Results 81 to 90 of about 123,227 (279)
Advanced Intelligent Systems, EarlyView.This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Subspace Trail Cryptanalysis and its Applications to AES
IACR Transactions on Symmetric Cryptology, 2017 We introduce subspace trail cryptanalysis, a generalization of invariant subspace cryptanalysis. With this more generic treatment of subspaces we do no longer rely on specific choices of round constants or subkeys, and the resulting method is as such a ...
Lorenzo Grassi +2 more
doaj +1 more source
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT To address the issues of neglecting the spatiotemporal correlations among process variables, low‐level features are vulnerable to noise interference, and the gradual loss of key information layer by layer during deep network training in traditional stacked autoencoder‐based soft‐sensor models, this paper proposes a hierarchical complementary ...
Xiaoping Guo, Jinghong Guo, Yuan Li
wiley +1 more source
Overlap-Kernel EPI: Estimating MRI Shot-to-Shot Phase Variations by Shifted-Kernel Extraction From Overlap Regions at Arbitrary k-Space Locations. [PDF]
Magn Reson MedABSTRACT Purpose In multi‐shot EPI, shot‐dependent phase fluctuations can introduce ghost artifacts, undermining advantages for enhancing resolution or reducing distortion, particularly in diffusion scans. Here, a novel self‐navigation strategy based on shift‐invariant kernel extraction is proposed, enabling robust estimation of phase inconsistencies ...
Tian R +3 more
europepmc +2 more sources
Asian Journal of Control, EarlyView.Abstract Large swarms often adopt a hierarchical network structure that incorporates information aggregation. Although this approach offers significant advantages in terms of communication efficiency and computational complexity, it can also lead to degradation due to information constraints.
Kento Fujita, Daisuke Tsubakino
wiley +1 more source
The Canadian Journal of Chemical Engineering, EarlyView.Abstract We develop a delay‐aware estimation and control framework for a non‐isothermal axial dispersion tubular reactor modelled as a coupled parabolic‐hyperbolic PDE system with recycle‐induced state delay. The infinite‐dimensional dynamics are preserved without spatial discretization by representing the delay as a transport PDE and adopting a late ...
Behrad Moadeli, Stevan Dubljevic
wiley +1 more source
The Huang–Yang Formula for the Low‐Density Fermi Gas: Upper Bound
Communications on Pure and Applied Mathematics, EarlyView.ABSTRACT We study the ground state energy of a gas of spin 1/2$1/2$ fermions with repulsive short‐range interactions. We derive an upper bound that agrees, at low density ϱ$\varrho$, with the Huang–Yang conjecture. The latter captures the first three terms in an asymptotic low‐density expansion, and in particular the Huang–Yang correction term of order
Emanuela L. Giacomelli +3 more
wiley +1 more source
Deep Underground Science and Engineering, EarlyView.This study investigates ground subsidence during tunnel excavation in karst areas, highlighting the combined effects of karst cave proximity, cave size, and soil spatial variability. Findings suggest that shorter cave distances and larger cave sizes increase subsidence variability, and a modified Peck formula is proposed for more accurate subsidence ...
Zhenghong Su +4 more
wiley +1 more source
Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices
Journal of Forecasting, EarlyView.ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer +3 more
wiley +1 more source
A new method for computing the stable invariant subspace of a real Hamiltonian matrix
Journal of Computational and Applied Mathematics, 1997 The problem of the numerical computation of the Lagrangian invariant subspaces of a real Hamiltonian matrix with a strongly backward stable algorithm is thoroughly examined. The solution of the Hamiltonian eigenvalue problem is important because of its close relation with the solution of the continuous-time algebraic Riccati equation.
Benner, P. ; https://orcid.org/0000-0003-3362-4103 +2 more
openaire +2 more sources