Results 71 to 80 of about 11,667,970 (301)
Bearing fault diagnosis by stochastic resonance method in periodical potential system
In industrial production, bearings are widely used in rotating machinery. Bearing fault diagnosis plays an important role in preventing disasters and protecting lives and properties.
ZHANG Jing-ling +4 more
doaj +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Parallel implementation of stochastic simulation for large-scale cellular processes [PDF]
Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional ...
Kevin Burrage +6 more
core +1 more source
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
The present research work introduces a novel computational approach to the study of a nonlinear stochastic epidemic model for skin sores and also a deterministic model.
Ali Raza +5 more
doaj +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
A class of stochastic Gronwall’s inequality and its application
This paper puts forward the basic form of stochastic Gronwall’s inequality and uses, respectively, the iterative method, the integral method and the martingale representation method to prove it.
Xin Wang, Shengjun Fan
doaj +1 more source
This study presents a novel stochastic precision analysis method for hypersonic flight vehicle (HFV) attitude control system in the presence of uncertainties, including parameter perturbation and external disturbance.
Ruimin Jiang, Jun Zhou, Jianguo Guo
doaj +1 more source

