Results 211 to 220 of about 4,805,610 (298)

Breaking Extrapolation Barriers: Dual Innovations for Property and Component Design of Multi‐Component Alloy

Materials Genome Engineering Advances, EarlyView.
This study breaks extrapolation barriers in alloy design by merging symbolic regression with latent space sampling. The dual‐strategy framework enables accurate prediction of high‐hardness properties and navigates uncharted compositional spaces. The approach successfully designs novel high‐entropy alloys with hardness exceeding 863.5 HV, demonstrating ...
Zhigang Yu, Boyu Zhao, Jianhua Chen, Jun Luan, Yunying Fan, Xingli Zou, Xionggang Lu   +6 more
wiley   +1 more source

Fast Reconstruction of Motion‐Corrupted Data With Mobile‐GRAPPA: Motion and δB0$$ \delta {B}_0 $$ Inhomogeneity Correction Leveraging Efficient GRAPPA

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop an accurate and computationally efficient motion‐corrected MRI reconstruction framework that incorporates hundreds to thousands of motion and δB0$$ \delta {B}_0 $$ estimates from high‐temporal‐resolution tracking. Methods We propose Mobile‐GRAPPA, a k‐space preprocessing approach that uses MLP‐parameterized local GRAPPA ...
Yimeng Lin, Nan Wang, Daniel Abraham, Daniel Polak, Xiaozhi Cao, Aizada Nurdinova, Stephen Cauley, Kawin Setsompop   +7 more
wiley   +1 more source

Spatially Aware Acquisition‐Independent Deep Learning for IVIM MRI Parameter Estimation in Patients With Esophageal Cancer

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Neural controlled differential equations (NCDEs) recently emerged as a robust deep learning approach for quantitative MRI parameter estimation. NCDEs offer flexibility to changes in acquisition protocols by modeling the signal evolution dynamics. However, NCDE implementations operate on a voxel‐by‐voxel basis and cannot exploit spatial
Daan Kuppens, Roman S. Oort, Sebastiano Barbieri, Stella Mook, Gert J. Meijer, Oliver J. Gurney‐Champion   +5 more
wiley   +1 more source

Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch

Naval Research Logistics (NRL), EarlyView.
ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley   +1 more source

Diagnosis of Portal Hypertension: Advancing Towards Non‐Invasive Solutions

Portal Hypertension &Cirrhosis, EarlyView.
This review systematically summarizes a full spectrum of non‐invasive diagnostic approaches for portal hypertension (PH), including imaging modalities, elastography, serum biomarkers, composite scoring systems and endoscopic ultrasound‐guided portal pressure gradient (EUS‐PPG), and analyzes their performance across different liver disease etiologies ...
Lijia Yin, Huikuan Chu, Ling Yang
wiley   +1 more source

Application of a Multi-Layer Perceptron and Markov Chain Analysis-Based Hybrid Approach for Predicting and Monitoring LULCC Patterns Using Random Forest Classification in Jhelum District, Punjab, Pakistan. [PDF]

Sensors (Basel)
Aftab B, Wang Z, Wang S, Feng Z.
europepmc   +1 more source

Object‐based deep learning for probabilistic convective‐core nowcasting from satellite data

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Convective cores detected from Meteosat infrared imagery are represented as compact physical objects to generate probabilistic nowcasts up to 6 h ahead. A spatio‐temporal transformer models interactions among evolving core populations and produces gridded probability forecasts across the western Sahel.
Mendrika Rakotomanga, Douglas J. Parker, Nadhir Ben Rached, Seonaid R. Anderson, Cornelia Klein, Steven C. Wells   +5 more
wiley   +1 more source

Weibull Variational Autoencoder for Remaining Useful Life Prediction

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Remaining useful life (RUL) prediction is a critical technology for preventing unexpected failures and reducing maintenance costs in modern industrial systems. However, traditional model‐based approaches are limited by the need for explicit mathematical modeling of degradation mechanisms, while data‐driven methods often require large‐scale ...
JunWoo Yu, Yoojin Jang, Kwanghui Shin, Jinsoo Jeong, Yong Soo Kim   +4 more
wiley   +1 more source

An automated multi-layer perceptron discriminative neural network based on Bayesian optimization achieves high-precision one-source single-snapshot direction-of-arrival estimation. [PDF]

Sci Rep
Zhang B, He J, Liu P, Wang L, Tang R.
europepmc   +1 more source

Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks. [PDF]

Bioengineering (Basel), 2018
Savalia S, Emamian V.
europepmc   +1 more source