Zobrazeno 1 - 10
of 331
pro vyhledávání: '"Takako Hashimoto"'
Autor:
Ryota Kobayashi, Yuka Takedomi, Yuri Nakayama, Towa Suda, Takeaki Uno, Takako Hashimoto, Masashi Toyoda, Naoki Yoshinaga, Masaru Kitsuregawa, Luis E C Rocha
Publikováno v:
Journal of Medical Internet Research, Vol 24, Iss 12, p e41928 (2022)
BackgroundVaccines are promising tools to control the spread of COVID-19. An effective vaccination campaign requires government policies and community engagement, sharing experiences for social support, and voicing concerns about vaccine safety and e
Externí odkaz:
https://doaj.org/article/ba2f85edb5c04b38b24573653bcf744b
Publikováno v:
東洋文化研究. (23):283-304
application/pdf
インドネシアにおけるジェンダー・エンパワーメント指数を州別に分析した。興味深い発見として地理的な2 種類のクラスターを見つけた。第1 番目は女性の専門職率の高
インドネシアにおけるジェンダー・エンパワーメント指数を州別に分析した。興味深い発見として地理的な2 種類のクラスターを見つけた。第1 番目は女性の専門職率の高
Publikováno v:
東洋文化研究. (24):287-328
application/pdf
論説
論説
Publikováno v:
Information Systems Frontiers
In Japan, cashless is not yet popular but government and companies are devoted to the development of mobile payment methods. This research collected 241 Japanese users and applied decision trees algorithm. Six types of perceived risks (financial, pri
Publikováno v:
2022 International Electronics Symposium (IES).
Autor:
David Lawrence Shepard, Tetsuji Kuboyama, Takeaki Uno, Ryota Kobayashi, Kilho Shin, Takako Hashimoto
Publikováno v:
The Journal of Supercomputing. 77:4375-4388
During a disaster, social media can be both a source of help and of danger: Social media has a potential to diffuse rumors, and officials involved in disaster mitigation must react quickly to the spread of rumor on social media. In this paper, we inv
Autor:
Takako Hashimoto, Takeaki Uno, Yuka Takedomi, David Shepard, Masashi Toyoda, Naoki Yoshinaga, Masaru Kitsuregawa, Ryota Kobayashi
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Publikováno v:
2021 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI).
Publikováno v:
TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON).
Publikováno v:
Information, Vol 8, Iss 4, p 159 (2017)
Feature selection is a useful tool for identifying which features, or attributes, of a dataset cause or explain the phenomena that the dataset describes, and improving the efficiency and accuracy of learning algorithms for discovering such phenomena.
Externí odkaz:
https://doaj.org/article/774d86101ce64ed180279cac3d4541b1