Results 41 to 50 of about 68,163 (244)

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

open access: yesAdvanced 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

Hypercube Bivariate-Based Key Management for Wireless Sensor Networks [PDF]

open access: yesJournal of Sciences, Islamic Republic of Iran, 2017
Wireless sensor networks are composed of very small devices, called sensor nodes,for numerous applications in the environment. In adversarial environments, the securitybecomes a crucial issue in wireless sensor networks (WSNs).
I. Qasemzadeh Kolagar   +2 more
doaj  

Matchings Extend to Hamiltonian Cycles in 5-Cube

open access: yesDiscussiones Mathematicae Graph Theory, 2018
Ruskey and Savage asked the following question: Does every matching in a hypercube Qn for n ≥ 2 extend to a Hamiltonian cycle of Qn? Fink confirmed that every perfect matching can be extended to a Hamiltonian cycle of Qn, thus solved Kreweras’ conjecture.
Wang Fan, Zhao Weisheng
doaj   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Characterizing which Powers of Hypercubes and Folded Hyper- cubes Are Divisor Graphs

open access: yesDiscussiones Mathematicae Graph Theory, 2015
In this paper, we show that Qkn is a divisor graph, for n = 2, 3. For n ≥ 4, we show that Qkn is a divisor graph iff k ≥ n − 1. For folded-hypercube, we get FQn is a divisor graph when n is odd.
AbuHijleh Eman A.   +2 more
doaj   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan   +3 more
wiley   +1 more source

Distance Magic Cartesian Products of Graphs

open access: yesDiscussiones Mathematicae Graph Theory, 2016
A distance magic labeling of a graph G = (V,E) with |V | = n is a bijection ℓ : V → {1, . . . , n} such that the weight of every vertex v, computed as the sum of the labels on the vertices in the open neighborhood of v, is a constant.
Cichacz Sylwia   +3 more
doaj   +1 more source

The Capture Time of the Hypercube [PDF]

open access: yesThe Electronic Journal of Combinatorics, 2013
In the game of Cops and Robbers, the capture time of a graph is the minimum number of moves needed by the cops to capture the robber, assuming optimal play. We prove that the capture time of the $n$-dimensional hypercube is $\Theta (n\ln n)$. Our methods include a novel randomized strategy for the players, which involves the analysis of the coupon ...
Anthony Bonato   +3 more
openaire   +3 more sources

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

open access: yesAdvanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang   +4 more
wiley   +1 more source

The Path-Distance-Width of Hypercubes

open access: yesDiscussiones Mathematicae Graph Theory, 2013
The path-distance-width of a connected graph G is the minimum integer w satisfying that there is a nonempty subset of S ⊆ V (G) such that the number of the vertices with distance i from S is at most w for any nonnegative integer i.
Otachi Yota
doaj   +1 more source

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