キーワード: machine learning
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36 件のレコードが見つかりました。

Manuscript.pdf
Graph Network-Based Simulation of Multicellular Dynamics Driven by Concentrated Polymer Brush-Modified Cellulose Nanofibers
ジャーナル論文
著者
Chiaki Yoshikawa (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Duc Anh Nguyen (author) (この著者で検索)
;
Tadashi Nakaji-Hirabayashi (author) (この著者で検索)
;
Ichigaku Takigawa (author) (この著者で検索)
;
Hiroshi Mamitsuka (author) (この著者で検索)
キーワード
cellulose nanofiber, concentrated polymer brush, hMSC, self-assembly, machine learning
刊行年月日
2024-04-08
更新時刻
2024-08-27 08:30:31 +0900
Estimation the S-N Curve by Machine Learning Random Forest Method_Mater. Trans. 65(2024)428-433.pdf
Estimating the S-N Curve by Machine Learning Random Forest Method
ジャーナル論文
著者
Nobuo Nagashima (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Masao Hayakawa (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Hiroyuki Masuda (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Kotobu Nagai (author) (この著者で検索)
National Institute for Materials Science
キーワード
fatigue, high-cycle fatigue, data-sheet, machine learning, random forest method
刊行年月日
2024-04-01
更新時刻
2024-12-27 16:30:58 +0900
Development of an AI-based acoustic disturbance-detection method for robotic arc welding processes.pdf
Development of an AI-based acoustic disturbance-detection method for robotic arc welding processes
ジャーナル論文
著者
Houichi Kitano (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Masaki Kobayashi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Masahiko Demura (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
Acoustic sensing, in-process monitoring, gas metal arc welding, disturbance detection, machine learning, explainable AI, smart manufacturing
刊行年月日
2026-12-31
更新時刻
2026-06-25 09:51:40 +0900
main.pdf
Automatic Identification and Normalisation of Physical Measurements in Scientific Literature
ジャーナル論文
著者
ORCID ;
ROMARY, Laurent (author) (この著者で検索)
ORCID ; ORCID SAMURAI ; ORCID
キーワード
tdm, physical quantities, machine learning
刊行年月日
2019-09-23
更新時刻
2022-10-03 02:00:14 +0900
Abstract_YenJu Wu.docx
Designing Thermal Insulating thin films with Data-Driven Innovation
プレゼンテーション
著者
Yen-Ju Wu (author) (この著者で検索)
National Institute for Materials Science Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Inorganic Materials Group
ORCID SAMURAI ;
Yibin Xu (author) (この著者で検索)
National Institute for Materials Science Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Inorganic Materials Group
ORCID SAMURAI
キーワード
Interfacial thermal resistance, machine learning, thermal insulator, thin film
刊行年月日
更新時刻
2025-03-12 16:30:31 +0900
nanomaterials-3261714-Revision_T.pdf
Machine Learning as a “Catalyst” for Advancements in Carbon Nanotube Research
ジャーナル論文
著者
Guohai Chen (author) (この著者で検索)
ORCID ; ORCID SAMURAI
キーワード
machine learning, carbon nanotube, in situ TEM, growth mechanism
刊行年月日
2024-10-22
更新時刻
2024-12-24 13:58:23 +0900
2025 ogawa APL final.pdf
Er-driven magnetic tunability in FePt thin films investigated via high-throughput experiments and microstructure analysis for future HAMR media
ジャーナル論文
著者
Daisuke Ogawa (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yuma Iwasaki (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Jun Uzuhashi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Yuta Sasaki (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI ;
Masato Kotsugi (author) (この著者で検索)
;
Yukiko K. Takahashi (author) (この著者で検索)
National Institute for Materials Science
ORCID SAMURAI
キーワード
heat-assisted magnetic recording, FePt, combinatorial, high throughput, machine learning, rare-earth doping
刊行年月日
2025-06-23
更新時刻
2025-07-11 08:30:48 +0900
Dataset
Supercon 2 Dataset
データセット
著者
ORCID
キーワード
superconductors, machine learning, dataset, tdm, materials science
刊行年月日
2022-09-10
更新時刻
2022-10-18 10:11:01 +0900
materials-17-02866.pdf
Multi-Objective Optimization of Adhesive Joint Strength and Elastic Modulus of Adhesive Epoxy with Active Learning
ジャーナル論文
著者
ORCID SAMURAI ; ORCID SAMURAI ;
Chao Kang (author) (この著者で検索)
ORCID ;
Chiaki Sato (author) (この著者で検索)
キーワード
experimental testing, multi-objective optimization, epoxy, adhesive, elastic modulus, machine learning, active learning
刊行年月日
2024-06-12
更新時刻
2025-01-07 08:30:26 +0900
74_Roadmap_J Phys Energy 2023_Roadmap on molecular modelling of electrochemical energy materials.pdf
2023 Roadmap on molecular modelling of electrochemical energy materials
ジャーナル論文
著者
Chao Zhang (author) (この著者で検索)
;
Jun Cheng (author) (この著者で検索)
;
Yiming Chen (author) (この著者で検索)
;
Maria K Y Chan (author) (この著者で検索)
;
Qiong Cai (author) (この著者で検索)
;
Rodrigo P Carvalho (author) (この著者で検索)
;
Cleber F N Marchiori (author) (この著者で検索)
;
Daniel Brandell (author) (この著者で検索)
;
C Moyses Araujo (author) (この著者で検索)
;
Ming Chen (author) (この著者で検索)
;
Xiangyu Ji (author) (この著者で検索)
;
Guang Feng (author) (この著者で検索)
;
Kateryna Goloviznina (author) (この著者で検索)
;
Alessandra Serva (author) (この著者で検索)
;
Mathieu Salanne (author) (この著者で検索)
;
Toshihiko Mandai (author) (この著者で検索)
National Institute for Materials Science (NIMS)
ORCID SAMURAI ;
Tomooki Hosaka (author) (この著者で検索)
;
Mirna Alhanash (author) (この著者で検索)
;
Patrik Johansson (author) (この著者で検索)
;
Yun-Ze Qiu (author) (この著者で検索)
;
Hai Xiao (author) (この著者で検索)
;
Michael Eikerling (author) (この著者で検索)
;
Ryosuke Jinnouchi (author) (この著者で検索)
;
Marko M Melander (author) (この著者で検索)
;
Georg Kastlunger (author) (この著者で検索)
;
Assil Bouzid (author) (この著者で検索)
;
Alfredo Pasquarello (author) (この著者で検索)
;
Seung-Jae Shin (author) (この著者で検索)
;
Minho M Kim (author) (この著者で検索)
;
Hyungjun Kim (author) (この著者で検索)
;
Kathleen Schwarz (author) (この著者で検索)
;
Ravishankar Sundararaman (author) (この著者で検索)
キーワード
electrochemical interfaces, density-functional theory, molecular dynamics simulation, electrochemical energy storage, machine learning, electrocatalysis
刊行年月日
2023-10-01
更新時刻
2024-03-22 00:53:39 +0900