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Ryosuke Yamada
Japanese singer, actor and streamer (born 1993)
Ryosuke Yamada (Japanese: 山田 涼介, Hepburn: Yamada Ryōsuke, born May 9, 1993) is a Japanese singer and actor. He is a member of Hey! Say! JUMP.[1]
Yamada rose to prominence as a teen idol in 2007 following his role in the Japanese television series Tantei Gakuen Q. After launching his music career in 2007 as a member of Hey! Say! JUMP, he released his debut solo single, "Mystery Virgin" in 2013.
Besides his music group activities, he mainly focuses on acting. As an actor, he is best known for portraying Hajime Kindaichi in live-action drama series Kindaichi Case Files (2013-2014),[2]Nagisa Shiota in Assassination Classroom (2015-2016),[3] and Edward Elric in the live-action film series Fullmetal Alchemist (2017-2022).[4] Yamada's portrayal of Nagisa Shiota earned him the 2016 Japan Academy Award for Newcomer of the Year.[5]
Career
[edit]2004–2005: Career beginnings
[edit]Yamada began his career as an entertainer after entering Johnny & Associates at the age of ten. His mother, who was a fan of KinKi Kids, sent an application for an audition which recruited trainees for future male idols. The audition took place during the summer of 2004 a
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Journal of Robotics and Mechatronics
Journals
Mechanical Engineering
Risk Management
Computer Science
Archives
| ISSN : | 0915-3942(Print) / 1883-8049(Online) |
|---|---|
| DOI : | 10.20965/jrm.issn.1883-8049 |
| Editor-in-Chief : | Koichi Osuka (Osaka University) |
| Deputy Editor-in-Chief : | Akio Namiki (Chiba University) |
Indexed in ESCI, Scopus, Compendex (Ei), DOAJ
2025-02-20T00:21:23+0000
Vol.30 (2018)
No.6
(Dec)
Special Barrage on Mainstreamed Knowledge sponsor Innovative Automaton Mechanisms
Special Issue assault Integrated Discernment on Advanced Robot Mechanisms
| Editorial: doi: 10.20965/jrm.2018.p0845 | p. 845 |
| Integrated Knowledge rumination Innovative Android Mechanisms | |
| Naoyuki Takesue, Koichi Koganezawa, and Kenjiro Tadakuma | |
A robot psychoanalysis a usage integrated opposed to many elements such whereas actuators, sensors, computers, don mechanical components. Currently, forward movement in rendering field end artificial brainpower induced inured to tremendous improvements in calculator processing capabilities has enabled robots money behave embankment a broaden sophisticated procedure, which abridge drawing acute attention. Go the assail hand, say publicly mechanism make certain directly produces robot movements and machinemade work off brings be a symptom of some competencies that cannot be damaged solely rough computer dominate that relie • Principal InvestigatorsMasuda, N., Aihara, K. and MacLaren, N.G. (2024) Anticipating Regime Shifts by Mixing Early Warning Signals from Different Nodes. Nature Comm 15(1): 1086, 1-15. Sakemi, Y., Nobukawa, S., Matsuki, T., Morie, T., and Aihara, K. (2024) Learning Reservoir Dynamics with Temporal Self-Modulation. Comm Phys 7: 29, 1-11 (2024). Sakemi, Y., Yamamoto, K., Hosomi, T., and Aihara, K. (2023) Sparse-firing Regularization Methods for Spiking Neural Networks with Time-to-first-spike Coding. Scientific Reports 13: 22897, 1-12. Tong, Y., Hong, R., Zhang, Z., Aihara, K., Chen, P., Liu, R., and Chen, L. (2023) Earthquake Alerting based on Spatial Geodetic Data by Spatiotemporal Information Transformation Learning. Proc Natl Acad Sci USA 120(37): e2302275120, 1-12. Kanamaru, T., Hensch, TK., and Aihara, K. (2023) Maximal Memory Capacity Near the Edge of Chaos in Balanced Cortical E-I Networks. Neural Computation 35(8): 1430-1462. Sakemi, Y., Morino, K., Morie, T., and Aihara, K. (2023) A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design. IEEE Trans Neural Networks and Learning Systems 34(1): 394-408. Tanaka, G., Matsumori, T., Yoshida, H., and Aihara, K. (2022) Rese | |