Results 191 to 200 of about 9,482,218 (334)

Transferable Hot‐Deformation Flow‐Curve Modeling Across Steels Through Transfer Learning

Materials Genome Engineering Advances, EarlyView.
We propose a transferable sequence model that moves steel hot‐deformation ML beyond the “one‐case, one‐model” paradigm. Pretrained across compositions/windows and personalized with four extreme‐condition curves, it improves accuracy and robustness in 10‐fold evaluation.
Changqing Shu, Zhengjun Yao, Shuyan Wang, Xiaolin Zhu, Siyi Sheng, Guojin Xiang, Jicong Zhang, Qiuhao Gu, Liukai Hua, Shasha Zhang   +9 more
wiley   +1 more source

Numerical modeling of 2D sutterby fluid stagnation-point flow over a stretching surface using levenberg-marquardt backpropagation. [PDF]

Discov Nano
Areshi M, Bariq A, Alamrani FM, Raizah Z, Al-Essa LA, Saeed A.   +5 more
europepmc   +1 more source

ChatXRD: A LLM‐Driven Framework for Crystal System Classification and Lattice Parameters Prediction Based on XRD

Materials Genome Engineering Advances, EarlyView.
ChatXRD is an LLM‐driven framework that autonomously performs crystal system classification and lattice parameter prediction from XRD data. By integrating a GPT‐5‐based agent with specialized tools and decision tree reasoning, it achieves state‐of‐the‐art accuracy, enabling scalable and reliable high‐throughput materials characterization. ABSTRACT High‐
Xiaoyue He, Qian Cao, Bo Chen, Kun Hu, Yin Xu, Mingjun Xiao, Xin Chen   +6 more
wiley   +1 more source

The inherent capacity of neurons to learn order relations and support abstract reasoning. [PDF]

Nat Commun
Yang Y, Maass W.
europepmc   +1 more source

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

Diagnostic performance of artificial intelligence in fracture detection with ultrasound: A systematic review and meta-analysis. [PDF]

Ultrasound J
Xie M, Kim JJ, Im JH, Dennett L, Hareendranathan A, Jaremko JL.   +5 more
europepmc   +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

Machine learning-based fetal health prediction and development of smart web application. [PDF]

Front Artif Intell
Puri C, Reddy KTV, Gote PM.
europepmc   +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

DrugPred: an EdgeConv-GNN and Bio_ClinicalBERT based polypharmacy ADR prediction and specialist recommendation model. [PDF]

Front Artif Intell
Arjay JG, Pushan KA, Roshanthraj N, Subburaj B, Alphonse S, Subramanian G.   +5 more
europepmc   +1 more source