• 한국통신학회:학술대회논문집
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• 한국통신학회 2004년도 추계종합학술대회 논문 초록집
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• pp.26-26
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• 2004

• Asian Journal of Innovation and Policy
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• 제6권1호
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• pp.85-93
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• 2017

This paper focuses on the relationship between the characteristics of network and the productivity of scientists, which is rarely examined in previous studies. Utilizing a unique dataset from the Korean Citation Index (KCI), we examine the overall characteristics of the research network (e.g. distribution of nodes, density and mean distance), and analyze whether the network centrality is related to the scientific productivity. According to the results, firstly we have found that the collaborative research network of the Korean academics in the field of statistics and computer science is a scale-free network. Secondly, these research networks show a disciplinary difference. The network of statisticians is denser than that of computer scientists. In addition, computer scientists are located in a fragmented network compared to statisticians. Thirdly, with regard to the relationship between the researchers' network position and scientific productivity, a significant relation and their disciplinary difference have been observed. In particular, the degree centrality is the strongest predictor for the scientists' productivity. Based on these findings, some policy implications are put forward.

• 한국해양공학회지
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• 제34권6호
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• pp.461-468
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• 2020

This study examined how national research and development (R&D) in the domain of logistics has changed recently in the Republic of Korea. We conducted basic statistical analysis and social network analysis on 5,327 logistics-related R&D projects undertaken during 2005-2019. Data for performing these analyses were collected from the R&D database of the National Science and Technology Information Service (NTIS). By constructing a co-occurrence matrix with keywords, we conducted degree and betweenness centrality analysis and visualized the network matrix to display a cluster map. This study presents our observations related to the following findings: (1) the chronical trends of logistics R&D, (2) focused fields of logistics R&D, (3) the relations among keywords, and (4) the characteristics of logistics R&D. Finally, we suggest policy implications to boost and diversify logistics R&D.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.940-942
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• 2003

In an attempt to enhance the visual effect of SPOT image, this study develops a neural network algorithm to transform SPOT false color into simulated true color. The method has been tested using Landsat TM and SPOT images. The qualitative and quantitative comparisons indicate that the striking similarity can be found between the true and simulated true images in terms of the visual looks and the statistical analysis.

• 전자공학회논문지
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• 제54권6호
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• pp.106-113
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• 2017

본 논문에서는 자율주행형 다관절 차량용 제어 시스템 구축 시 장치 간 네트워크로 이더넷 기반의 Train Communication Network(TCN)를 적용할 경우 적합한 네트워크 토폴로지를 제안하고 실험을 통하여 그 결과를 측정하여 검증한다. 케이블 수, 포트 수 등 구조적인 제한조건과 네트워크 응답시간, 최대 전송량 등 성능적인 제한조건을 고려하여 네트워크 토폴로지를 제안한다. 스타 토폴로지, 데이지체인 토폴로지, 그리고 이들을 절충한 하이브리드 토폴로지를 각각 적용하여 비교하며 본 논문에서는 특히 하이브리드 토폴로지의 적절한 구성을 위해 그룹으로 묶이는 노드 수를 구한다. 적절하게 노드의 그룹이 구성된 하이브리드 토폴로지는 본 논문에서 최적 토폴로지로 제안하는 구조이다. 먼저 시뮬레이션을 통해 각각의 토폴로지 구성 시의 네트워크 성능에 대한 예상치를 도출하며 이 후 실제 장치를 연결하여 네트워크를 구현한다. 다양한 네트워크 성능 측정 프로그램을 이용하여 각 토폴로지에서의 성능을 측정하고 비교를 통해 제안한 방안의 우수성을 기술한다.

• 간호행정학회지
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• 제23권1호
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• pp.101-110
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• 2017

Purpose: This study aimed to identify research trends in the Journal of Korean Academy of Nursing Administration from 2013 to 2015. Methods: For this study, 171 articles were analyzed. Research designs, participants, research settings, sampling, and data analyses methods were reviewed using established analysis criteria. Keyword centrality and clusters were generated by keyword network analysis. Results: Most of studies used quantitative methods (82.5%), and sampling mainly focused on nurses (68.8%). The most commonly used data analyses methods were t-test, ANOVA, correlation, and regression. The most central keywords were turnover and empowerment. Network analysis generated four network groups: 1) burnout; 2) turnover; 3) happiness; and 4) nursing professionalism. Conclusion: The results of this study identify current trends and interests in Korean nursing administration research. The findings from this study suggest that future studies include a variety of research methods and maintain appropriate research ethics.

• Journal of Power Electronics
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• 제16권3호
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• pp.1131-1140
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• 2016

A simple design for a sliding mode observer is proposed for EV lithium battery SOC estimation in this paper. The proposed observer does not have the limiting conditions of existing observers. Compared to the design of previous sliding mode observers, the new observer does not require a solving matrix equation and it does not need many observers for all of the state components. As a result, it is simple in terms of calculations and convenient for engineering applications. The new observer is suitable for both time-variant and time-invariant models of battery SOC estimation, and the robustness of the new observer is proved by Liapunov stability theorem. Battery tests are performed with simulated FUDS cycles. The proposed observer is used for the SOC estimation on both unchanging parameter and changing parameter models. The estimation results show that the new observer is robust and that the estimation precision can be improved base on a more accurate battery model.

• 한국과학교육학회지
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• 제42권3호
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• pp.341-356
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• 2022

이 연구의 목적은 행위자-네트워크 이론이 과학교육 연구에 주는 시사점을 도출하는 것이었다. 이를 위해 최근 국내외의 교육 분야의 연구에서는 어떻게 행위자-네트워크 이론을 적용해왔는지를 중심으로 선행연구를 분석하였다. 연구 결과 교육 분야에서 행위자-네트워크 이론을 적용한 교육 연구들은 크게 세 가지 접근방식으로 분류되었다. 첫째, 교육 방법이나 관점을 구성하기 위한 인식론적 관점으로 활용하거나 둘째, 비인간의 행위성을 인식하는 존재론적 관점으로 활용하거나 셋째, 교육 연구를 위한 방법론으로 활용 또는 제안하였다. 연구 결과를 토대로 과학교육 연구에의 기여 가능성을 논의하였다. 새로운 이론적 관점으로써 행위자-네트워크 이론이 과학교육의 실천과 연구에 있어 함의를 줄 수 있을 것으로 기대한다.

• Journal of Ginseng Research
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• 제48권5호
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• pp.511-519
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• 2024

Background: The cycle of seasonal dormancy of perennating buds is an essential adaptation of perennial plants to unfavorable winter conditions. Plant hormones are key regulators of this critical biological process, which is intricately connected with diverse internal and external factors. Recently, global warming has increased the frequency of aberrant temperature events that negatively affect the dormancy cycle of perennials. Although many studies have been conducted on the perennating organs of Panax ginseng, the molecular aspects of bud dormancy in this species remain largely unknown. Methods: In this study, the molecular physiological responses of three P. ginseng cultivars with different dormancy break phenotypes in the spring were dissected using comparative genome-wide RNA-seq and network analyses. These analyses identified a key role for abscisic acid (ABA) activity in the regulation of bud dormancy. Gene set enrichment analysis revealed that a transcriptional network comprising stress-related hormone responses made a major contribution to the maintenance of dormancy. Results: Increased expression levels of cold response and photosynthesis-related genes were associated with the transition from dormancy to active growth in perennating buds. Finally, the expression patterns of genes encoding ABA transporters, receptors (PYRs/PYLs), PROTEIN PHOSPHATASE 2Cs (PP2Cs), and DELLAs were highly correlated with different dormancy states in three P. ginseng cultivars. Conclusion: This study provides evidence that ABA and stress signaling outputs are intricately connected with a key signaling network to regulate bud dormancy under seasonal conditions in the perennial plant P. ginseng.

• 수산해양교육연구
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• 제28권3호
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• pp.872-880
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• 2016

The purpose of this study is to find the research trends relating to flipped learning through keyword network analysis. For investigating this topic, final 100 papers (removed due to overlap in all 205 papers) were selected as subjects from the result of research databases such as RISS, DBPIA, and KISS. After keyword extraction, coding, and data cleaning, we made a 2-mode network with final 202 keywords. In order to find out the research trends, frequency analysis, social network structural property analysis based on co-keyword network modeling, and social network centrality analysis were used. Followings were the results of the research: (a) Achievement, writing, blended learning, teaching and learning model, learner centered education, cooperative leaning, and learning motivation, and self-regulated learning were found to be the most common keywords except flipped learning. (b) Density was .088, and geodesic distance was 3.150 based on keyword network type 2. (c) Teaching and learning model, blended learning, and satisfaction were centrally located and closed related to other keywords. Satisfaction, teaching and learning model blended learning, motivation, writing, communication, and achievement were playing an intermediary role among other keywords.