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朴秉日 中央醫學社 1969 中央醫學 Vol.16 No.3
A case of optic nerve glioma was reported, occurred in the left eye of a 4-year-old Korean boy. Corneal opacity and proptosis of 13 months' duralion were his chief complaints prior to his visit to our hospital. Proptosis was slight in degree but the softening of the eye-ball was noted, due to phthisis bulbi with adherent leucoma after exposure keratitis and the mass was palpable in the left orbit. No "cafe-au-lait" spot was seen. Radiological examination confirmed that the diameter of the left optic foramina was larger than that of the right. Histology confirmed the lesion to be glioma(Astrocytoma type). Surgical removal was successful and no incidence of recurrance can be disclosed until now, 19 months after surgery.
진탕에 依하여 抽出한 菌體物質이 Phage 血球凝集反應에 미치는 影響
朴秉日 中央醫學社 1969 中央醫學 Vol.16 No.3
The bacterial substance extracted by shaking can form the phage hemagglutination, especially the cold reaction. On centrifugating of the bacterial suspension after shaking, the effective bacterial substance is more appeared in the supernatant fraction than sediment. The phage inactivating activities of the supernatant and sedimental fraction sobtained by centrifugating of the bacterial suspension after shaking are similar.
박병일,정금섭,전흥우,신경욱 한국정보통신학회 2000 한국정보통신학회논문지 Vol.4 No.2
셀룰러 신경망은 국부적 연결특성을 가지고 있어 실시간 영상처리에 폭넓게 이용되는 비선형 정보처리 시스템이다. 본 논문에서는 소규모의 $CNN(6\time6)$ 셀 블록을 이용하여, 크고 복잡한 처리에 적합한 시다중화 기법을 처리할 수 있는 CNN칩을 설계하였다. 대부분의 출력 형태는 기준 레벨화된 출력에 기인하여 흑백 영상처리에 적합하나, 본 논문의 출력형태는 아날로그 상태값으로 나타나기 때문에 그레이 레벨 영상처리에 적합하다. CNN 칩은 $0.65\mum$ 2P2M N-Well CMOS 공정으로 설계되었으며, 설계된 칩은 15400여개의 트랜지스터로 구성되며 칩면은 $1.85\times1.75m^2$ 이다. 설계된 $6\time6CNN$칩은 그 보다 큰 입력 영상에 대한 윤곽선 검출의 실험을 통하여 회로의 동작을 검증하였다. Cellular Neural Networks(CNN) is a nonlinear information-processing system that has a locally connected characteristic and is widely used in the real-time high speed image processing. In this paper, a practical system approach of time-multiplexing CNN implementations suitable for processing large and complex images using small CNN arrays is presented and $6\times6$ CNN hardware is designed for the processing of a large image. While previous implementations are mostly suitable for black and white applications because of the thresholded outputs, our approach is especially suitable for applications in gray image processing due to the analog nature of the state node. CNN chip is designed using a 0.65${\mu}{\textrm}{m}$ 2P2M(double poly, double metal) N-Well CMOS process technology. It contains about 15,400 devices on an area of about $1.85\times1.75$ md. The designed $6\times6$ CNN is tested for the edge detection of a large image input and it's performance is verified.