• 제목/요약/키워드: Science and Engineering

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Korean Engineering Firms' Competitiveness Change for the Last Decade

  • Jung, Mincheol;Kim, Handon;Choi, Seeun;Cho, Hyunsang;Oh, Donggeun;Kim, Jimin;Jang, Hyounseung
    • 국제학술발표논문집
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    • The 9th International Conference on Construction Engineering and Project Management
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    • pp.599-607
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    • 2022
  • Recently, there has been a steady decrease in the proportion of the construction sector among Korean engineering firms. Thus it is essential for Korean engineering firms in the construction sector, which lack experience in overseas ventures, to identify and improve their competitiveness for successful overseas expansion. Therefore, in this study, changes in Korean engineering firms' capabilities for the last decade were analyzed to promote entry into overseas road and water resource engineering markets. Competency factors that require urgent improvement were derived based on Importance-Performance Analysis (IPA) as a tool for quantitative measurement. As a result, the factor that shows low performance compared to the importance is an overall understanding of the target country in the road and water resource areas. Knowledge of regulatory issues on design, the ability of time management software, and knowledge of the regulatory problems on construction safety are also insufficient. This study can be used as a research methodology to identify competitiveness that Korean engineering firms have to strengthen when they advance into overseas markets in roads, water resources, and other areas.

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Oligomerizations and Polymerizations of Olefins by Various Late Transition Metal Catalysts

  • Bahuleyan Bijal Kottukkal;Lee Kyoung-Ju;Son Gi-Wan;Choi Jae-Ho;Chandran Deepak;Abraham Sinoj;Ha Chang-Sik;Kim Il
    • 한국고분자학회:학술대회논문집
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    • 한국고분자학회 2006년도 IUPAC International Symposium on Advanced Polymers for Emerging Technologies
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    • pp.155-155
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    • 2006
  • The most commercially and academically advanced catalysts of late transition metals are diimine complexes based on Pd(II)/Ni(II) and bis(imino)pyridyl complexes based on Fe(II)/Co(II). It is well known that the former systems yield branched polyethylenes and the latter linear PEs. In this presentation, effect of extremely bulky ligands with electron withdrawing/donating substituents at a remote position from Ni(II) metal center and of using multi-nuclear homo or hetero multi-metal on the ethylene polymerization is to be paged.

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Characterization of Volatile Compounds in Donkey Meat by Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) Combined with Chemometrics

  • Mengmeng Li;Mengqi Sun;Wei Ren;Limin Man;Wenqiong Chai;Guiqin Liu;Mingxia Zhu;Changfa Wang
    • 한국축산식품학회지
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    • 제44권1호
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    • pp.165-177
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    • 2024
  • Volatile compounds (VOCs) are an important factor affecting meat quality. However, the characteristic VOCs in different parts of donkey meat remain unknown. Accordingly, this study represents a preliminary investigation of VOCs to differentiate between different cuts of donkey meat by using headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with chemometrics analysis. The results showed that the 31 VOCs identified in donkey meat, ketones, alcohols, aldehydes, and esters were the predominant categories. A total of 10 VOCs with relative odor activity values ≥1 were found to be characteristic of donkey meat, including pentanone, hexanal, nonanal, octanal, and 3-methylbutanal. The VOC profiles in different parts of donkey meat were well differentiated using three- and two-dimensional fingerprint maps. Nine differential VOCs that represent potential markers to discriminate different parts of donkey meat were identified by chemometrics analysis. These include 2-butanone, 2-pentanone, and 2-heptanone. Thus, the VOC profiles in donkey meat and specific VOCs in different parts of donkey meat were revealed by HS-GC-IMS combined with chemometrics, whcih provided a basis and method of investigating the characteristic VOCs and quality control of donkey meat.

의견 어구 추출을 위한 생성 모델과 분류 모델을 결합한 부분 지도 학습 방법 (Semi-Supervised Learning for Sentiment Phrase Extraction by Combining Generative Model and Discriminative Model)

  • 남상협;나승훈;이예하;이용훈;김준기;이종혁
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (C)
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    • pp.268-273
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    • 2008
  • 의견(Opinion) 분석은 도전적인 분야로 언어 자원 구축, 문서의 Sentiment 분류, 문장 내의 의견 어구 추출 등의 다양한 문제를 다룬다. 이 중 의견 어구 추출문제는 단순히 문장이나 문서 단위로 분류하는 수준을 뛰어 넘는 문장 내 의견 어구를 추출하는 문제로 최근 많은 관심을 받고 있는 연구 주제이다. 그러나 의견 어구 추출에 대한 기존 연구는 문장 내 의견 어구부분이 태깅(tagging)된 학습 데이터와 의견 어휘 자원을 이용한 지도(Supervised)학습을 이용한 접근이 대부분으로 실제 적용 상의 한계를 갖는다. 본 논문은 문장 내 의견 어구 부분이 태깅된 학습 데이터와 의견 어휘 자원이 없는 환경에서도 문장단위의 극성 정보를 이용하여 의견 어구를 추출하는 부분 지도(Semi-Supervised)학습 장법을 제안한다. 본 논문의 방법은 Baseline에 비하여 정확률(Precision)은 33%, F-Measure는 14% 가량 높은 성능을 냈다.

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