Results 51 to 60 of about 8,116 (238)
Advanced Intelligent Discovery, EarlyView.This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
On the Question at the End of Theodicy
Religions, 2017 This article argues that theodicy provides an insufficient response to suffering - one that often further victimizes those who suffering most. In it’s place, I argue for a moralist response based on Albert Camus and W. E. B. Du Bois.
Anthony B. Pinn
doaj +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
PINN-Based Method for Predicting Flow Field Distribution of the Tight Reservoir after Fracturing
Geofluids, 2022 The physical-informed neural network (PINN) model can greatly improve the ability to fit nonlinear data with the incorporation of prior knowledge, which endows traditional neural networks with interpretability.
Jun Pu +5 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
Comparison of sleep and chronotype between senior and undergraduate university students
, 2020 This study was supported by a project of the Oviedo University (PINN-15-A-019)
Núñez Martínez, Paula +3 more
core +1 more source
Advanced Intelligent Systems, EarlyView.A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang +4 more
wiley +1 more source
Physics-Informed Neural Network for Unreacted-Core Shrinking Model of Coal Gasification
Chemical Engineering Transactions, 2021 Physics-informed neural network (PINN) has achieved success in many science and engineering disciplines by encoding physical laws into the loss functions of the neural network.
Ming Jian Li +4 more
doaj +1 more source
B-PL-PINN: Stabilizing PINN Training with Bayesian Pseudo Labeling
2025 International Joint Conference on Neural Networks (IJCNN)Training physics-informed neural networks (PINNs) for forward problems often suffers from severe convergence issues, hindering the propagation of information from regions where the desired solution is well-defined. Haitsiukevich and Ilin (2023) proposed an ensemble approach that extends the active training domain of each PINN based on i) ensemble ...
Rohrhofer, Franz Martin +2 more
openaire +4 more sources
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
Advanced Intelligent Systems, EarlyView.This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source