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송은아 ( Eun Ah Song ),강완 ( Wan Kang ),백석윤 ( Suck Yoon Paik ) 서울敎育大學校 初等敎育硏究所 2008 한국초등교육 Vol.18 No.2
또래교수활동에서 나타나는 교수자와 학습자 사이의 의사소통 활동을 분석하기 위하여 서울 관악구 소재 N 초등학교 5학년 학생 중 8명을 선정하여 이들의 또래교수 활동을 비디오 녹화하고 이를 바탕으로 프로토콜 작성, 번호 부여, 해석, 코드부여, 범주 분류의 방법을 사용하여 분석하였다. 분석 결과, 또래교수자의 지시 내용은 문제 풀도록 지시하기, 문제해결전략 지시하기, 유사문제 해결하기 등으로 분류되었다. 또래교수자의 발문 과정은 문제해결 가능 여부 확인, 문제해결 과정 이해 여부 확인, 학습자의 행동 이유 묻기, 학습자의 의견 묻기, 다음 단계로의 진행 유도 질문 등으로 분류되었다. 한편 또래 학습자는 문제해결이 곤란한 상황에서 해결 불가 의사 표현, 문제에 관한 질문, 불명확한 대답하기 등의 행동 특성을 보였으며, 문제해결 과정중 새로운 것을 알게 되었을 때는 감탄사로 표현하기, 문제해결에 바로 주도적으로 참여하기 등의 특성을 보였다. To analyse communications between peer tutor and peer learner in peer tutoring activities, 8 students of the 5th graders in an elementary school were selected and organized. Upon the video tape recording of their peer tutoring activities, drew up a protocol and analyzed them by means of numbering, comment, coding and categorizing. The study obtained the results and conclusion as in the following. The process of peer tutors` instructing an action to peer learners could be sub-divided as ① asking them to solve the problem, ② instructing them how-to-solve-the problem strategy and ③ instructing them how to solve similar problems, the process of peer tutors` asking a question to peer learners could be sub-divided as ① checking whether peer learners were able to solve problems, ② asking whether they understood the problem-solving procedures, ③ asking them the reason for their behavior, ④ asking a question about their opinion, ⑤ asking a leading question for the next stage. On the one hand, the characteristics shown in situations in which it was difficult for peer included the following as learners to solve problems, ① expressing that they would not be able to solve the problems, ② asking questions on the problems, ③ giving unclear answers. The characteristics shown when peer learners came to know something new during the problem-solving procedure included the following ① giving a signal by saying an injection, ② participating actively in problem solving.
컬러 벡터 오차확산법을 이용한 6색 프린터에서의 측색적 색 재현
이을환(Lee Eul Hwan),김재호(Kim Jae Ho),이남훈(Lee Nam Hoon),송은아(Song Eun Ah) 한국화상학회 1999 한국화상학회지 Vol.5 No.1
본 논문에서는 컬러 벡터 오차확산법을 이웅하여 6색 프린터에서의 측색적 색 재현을수행한다. Pappas프린터 모델을 사용하여 이웃하는 화소간의 중첩 영향을 고려한 벡터 오차확산법을 6색 컬러 프린터에 적용한다. 컬러 샘플을 이용하여 도트 크기를 추정하며, 수정 화소값에 임계치를 이용하여 스미어현상을 제거한다. 6색 프린터는 Light Cyan과 Light Magneta 잉크를 추가함으로써 3색 프린터에 비해 프린터 색역을 확장함과 동시에 밝은 영역에서 더 보기 좋은 컬러 영상을 재현할 수 있다. This paper describes colorimetric color reproduction using color vector error diffusion in six-color printer. Color vector error diffusion using Pappas`s printer model, which considers the dot overlap effect between neighboring dots, is applied to six-color printer. The dot size is estimated using color samples, and the smear artifact is also reduced by thresholding the modified value in error diffusion technique. Compared with three-color printer, six-color printer extends the printer gamut and reproduces the bright regions very well by adding light cyan and light magenta inks.
도축돈에서의 Actinobacillus pleuropneumoniae 분리, 동정 및 감염률 조사
김경언 ( Kyung Eon Kim ),구경녀 ( Kyung Nyer Ku ),고재형 ( Jae Hyung Ko ),문형준 ( Hyeong Jun Moon ),최권락 ( Kwon Rag Choi ),송은아 ( Eun Ah Song ),박미영 ( Mi Young Park ) 한국동물위생학회 2013 韓國家畜衛生學會誌 Vol.36 No.3
This study was conducted to isolate the Actinobacillus pleuropneumoniae (APP) and to find out the distribution of 15 serovars mainly in southern Gyeonggi province, Korea. From July 2011 to Nov. 2012, a total of 2,204 slaughter pigs (110 herds) were inspected for evaluation of APP like pneumonic lesions. 48 (33.8%) APP strains were isolated from the 142 lungs and identified using PCR assays (cps, apx/omlA, biovar). Consequently, the serotype ratio were as in the following; type2 41.7% (n=20), type5 33.3% (n=16), type12 10.4% (n=5), type1 6.2% (n=3), type4 and 7 2.1% (n=1) and unknown 4.2% (n=2). Also serological test was implemented for 452 (83 herds) serum samples randomly collected from above slaughter pigs using commercial ELISA kits. The positive ratio of each serotype for tested pigs were 19.1% (77/404) on [2], 7.1% (32/452) on [3, 6, 8], 6.9% (28/404) on [5a, 5b], 6.2% (28/452) on [4, 7], 2.8% (9/320) on [12], 2.0% (9/452) on [1, 9, 11] and 0.0% (0/452) on [10]. And 49.3% (223/452) of pigs were positive on apxⅣ antibody. On the basis of latter screening test, the infected farm ratio accounted for 71.1% (59/83) and that was much higher than previously reported data.