Results 151 to 160 of about 189,405 (333)
Simple Algebras Over Rational Function Fields [PDF]
, 1979 Tuula A. Nyman, G. Whaples
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Energy Science &Engineering, EarlyView.ABSTRACT The turbulent flow between coaxial cylinders, particularly when the inner cylinder is rotating, exhibits complex hydrodynamic and heat transfer behaviors critical for various engineering applications. Although many previous studies have simplified these systems with idealized assumptions, real‐world scenarios involve mixed convection and ...
Tohid Adibi +5 more
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Matrix Commutators Over an Algebraically Closed Field [PDF]
, 1975 P. M. Gibson
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Space‐Time Modeling and Numerical Simulations of Non‐Newtonian Fluids Using Internal Variables
International Journal for Numerical Methods in Fluids, EarlyView.Based on Hamilton's principle, the study focuses on a novel strategy for the modeling of non‐Newtonian fluids with the help of internal variables. Here, the viscosity evolves locally in space and time. Three configurations are numerically implemented, namely channel flow, a benchmark, and a lid‐driven cavity.
Philipp Junker, Thomas Wick
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Berichtigung zu der Arbeit: On Algebraic Curves over Real Closed Fields [PDF]
, 1977 Manfred Knebusch
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The Discretization‐Corrected Particle Strength Method for the Barotropic Vorticity Equations
International Journal for Numerical Methods in Fluids, EarlyView.Numerical solution for the barotropic vorticity equation in complex geometry using the meshless point collocation method. The spatial domain is represented by a set of nodes. The collocation method numerically solves the strong form governing equations.
G. C. Bourantas +9 more
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A General Approach to Dropout in Quantum Neural Networks
Advanced Quantum Technologies, EarlyView., 2023 Randomly dropping artificial neurons and all their connections in the training phase reduces overfitting issues in classical neural networks, thus improving performances on previously unseen data. The authors introduce different dropout strategies applied to quantum neural networks, learning models based on parametrized quantum circuits.
Francesco Scala +3 more
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Journal of Forecasting, EarlyView.ABSTRACT This paper proposes a multilayer artificial neural network (ANN) method to predict the probability of default (PD) within a survival analysis framework. The ANN method captures hidden interconnections among covariates that influence PD, potentially leading to improved predictive performance compared to both logit and skewed logit models.
Yiannis Dendramis +2 more
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Benefits of Open Quantum Systems for Quantum Machine Learning
Advanced Quantum Technologies, EarlyView., 2023 Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio +2 more
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On the Exterior Degree of a Finite-Dimensional Lie Algebra
Journal of MathematicsIn this paper, we define the exterior degree for a finite-dimensional Lie algebra over the field Fq and give upper and lower bounds. Also, we give some relations between this concept and commutativity degree, capability, and Schur multiplier.
Afsaneh Shamsaki +2 more
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