• Title/Summary/Keyword: Keyword Trends

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The Analysis of the Recent Research Trend of Pharmacopuncture (약침 관련 국내 연구 동향분석)

  • Yun, Jung Min;Kim, Kyeong Han;Oh, Yong Taek;Kim, Jong Uk;Yook, Tae-han
    • Journal of Society of Preventive Korean Medicine
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    • v.22 no.2
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    • pp.55-63
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    • 2018
  • Objectives : This study was conducted to survey on the research trends of Pharmacopuncture in Korea. Methods : We searched Korean research database by using keyword 'Pharmacopuncture', 'Bee venom'. Korean research databases were Korean Studies Information Service System(KISS), Research Information Service System(RISS), National Digital Science Library(NDSL) and Korean Medicine Information System(OASIS). We classified articles identified by publish year, type of research and diseases. Results : We analyzed 533 studies. Clinical studies and non-clinical studies except literature studies were decreased from 2015. However, Literature studies had not shown particular change over the past decade. Pharmacopuncture treated disease was classified by Korean standard classification of disease(KCD), M-code (37.8%), G-code(18.4%) were frequently used. Conclusions : A variety of disease was treated by pharmacopuncture. It is necessary to increase the level of evidence of pharmacopuncture. through additional studies in the future.

Electric Vehicle Technology Trends Forecast Research Using the Paper and Patent Data (논문 및 특허 데이터를 활용한 전기자동차 기술 동향 예측 연구)

  • Gu, Ja-Wook;Lee, Jong-Ho;Chung, Myoung-Sug;Lee, Joo-yeoun
    • Journal of Digital Convergence
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    • v.15 no.2
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    • pp.165-172
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    • 2017
  • In this paper, we analyze the research / technology trends of electric vehicles from 2001 to 2014, through keyword analysis using paper data published in SCIE or SSCI Journal on electric vehicles, time series analysis using patent data by IPC, and network analysis using nodeXL. also we predicted promising technologies of electric vehicles using one of the prediction methods, weighted moving average method. As a result of this study, battery technology among the electric vehicle component technologies appeared as a promising technology.

Recent trends of supercritical CO2 Brayton cycle: Bibliometric analysis and research review

  • Yu, Aofang;Su, Wen;Lin, Xinxing;Zhou, Naijun
    • Nuclear Engineering and Technology
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    • v.53 no.3
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    • pp.699-714
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    • 2021
  • Supercritical CO2 (S-CO2) Brayton cycle has been applied to various heat sources in recent decades, owing to the characteristics of compact structure and high efficiency. Understanding the research development in this emerging research field is crucial for future study. Thus, a bibliometric approach is employed to analyze the scientific publications of S-CO2 cycle field from 2000 to 2019. In Scopus database, there were totally 724 publications from 1378 authors and 543 institutes, which were distributed over 55 countries. Based on the software-BibExcel, these publications were analyzed from various aspects, such as major research areas, affiliations and keyword occurrence frequency. Furthermore, parameters such as citations, hot articles were also employed to evaluate the research output of productive countries, institutes and authors. The analysis showed that each paper has been cited 13.39 times averagely. United States was identified as the leading country in S-CO2 research followed by China and South Korea. Based on the contents of publications, existing researches on S-CO2 are briefly reviewed from the five aspects, namely application, cycle configurations and modeling, CO2-based mixtures, system components, and experiments. Future development is suggested to accelerate the commercialization of S-CO2 power system.

Topic Modeling Analysis of Beauty Industry using BERTopic and LDA

  • YANG, Hoe-Chang;LEE, Won-Dong
    • The Journal of Economics, Marketing and Management
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    • v.10 no.6
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    • pp.1-7
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    • 2022
  • Purpose: The purpose of this study is identifying the research trends of degree papers related to the beauty industry and providing information which can contribute to the development of the domestic beauty industry and the direction of various research about beauty industry. Research design, data and methodology: This study used 154 academic papers and 189 academic papers with English abstracts out of 299 academic papers. All of these papers were found by searching for the keyword "beauty industry" in ScienceON on August 15, 2022. For the analysis, BERTopic and LDA (Latent Dirichlet Allocation) analysis were conducted using Python 3.7. Also, OLS regression analysis was conducted to understand the annual increase and decrease trend of each topic derived with trend analysis. Results: As a result of word frequency analysis, the frequency of satisfaction, management, behavior, and service was found to be high. In addition, it was found that 'service', 'satisfaction' and 'customer' were frequently associated with program and relationship in the word co-occurrence frequency analysis. As a result of topic modeling, six topics were derived: 'Beauty shop', 'Health education', 'Cosmetics', 'Customer satisfaction', 'Beauty education', and 'Beauty business'. The trend analysis result of each topic confirmed that 'Beauty education' and 'Health education' are getting more attention as time goes by. Conclusions: The future studies must resolve the extreme polarization between the structure of the small beauty industry and beauty stores. Furthermore, the researches have to direct various ways to create the performance of internal personnel. The ways to maximize product capabilities such as competitive cosmetics and brands are also needed attentions.

Exploring Depression Research Trends Using BERTopic and LDA

  • Woo-Ryeong, YANG;Hoe-Chang, YANG
    • The Korean Journal of Food & Health Convergence
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    • v.9 no.1
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    • pp.19-28
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    • 2023
  • The purpose of this study is to explore which areas have been more interested in depression research in Korea through analysis of academic papers related to depression, and then to provide insights that can solve future depression problems. 1,032 papers searched with the keyword "depression" in scienceON were analyzed using Python 3.7 for word frequency analysis, word co-occurrence analysis, BERTopic, LDA, and OLS regression analysis. The results of word frequency and co-occurrence frequency analysis showed that related words were composed around words such as patient, disorder and symptom. As a result of topic modeling, a total of 13 topics including 'childhood depression' and 'eating anxiety' were derived. And it has been identified as a topic of interest that 'suicidal thoughts', 'treatment', 'occupational health', and 'health treatment program' were statistically significant topics, while 'child depression' and 'female treatment' were relatively less. As a result of the analysis of research trends, future research will not only study physiological and psychological factors but also social and environmental causes, as well as it was suggested that various collaborative studies of experts in academia were needed such as convergence and complex perspectives for depression relief and treatment.

Analysis of Media Trends and Social Perceptions on Nursing Law Legislation (간호법 제정에 대한 언론 동향 및 사회적 인식 분석)

  • Lee, Seung-Hee;Joo, Min-Ho
    • Journal of Korean Academy of Nursing
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    • v.53 no.4
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    • pp.439-452
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    • 2023
  • Purpose: This study aimed to derive considerations for the enactment of nursing law by analyzing the trends and social perceptions of nursing law mentioned in major daily newspapers, cafes, and blogs. Methods: Main texts and comments that included nursing law as a keyword were collected from major daily news and online postings from January 2021 to August 2022. The data collected through web crawling were analyzed using a TousFlux program used for big data analysis. Results: During the period of study, the awareness level around nursing law enactment increased. In particular, public concern over nursing law enactment intensified due to the two political parties' policy pledges related to nursing law in January 2022 and the failure to introduce the nursing law to the national assembly judiciary committee in May 2022. Except in December 2021, public perception of nursing law enactment was generally favorable, with public opinion tilting more in favor of than against enactment. Conclusion: Public opinion should be considered when drafting and implementing the nursing law to make it easier for the people to understand what the law constitutes. In addition, it is necessary to pay attention to and continuously promote the relationship between medical care and nursing in the nursing law system of developed nations. Lastly, nursing law enactment can enhance nurses' retention intention and provide a sense of efficacy to medical services.

Analysis of remote learning trends in the COVID-19 period using news big data (뉴스 빅데이터를 활용한 코로나 19시기의 원격 교육 동향 분석)

  • Lee, Youngho;Koo, Dukhoi
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.193-197
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    • 2021
  • The pandemic situation caused by COVID-19 has a large and small impact on our society socially, economically, psychologically, and other aspects. In order to prevent the spread of COVID-19, various countries, including Korea, have entered into long-term home care and distance learning systems. However, distance learning experiments conducted in many countries have raised whether face-to-face education can be replaced by distance learning. Therefore, in this study, public opinion, social perception, and field trends were analyzed based on media reports on distance learning. For this purpose, 2,600 articles from 11 newspapers and four broadcasters related to distance learning were collected in this study. Based on this data, keyword trend analysis, topic modeling analysis, sentiment analysis were performed.

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Analysis of artificial intelligence research trends using topic modeling (토픽모델링을 활용한 인공지능 연구동향 분석)

  • Daesoo Choi
    • Convergence Security Journal
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    • v.22 no.5
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    • pp.61-67
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    • 2022
  • The purpose of this study is to analyze research trends in artificial intelligence. For a three-dimensional analysis, an attempt was made to objectively compare and present the difference between the research direction of artificial intelligence in social science and engineering. For the research method, topic modeling was used among the big data analysis methodologies, and 1000 English papers searched with the keyword artificial intelligence (AI) in the academic research information system were used for the analysis data. As a result of the analysis, in the field of social science, it was possible to identify groups formed around the keywords of 'human', 'impact', and 'future' for artificial intelligence, and in the field of engineering, 'artificial intelligence-based technology development', 'system', 'Groups such as 'Risk-Security' were formed.

Analysis of Research Trends in Monitoring Mental and Physical Health of Workers in the Industry 4.0 Environment (Industry 4.0 환경에서의 작업자 정신 및 신체 건강 상태 모니터링 연구 동향 분석)

  • Jungchul Park
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.3
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    • pp.701-707
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    • 2024
  • Industry 4.0 has brought about significant changes in the roles of workers through the introduction of innovative technologies. In smart factory environments, workers are required to interact seamlessly with robots and automated systems, often utilizing equipment enhanced by Virtual Reality (VR) and Augmented Reality (AR) technologies. This study aims to systematically analyze recent research literature on monitoring the physical and mental states of workers in Industry 4.0 environments. Relevant literature was collected using the Web of Science database, employing a comprehensive keyword search strategy involving terms related to Industry 4.0 and health monitoring. The initial search yielded 1,708 documents, which were refined to 923 journal articles. The analysis was conducted using VOSviewer, a tool for visualizing bibliometric data. The study identified general trends in the publication years, countries of authors, and research fields. Keywords were clustered into four main areas: 'Industry 4.0', 'Internet of Things', 'Machine Learning', and 'Monitoring'. The findings highlight that research on health monitoring of workers in Industry 4.0 is still emerging, with most studies focusing on using wearable devices to monitor mental and physical stress and risks. This study provides a foundational overview of the current state of research on health monitoring in Industry 4.0, emphasizing the need for continued exploration in this critical area to enhance worker well-being and productivity.

Text Analysis on the Research Trends of Nature Restoration in Korea (텍스트 분석을 활용한 국내 자연환경복원 연구동향 분석)

  • Lee, Gil-sang;Jung, Yee-rim;Song, Young-keun;Lee, Sang-hyuk;Son, Seung-Woo
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.27 no.2
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    • pp.29-42
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    • 2024
  • As a global response to climate and biodiversity challenges, there is an emphasis on the conservation and restoration of ecosystems that can simultaneously reduce carbon emissions and enhance biodiversity. This study comprised a text analysis and keyword extraction of 1,100 research papers addressing nature restoration in Korea, aiming to provide a quantative and systematic evaluation of domestic research trends in this field. To discern the major research topics of these papers, topic modeling was applied and correlations were established through network analysis. Research on nature restoration exhibited a mainly upward trend in 2002-2022 but with a slight recent decline. The most common keywords were "species," "forest," and "water". Research topics were broadly classified into (1) predictions of habitat size and species distribution, (2) the conservation and utilization of natural resources in urban areas, (3) ecosystems and landscape managements in protected areas, (4) the planting and growth of vegetation, and (5) habitat formation methods. The number of studies on nature restoration are increasing across various domains in Korea, with each domain experiencing professional development.