著者

Naoki Kobayakawa Mitsuyoshi Imamura Kei Nakagawa Kenichi Yoshida

出版者

Information Processing Society of Japan

雑誌

Journal of Information Processing (ISSN:18826652)

巻号頁・発行日

vol.28, pp.650-657, 2020 (Released:2020-09-15)

参考文献数

28

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Open source software (OSS) has become indispensable to our society. The success of OSS depends on the participation of a large number of developers or maintainers (contributors). Shedding light on the mechanisms of their participation has been an important academic and practical matter. One aspect to decide participation is the future prospects of a project. However, the causal mechanism behind participation has yet to be studied exhaustively and remains unclear. In this study, we used cryptocurrency projects, many of them were developed on GitHub, to better understand this mechanism. Both GitHub and cryptocurrencies are highly transparent, i.e., information is fully disclosed; we can analyze relevant information on a project, such as the contributors' activities, financial information, and development status. We adopted market capitalization as the substitution index of future prospects and the number of contributors and analyzed the relationship using time series analysis techniques, such as the Granger causality test and regression. We found that the number of contributors increases two months after market capitalization increases. This quantifies the impact of the future prospects of the project, i.e., of the market capitalization of a cryptocurrency, on the participation of contributors.

著者

Yunfan Li Yukai Gong Jyun-Rong Zhuang Junyan Yang Keisuke Osawa Kei Nakagawa Hee-hyol Lee Louis Yuge Eiichiro Tanaka

出版者

Fuji Technology Press Ltd.

雑誌

Journal of Robotics and Mechatronics (ISSN:09153942)

巻号頁・発行日

vol.34, no.6, pp.1383-1397, 2022-12-20 (Released:2022-12-20)

参考文献数

32

被引用文献数

6

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The world’s aging population is increasing. The number of elderly individuals having walking impairments is also increasing. Adequate exercise is becoming necessary for them. Therefore, several walking assistive devices have been developed or are under development. However, elderly individuals may have low motivation for exercising, or they may experience physical damage by excessive fatigue. This study proposed a method to enable elderly individuals to exercise with a positive emotion and prevent damage such as muscle fatigue. We proposed a 3D human condition model to control the walking assistive device. It includes the arousal, pleasure, and fatigue dimensions. With regard to the arousal and pleasure dimensions, we used heartbeat and electromyography (EEG) signals to train a deep neural network (DNN) model to identify human emotions. For fatigue detection, we proposed a method based on near-infrared spectroscopy (NIRS) to detect muscle fatigue. All the sensors are portable. This implies that it can be used for outdoor activities. Then, we proposed a walking strategy based on a 3D human condition model to control the walking assistive device. Finally, we tested the effectiveness of the automatic control system. The wearing of the walking assistive device and implementation of the walking strategy can delay the fatigue time by approximately 24% and increase the walking distance by approximately 16%. In addition, we succeeded in visualizing the distribution of emotion during each walking method variation. It was verified that the walking strategy can improve the mental condition of a user to a certain extent. These results showed the effectiveness of the proposed system. It could help elderlies maintain higher levels of motivation and prevent muscle damage by walking exercise, using the walking assistive device.