30 件のレコードが見つかりました。
Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array
- ジャーナル論文
- 著者
-
;Yusuke Saeki (author) (この著者で検索);Naoki Maki (author) (この著者で検索);Takahiro Nemoto (author) (この著者で検索)National Institute for Materials Science;Katsushige Inada (author) (この著者で検索)Kosuke Minami (author) (この著者で検索)National Institute for Materials Science
;
Ryo Tamura (author) (この著者で検索)National Institute for Materials Science
;
Gaku Imamura (author) (この著者で検索)National Institute for Materials Science
;
;Yukiko Cho-Isoda (author) (この著者で検索);Shinsuke Kitazawa (author) (この著者で検索);Hiroshi Kojima (author) (この著者で検索)Genki Yoshikawa (author) (この著者で検索)National Institute for Materials Science
;
Yukio Sato (author) (この著者で検索) - キーワード
- Lung cancer, Breath analysis, Electronic nose (e-nose), Membrane-type Surface stress Sensor (MSS), Machine learning
- 刊行年月日
- 2024-02-25
- 更新時刻
- 2025-02-25 12:30:08 +0900
Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography
- ジャーナル論文
- 著者
-
;Sitanan Sartyoungkul (author) (この著者で検索);Balasubramaniyan Sakthivel (author) (この著者で検索)Pavel Sidorov (author) (この著者で検索)
https://orcid.org/0000-0001-6462-702X
(unauthenticated)
;
Yuuya Nagata (author) (この著者で検索)
https://orcid.org/0000-0001-5926-5845
(unauthenticated)
- キーワード
- Automated synthesis, Fragment descriptor, Machine learning, Retention time prediction, Supercritical fluid chromatography
- 刊行年月日
- 2025-11-26
- 更新時刻
- 2025-12-24 15:05:55 +0900
Autonomous search for materials with high Curie temperature using ab initio calculations and machine learning
- ジャーナル論文
- 著者
-
Yuma Iwasaki (author) (この著者で検索)
- キーワード
- Machine learning, Autonomous, Curie temperature, ab initio
- 刊行年月日
- 2024-12-31
- 更新時刻
- 2024-10-04 08:30:28 +0900
Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis
- ジャーナル論文
- 著者
-
Ryo Tamura (author) (この著者で検索)National Institute for Materials Science
;
;Kenji Nagata (author) (この著者で検索);Keitaro Sodeyama (author) (この著者で検索);Kensaku Nakamura (author) (この著者で検索);Toshiki Tokuhira (author) (この著者で検索);Satoshi Shibata (author) (この著者で検索);Kazuki Hammura (author) (この著者で検索);Hiroki Sugisawa (author) (この著者で検索);Masaya Kawamura (author) (この著者で検索);Teruki Tsurimoto (author) (この著者で検索);Masanobu Naito (author) (この著者で検索)Masahiko Demura (author) (この著者で検索)National Institute for Materials Science
;
Takashi Nakanishi (author) (この著者で検索)National Institute for Materials Science
- キーワード
- Polypropylene, X-ray diffraction, Bayesian spectral deconvolution, Ising machine, Machine learning
- 刊行年月日
- 2024-12-31
- 更新時刻
- 2024-08-30 16:31:01 +0900
A straightforward gradient-based approach for designing superconductors with high critical temperature: exploiting domain knowledge via adaptive constraints
- ジャーナル論文
- 著者
-
;Akihiro Fujii (author) (この著者で検索)Anh Khoa Augustin Lu (author) (この著者で検索)National Institute for Materials Science
;
;Koji Shimizu (author) (この著者で検索)Satoshi Watanabe (author) (この著者で検索)
https://orcid.org/0000-0002-8069-6938
(unauthenticated)
National Institute for Materials Science
- キーワード
- Gradient-based optimization, Superconductor, Domain knowledge integration, Materials discovery, Critical temperature, Machine learning
- 刊行年月日
- 2025-10-29
- 更新時刻
- 2026-05-18 14:53:14 +0900
In Situ Forming Supramolecular Nanofiber Hydrogel as a Biodegradable Liquid Embolic Agent for Postembolization Tissue Remodeling
- ジャーナル論文
- 著者
-
Akihiro Nishiguchi (author) (この著者で検索)National Institute for Materials Science
;
;Miho Ohta (author) (この著者で検索)Debabrata Palai (author) (この著者で検索)National Institute for Materials Science
;
Shima Ito (author) (この著者で検索)National Institute for Materials Science
;
;Kensaku Mori (author) (この著者で検索);Ryotaro Akagi (author) (この著者で検索)Christophe Bajan (author) (この著者で検索)National Institute for Materials Science
;
Guillaume Lambard (author) (この著者で検索)National Institute for Materials Science
;
Keitaro Sodeyama (author) (この著者で検索)National Institute for Materials Science
;
Tetsushi Taguchi (author) (この著者で検索)National Institute for Materials Science
- キーワード
- Hydrogel, Embolic agent, Machine learning
- 刊行年月日
- 2024-11-07
- 更新時刻
- 2025-02-26 16:30:29 +0900
Prediction and optimization of epoxy adhesive strength from a small dataset through active learning
- ジャーナル論文
- 著者
-
Lambard, Guillaume (author) (この著者で検索)
;
Naito, Masanobu (author) (この著者で検索)
;
Samitsu, Sadaki (author) (この著者で検索)
;
Pruksawan, Sirawit (author) (この著者で検索)
https://orcid.org/0000-0002-9380-1872
(unauthenticated)
;
Sodeyama, Keitaro (author) (この著者で検索)
- キーワード
- active learning, Machine learning, adhesive
- 刊行年月日
- 2019-12-31
- 更新時刻
- 2024-01-05 22:11:50 +0900
From Random Networks to AI-Driven Glass Design
- プレゼンテーション
- 著者
-
N. M. Anoop Krishnan (author) (この著者で検索)Indian Institute of Technology Delhi Department of Civil Engineering
- キーワード
- Machine learning, AI-Driven Glass Design
- 刊行年月日
- 更新時刻
- 2025-09-25 16:30:42 +0900
Autonomous closed-loop exploration of composition-spread films for the anomalous Hall effect
- ジャーナル論文
- 著者
-
Ryo Toyama (author) (この著者で検索)
;
Ryo Tamura (author) (この著者で検索)
;
Shoichi Matsuda (author) (この著者で検索)
;
Yuma Iwasaki (author) (この著者で検索)
;
Yuya Sakuraba (author) (この著者で検索)
- キーワード
- Machine learning, Autonomous, Combinatorial, Anomalous Hall effect
- 刊行年月日
- 2025-11-19
- 更新時刻
- 2025-12-25 17:32:06 +0900
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning
- ジャーナル論文
- 著者
-
Ryo Toyama (author) (この著者で検索)
;
Yuma Iwasaki (author) (この著者で検索)
;
Prabhanjan D. Kulkarni (author) (この著者で検索)
;
Hirofumi Suto (author) (この著者で検索)
;
Tomoya Nakatani (author) (この著者で検索)
;
Yuya Sakuraba (author) (この著者で検索)
- キーワード
- Machine learning, High-throughput, Combinatorial, Anomalous Hall effect
- 刊行年月日
- 2025-09-03
- 更新時刻
- 2025-12-26 13:11:05 +0900