• 복식
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• 제63권3호
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• pp.138-150
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• 2013

The purpose of this study was to investigate research trends of subject matter in clothing construction field in clothing and textiles and to suggest the information for the future directions for fashion business and research. 2737 articles with clothing and textiles subject matter, 350 articles with clothing construction field in the Journal of Korean Society of Costume and Journal of the Korean Society of Clothing and Textiles from 2001 through 2010 were analyzed. The major conclusions of the study are as follows: 1. Clothing construction field took 12.8% with 350 articles in the researches of the Journal Publications in 2000s. 2. Clothing construction field showed more proportions in the latter half of the decade. 3. Clothing construction field were classified into 5 topics : topic of basic pattern and pattern for apparel, topic of body types, topic of functionality of clothing and protective clothing, topic of size system of apparel, topic of sewing and manufacturing process. 4. In clothing construction field, topic of basic pattern and pattern for apparel took the most proportions. 5. Topic of body types, topic of functionality of clothing and protective clothing, topic of size system of apparel, topic of sewing and manufacturing process were followed.

• Asian Journal of Innovation and Policy
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• 제10권3호
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• pp.380-403
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• 2021

Recently, smart factories have gained significant importance since the development of the fourth industrial revolution and the rise of global industrial competition. Therefore, the industries' survival to meet the global market trends requires accurate technological planning. Although, different works are available to investigate forecasting technologies and their influence on the smart factory. However, little significant work is available yet on the analysis of technological trends concerning the smart factory, which is the core focus herein. This work was performed to analyze the technological trends of the smart factory, followed by a detailed investigation of recent research hotspots/frontiers in the field. A well-known topic modeling technique, namely Latent Dirichlet Allocation (LDA), was employed for this study described above. The technological trends were further strengthened with the in-depth analysis of a smart factory-based case study. The findings produced the technological trends which possess significant potential in determining the technological strategies. Moreover, the results of this work may be helpful for researchers and enterprises in forecasting and planning future technological evolution.

• 의학교육논단
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• 제24권2호
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• pp.93-102
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• 2022

We use the concept of the "doctor's role" as a guideline for developing medical education programs for medical students, residents, and doctors. Therefore, we should regularly reflect on the times and social needs to develop a clear sense of that role. The objective of the present study was to understand the knowledge structure related to doctor's job competencies in Korea. We analyzed research trends related to doctor's job competencies in Korea Citation Index journals using text network analysis through an integrative approach focusing on identifying social issues. We finally selected 1,354 research papers related to doctor's job competencies from 2011 to 2020, and we analyzed 2,627 words through data pre-processing with the NetMiner ver. 4.2 program (Cyram Inc., Seongnam, Korea). We conducted keyword centrality analysis, topic modeling, frequency analysis, and linear regression analysis using NetMiner ver. 4.2 (Cyram Inc.) and IBM SPSS ver. 23.0 (IBM Corp., Armonk, NY, USA). As a result of the study, words such as "family," "revision," and "rejection" appeared frequently. In topic modeling, we extracted five potential topics: "topic 1: Life and death in medical situations," "topic 2: Medical practice under the Medical Act," "topic 3: Medical malpractice and litigation," "topic 4: Medical professionalism," and "topic 5: Competency development education for medical students." Although there were no statistically significant changes in the research trends for each topic over time, it is nonetheless known that social changes could affect the demand for doctor's job competencies.

• 한국IT서비스학회지
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• 제13권4호
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• pp.275-287
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• 2014

Recently, the volume of unstructured text data generated by various social media has been increasing rapidly; consequently, the use of text mining to support decision-making has also been growing. In particular, academia and industry are paying significant attention to topic analysis in order to discover the main issues from a large volume of text documents. Topic analysis can be regarded as static analysis because it analyzes a snapshot of the distribution of various issues. In contrast, some recent studies have attempted to perform dynamic issue tracking, which analyzes and traces issue trends during a predefined period. However, most traditional issue tracking methods have a common limitation : when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. Additionally, traditional issue tracking methods do not concentrate on the transition of individuals' interests from certain issues to others, although the methods can illustrate macro-level issue trends. In this paper, we propose an individual interests tracking methodology to overcome the two limitations of traditional issue tracking methods. Our main goal is not to track macro-level issue trends but to analyze trends of individual interests flow. Further, our methodology has extensible characteristics because it analyzes only newly added documents when the period of analysis is extended. In this paper, we also analyze the results of applying our methodology to news articles and their access logs.

• 복식문화연구
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• 제29권4호
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• pp.538-553
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• 2021

As interest in the sustainable fashion industry continues to increase along with climate issues, it is necessary to identify research trends in sustainable fashion and seek new development directions. Therefore, this study aims to analyze research trends on sustainable fashion. For this purpose, related papers were collected from the KCI (Korean Citation Index) and Scopus, and 340 articles were used for the study. The collected data went through data transformation, data preprocessing, topic modeling analysis, core topic derivation, and visualization through a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: consumer clothing consumption behavior and environment, upcycle product development, product types by environmental approach, ESG business activities, materials and material development, process-based approach, lifestyle and consumer experience, and brand strategy. Topics were related to consumption, production, and education of sustainable fashion, respectively. KCI analysis results and Scopus analysis results derived eight topics but showed differences from the comprehensive analysis results. This study provides primary data for exploring various themes of sustainable fashion. It is significant in that the data were analyzed based on probability using a research method that excluded the subjective value of the researcher. It is recommended that follow-up studies be conducted to examine social trends.

• 연구윤리
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• 제3권1호
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• pp.7-11
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• 2022

Purpose: The purpose of this study is to derive clues about the development direction of research ethics and areas of interest which has recently become a social issue in Korea by confirming overseas research trends. Research design, data and methodology: We collected 2,760 articles in scienceON, which including 'research ethics' in their paper. For analysis, frequency analysis, word clouding, keyword association analysis, and LDA topic modeling were used. Results: It was confirmed that many of the papers were published in medical, bio, pharmaceutical, and nursing journals and its interest has been continuously increasing. From word frequency analysis, many words of medical fields such as health, clinical, and patient was confirmed. From topic modeling, 7 topics were extracted such as ethical policy development and human clinical ethics. Conclusions: We founded that overseas research trends on research ethics are related to basic aspects than Korea. This means that a fundamental approach to ethics and the application of strict standards can become the basis for cultivating an overall ethical awareness. Therefore, academic discussions on the application of strict standards for publishing ethics and conducting researches in various fields where community awareness and social consensus are necessary for overall ethical awareness.

• 한국산학기술학회논문지
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• 제22권3호
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• pp.661-670
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• 2021

연구동향은 시기별 연구주제에 대한 중요도 판단과 부족한 연구 분야를 파악하고 신규 분야를 발굴하는데 유용하게 활용될 수 있다. 본 연구에서는 인구집중과 도시화로 인해 다양한 문제가 발생하고 있는 도시공간을 대상으로 한 논문들을 대상으로 시기별 연구동향을 분석하였다. 이를 위해 2002년부터 2019년 사이에 게재된 한국학술지인용색인(KCI)에 등재된 논문의 초록을 대상으로 데이터마이닝 기법 중 하나인 토픽모델링 분석을 수행하였다. 토픽모델링은 전체 내용에서 일정한 패턴을 발견해낼 수 있는 알고리즘 기반의 텍스트마이닝 기법으로 방대한 문헌에서 주제를 찾아내고 군집하는데 용이하다. 본 연구에서는 키워드 빈도, 연도별 경향, 토픽 도출, 토픽별 군집, 토픽유형별 경향에 대한 분석을 실시하였다. 그 결과 먼저 도시재생 분야연구가 지속적으로 증가되고 있고 앞으로도 세부 주제가 확대될 수 있는 분야로 분석되었다. 그리고 도시재생 주제는 이제 정규 연구분야로 자리 잡고 있는 것으로 파악되었다. 반면, 개발/성장과 에너지/환경과 같은 주제는 정체기에 들어간 것으로 분석되었다. 본 연구는 국내 전체 도시분야 연구를 대상으로 데이터마이닝 기법인 토픽모델링을 이용하여 키워드 간 연관성과 경향을 함께 분석하였다는 데 의의가 있다.

• 디지털융복합연구
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• 제20권2호
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• pp.203-215
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• 2022

본 연구의 목적은 토픽모델링과 언어네트워크분석을 활용하여 한국의 스마트팜 분야 연구 동향과 지식구조를 파악하는 것이다. 연구목적을 달성하기 위하여 KCI(Korea Citation Index)의 스마트팜 관련 국내 학술지 104편을 대상으로 핵심어와 핵심어들의 연결 관계를 분석하고, LDA 토픽모델링 기법을 이용하여 연구주제와 관련된 토픽들을 분석하였다. 언어네트워크분석 결과, 국내 스마트팜 관련 연구 분야의 주요핵심어는 '환경', '시스템', '사용', '기술', '재배' 등이 나타났으며, 연결중심성, 매개중심성, 위세중심성 결과도 제시하였다. 토픽모델링분석결과, Topic 1은 '스마트팜 도입 분석', Topic 2는 '친환경 스마트팜과 스마트팜의 경제적 효율성', Topic 3은 '스마트팜 플랫폼 설계', Topic 4는 '스마트팜 생산 최적화', Topic 5는 '스마트팜 생태계', Topic 6은 '스마트팜 시스템 구현', Topic 7은 '스마트팜 관련 정부 정책'으로 나타났다. 본 연구는 국내 스마트팜 관련 연구 동향을 살펴봄으로써, 향후 국내의 스마트팜을 발전시키는 데 필요한 정책개발과 연구 방향성을 설정하는데 기초자료가 될 것으로 기대한다.

• Smart Structures and Systems
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• 제29권2호
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• 연구윤리
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• 제5권2호
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• pp.1-6
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• 2024

Purpose: PBM is emerging as a major management system for securing corporate productivity and enhancing competitiveness, and various studies are being conducted. The purpose of this study is to analyze research trends published in KCI-listed journals and papers since 1999 to understand the current status of research and provide basic data for more extensive research and development of performance management in the future. Research design, data and methodology: A detailed examination of research trends was conducted through the analysis of abstracts from 154 research papers on PBM. To facilitate a comprehensive analysis of these trends, LDA topic modelling was employed. Results: First, it should be noted that research on PBM is not limited to the area of HRM. Instead, PBM research is expanding to encompass comprehensive personnel systems. Second, the results of topic modeling analysis show that although the initial focus of research was on human resource management, there is now a growing interest in fairness and organizational culture in the entire organization. Conclusions: PBM is becoming a dominant paradigm as it shifts from HR systems to organizational fairness and culture. This suggests that future research should consider both quantitative and qualitative aspects of PBM to improve corporate performance while prioritizing organizational fairness and culture.