Results 111 to 120 of about 12,930,500 (303)
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
National Intelligence Daily 13 July 1983 [PDF]
Declassified on 2017-11 ...
United States. Central Intelligence Agency.
core
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Coordination Techniques for Distributed Artificial Intelligence
Coordination, the process by which an agent reasons about its local actions and the (anticipated) actions of others to try and ensure the community acts in a coherent manner, is perhaps the key problem of the discipline of Distributed Artificial ...
Jennings, N. R., Jennings, NR
core
The PRIMA Thesaurus for Materials Science and Engineering
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa +8 more
wiley +1 more source
National Intelligence Daily 25 July 1983 [PDF]
Declassified on 2017-11 ...
United States. Central Intelligence Agency.
core
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
National Intelligence Daily (Cable) 11 March 1982 [PDF]
Declassified on 2017-11 ...
United States. Central Intelligence Agency.
core
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
National Intelligence Daily 2 March 1981
Declassified on 2017-11 ...
United States. Central Intelligence Agency.
core

