Results 221 to 230 of about 18,341 (302)

Training of physics-informed neural networks: a multi-criterion viewpoint

International audiencePartial differential equations (PDEs) are usually solved by numerical methods requiring specific grids and discretisation schemes.
Duvigneau, Régis, Ricard, Nathan, Binois, Mickael   +2 more
core  

Physics-informed neural networks for predicting the surface temperature of carbon fiber reinforced polymers under laser irradiation. [PDF]

Sci Rep
Gao S, Wang J, Yang D, Zhang J, Wu L, Yang P, Wang P.   +6 more
europepmc   +1 more source

Machine Learning Enables Inverse Design of Optically Driven Microscopic Metavehicles

Advanced Optical Materials, EarlyView.
Machine‐learning‐based inverse design is used optimize “metavehicles” — flat microparticles based on metagratings that generate a strong lateral optical force from normally incident light. The optimized design exhibits a force efficiency of ∼88% and a measured propulsion speed in water much higher than previously reported, demonstrating that inverse ...
Vasilii Mylnikov, Mahdi Shanei, Mikael Käll   +2 more
wiley   +1 more source

Short-Dipole Sensor Response Linearization Through Physics-Informed Neural Networks. [PDF]

Bioelectromagnetics
Fasse A, Meyer R, Neufeld E, Haas M, Chavannes N, Kuster N.   +5 more
europepmc   +1 more source

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source

Unsupervised spectra information extraction using physics-informed neural networks in the presence of non-linearities and multi-agent problems. [PDF]

Sci Rep
Puleio A, Gaudio P.
europepmc   +1 more source

Remote Control of Hand Actuators via Glove Sensors for Medical Care Applications

Advanced Robotics Research, EarlyView.
This study presents a novel textile‐based sensory glove–actuator system for remote medical care, explored through finite element simulations. By integrating capacitive sensors, pneumatic actuators, and machine learning, the system models real‐time hand movement control.
Bahman Taherkhani, Mahdi Bodaghi
wiley   +1 more source

Trainable embedding quantum physics informed neural networks for solving nonlinear PDEs. [PDF]

Sci Rep
Berger S, Hosters N, Möller M.
europepmc   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

A noninvasive method for determining elastic parameters of valve tissue using physics-informed neural networks. [PDF]

Acta Biomater
Wu W, Daneker M, Herz C, Dewey H, Weiss JA, Pouch AM, Lu L, Jolley MA.   +7 more
europepmc   +1 more source