Results 211 to 220 of about 13,423,347 (294)

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

DAGAF: A directed acyclic generative adversarial framework for joint structure learning and tabular data synthesis. [PDF]

Appl Intell (Dordr)
Petkov H, MacLellan C, Dong F.
europepmc   +1 more source

Mining human preference via self-correction causal structure learning. [PDF]

Sci Rep, 2022
Sun J, Wu C, Peng W, Huang J, Han C, Zhu Y, Lyu Y.   +6 more
europepmc   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
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, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

DAGSLAM: causal Bayesian network structure learning of mixed type data and its application in identifying disease risk factors. [PDF]

BMC Med Res Methodol
Zhao Y, Jia J.
europepmc   +1 more source

Dynamic Programming BN Structure Learning Algorithm Integrating Double Constraints under Small Sample Condition. [PDF]

Entropy (Basel), 2022
Lv Z, Chen Y, Di R, Wang H, Sun X, He C, Li X.   +6 more
europepmc   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

M³ASD: Integrating Multi-Atlas and Multi-Center Data via Multi-View Low-Rank Graph Structure Learning for Autism Spectrum Disorder Diagnosis. [PDF]

Brain Sci
Yang S, Yin Z, Ma Y, Wang M, Huang S, Zhang L.   +5 more
europepmc   +1 more source

Complementary Structure-Learning Neural Networks for Relational Reasoning. [PDF]

Cogsci, 2021
Russin J, Zolfaghar M, Park SA, Boorman E, O'Reilly RC.   +4 more
europepmc   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
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, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source