Results 151 to 160 of about 1,761,761 (285)
Convpaint-Interactive pixel classification using pretrained neural networks. [PDF]
Hinderling L +9 more
europepmc +1 more source
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
StabLyzeGraph: High-throughput screening of combinatorial mutations using graph neural networks. [PDF]
Waqas M +5 more
europepmc +1 more source
Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
Extending the range of graph neural networks with global encodings. [PDF]
Caruso A +6 more
europepmc +1 more source
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
wiley +1 more source
Mele's Digital Zygote: Developer Responsibility for Neural Networks. [PDF]
Søgaard A, Stamatiou F.
europepmc +1 more source
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Artificial Neural Networks for Discrimination of Automotive Clear Coats by Vehicle Manufacturer. [PDF]
Lavine BK, White CG, Heisterkamp DR.
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source

