Online edition: ISSN 2432-6380
[TOP] | [2017] | [2018] | [2019] | [2020] | [2021] | [2022] | [2023] | [Japanese] / [English]
DC2020-59
A Degradation Prediction of Circuit Delay Using A Gradient Descent Method
Seiichirou Mori, Masayuki Gondou, Yousuke Miyake, Takaaki Kato, Seiji Kajihara (Kyutech)
pp. 1 - 6
DC2020-60
Proposal of a Location-Based DTN Routing Method for Message Delivery between Fixed Nodes
Yoshihiko Yonezawa, Masato Kitakami (Chiba Univ.)
pp. 7 - 11
DC2020-61
Study of Deep Learning based Object Detection for Automatic Train Operation in Railways
Shiva Krishna Maheshuni (UTokyo), Shimura Takahiro, Yabuki Kohei, Hasegawa Takumi (Kyosan Electric Mfg), Takeshi Mizuma (UTokyo)
pp. 12 - 17
DC2020-62
How to collect teacher data for machine learning models to classify internal document know-how
Takahiro Shimura, Kohei Yabuki, Takumi Hasegawa (Kyosan Electric Mfg), Shiva Krishna Maheshuni, Takeshi Mizuma (Univ.Tokyo)
pp. 18 - 22
DC2020-63
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)
pp. 23 - 26
DC2020-64
Study on Approach for the NS type Electric Point Machine Maintenance using Condition Based Maintenance
Hiroshi Shida (JR WEST), Yuki Misaki (JR Shikoku), Hiroshi Takahashi (Ehime Univ)
pp. 27 - 32
DC2020-65
Vibration Measurement of Signal Bonds for Automatic Train Control
Yuki Echigo, Satoshi Ohtake (Oita Univ.)
pp. 33 - 38
DC2020-66
Development of train self-position estimation device based on brightness information of LiDAR sensor
Noriyuki Shinoda (Shinoda Gi), Takeshi Mizuma (Tokyo Univ)
pp. 39 - 42
DC2020-67
(See Japanese page.)
pp. 43 - 48
DC2020-68
A Survey of the Revisised Standard EN 50126:2017 Concerning Railway System RAMS
-- Comparison of revision lists shown in a Japanese Literature and an European one --
Koji Iwata (R.T.R.I)
pp. 49 - 54
Note: Each article is a technical report without peer review, and its polished version will be published elsewhere.