http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
고 Si-P 첨가가 박육구상흑연주철의 미세 조직과 기계적 성질에 미치는 영향
박용진,최양진,박인선,김영환,이효상 ( Yong Jin Park,Yang Jin Choi,In Sun Park,Young Hwan Kim,Hyo Sang Lee ) 한국주조공학회 1995 한국주조공학회지 Vol.15 No.6
N/A Effects of high Si-P addition on microstructure and mechanical properties of thin ductile cast iron have been investigated. The amount of silicon addition have fixed on 4.0wt% and the amounts of phosphorus addition and thickness of specimen have been varied from 0.05 to 0.8wt% and ø13㎜, ø10㎜ and ø6㎜, respectively. As the casting thickness decreased, the average diameter of spheroidal graphite was decreased and the hardness of the cast iron increased. By adding P, the average diameter of spheroidal graphite was increased and the count of the spheroidal graphite was decreased continuously. And the tensile strength and the elongation was decreased, and the hardness was increased. With the P added more than 0.2wt%, the abraded amount was decreased significantly. The addition of P improved the wear resistance and the hardness of thin ductile cast iron.
영교차점과 켑스트럼 전처리 기술을 이용한 반향환경에서의 음원방향 추정
박용진,이수연,박형민,Park, Yong-Jin,Lee, Soo-Yeon,Park, Hyung-Min 대한음성학회 2008 말소리 Vol.67 No.-
To estimate directions of multi-sound sources, we consider an approach based on zero crossings which provided more robust results to diffuse noise than the conventional cross-correlation-based method [6][7]. In reverberant environments, the performance of source direction estimation can be improved by using signal components through direct paths from sources to microphones. Since a cepstral prefiltering technique [8] removes the effect of reverberation, we propose a source direction estimation method which can find out intervals of the direct-path components by comparing original and cepstral-prefiltered envelopes. Simulations demonstrate that the proposed method can improve the performance of source direction estimation in reverberant environments.
이용한 ( Yong-han Lee ),김범영 ( Beom-young Kim ),이신효 ( Sin-hyo Lee ),이지훈 ( Ji-hun Lee ) 한국정보처리학회 2017 한국정보처리학회 학술대회논문집 Vol.24 No.2
본 시스템은 자율 주행 버스를 위한 시스템이다. 딥러닝(Deep Learning) 기반 컴퓨터 비전 기술을 이용해 차선과 물체 인식을 하여 버스를 제어하는 방식으로 자율 주행을 가능하게 하는 시스템으로 교통비 완화 및 안정성 증대를 기대할 수 있다. This system is designed for autonomous buses. It controls buses by lane and object recognition using Deep Learning based computer vision technology. Through this system, we can expect to reduce traffic costs and increase stability.