Results 191 to 200 of about 4,639 (261)

Advanced Signal Processing Methods for Partial Discharge Analysis: A Review. [PDF]

Sensors (Basel)
Wen H, Abu Talip MS, Othman M, Azam SMK, Mohamad M, Ibrahim MF, Arof H, Ababneh A.   +7 more
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Woa-wtconv-kanformer for long term time series forecasting. [PDF]

PLoS One
Ling Ming M, Wei Min Q, Yi Fan D, Yu Ning Z.   +3 more
europepmc   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

Multiscale analysis of heart sound signals in the wavelet domain for heart murmur detection. [PDF]

Sci Rep
Vimalajeewa D, Lee C, Vidakovic B.
europepmc   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

Capturing temporal heterogeneity of communities: A temporal β-diversity based on Hill numbers and time series analysis. [PDF]

PLoS One
Sánchez-Ochoa DJ, González EJ, Arizmendi MDC, Koleff P, Martell-Dubois R, Meave JA, Pérez-Mendoza HA.   +6 more
europepmc   +1 more source

Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry

Advanced Intelligent Discovery, EarlyView.
Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa, Erving Ximendes, Luís D. Carlos, Carlos D. S. Brites   +3 more
wiley   +1 more source

HyFusion-X: hybrid deep and traditional feature fusion with ensemble classifiers for breast cancer detection using mammogram and ultrasound images. [PDF]

Sci Rep
Shaukat A, Farhan S, Javed R, Idris S, Alamri FS, Ara A, Saba T.   +6 more
europepmc   +1 more source

Breast cancer histopathological image classification based on collaborative multi-domain feature learning. [PDF]

PLoS One
He L, Hu H, Cheng R.
europepmc   +1 more source