Results 91 to 100 of about 68,163 (244)

Hypercube technology [PDF]

open access: yes
The JPL designed MARKIII hypercube supercomputer has been in application service since June 1988 and has had successful application to a broad problem set including electromagnetic scattering, discrete event simulation, plasma transport, matrix ...
Cwik, Tom   +4 more
core   +1 more source

Hunting rabbits on the hypercube

open access: yesDiscrete Mathematics, 2019
We explore the Hunters and Rabbits game on the hypercube. In the process, we find the solution for all classes of graphs with an isoperimetric nesting property and find the exact hunter number of $Q^n$ to be $1+\sum\limits_{i=0}^{n-2} \binom{i}{\lfloor i/2 \rfloor}$.
Jessalyn Bolkema, Corbin Groothuis
openaire   +2 more sources

Structural Optimization of 3D Braided Tungsten–Copper Composites via Active Learning and Finite Element Simulation

open access: yesMaterials Genome Engineering Advances, EarlyView.
An uncertainty‐aware FEM–GPR active learning framework efficiently explores the design space of 3D braided W–Cu composites, identifying architectures with higher yield strength and preserved electrical conductivity, whereas SHAP interpretation highlights yarn spacing in the braid plane as the key structural factor controlling composite performance ...
Lai Zhang   +6 more
wiley   +1 more source

On r-factors with components containing specified vertices in a torus

open access: yesAKCE International Journal of Graphs and Combinatorics
Let T be a graph obtained by taking the Cartesian product of n cycles of even lengths [Formula: see text]. It is known that for any subset of k vertices of T with [Formula: see text] there exists a 2-factor in T where each cycle contains exactly one of ...
A. V. Sonawane, Y. M. Borse
doaj   +1 more source

On Recursively Directed Hypercubes [PDF]

open access: yesThe Electronic Journal of Combinatorics, 2001
In this paper we introduce the recursively directed hypercubes, and analyze some of their structural properties. We show that every recursively directed hypercube is acyclic, and has a unique pair of source and sink nodes. The main contribution of the paper is an analysis of distances between the nodes in such a graph.
openaire   +2 more sources

Uncertainty, Sensitivity, and Efficiency Analysis of a Hybrid Piezoelectric–Electromagnetic Energy Harvester

open access: yesInternational Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Digitalization and emerging technologies are increasing the demand for wireless sensing and the Internet of Things (IoT), which provide opportunities for autonomous sources of electricity in the form of energy harvesting systems. This paper focuses on the challenges in hybrid piezoelectric‐electromagnetic kinetic energy harvesting systems that
Petr Sosna, Damian Gaska, Zdeněk Hadaš
wiley   +1 more source

Conditional Diagnosability of Exchanged Hypercube Under the MM* Model

open access: yesIEEE Access, 2018
Exchanged hypercube EH(s, t) is a typical hypercube variant, which is built up by systematically removing a range of edges from hypercube Qs±t±1.
Chen Guo   +3 more
doaj   +1 more source

Optimal Gain Selection for the Arbitrary‐Order Homogeneous Differentiator

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Differentiation of noisy signals is a relevant and challenging task. Widespread approaches are the linear high‐gain observer acting as a differentiator and Levant's robust exact differentiator with a discontinuous right‐hand side. We consider the family of arbitrary‐order homogeneous differentiators, which includes these special cases.
Benjamin Calmbach   +2 more
wiley   +1 more source

Dynamical simulations of QCD at finite temperature with a truncated perfect action

open access: yes, 2006
The Hypercube operator determines a variant of the approximate, truncated perfect fermion action. In this pilot study we are going to report on first experiences in dynamical QCD simulations with the Hypercube fermions.
Laermann, Edwin, Shcheredin, Stanislav
core  

Micro‐Mechanism Informed Neural Networks for Process‐Property Prediction in Laser Powder Bed Fusion

open access: yesArtificial Intelligence for Engineering, EarlyView.
Hard physics embedding, where neural networks learn residuals relative to analytical baselines, substantially outperforms soft loss‐function constraints for extrapolation in LPBF process–property prediction. Physics integration architecture determines generalization capability more than constraint quantity.
Yo‐Lun Yang
wiley   +1 more source

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