Results 71 to 80 of about 389,041 (190)

Kilonova light-curve interpolation with neural networks

Physical Review Research
Kilonovae are the electromagnetic transients created by the radioactive decay of freshly synthesized elements in the environment surrounding a neutron star merger. To study the fundamental physics in these complex environments, kilonova modeling requires,
Yinglei Peng, Marko Ristić, Atul Kedia, Richard O'Shaughnessy, Christopher J. Fontes, Chris L. Fryer, Oleg Korobkin, Matthew R. Mumpower, V. Ashley Villar, Ryan T. Wollaeger   +9 more
doaj   +1 more source

Simulating the neural correlates of stuttering

Neurocase, 2013
For functional neuroimaging studies of stuttering, two challenges are (1) the elicitation of naturally stuttered versus fluent speech and (2) the separation of activation associated with abnormal motor execution from activation that reflects the cognitive substrates of stuttering.
den Ouden, Dirk B., Adams, Charles F., Montgomery, Allen A.   +2 more
openaire   +3 more sources

A U-net based reconstruction of high-fidelity simulation results for flow around a ship hull based on low-fidelity inviscid flow simulation

International Journal of Naval Architecture and Ocean Engineering
In this study, neural networks are trained to transform inviscid simulation data for flow around a ship hull into data representative of viscous flow simulations.
Dayeon Kim, Jeongbeom Seo, Inwon Lee
doaj   +1 more source

DAMNED: A Distributed and Multithreaded Neural Event-Driven simulation framework

, 2006
In a Spiking Neural Networks (SNN), spike emissions are sparsely and irregularly distributed both in time and in the network architecture. Since a current feature of SNNs is a low average activity, efficient implementations of SNNs are usually based on ...
Mouraud, Anthony, Paugam-Moisy, Hélène, Puzenat, Didier   +2 more
core   +2 more sources

Upset Prediction in Friction Welding Using Radial Basis Function Neural Network

Advances in Materials Science and Engineering, 2013
This paper addresses the upset prediction problem of friction welded joints. Based on finite element simulations of inertia friction welding (IFW), a radial basis function (RBF) neural network was developed initially to predict the final upset for a ...
Wei Liu, Feifan Wang, Xiawei Yang, Wenya Li   +3 more
doaj   +1 more source

Extrapolation of Hydrodynamic Pressure in Lubricated Contacts: A Novel Multi-Case Physics-Informed Neural Network Framework

Lubricants
In many technical applications, understanding the behavior of tribological contacts is pivotal for enhancing efficiency and lifetime. Traditional experimental investigations into tribology are often both costly and time-consuming. A more profound insight
Faras Brumand-Poor, Niklas Bauer, Nils Plückhahn, Matteo Thebelt, Silas Woyda, Katharina Schmitz   +5 more
doaj   +1 more source

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

npj Digital Medicine
Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-
Matteo Salvador, Marina Strocchi, Francesco Regazzoni, Christoph M. Augustin, Luca Dede’, Steven A. Niederer, Alfio Quarteroni   +6 more
doaj   +1 more source

Direct Photon Identification with Artificial Neural Network in the Photon Spectrometer PHOS

, 2004
A neural network method is developed to discriminate direct photons from the neutral pion background in the PHOS spectrometer of the ALICE experiment at the LHC collider.
Bogolyubsky, M. Yu., Kharlov, Yu. V., Sadovsky, S. A.   +2 more
core  

An Ultrafast Image Simulation Technique with Spatially Variable Point-spread Functions

The Astronomical Journal
Simulated images are essential in algorithm development and instrument testing for optical telescopes. During real observations, images obtained by optical telescopes are affected by spatially variable point-spread functions (PSFs), a crucial effect ...
Zeyu Bai, Peng Jia, Jiameng Lv, Xiang Zhang, Wennan Xiang, Lin Nie   +5 more
doaj   +1 more source

Interpreting Cosmological Information from Neural Networks in the Hydrodynamic Universe

The Astrophysical Journal
What happens when a black box (neural network) meets a black box (simulation of the Universe)? Recent work has shown that convolutional neural networks (CNNs) can infer cosmological parameters from the matter density field in the presence of complex ...
Arnab Lahiry, Adrian E. Bayer, Francisco Villaescusa-Navarro   +2 more
doaj   +1 more source