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정부 R&D 지원의 기업 R&D 투자에 대한 효과 분석 -제약산업을 중심으로-
사공진,신유원 한국보건행정학회 2010 보건행정학회지 Vol.20 No.1
The purpose of this study is to analyze the effect of the R&D subsidies by the government on the private firms' R&D investments in the Korean pharmaceutical industry, which are supposed to have positive effects on their economic performance. We also estimate the relationship between the private firms' R&D investments and firms' economic outcome. Empirical analysis is done by Error Component 2 Stage Least Squares(EC2SLS) estimation using 43 pharmaceutical firms' 8 years' panel data. The elasticity of the government R&D subsidies on the private R&D investments is 0.021%, which we cannot say 'efficient'. Also R&D investments have positive effects on the economic outcome of the pharmaceutical firms, as we expected. We propose several suggestions in the conclusion for theefficient way of government R&D subsidies to induce more private R&D investments.
金憲奎,申裕垣 이화여자대학교 한국문화연구원 1959 韓國文化硏究院 論叢 Vol.1 No.-
1. Sixty-five species were known from this area by 1932 with no additional species being reported to date. 2. In order to clarify the fauna, the authors made one full year's collection from October, 1958 to October, 1959. Thirty-two species are added to the fauna of Kwangnung, raising the number of species to ninety-seven. 3. Weekly collections were made by the authors along several preset courses in order to cover the area adequately as shown on the map. Collections were made as recorded in the following table: 1958 1959 month Oct Apr May June July Aug Sept Oct date 24 12, 1819, 25 2, 9, 1512,28,30 12, 1320, 28 5, 1125 2, 1624, 30 13, 2027 4, 25 4. The species were grouped in four categories according to the number of specimens appearing in our collections. The following table presents the numbers of species in each categories: A=most abundant - 22 species B=common - 16 ˝ C=rare - 15 ˝ D=very rare - 38 ˝ 5. The greatest numbers for most species were collected in June, with fewer in May, August, and July respectively.
딥러닝 표정 인식을 활용한 실시간 온라인 강의 이해도 분석
이자연,정소현,신유원,이은혜,하유빈,최장환,Lee, Jaayeon,Jeong, Sohyun,Shin, You Won,Lee, Eunhye,Ha, Yubin,Choi, Jang-Hwan 한국멀티미디어학회 2020 멀티미디어학회논문지 Vol.23 No.12
Due to the spread of COVID-19, the online lecture has become more prevalent. However, it was found that a lot of students and professors are experiencing lack of communication. This study is therefore designed to improve interactive communication between professors and students in real-time online lectures. To do so, we explore deep learning approaches for automatic recognition of students' facial expressions and classification of their understanding into 3 classes (Understand / Neutral / Not Understand). We use 'BlazeFace' model for face detection and 'ResNet-GRU' model for facial expression recognition (FER). We name this entire process 'Degree of Understanding (DoU)' algorithm. DoU algorithm can analyze a multitude of students collectively and present the result in visualized statistics. To our knowledge, this study has great significance in that this is the first study offers the statistics of understanding in lectures using FER. As a result, the algorithm achieved rapid speed of 0.098sec/frame with high accuracy of 94.3% in CPU environment, demonstrating the potential to be applied to real-time online lectures. DoU Algorithm can be extended to various fields where facial expressions play important roles in communications such as interactions with hearing impaired people.