• Nuclear Engineering and Technology
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• 제53권3호
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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.

• 한국컴퓨터정보학회논문지
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• 제22권3호
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• pp.131-138
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• 2017

New drug development is time-consuming and costly. Hence, it is necessary to repurpose old drugs for finding new indication. We suggest the way that repurposing old drug using massive literature data and biological network. We supposed a disease-drug relationship can be available if signal pathways of the relationship include significant genes identified in literature data. This research is composed of three steps-identifying significant gene using co-occurrence in literature; analyzing the shortest path on biological network; and scoring a relationship with comparison between the significant genes and the shortest paths. Based on literatures, we identify significant genes based on the co-occurrence frequency between a gene and disease. With the network that include weight as possibility of interaction between genes, we use shortest paths on the network as signal pathways. We perform comparing genes that identified as significant gene and included on signal pathways, calculating the scores and then identifying the candidate drugs. With this processes, we show the drugs having new possibility of drug repurposing and the use of our method as the new method of drug repurposing.

• 인터넷정보학회논문지
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• 제17권6호
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• pp.153-158
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• 2016

최근 소셜 네트워크 사용자들이 늘어나면서, 각 지역에서 관심 받고 있는 사회적인 이슈나 재해 등과 같은 이벤트에 대한 정보들이 소셜 미디어 사이트를 통해 실시간으로 빠르게 대량으로 게시되고 있으며, 사회적 파급효과도 매우 커지고 있다. 본 논문에서는 지역정보를 가진 트위터 데이터를 이용하여 특정 시간, 지역에 사용자들이 관심을 가지고 있는 이벤트를 탐지하는 방법을 제안하고자 한다. 이를 위해 트위터 스트리밍 API를 이용해 데이터를 수집하고, 트윗의 키워드들의 시간에 따른 빈도수를 분석하여 정상적인 패턴과 다른 패턴을 가진 키워드를 이벤트로 추출하고, 같은 이벤트에 대한 키워드들을 군집화 하기 위해 co-occurrence 그래프를 이용하여 이벤트 감지 시스템을 구현하였다. 그리고 실험을 통해 제안한 기법의 유효성을 검증한다.

• ETRI Journal
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• 제40권6호
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• pp.745-758
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• 2018

A wide range of studies in various disciplines has focused on the Internet of Things (IoT) and cyber-physical systems (CPS). However, it is necessary to summarize the current status and to establish future directions because each study has its own individual goals independent of the completion of all IoT applications. The absence of a comprehensive understanding of IoT and CPS has disrupted an efficient resource allocation. To assess changes in the knowledge structure and emerging technologies, this study explores the dynamic research trends in IoT by analyzing bibliographic data. We retrieved 54,237 keywords in 12,600 IoT studies from the Scopus database, and conducted keyword frequency, co-occurrence, and growth-rate analyses. The analysis results reveal how IoT technologies have been developed and how they are connected to each other. We also show that such technologies have diverged and converged simultaneously, and that the emerging keywords of trust, smart home, cloud, authentication, context-aware, and big data have been extracted. We also unveil that the CPS is directly involved in network, security, management, cloud, big data, system, industry, architecture, and the Internet.

• Journal of Advanced Research in Ocean Engineering
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• 제1권4호
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• pp.239-251
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• 2015

In this study, a spectral fatigue analysis was performed for the topside structure of an offshore floating vessel. The topside structure was idealized using beam elements in the SACS program. The fatigue analysis was carried out considering the wave and wind loads separately. For the wave-induced fatigue damage calculation, motion RAOs calculated from a direct wave load analysis and regular waves with different periods and unit wave heights were utilized. Then, the member end force transfer functions were generated covering all the loading conditions. Stress response transfer functions at each joint were produced using the specified SCFs and member end force transfer functions. fatigue damages were calculated using the obtained stress ranges, S-N curve, wave spectrum, heading probability of each loading condition, and their corresponding occurrences in the wave scatter diagrams. For the wind induced fatigue damage calculation, a dynamic wind spectral fatigue analysis was performed. First, a dynamic natural frequency analysis was performed to generate the structural dynamic characteristics, including the eigenvalues (natural frequencies), eigenvectors (mode shapes), and mass matrix. To adequately represent the dynamic characteristic of the structure, the number of modes was appropriately determined in the lateral direction. Second, a wind spectral fatigue analysis was performed using the mode shapes and mass data obtained from the previous results. In this analysis, the Weibull distribution of the wind speed occurrence, occurrence probability in each direction, damping coefficient, S-N curves, and SCF of each joint were defined and used. In particular, the wind fatigue damages were calculated under the assumption that the stress ranges followed a Rayleigh distribution. The total fatigue damages were calculated from the combination with wind and wave fatigue damages according to the DNV rule.

• 지역사회간호학회지
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• 제29권4호
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• pp.429-439
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• 2018

Purpose: The aim of this study is to identify core keyword of frailty research in the past 35 years to understand the structure of knowledge of frailty. Methods: 10,367 frailty articles published between 1981 and April 2016 were retrieved from Web of Science. Keywords from these articles were extracted using Bibexcel and social network analysis was conducted with the occurrence network using NetMiner program. Results: The top five keywords with a high frequency of occurrence include 'disability', 'nursing home', 'sarcopenia', 'exercise', and 'dementia'. Keywords were classified by subheadings of MeSH and the majority of them were included under the healthcare and physical dimensions. The degree centralities of the keywords were arranged in the order of 'long term care' (0.55), 'gait' (0.42), 'physical activity' (0.42), 'quality of life' (0.42), and 'physical performance' (0.38). The betweenness centralities of the keywords were listed in the order of depression' (0.32), 'quality of life' (0.28), 'home care' (0.28), 'geriatric assessment' (0.28), and 'fall' (0.27). The cluster analysis shows that the frailty research field is divided into seven clusters: aging, sarcopenia, inflammation, mortality, frailty index, older people, and physical activity. Conclusion: After reviewing previous research in the 35 years, it has been found that only physical frailty and frailty related to medicine have been emphasized. Further research in psychological, cognitive, social, and environmental frailty is needed to understand frailty in a multifaceted and integrative manner.

• Journal of Information Technology Applications and Management
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• 제22권3호
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• pp.83-103
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• 2015

The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.

• 한국문헌정보학회지
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• 제57권2호
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• pp.97-122
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• 2023

메타리터러시는 정보 리터러시의 재구조화된 결과물이다. 메타리러러시는 포스트모더니즘, 사회적 구성주의, 메타인지의 도입을 통해 정보 리터러시와 구분되었다. 그러나 메타리터러시 연구들이 이 개념적 차이를 반영하고 있는지는 검토되지 않았다. 따라서 이 연구의 목적은 메타리터러시 이론을 연구한 학술논문들에서 이 개념적 차이를 어떻게 반영하고 있는지 연구동향을 관찰하는 것이다. 이 연구는 문헌연구를 실시하고, 메타리터러시 연구 80편을 대상으로 빈도분석 및 지식 네트워크 분석(동시출현·서지결합)을 실시하였다. 결과는 다음과 같다. 동시출현분석 결과, 메타인지(빈도 1위)와 더불어 스킬(연결중심성 1위, 근접중심성 1위, 매개중심성 1위)로 나타났다. 메타리터러시는 스킬 기반의 정보 리터러시를 비판하기 때문에 이 결과는 정보 리터러시와 메타리터러시 개념이 혼재되어 있음을 시사한다. 한편 서지결합분석 결과, 서지결합도가 높은 논문은 정보 리터러시와 메타리터러시의 차이를 메타인지를 통해 설명하고 있다.

• 대한통합의학회지
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• 제12권2호
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• pp.197-210
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• 2024

Purpose : This study aimed to analyze research trends in the field of integrative medicine through a bibliometric analysis of articles published in Integrative Medicine Research (IMR) journal from 2017 to 2022. Methods : Articles published in IMR journal between 2017 and 2022 were searched using the Web of Science database on August 22, 2023. The analysis was performed using the Bibliometrix and Biblioshiny tools in R (version 4.3.1) and VOSviewer (version 1.6.19). Results : The key findings were as follows: average citations per article (9.41), total authors (1,142), single-authored articles (12), average articles per author (0.27), average co-authors per article (5.27), and rate of international co-authorships (15.69 %). The most-cited article was on the cryopreservation of cells or tissues and their clinical applications. The top keyword analysis by author keywords showed that "acupuncture" was the most frequently used keyword (33 times). Co-occurrence network analysis showed 85 high-frequency keywords that appeared five or more times, and the top five keywords by total link strength were "acupuncture," "herbal medicine," "prevalence," "alternative medicine," and "complementary." The study found that, contrary to the trend in complementary and alternative medicine research in Korea, the IMR journal actively conducts intervention studies to provide clinical evidence. Conclusion : In the IMR journal, "acupuncture" was the most frequent of author keywords. The analysis of keyword trend topics over time showed that the keyword "systematic review" continued to appear from 2020 to 2022, and the keyword "clinical practice guideline" appeared for the first time in 2021. In particular, the co-occurrence network analysis highlighted keywords related to intervention research, in contrast to domestic research trends. While this study analyzed only one journal, future studies expanding the category of integrative medicine and increasing the number of journals analyzed may provide further insights.

• Journal of Magnetics
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• 제7권4호
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• pp.160-164
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• 2002

A new discovery of the super-giant magneto-impedance (SGMI) effect was found out in a LC-resonator consisted of a glass-coated amorphous $CO_{83.2}B_{3.3}Si_{5.9}Mn_{7.6}$ microwire. The measurement was carried out at high frequency range from 100 MHz up to 1 GHz of an ac-current flowing along the wire and at varying axial dcmagnetic field in its range of $\pm$120 Oe. The wires, about 16${\mu}m$ in diameter, were fabricated by a glass-coated melt spinning technique. The shape of the impedance curves plotted vs. a dc-field is changing dramatically with the frequency. The phase angle was also strongly dependent on this field. The external dc-magnetic field changes the circumferential permeability as well as the penetration depth, both in turn change the impedance of the sample. The drastic increments of SGMI at high frequency can be understood in terms of the LC-resonance phenomena. The sudden change of the phase angle, as large as $180^{\circ}$ evidenced the occurrence of the resonance at a given intensity of the external dc-field. The maximum ratio of SGMI reached in the experiment by precise tuning frequency equals 450,000％ at the frequency of around 551.9075 MHz.