Results 201 to 210 of about 13,423,347 (294)

Potential cognitive and neural benefits of a computerised cognitive training programme based on Structure Learning in healthy adults: study protocol for a randomised controlled trial. [PDF]

Trials, 2023
Liu CL, Cheng X, Choo BL, Hong M, Teo JL, Koo WL, Tan JYJ, Ubrani MB, Suckling J, Gulyás B, Leong V, Kourtzi Z, Sahakian B, Robbins T, Chen AS.   +14 more
europepmc   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

Assessing Credibility in Bayesian Networks Structure Learning. [PDF]

Entropy (Basel)
Barth V, Serrão F, Maciel C.
europepmc   +1 more source

Simultaneous cluster structure learning and estimation of heterogeneous graphs for matrix-variate fMRI data. [PDF]

Biometrics, 2023
Liu D, Zhao C, He Y, Liu L, Guo Y, Zhang X.   +5 more
europepmc   +1 more source

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

Advanced Engineering Materials, EarlyView.
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

Frontiers in Systems Biology
Francesco Canonaco, Francesco Canonaco, Joverlyn Gaudillo, Nicole Astrologo, Fabio Stella, Enzo Acerbi   +5 more
doaj   +1 more source

Contribution of Structure Learning Algorithms in Social Epidemiology: Application to Real-World Data. [PDF]

Int J Environ Res Public Health
Colineaux H, Lepage B, Chauvin P, Dimeglio C, Delpierre C, Lefèvre T.   +5 more
europepmc   +1 more source

Treatment of missing data in Bayesian network structure learning: an application to linked biomedical and social survey data. [PDF]

BMC Med Res Methodol, 2022
Ke X, Keenan K, Smith VA.
europepmc   +1 more source

A Simplified Laminar Flow Model for the Pultrusion of Glass Fiber/Polyethylene Terephthalate Commingled Yarns

Advanced Engineering Materials, EarlyView.
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares, Nadège Bouchonneau, Christian Jochum, Donald Radford   +3 more
wiley   +1 more source

Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing. [PDF]

PLoS One
Shou Z, Li Y, Li D, Mo J, Zhang H.
europepmc   +1 more source