http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Yamaguchi, Manabu,Ikeda, Kentaro,Takenouchi, Naoki,Higashiyama, Masakazu,Watanabe, Akira Asian Australasian Association of Animal Productio 2013 Animal Bioscience Vol.26 No.7
The growth performance of embryo-transferred Japanese Black calves that were born from, and suckled by, Japanese Shorthorn cows in a cow-calf grazing system (BS-group, n = 5) was compared to that of Japanese Black calves from Japanese Black cows in a cowshed (BB-group, n = 5). The daily weight gain from birth to 1 month was higher in the BS-group than in the BB-group (p<0.01), and the same trend (p<0.05) was observed at 2 and 3 months of age. This resulted in body weight that was significantly higher for the BS-group between 1 and 3 months of age than what was observed for the BB-group (p<0.05). Heart girth was significantly greater in the BS-group than in the BB-group throughout the experimental period (p<0.01), and chest depth and withers height in the BS-group were significantly greater from 2 to 4 months of age (p<0.05) and at 4 months of age only (p<0.05). No difference in body length (p>0.05) was observed between the groups. These results suggest that the maternal effect of Japanese Shorthorn cows was positive for embryo-transferred Japanese Black calf growth during the early suckling stage. As Japanese Black calves are traded at a high price on the Japanese market, we conclude that this proposed production system is likely to improve the profitability of herd management in upland Japan.
Between Exploration and Exploitation in Motor Babbling
김전해,Kanta Watanabe,Shun Nishide,Manabu Gouko 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.4
Motor babbling allows an agent sampling trajectory data without a priori knowledge about self-body and environment dynamics. We discuss about the efficiency of motor babbling through the example of drawing task. In authors’ insight, natural motor babbling may be featured by exploration and exploitation processes. From this idea, we propose exploitation babbling and ε-greedy babbling. In order to implement the proposed babblings, we developed dynamics learning tree (DLT). DLT is an online incremental learning algorithm that has constant calculation order O(1). The proposed exploitation babbling and ε-greedy babbling improved the rate of effective data at 8 and 7 % from previous babbling respectively. ε-greedy babbling converged its prediction error fastest among the three babblings. Using ε-greedy babbling, a humanoid robot with wired flexible fingers successfully drew a figure without a priori knowledge about the dynamics among self-body, pen, and pen tablet.