Results 51 to 60 of about 98,858 (265)
The Arsenal of Perturbation Bounds for Finite Continuous-Time Markov Chains: A Perspective
MathematicsPerturbation bounds are powerful tools for investigating the phenomenon of insensitivity to perturbations, also referred to as stability, for stochastic and deterministic systems.
Alexander Y. Mitrophanov
doaj +1 more source
Computational study of permeability in cardboard coating layers
AIChE Journal, EarlyView.Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman +6 more
wiley +1 more source
Thermodynamic bounds and symmetries in first-passage problems of fluctuating currents
New Journal of PhysicsWe develop a method for deriving thermodynamic bounds for first-passage problems of currents with two boundaries in Markov chains. Using this method, we derive a thermodynamic bound on the rate of dissipation in terms of the splitting probability and the
Adarsh Raghu, Izaak Neri
doaj +1 more source
Availability Model for Virtualized Platforms
Advances in Electrical and Electronic Engineering, 2013 Network virtualization is a method of providing virtual instances of physical networks. Virtualized networks are widely used with virtualized servers, forming a powerful dynamically reconfigurable platform.
Jiri Hlavacek, Robert Bestak
doaj +1 more source
Mathematics, 2023 We consider the computing issues of the steady probabilities for block-structured discrete-time Markov chains that are of upper-Hessenberg or lower-Hessenberg transition kernels with a continuous phase set.
Shuxia Jiang, Nian Liu, Yuanyuan Liu
doaj +1 more source
Discrete-time thermodynamic uncertainty relation
, 2017 We generalize the thermodynamic uncertainty relation, providing an entropic upper bound for average fluxes in time-continuous steady-state systems (Gingrich et al., Phys. Rev. Lett. 116, 120601 (2016)), to time-discrete Markov chains and to systems under
Broeck, Christian Van den +1 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Applying Mean-field Approximation to Continuous Time Markov Chains [PDF]
, 2013 The mean-field analysis technique is used to perform analysis of a systems with a large number of components to determine the emergent deterministic behaviour and how this behaviour modifies when its parameters are perturbed.
Kolesnichenko, Anna +2 more
core
Advanced Intelligent Systems, EarlyView.Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source