Results 181 to 190 of about 10,239,244 (295)

Solid Harmonic Wavelet Bispectrum for Image Analysis

open access: yesAdvanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown   +3 more
wiley   +1 more source

Photonic Time Crystals and Time‐Varying Electromagnetic Metamatter: A New Direction for Ultrafast Tunable Photonic and Microwave Materials and Devices

open access: yesAdvanced Science, EarlyView.
Photonic time crystals (PTCs) are systems in which electromagnetic parameters are modulated periodically in time, producing momentum bandgaps via temporal scattering rather than spatial Bragg processes. This review examines the theoretical frameworks, modeling, and computational tools for time‐varying media, and summarizes experimental demonstrations ...
Ranjan Kumar Patel   +3 more
wiley   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

open access: yesAdvanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju   +5 more
wiley   +1 more source

Computational Oncology of Chemotaxis-Driven Tumour-Immune Spatial Patterning and Stability. [PDF]

open access: yesBioengineering (Basel)
Liu Z   +6 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Chaos Detection in Noisy Signals Using Refined Signal Representations. [PDF]

open access: yesSensors (Basel)
Harężlak K   +5 more
europepmc   +1 more source

Home - About - Disclaimer - Privacy