Results 21 to 30 of about 21,388 (184)

Spatial‐Wavelength Multiplexing Error‐Controlled Photonic Analog Computing System

open access: yesAdvanced Science, EarlyView.
A novel photonic integrated circuit prototype implementing the concept of general‐purpose analog computing and demonstrate its capability in radio frequency applications. The chip features a multichannel architecture and performs fully optical analog computation with frequency‐domain parallel processing. An FPGA‐based error‐correction algorithm aims to
Tao Zhu   +15 more
wiley   +1 more source

The Variational Bi-Complex for Systems of Semi-Linear Hyperbolic PDEs in Three Variables

open access: yes, 2018
This paper extends, to a class of systems of semi-linear hyperbolic second order PDEs in three variables, the geometric study of a single nonlinear hyperbolic PDE in the plane as presented in [Anderson I.M., Kamran N., Duke Math. J.
Froehlich, Sara
core   +1 more source

Physical Implementation of Optical Material‐Based Neural Networks Processing Enabled by Long‐Persistent Luminescence

open access: yesAdvanced Science, EarlyView.
This study reports on the physical implementation of optical material‐based neural processing using long‐persistent luminescence as memory‐retention and nonlinear optical material. The system performs optical‐domain preprocessing with opto‐electronic interfaces for stimulus delivery and readout, enabling real‐time demonstrations including Pong gameplay
Sangwon Wi, Yunsang Lee
wiley   +1 more source

Nonlinear elliptic equations with high order singularities [PDF]

open access: yes, 2016
We study non-variational degenerate elliptic equations with high order singular structures. No boundary data are imposed and singularities occur along an {\it a priori} unknown interior region. We prove that positive solutions have a universal modulus of
Teixeira, Eduardo V.
core  

Capacitive versus Faradaic Microelectrodes for Extracellular Stimulation: A Fully Coupled FEM–Hodgkin–Huxley Study of Thresholds and Current Redistribution

open access: yesAdvanced Electronic Materials, EarlyView.
A fully coupled FEM–HH model shows that ideally capacitive microelectrodes can achieve lower charge‐density thresholds than Faradaic contacts under current‐controlled stimulation. The advantage stems from the dynamics of surface current density on capacitive interfaces, which redirects current beneath adherent neurons.
Aleksandar Opančar   +2 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

open access: yesAdvanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee   +3 more
wiley   +1 more source

Wavelet Galerkin method for fractional elliptic differential equations [PDF]

open access: yes, 2014
Under the guidance of the general theory developed for classical partial differential equations (PDEs), we investigate the Riesz bases of wavelets in the spaces where fractional PDEs usually work, and their applications in numerically solving fractional ...
Deng, Weihua   +2 more
core  

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

open access: yesAdvanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang   +4 more
wiley   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

open access: yesAdvanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez   +4 more
wiley   +1 more source

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