue form were evaluated by computing the degree of distortion in each triangle after treatment compared with the triangle before treatment. The conclusions were as follows; 1. The soft tissue profile forms were evaluated by finite element method and independent evaluation of each element by local changes was possible. 2. Maximum and minimum principal strains showed marked variability depending on the particular finite element and each group and Class II, III sample was greater than Class I sample. 3. Soft tissue size changes as a result of orthodontic treatment was not related to those of shape. 4. Soft tissue changes by orthodontic treatment were variable in individual patient, and were not related to Angle's classification.

• 천문학회보
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• 제39권1호
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• pp.75.2-75.2
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• 2014

We have developed a set of daily solar flare peak flux forecast models using the multiple linear regression (MLR), the auto regression (AR), and artificial neural network (ANN) methods. We consider input parameters as solar activity data from January 1996 to December 2013 such as sunspot area, X-ray flare peak flux, weighted total flux $T_F=1{\times}F_C+10{\times}F_M+100{\times}F_X$ of previous day, mean flare rates of a given McIntosh sunspot group (Zpc), and a Mount Wilson magnetic classification. We compute the hitting rate that is defined as the fraction of the events whose absolute differences between the observed and predicted flare fluxes in a logarithm scale are ${\leq}$ 0.5. The best three parameters related to the observed flare peak flux are as follows: weighted total flare flux of previous day (r=0.5), Mount Wilson magnetic classification (r=0.33), and McIntosh sunspot group (r=0.3). The hitting rates of flares stronger than the M5 class, which is regarded to be significant for space weather forecast, are as follows: 30% for the auto regression method and 69% for the neural network method.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제22권2호
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• pp.211-227
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• 2008

수학과 협동학습에서 학생들의 의사소통을 포함한 유기적인 상호과정은 매우 중요하며, 소집단의 구성 방법은 학습 결과에 많은 영향을 미친다. 따라서 수학과 협동학습의 효과를 높이기 위해서는 학습자의 다양한 특성에 따라 소집단이 구성되어야 하며 이때에는 인지적 요인뿐만 아니라 정의적 요인도 신중히 고려되어야 한다. 이에 본 연구에서는 정의적 요인 중, 학생이 어떻게 학습하고 무엇을 학습하는지의 개인차를 나타내주는 성격유형을 협동학습을 위한 소집단 구성의 중요한 기준으로 보고 5학년을 대상으로 MMTIC 검사를 통해 성격유형별 동질집단과 이질집단을 구성하여 소집단 협동학습을 실시하였다. 그 결과 성격유형별 동질집단과 이질집단 간 수학적 태도는 차이를 보이지 않았으나 수학 성취도에 있어서는 유의미한 차이를 보였다. 즉 수학과 소집단 협동학습에서 성격유형별 동질집단 구성이 수학 성취도 향상에 효과적임을 알 수 있었다.

• 의정연구
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• 제25권2호
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• pp.35-67
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• 2019

본 연구는 유럽의회 선거에서 극우정당들이 거둔 성과를 논하거나 지지세 추이를 확인하기 위해서 유럽의회 정치그룹이 확보한 의석수를 중심으로 분석하는 기존의 방법을 지양하고, 그 대신 EU 회원국들 국내 정치에서의 극우 동종정당(far-right party family) 분류를 통하여 그들이 유럽의회 선거에서 거둔 의석수를 합산하는 방식으로 분석한다. 이러한 극우 동종정당에 기반한 선거 결과 분석이 필요한 이유는 두 가지이다. 첫째로 유럽의회 선거에서 선출된 극우성향의 유럽의회의원들 중 일부는 극우성향의 정치그룹에 가입하지 않기 때문이며, 둘째로 극우성향으로 분류되는 일부 정치그룹의 경우에 소속 의원들의 성향이 균질하지 않아 오히려 다수는 중도우파성향의 의원들로 구성된 경우도 있기 때문이다. 이러한 문제의식에서 출발한 본 연구는 구체적으로 2019년 유럽의회 선거에서 극우정당이 거둔 성과를 극우 동종정당 분류에 기반하여 분석해 보았다. 그 결과, 유럽의회 정치그룹이 확보한 의석수 중심 분석에 기반하여 극우정당들이 이번 유럽의회 선거에서 그다지 약진하지 못했다는 평가를 내린 서구 주요 언론들의 분석에 명확한 한계가 있음을 확인할 수 있었다. 극우 동종정당 분류에 기반한 선거 결과 분석에 따르면, 2019년 유럽의회 선거에서 극우정당들이 확보한 의석수는 선거 전 여론조사 결과를 오히려 크게 상회하는 것으로 나타났음은 물론, 2014년 유럽의회 선거와 비교하더라도 극우정당들의 의석수가 큰 폭으로 증가한 것인 바, 본 연구는 2019년 유럽의회 선거에서 극우정당은 크게 약진했다고 평가하는 것이 타당하다고 주장한다.

• 정보처리학회논문지B
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• 제8B권5호
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• pp.447-454
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• 2001

새로운 문서를 기존에 존재하는 클래스들에 할당하는 방법을 문서의 자동 분류라고 한다. 문서의 자동 분류는 뉴스 그룹의 기사분류, 웹 문서의 범주화, 전자 메일의 순서화, 사용자의 관심을 학습하여 보다 정확한 정보 검색을 제시하는데 사용될수 있다. 본 논문에서는 한국어 문서분류의 정확도를 높이기 위하여 문서내의 모든 단어들에 대한 확률값을 사용하여, 문서를 분류하는 기존의 방법과 달리 문서의 주제어를 선정하여 주제어로 선정된 단어들에 가중치를 부여하고 그렇지 않은 단어들에 대해서는 제거하너가 낮은 가중치를 부여하는 베이지안 분류자를 사용한다. 문서에는 특징으로 추출된 단어가 적어 문서를 분류하기 위한 만족할 만한 정보를 제공하지 못할 경우에 부족한 문서의 특징을 보충하기 위하여 말뭉치로부터 자동 단어 군집화를 통해 형성된 연관 단어 군집을 사용한다. 이러한 방법을 한국어 문서에 적용한 결과 기존의 베이지안 확률을 사용한 분류법보다 향상된 분류 정확도를 얻을 수 있었다.

• 대한산업공학회지
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• 제28권1호
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• pp.112-127
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• 2002

A useful pattern is a pattern that contributes much to learning. For a classification problem those patterns near the class boundary surfaces carry more information to the classifier. For a regression problem the ones near the estimated surface carry more information. In both cases, the usefulness is defined only for those patterns either without error or with negligible error. Using only the useful patterns gives several benefits. First, computational complexity in memory and time for learning is decreased. Second, overfitting is avoided even when the learner is over-sized. Third, learning results in more stable learners. In this paper, we propose a pattern 'utility index' that measures the utility of an individual pattern. The utility index is based on the bias and variance of a pattern trained by a network ensemble. In classification, the pattern with a low bias and a high variance gets a high score. In regression, on the other hand, the one with a low bias and a low variance gets a high score. Based on the distribution of the utility index, the original training set is divided into a high-score group and a low-score group. Only the high-score group is then used for training. The proposed method is tested on synthetic and real-world benchmark datasets. The proposed approach gives a better or at least similar performance.

• Clinics in Shoulder and Elbow
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• 제9권2호
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• pp.155-161
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• 2006

Purpose: To compare the clinical and radiological results between the modified Weaver-Dunn method and modified Phemister method in the acute acromioclavicular joint dislocation. Materials and Methods: We reviewed 19 patients who were treated for the acute acromioclavicular joint dislocation from 2001 to 2002. 10 patients were operated with the modified Weaver-Dunn method (group A) and the others with modified Phemister method (group B). The classification of preoperative injury was analyzed by using the Rockwood system, the clinical assessment of preoperative and postoperative by the modified UCLA rating scale and the radiological assessment by simple x-ray. Results: With the modified UCLA rating scale, group A showed 5 cases(50%) of excellent and 5 cases(50%) of good, group B showed 4 cases(44.4%) of excellent and 5 cases(55.6%) of good. In the radiologic findings of the coracoclavicular distances, group A was 16.2 mm at preoperative, 8.8 mm at postoperative, 9.7 mm at last follow-up and group B was 12.9 mm, 6.7 mm and 7.9 mm respectively. Postoperatively there were no complications such as surgical wound infection and failure of Kirschner wires. Conclusion: Both the modified Weaver-Dunn and modified Phemister methods have shown satisfied clinical and radiologic results, and there was no difference in these result between two groups (p>0.05).

• 한국의료질향상학회지
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• 제12권2호
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• pp.84-92
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• 2006

Background : To examine the difference between ICD-10 and The Korean standard classification of disease(oriental medicine), and to aim at improve the practical use as statistical data. It is one of the reason of disease classification. On that account we convert the many to many correspondence presenting classification of oriental medicine into many to one correspondence. Method : The study tracked out 155 patients discharged from the university hospital which is located in Gyeonggi Province and managing hospital and oriental medicine hospital from July to October this year. The period of this study was from August 1 to November 18. We compared correspondence between the two services' diagnosis(hospital services and oriental medicine hospital services) at the same time and attempted many to one correspondence classification. That is for production of statistical data. Result : We investigated the group which have had medical treatment experience of two kinds of services at the same time. The result of this investigation was that the same oriental medicine diagnosis used differently in western medicine diagnosis. 44.5% was accorded with western medicine diagnosis. Correspondence of the western medicine diagnose with the top of the Korean standard classification of disease(oriental medicine) list's western medicine diagnosis was 13.5%. For many to one correspondence classification for statistics, one western medicine diagnosis was selected for one oriental medicine diagnosis. In case of the main diagnosis(I sign) was not enough to explain oriental medicine diagnosis' characteristic, we chose multiple other diagnosis, so other diagnosis(II sign) about patient's cause of disease could be selected for supplement after we examined the patient's records. The statistics was possible with this many to one correspondence. Conclusion : The result of this study about correspondence between western medicine diagnoses and those of oriental medicine confirms that The Korean standard classification of disease(oriental medicine) is hard to be standardized with western medicine diagnosis. Therefore, according to this study, we use new many to one correspondence classification, multiple oriental medicine diagnoses with one ICD-10, which can be used by statistical data.

• 산업경영시스템학회지
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• 제46권4호
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• pp.1-14
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• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.