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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 9 of 9  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
DC 2024-12-06
14:50
Oita Southern Cross Community Square (Oita) A Study of Personal Identification Using Whirlpool Features
Chitose Ishizu, Takumi Fukuda, Sei Takahashi (Nihon Univ.) DC2024-100
In recent years, the value of waste treatment facilities as educational sites has been questioned. In Japan, these facil... [more] DC2024-100
pp.13-16
DC 2024-12-06
15:15
Oita Southern Cross Community Square (Oita) A Study on Real-Time Signal Control of Multiple Intersections Using Deep Reinforcement Learning
Mizuki Kato, Takumi Fukuda, Sei Takahashi, Hideo Nakamura (Nihon Univ.) DC2024-101
Recently, the significance of signal control by deep reinforcement learning, a type of machine learning, has been demons... [more] DC2024-101
pp.17-20
DC 2024-12-06
15:50
Oita Southern Cross Community Square (Oita) Study on Optimization of Train Approach Patterns to Reduce Stops Between Stations in Moving Block
Shunichi Sato, Takumi Fukuda, Sei Takahashi, Hideo Nakamura (Nihon University) DC2024-102
In this paper, we propose an optimization method for determining appropriate approach patterns to preceding trains to re... [more] DC2024-102
pp.21-24
BioX, SIP, IE, ITE-IST, ITE-ME [detail] 2023-05-19
13:30
Mie Sansui Hall, Mie University (Mie, Online)
(Primary: On-site, Secondary: Online)
Writer Verification Based on Finger-writing of a Simple Symbol -- Introduction of Finger-softness Feature --
Takumi Fukuda, Takahiro Horiuchi, Isao Nakanishi (Tottori Univ) SIP2023-14 BioX2023-14 IE2023-14
We proposed writer verification based on writing of a simple symbol on a smartphone screen, called where users draw a si... [more] SIP2023-14 BioX2023-14 IE2023-14
pp.63-68
DC 2022-12-16
15:00
Yamaguchi (Yamaguchi, Online)
(Primary: On-site, Secondary: Online)
Learning of train control measures by means of Deep Q-Network -- Preliminary study with a single train control --
Shogo Igarashi, Takumi Fukuda, Sei Takahashi, Hideo Nakamura (Nihon Univ), Tetsuya Takata (Kyosan Electric Manufacturing) DC2022-77
Although the predictive fuzzy control technique has been put to practical use as a train control strategy for automatic ... [more] DC2022-77
pp.26-29
DC 2021-12-10
15:05
Kagawa (Kagawa, Online)
(Primary: On-site, Secondary: Online)
A study on the optimal offset search method for traffic signals by GA with initial population generated based on standard road length
Minoru Takahashi, Takumi Fukuda, Hiroshi Mochizuki, Sei Takahashi (Nihon Univ.), Hideo Nakamura (UTokyo), Hiroshi Kazama (Kyosan) DC2021-60
To ensure the smooth running of automobile on public roads, systematic control of traffic signal offsets is necessary. W... [more] DC2021-60
pp.30-33
DC 2021-12-10
15:25
Kagawa (Kagawa, Online)
(Primary: On-site, Secondary: Online)
Prediction of Train Delays at Stations Using Multiple Convolutional Neural Networks with Actual Operation Data
Tsukasa Takahashi, Takumi Fukuda, Sei Takahashi (Nihon Univ.), Hideo Nakamura (UTokyo) DC2021-61
In the metropolitan area, railroads are frequently delayed due to high congestion rates during rush hours, and many meas... [more] DC2021-61
pp.34-37
DC 2020-12-11
14:20
Hyogo (Hyogo, Online)
(Primary: On-site, Secondary: Online)
Prediction of Train Delays at Stations Using Convolutional Neural Networks with Actual Operation Data
Tsukasa Takahashi, Takumi Fukuda, Sei Takahashi (Nihon Univ.), Hideo Nakamura (The Univ. of Tokyo) DC2020-63
Trains in the metropolitan area have high congestion rates during rush hours. Congestion causes delays, and there is a l... [more] DC2020-63
pp.23-26
NLP 2016-09-14
10:55
Hyogo Konan Univ. (Hyogo) Development of a Quadrotor with Tilting Parallel Linked Body
Takumi Fukuda, Sakaguchi Akinori (Osaka Univ), Takimoto Takashi (NIT), Ushio Toshimitu (Osaka Univ) NLP2016-45
A quadrotor cannot hover in any attitude. We suggest a quadrotor with a tilting parallel linked body for improvement of ... [more] NLP2016-45
pp.5-8
 Results 1 - 9 of 9  /   
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