• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.48 no.1
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• pp.34-42
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• 2016

In this study, we classified three copying papers and Korean, Chinese, and Japanese traditional papers using IR and/or NIR spectra and principal component analysis. Various chemicals are used when producing fine papers. In this case, the IR method to analyze functional groups is suitable for the classification of paper. On the other hand, NIR analysis is more suitable for the classification of traditional papers, as it uses nearly raw materials (pulp). Therefore, principal component analysis using IR and NIR depending on the paper production process will be the classification tool of paper.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.2
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• pp.37-42
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• 2022

Purpose Since 1985, the Korean society of nuclear medicine technology (KSNMT) has been engaged in academic activities related to nuclear medicine imaging. From 2017 to 2021, the papers published in the journal were classified by the specific fields to examine the trends in the research and the direction of nuclear medicine in comparison with the papers submitted to the Korean Society of Nuclear Medicine (KSNM) during the same period. Materials and Methods From 2017 to 2021, papers submitted to KSNMT and KSNM were classified and databaseization using the Excel program by submission type, examination equipment, and examination field. Through this data, the number of papers published in journals by year, the number of papers submitted by detailed fields, and key words by era were analyzed and compared. Results The papers included by journal was 57 KSNMT and 280 KSNM. The major large classification of equipment, PET, Planar and SPECT was 26.3%, 21.1%, 19.3% in the KSNMT, KSNM was 49.6%, 6.4%, and 9.3%, with 66.7% and 65.3%, respectively. the major medium classification of equipment, industrial safety, urogenital system, nervous system, and quality control accounted for 54.4% of the total papers of the total ratio in the KSNMT, while the medium classification of oncology, endocrine system, urogenital system, therapy, and nervous system accounted for 61.1% of KSNM. In the major small classification of image acquisition, improvement effect, and exposure management accounted for 70.2% in KSNMT, while the items of image acquisition, report, and improvement effect accounted for 60.7% in KSNM. The major keywords except for equipment-related keywords such as PET/CT, PET/MR, and SPECT were SUV, Planar Image, and Respiration Gating Method in KSNMT and Ga68, Thyroid, and Lymphoma in the KSNM. Conclusion When checking the last 5 years of submissions, we can see that KSNMT is mainly concerned with image acquisition using existing radiotracers, while KSNM has focused on new radiotracers such as ⁶⁸Ga, ¹⁷⁷Lu, etc., and new medical technologies of theranostic. It has been confirmed that more PET-related papers than other examination equipment will account for a greater number of papers, and it is believed that future submissions will also account for a higher proportion of PET-related papers than other equipment.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.33-59
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• 2016

This study examined the factors affecting the performance of automatic classification for the domestic conference papers based on machine learning techniques. In particular, In view of the classification performance that assigning automatically the class labels to the papers in Proceedings of the Conference of Korean Society for Information Management using Rocchio algorithm, I investigated the characteristics of the key factors (classifier formation methods, training set size, weighting schemes, label assigning methods) through the diversified experiments. Consequently, It is more effective that apply proper parameters (${\beta}$, ${\lambda}$) and training set size (more than 5 years) according to the classification environments and properties of the document set. and If the performance is equivalent, I discovered that the use of the more simple methods (single weighting schemes) is very efficient. Also, because the classification of domestic papers is corresponding with multi-label classification which assigning more than one label to an article, it is necessary to develop the optimum classification model based on the characteristics of the key factors in consideration of this environment.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.22 no.3
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• pp.108-121
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• 2009

Objective : This study was carried out to analyze and understand the trends of Atopic dermatitis papers Published in the Journal of Korean Oriental Ophthalmology & Otolaryngology & Dermatology(JKOOOD) Methods : We have reviewed 43 articles of atopic dermatitis which were published in JKOOOD during 1988-2008. All the papers are classified into three categories; original article, review article and case report. Results : 1. The number of journals associated with atopic dermatitis is 43 papers: 16 original articles(16/43%), 16 case reports(16/43%), 11 review articles(11/43%). 2. Classification of 16 original articles in terms of methodology: 11 experimental studies(11/16%), 5 descriptive studies (5/16%), 0 analytic studies(0%). 3. Classification of 16 case reports in terms of the number of patients: 1 person(8/16%), 2 persons(3/16%), 3 persons(2/16%). Conclusions : In this study, we analyzed the trends of Atopic dermatitis papers Published in the Journal of Korean Oriental Ophthalmology & Otolaryngology & Dermatology during 1988-2008. It is needed to adopt the qualitative methods of evaluation in order to develop a level of evidence.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.69-90
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• 2022

As basic data that can systematically support and evaluate R&D activities as well as set current and future research directions by grasping specific trends in domestic academic research, I sought efficient ways to assign standardized subject categories (control keywords) to individual journal papers. To this end, I conducted various experiments on major factors affecting the performance of automatic classification, focusing on feature selection techniques, for the purpose of automatically allocating the classification categories on the National Research Foundation of Korea's Academic Research Classification Scheme to domestic journal papers. As a result, the automatic classification of domestic journal papers, which are imbalanced datasets of the real environment, showed that a fairly good level of performance can be expected using more simple classifiers, feature selection techniques, and relatively small training sets.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.16 no.1
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• pp.1-32
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• 2003

Objectives: This study was carried out to analyze and understand the trends of research papers published In the Journal of Oriental Medical Surgery？phthalmology & Otolaryngology Society(JOMSOOS). Methods: We studied the 308 research papers that had been published in JOMSOOS from 1988 Vol. 1. No. 1. to 2002 Vol. 15. No. 2. Our study was developed through the four stages in order to analyze the papers; 1) we analyzed all the papers overall to classify them into three categories; original article. review article and case report. 2) we classified the original articles in terms of methodology. 3) we also analyzed the case reports according to the sort of disease each paper dealt with. 4) we had another statistical approach to each paper to figure out the distribution of diagnoses in detail. Results: We have got the following outcomes from our analysis of the papers in terms of the four stages. 1. Overall Analysis. 1) Classification of 308 research papers between 1988 and 2002: 137 original articles(44.48$\%$), 111 review articles(36.04$\%$), 56 case reports(18.18$\%$). 2) Used language: Korean(99.03$\%$). English(0.97$\%$). 3) The Number of Authors: 2 persons(42.86$\%$). 3 persons(29.87$\%$), 1 person(14.61$\%$). 2. Original Article Analysis 1) Classification of 137 original articles in terms of methodology: 90 experimental studies(65.69$\%$)46 descriptive studies(33.58$\%$), 1 analytic study(0.73$\%$). 2) Classification of the original articles according to the use of statistical methods: No statistical methods(36.42$\%$), Descriptive methods only(1.99$\%$), Not defined(23.18$\%$), t-test(24.50$\%$), ANOVA(3.97$\%$), Multiple comparison(2.65$\%$), Non-parametric test(2.65$\%$), Other methods(1.32$\%$). 3) Classification of 46 descriptive articles in terms of diseases: otorhinolaryngology(43.48$\%$), dermatology(23.91$\%$), ophthalmology(13.04$\%$), facial palsy(13.04$\%$). 4) Classification of descriptive articles in terms of the number of patients: the highest was 'more than 26 but less than 50 persons'(19 articles - 41.30$\%$). 5) Classification of descriptive articles in terms of the period for patients observation: the highest was the time 'more than 9 but less than 12 months(34.78$\%$)' Out of the 34.78$\%$, the number of articles with the patients observed for more than 12 months was 13(28.26$\%$). 3. Case Report Analysis 1) Classification of 56 case reports in terms of the sort of disease: dermatology(44.64$\%$), ophthalmology(19.64$\%$), otorhinolaryngology(14.29$\%$), facial palsy(8.93$\%$). 2) Classification in terms of the number of patients: 1 person(50$\%$), 3 persons(16.07$\%$), 2 persons(14.29$\%$). 4. Diagnosis Distribution of Each Disease. 1) Studies regarding ophthalmology : the percentage of 'strabismus' cases was the highest(33.33$\%$). 2) Studies regarding otorhinolaryngology : nasal inflammation(34.48$\%$), tinnitus(20.69$\%$). 3) Studies regarding dermatology: the percentage of 'allergic skin disease' was the highest(33.33$\%$). Conclusions: We analyzed the trends of research papers that have been published in JOMSOOS in detail. We came to understand the trends of the research through this study. However, we acknowledge that we only adopted the quantitative method out of various possible analysis methods. For further studies, we strongly urge to adopt the qualitative methods as well.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.1
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• pp.118-122
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• 2007

Purpose: This study was to understand the major subjects of the recent nursing research in Nursing administration from keywords. Method: Keywords of journals were extracted and the frequency of the appearance of each key words was sorted by a descending order. Results: A total of 327 key words were used. The most frequently used key words were 'Job satisfaction', 'Organizational commitment', 'Leadership'. Out of them, organizational culture, nursing performance, nursing classification, patient satisfaction, and ethics appeared most frequently in descending order. Conclusion: From the above it can be noted that many nursing administration concepts were handled in the papers. But there were not enough papers on the characteristics of the Nursing administration. It is suggested that in depth research be made on 'Nursing error', 'Nursing informatics', 'Web based learning'.

• Journal of Sasang Constitutional Medicine
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• v.22 no.3
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• pp.67-74
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• 2010

1. Objectives: The research papers published by researchers in other fields except Oriental medicine were analyzed to study the research trends and characteristic of Sasang Constitutional medicine. 2. Methods: Systematic searches were performed on KISS, RISS, KISTI and DBPIA and finally 123 papers were selected. The publication year, research field of the first author, title's characteristic, research topic and the classification method of Sasang Constitution were investigated. 3. Results and conclusions: 1) In the analysis of publication year, the number of studies on Sasang Constitution has increased dramatically since 2000. 2) In the analysis of the first author's research field, physical training, nursing, engineering and food and nutrition were the majority. 3) In the analysis of the research topic, the classification method of Sasang Constitution was the majority. 4) In the analysis of the classification method of Sasang Constitution, QSCC II was the most popular method accounted for 68% and interview by specialist of Sasang Constitutional medicine accounted for 42%.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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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.

• Journal of The Korean Association For Science Education
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• v.12 no.3
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• pp.17-33
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• 1992

The Purpose of this study was to develop a data base system for the information on science education research and development. As a part of this study, an analysis of papers on science education included in five selected jounals related science education was done by the use of the authors classification system for the research and development materials of science education. A total of 640 papers from the first issues to the 1991 issues of the journals were classified and analyzed. The selected five journals were Journal of the Korean Association for Research in Science Education (published by The Korean Association for Research in Science Education, 148 papers), Teaching Physics(published by Korean Physical Society, 164papers), Chemical Education (published by The Korean Chemical Socity, 98 papers), The Korean Journal of Biological Education(published by The Korean Society of Biological Education, 148papers), and Journal of Science Education (published by Science Education Center.College of Education, Seoul National University, 82 papers).