• 제목/요약/키워드: R&D Trends

검색결과 581건 처리시간 0.039초

일본에서의 한방의학(漢方醫學)에 대한 국비 지원 연구 동향과 그 함의 (Trends of Government Funded Research for Kampo Medicine in Japan and It's Implication)

  • 정창운;최창혁;조희근;송민영;백은혜
    • 한방재활의학과학회지
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    • 제28권1호
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    • pp.121-131
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    • 2018
  • Objectives We analyzed the trends of government-funded research on Kampo medicine in Japan to provide advanced evidence to R&D support policy for Korean medicine, and to introduce new research fields and trends to the researchers. Methods We reviewed the researches on Kampo medicine through 'research-er.jp' and 'KAKEN' database which contain R&D status in Japan and scientific research funding project issued by the Japan Ministry of Education, Culture, Sports, Science and Technology. Results Since 1976, government-funded research on Kampo medicine has been continuously announced, and now 533 tasks have been completed or are in progress. The average duration of the study is 2.54 years, but it has been prolonged to 3.52 years in recent years. 4~5 million yen was supported per project for laboratory research, and an average of 44,342 thousand yen was supported per project for specialized laboratory research and clinical research. Conclusions Despite the absence of systematically supporting departments, the researches on Kampo medicine in Japan were qualitatively superior since they focused on providing the scientific basis for clinical application. As competition in the world's traditional medicine market becomes more intense, it is necessary to improve the competitiveness of Korean medicine. Therefore, a keen interest in Korean medicine and active support from the government is needed.

수소 스테이션의 연구개발 동향 및 단위공정 기술 (R&D Trends and Unit Processes of Hydrogen Station)

  • 문동주;이병권
    • Korean Chemical Engineering Research
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    • 제43권3호
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    • pp.331-343
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    • 2005
  • 연료전지와 수소를 사용하는 연료전지 자동차의 상용화를 위해서는 수소 공급용 수소 스테이션(hydrogen station)의 개발이 중요한 핵심 기반기술이다. 일반적으로 수소 스테이션은 탈황반응, 개질반응(reforming), 수성가스전환(WGS) 반응 및 수소분리(PSA) 장치로 구성된 수소제조 공정과 압축, 저장 및 분배 장치로 구성된 후처리(post-treatment) 공정으로 구성되어 있다. 본 총설에서는 수소 경제(hydrogen economy) 사회로의 진입을 위해 국내외에서 연구개발 중인 수소 스테이션에 대한 연구 개발 동향과 전망을 고찰하였다. 그리고 향후 풍력 및 태양열 등 재생 가능 에너지(renewable energy)원으로부터 물의 분해에 의한 수소제조 기술이 확립되기 전까지는 화석연료의 개질 반응이 수소를 제조하는 핵심기술이 될 것으로 판단된다. 따라서 화석연료의 탈황반응, 화석연료의 개질 반응에 의한 수소제조, CO 농도 저감을 위한 수성가스 전환반응 및 수소의 분리기술 등 수소 스테이션의 상용화에 필수적인 단위공정개발에 대한 최근의 연구동향을 정리하였다.

화학기계적 연마기술 연구개발 동향: 입자 거동과 기판소재를 중심으로 (Chemical Mechanical Polishing: A Selective Review of R&D Trends in Abrasive Particle Behaviors and Wafer Materials)

  • 이현섭;성인하
    • Tribology and Lubricants
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    • 제35권5호
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    • pp.274-285
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    • 2019
  • Chemical mechanical polishing (CMP), which is a material removal process involving chemical surface reactions and mechanical abrasive action, is an essential manufacturing process for obtaining high-quality semiconductor surfaces with ultrahigh precision features. Recent rapid growth in the industries of digital devices and semiconductors has accelerated the demands for processing of various substrate and film materials. In addition, to solve many issues and challenges related to high integration such as micro-defects, non-uniformity, and post-process cleaning, it has become increasingly necessary to approach and understand the processing mechanisms for various substrate materials and abrasive particle behaviors from a tribological point of view. Based on these backgrounds, we review recent CMP R&D trends in this study. We examine experimental and analytical studies with a focus on substrate materials and abrasive particles. For the reduction of micro-scratch generation, understanding the correlation between friction and the generation mechanism by abrasive particle behaviors is critical. Furthermore, the contact stiffness at the wafer-particle (slurry)-pad interface should be carefully considered. Regarding substrate materials, recent research trends and technologies have been introduced that focus on sapphire (${\alpha}$-alumina, $Al_2O_3$), silicon carbide (SiC), and gallium nitride (GaN), which are used for organic light emitting devices. High-speed processing technology that does not generate surface defects should be developed for low-cost production of various substrates. For this purpose, effective methods for reducing and removing surface residues and deformed layers should be explored through tribological approaches. Finally, we present future challenges and issues related to the CMP process from a tribological perspective.

인문사회 과학기술 분야 연구의 학제적 동향 분석 : 토픽 모델링과 네트워크 분석의 활용 (Identifying Interdisciplinary Trends of Humanities, Sociology, Science and Technology Research in Korea Using Topic Modeling and Network Analysis)

  • 최재웅;장재혁;김대환;윤장혁
    • 산업경영시스템학회지
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    • 제42권1호
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    • pp.74-86
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    • 2019
  • As many existing research fields are matured academically, researchers have encountered numbers of academic, social and other problems that cannot be addressed by internal knowledge and methodologies of existing disciplines. Earlier, pioneers of researchers thus are following a new paradigm that breaks the boundaries between the prior disciplines, fuses them and seeks new approaches. Moreover, developed countries including Korea are actively supporting and fostering the convergence research at the national level. Nevertheless, there is insufficient research to analyze convergence trends in national R&D support projects and what kind of content the projects mainly deal with. This study, therefore, collected and preprocessed the research proposal data of National Research Foundation of Korea, transforming the proposal documents to term-frequency matrices. Based on the matrices, this study derived detailed research topics through Latent Dirichlet Allocation, a kind of topic modeling algorithm. Next, this study identified the research topics each proposal mainly deals with, visualized the convergence relationships, and quantitatively analyze them. Specifically, this study analyzed the centralities of the detailed research topics to derive clues about the convergence of the near future, in addition to visualizing the convergence relationship and analyzing time-varying number of research proposals per each topic. The results of this study can provide specific insights on the research direction to researchers and monitor domestic convergence R&D trends by year.

MEDLINE 검색을 통한 산업안전보건 분야에서의 인간공학 연구동향 : 워드임베딩을 활용한 초록 단어 모델링을 중심으로 (Research Trends of Ergonomics in Occupational Safety and Health through MEDLINE Search: Focus on Abstract Word Modeling using Word Embedding)

  • 김준희;황의재;안선희;곽경태;정성훈
    • 한국안전학회지
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    • 제36권5호
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    • pp.61-70
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    • 2021
  • This study aimed to analyze the research trends of the abstract data of ergonomic studies registered in MEDLINE, a medical bibliographic database, using word embedding. Medical-related ergonomic studies mainly focus on work-related musculoskeletal disorders, and there are no studies on the analysis of words as data using natural language processing techniques, such as word embedding. In this study, the abstract data of ergonomic studies were extracted with a program written with selenium and BeutifulSoup modules using python. The word embedding of the abstract data was performed using the word2vec model, after which the data found in the abstract were vectorized. The vectorized data were visualized in two dimensions using t-Distributed Stochastic Neighbor Embedding (t-SNE). The word "ergonomics" and ten of the most frequently used words in the abstract were selected as keywords. The results revealed that the most frequently used words in the abstract of ergonomics studies include "use", "work", and "task". In addition, the t-SNE technique revealed that words, such as "workplace", "design", and "engineering," exhibited the highest relevance to ergonomics. The keywords observed in the abstract of ergonomic studies using t-SNE were classified into four groups. Ergonomics studies registered with MEDLINE have investigated the risk factors associated with workers performing an operation or task using tools, and in this study, ergonomics studies were identified by the relationship between keywords using word embedding. The results of this study will provide useful and diverse insights on future research direction on ergonomic studies.

토픽모델링과 시계열 분석을 활용한 클라우드 보안 분야 연구 동향 분석 : NTIS 과제를 중심으로 (Analysis of Research Trends in Cloud Security Using Topic Modeling and Time-Series Analysis: Focusing on NTIS Projects)

  • 윤선영;조남옥
    • 융합보안논문지
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    • 제24권2호
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    • pp.31-38
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    • 2024
  • 최근 클라우드 서비스 사용이 확산하면서 클라우드 보안의 중요성이 증가하였다. 본 연구의 목적은 클라우드 보안 분야의 최근 연구 동향을 분석하고 시사점을 도출하는 것이다. 이를 위해 2010년부터 2023년까지 국가과학기술지식정보서비스(NTIS)에서 제공하는 R&D 과제 데이터를 활용하여 클라우드 보안 연구 동향을 분석하였다. LDA 토픽모델링과 ARIMA 시계열 분석을 통해 클라우드 보안 연구의 핵심 토픽 15개를 도출하였으며, AI를 활용한 보안 기술, 개인정보 및 데이터보안, IoT 환경에서의 보안 문제 해결이 연구에서 중요한 영역임을 확인했다. 이는 클라우드 기술의 확산과 기반 시설의 디지털 전환으로 인해 발생할 수 있는 보안 위협에 대응하기 위해 관련 연구가 필요함을 시사한다. 도출된 토픽들을 기반으로 클라우드 보안 분야를 네 가지 범주로 나누어 기술참조모델을 정의하였으며, 전문가 인터뷰를 통해 해당 기술참조모델을 개선하였다. 본 연구는 클라우드 보안 발전의 방향을 제시하며 학계 및 산업계에 미래 연구와 투자에 대한 중요한 지침을 제공할 것으로 기대된다.

HYBRIDIZATION EFFECTS IN $RT_2$ COMPOUNDS (R = Ce, Pr, Nd, Sm, Gd; T = Fe, Co, Ni)

  • Kang, Kicheon;Min, B.I.;Kang, J.S.
    • 한국자기학회지
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    • 제5권5호
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    • pp.376-379
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    • 1995
  • Employing the muffin-tin-orbital theory combined with pseudo-potential concepts, we have evaluated hybridization matrix elements between R and T sites in $RT_{2}$ compounds. The matrix elements are calculated with two parameters, the interatomic distance between R and T atoms from the crystal structure data, and the expectation values of the radial distances for the radial wave functions of the ground state charge densities, which are obtained from the linearized muffin-tin orbital band method within the local density approximation. It is found that the R 4f/T 3d hybridization matrix elements decrease with an increasing atomic number from R=Ce to Gd, and that they are smaller in $RNi_{2}$ than in $RCo_{2}$, which are consistent with trends observed in recent photoemission spectroscopy experiments. It is also found that the magnitudes of the hybridization matrix elements in $RFe_{2}$ are comparable to those in $RNi_{2}$.

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Water Quality in Artificial Reservoirs and Its Relations to Dominant Reservoir Fishes

  • Hwang, Yoon;Han, Jeong-Ho;An, Kwang-Guk
    • 생태와환경
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    • 제42권4호
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    • pp.441-451
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    • 2009
  • The major objectives of this study were to evaluate trophic state of reservoirs using major water quality variables and its relations in terms of trophic guilds and tolerance guilds with dominant lentic fishes. For this study, we selected 6 artificial reservoirs such as Namyang Reservoir ($N_yR$), Youngsan Reservoir ($Y_sR$), Daechung Reservoir ($D_cR$), Chungju Reservoir ($Cj_R$), Chungpyung Reservoir ($C_pR$), and Paldang Reservoir ($P_dR$), and collected fish during 2000~2007 along with data analysis of water quality monitored by the ministry of environment, Korea. Biological oxygen demand (BOD) and chemical oxygen demand (COD), indicators of organic matter pollution, varied depending on types of the reservoirs and the spatial patterns in terms of trophic gradients were similar to patterns of nutrients, Secchi depth and chlorophyll-a. Analysis of trophic state index (TSI) showed that reservoirs of $D_cR$ and $C_jR$ were mesotrophy and other 4 reservoirs were eutrophic state. The relations of trophic relations showedthat TSI (Chl-a) had a positive linear function [TSI (CHL)=0.407 TSI (TP)+28.2, n=138, p<0.05] with TSI (TP) but had a weak relation with TSI (TN). Also, TSI (TP) were negatively correlated ($R^2=0.703$, p<0.05) with TSI (SD), whereas TSI (TN) was not significant (p>0.05) relations with TSI (SD). Tolerance guilds of lentic fishes, based on three types of the reservoirs, reflected the exactly water quality in the TN, TP, BOD, and COD, and similar trends were shown in the fish feeding/trophic guilds.

한국어 기술문서 분석을 위한 BERT 기반의 분류모델 (BERT-based Classification Model for Korean Documents)

  • 황상흠;김도현
    • 한국전자거래학회지
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    • 제25권1호
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    • pp.203-214
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    • 2020
  • 최근 들어 기술개발 현황, 신규기술 분야 출현, 기술융합과 학제 공동연구, 기술의 트렌드 변화 등을 파악하기 위해 R&D 과제정보, 특허와 같은 기술문서의 분류정보가 많이 활용되고 있다. 이러한 기술문서를 분류하기 위해 주로 텍스트마이닝 기법들이 활용되어 왔다. 그러나 기존 텍스트마이닝 방법들로 기술문서를 분류하기 위해서는 기술문서들을 대표하는 특징들을 직접 추출해야 하는 한계점이 있다. 따라서 본 연구에서는 딥러닝 기반의 BERT모델을 활용하여 기술문서들로부터 자동적으로 문서 특징들을 추출한 후, 이를 문서 분류에 직접 활용하는 모델을 제안하고, 이에 대한 성능을 검증하고자 한다. 이를 위해 텍스트 기반의 국가 R&D 과제 정보를 활용하여 BERT 기반 국가 R&D 과제의 중분류코드 예측 모델을 생성하고 이에 대한 성능을 평가한다.

LDA알고리즘을 활용한 태양광 에너지 기술 특허 및 논문 동향 연구 (Patents and Papers Trends of Solar-Photovoltaic(PV) Technology using LDA Algorithm)

  • 이종호;이인수;정경수;채병훈;이주연
    • 디지털융복합연구
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    • 제15권9호
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    • pp.231-239
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    • 2017
  • 산업의 급격한 발전은 화석에너지의 고갈을 야기하였고, 이러한 이유로 화석연료를 대체하기 위한 에너지로 태양광에너지가 각광받기 시작하였다. 하지만 기술발전에 있어 전체적인 연구방향 및 향후 연구 방향에 대한 논의가 부족하였다. 이에 보다 효과적인 기술개발을 위해 특허 데이터와 논문 데이터를 활용하여 태양광 에너지의 기술 동향을 파악하고 논의를 진행하였다. 분석방법으로는 토픽 모델링과 텍스트 마이닝을 활용하여 1997년도부터 2015년까지의 데이터를 토대로 기술 동향과 연구의 방향성에 대하여 분석한다. LDA알고리즘을 통하여 토픽을 선정하고, 선정된 기술 범주에 포함된 키워드의 증가량을 살펴보고, 태양광 기술의 발전방향에 대하여 분석하였다. 태양광 발전 기술에 대한 연구는 꾸준히 진행될 것으로 예상되며, 특히 고효율화 및 고성능화 기술에 대하여 집중적으로 연구가 이루어질 것으로 분석된다. 향후 연구로는 해외의 특허데이터와 다양한 논문데이터를 추가하여 연구를 진행할 수 있을 것이다.