• Journal of Korean Academy of Dental Administration
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• v.11 no.1
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• pp.47-53
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• 2023

This study aims to analyze the research trends of the Journal of Korean Academy of Dental Administration and identify the characteristics of the journal. The research was based on 10 academic journals from 2013 to 2022 and related documents. The type of paper, research method, statistical analysis, topic classification, and research subject of 65 papers were extracted and categorized. As a result, the distribution of paper types was as follows: research articles accounted for 83.2%, review articles for 12.3%. In terms of research methods, questionnaire surveys were used in 46.2% of the papers, literature reviews in 23.1%, and national data analysis in 7.7%. Research topics included dental manpower at 20.0%, infection control at 7.7%, dental information at 6.2%, patient safety at 6.2%, and oral health care quality at 6.2%. 72.3% of the papers were quantitative studies, and the majority of research subjects were dental hygienists or dental hygiene students, accounting for 26.2% of the total. The Journal of Korean Academy of Dental Administration covers topics such as dental healthcare marketing, dental healthcare organization and management, dental healthcare information, dental healthcare policy, dental healthcare insurance, dental healthcare quality management, patient safety, medical disputes, and infection control. The authors are also contributed by a variety of dental personnel, including dentists, dental hygienists, and dental technicians.

• Asia pacific journal of information systems
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• v.29 no.1
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• pp.65-82
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• 2019

Technological innovations over the years have accentuated the workings in corporate- connected organizations and different application platforms. Hence, a unified management information system (MIS) that can utilize the Web and propel programming developments is required. Software agents, the latest developments in computer software technology, can be utilized to rapidly and effortlessly build integrated information systems. Consequently, 59 research papers on the use of software agents in MIS were identified from top 40 MIS journals published between 2007 and 2017. Then, we reviewed and classified all the research papers according to two categories: application fields and application categories. The application fields consisted of eight sub-groups: manufacturing, telecommunication systems, traffic and transportation management, information filtering and gathering, electronic commerce, business process management, entertainment, and medical care; whereas the application categories consisted of three sub-groups: multi-agent systems, personal assistants, and multi-agent simulation. The research papers were further divided into journal and year of publication, and journal and application field. The objective of our research was to understand the trend of the use software agent technology in MIS by examining the published research paper beside to add knowledge and content to the information system academic discipline.

• Journal of Haehwa Medicine
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• v.22 no.1
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• pp.37-48
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• 2013

This study aims to summarize and makes a reference of anti-inflammatory activities of herbal medicines. In this process, this review collated papers of anti-inflammation-focused studies using herbal medicines in Oriental medical journals since 2003. Finally 221 papers were included and the type of materials, the type and effective classification of herbal medicines, the type of cells used in the experiments and the action and mechanisms of herbal medicine were analysed. The herbal medicines having the effects of decreasing fire and tonifying and nourishment were used the most. Most herbal medicines in this study can decrease proinflammatory cytokines, NO and prostaglandin 2 (PGE 2) production, inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expression by regulating of nuclear factor kappa B (NF-${\kappa}B$) and/or mitogen activated protein kinases (MAPKs).

• Asia pacific journal of information systems
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• v.5 no.2
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• pp.37-50
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• 1995

This study analyzed 89 MIS published in Korea since 1974. The keyword classification scheme proposed by Barki et al. [1993] was employed to classify researched themes of the papers. Research methods and research variables were also examined. The results showed that (1) the Korean MIS research focused on DSS/ES, IS evaluation, IS development and operations, (2) nonempirical studies took 46% of the 89 papers while survey method was frequently used in empirical studies, (3) in empical studies, user-related variables were most frequently included as dependent variable while organization-related variables were most frequently selected as independent variable. Some recommendations for the future MIS research in Korea were suggested.

• Journal of the Korean Society of Food Culture
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• v.4 no.4
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• pp.375-382
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• 1989

About 760 papers and patents of the traditional fermented food in Korea were collected which were published during 1917-1988, and then the papers were classified, outlined and reviewed. Study of traditional fermented food was about 10% of total study on Korean Foods, and that of alcoholic beverage was 50%, soy sauce and related product was 30% and kimchi was less than 20% of total study of traditional fermented foods. Though considerable amount of studies were accomplished before the World War II, but a few study was accomplished during the Korean war. The research activity is, hitherto, increasing gradually, but the systematic studies were rarely done. The studies to be investigated were processing quality of raw materials, classification, standardization, sensory quality of the product and so on.

• Journal of Engineering Education Research
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• v.10 no.2
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• pp.19-43
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• 2007

The Korean Society for Engineering Education (KSEE) was founded in 1994, and the Journal of Engineering Education Research has published since 1998. The purpose of the study was to analyze the research methodologies and contents for all 126 papers which were published from 1998 to 2005. A statistical package SPSS(ver. 15.0) was used to analyze the coding data of all papers. The research contents were as follows: (1) A classification of the number of papers published according to year and researcher features (gender, institution, major field, number of authors, etc) was performed, (2) The analysis of research methodologies and contents of the papers published was performed, (3) Strategies to improve the quality of the journal were suggested by discussion from the analysis results. The results showed that the development research method was used most frequently, most papers were mode by major scholars of electrical and electronic engineering and scholars of Yonsei University made the most papers. In order to use the survey research method, the sampling methods were mainly used by total number, purposive, convenience, stratified sampling method, etc, questionnaire was used of 89.5%, descriptive statistics of frequency/% was used of 50%. To conduct the experimental research method, the models of nonequivalent groups posttest-only design and one-group pretest-posttest design were adopted, respectively. Finally, research strategies and new direction for improving the engineering education journal's papers at the section of discussion and suggestion were suggested.

• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.191-197
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• 2003

Accurate detection and classification of faults on transmission lines is vitally important. In this respect, many different types of faults occur, such as inter alia low impedance faults (LIF) and high impedance faults (HIF). The latter in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if undetected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. Because of the randomness and asymmetric characteristics of HIFs, their modeling is difficult and numerous papers relating to various HIF models have been published. In this paper, the model of HIFs in transmission lines is accomplished using the characteristics of a ZnO arrester, which is then implemented within the overall transmission system model based on the electromagnetic transients program (EMTP). This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs using Adaptive Network-based Fuzzy Inference System (ANFIS). The inputs into ANFIS are current signals only based on Root-Mean-Square (RMS) values of 3-phase currents and zero sequence current. The performance of the proposed algorithm is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results demonstrate that the ANFIS can detect and classify faults including LIFs and HIFs accurately within half a cycle.

• Youth Facilities and Environment
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• v.17 no.1
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• pp.131-141
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• 2019

The purpose of this study is to derive and type utilization indexes by comparing public design indicators with preceding studies related to closed school facilities, and to derive preliminary classification systems through a correlation review between indicators. Pre-research was conducted in the scope of academic papers, academic journals, research reports, and special act for promoting the utilization of closed school assets. Public design indicators were set in the scope of domestic design guidelines, the Seoul city public design assessment system, the 'Good Building' designation system, and the UK Design Quality Index (DQI). and the design review of the British architects. First of all, the research method looked at laws, procedures and utilization of closed schools, and reviewed the preceding study and domestic and international public design indicators sequentially. Next, the association was reviewed through a comparison between the preceding study and the public design indicators, and a preliminary classification system for the use of closed schools was derived from this.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.178-186
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• 2018

Subject classification of thesis units is essential to serve scholarly information deliverables. However, to date, there is a journal-based topic classification, and there are not many article-level subject classification services. In the case of academic papers among domestic works, subject classification can be a more important information because it can cover a larger area of service and can provide service by setting a range. However, the problem of classifying themes by field requires the hands of experts in various fields, and various methods of verification are needed to increase accuracy. In this paper, we try to classify topics using the unsupervised learning algorithm to find the correct answer in the unknown state and compare the results of the subject classification algorithms using the coherence and perplexity. The unsupervised learning algorithms are a well-known Hierarchical Dirichlet Process (HDP), Latent Dirichlet Allocation (LDA) and Latent Semantic Indexing (LSI) algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.747-752
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• 2011

Microarray classification typically possesses two striking attributes: (1) classifier design and error estimation are based on remarkably small samples and (2) cross-validation error estimation is employed in the majority of the papers. A Microarray data of ovarian cancer consists of the expressions of thens of thousands of genes, and there is no systematic procedure to analyze this information instantaneously. In this paper, gene markers are selected by ranking genes according to statistics, popular classification rules - linear discriminant analysis, k-nearest-neighbor and decision trees - has been performed comparing classification accuracy of data selecting gene markers and not selecting gene markers. The Result that apply linear classification analysis at Microarray data set including marker gene that are selected using ANOVA method represent the highest classification accuracy of 97.78% and the lowest prediction error estimate.