Results 81 to 90 of about 133,004 (188)

Integration of response surface methodology (RSM), machine learning (ML), and artificial intelligence (AI) for enhancing properties of polymeric nanocomposites‐A review

Polymer Composites, EarlyView.
AI/ML and RSM‐Driven Optimization of Polymeric Nanocomposites for Enhanced Properties. Abstract This review elucidates the amalgamation of machine learning (ML), artificial intelligence (AI), and response surface methodology (RSM) for the optimization of fabrication and the enhancement of the properties of polymeric nanocomposites.
Yasir Raza, Hassan Raza, Arslan Ahmed, Moinuddin Mohammed Quazi, Muhammad Jamshaid, Muhammad Tuoqeer Anwar, Muhammad Nasir Bashir, Talha Younas, Ali Turab Jafry, Manzoore Elahi M. Soudagar   +9 more
wiley   +1 more source

Data assimilation errors due to incomplete accounting of balanced versus unbalanced moisture

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We investigate data assimilation strategies with moisture and assess the impact of accounting for moisture's balanced and unbalanced components. To illustrate the main ideas, examples are presented using a simple model consisting of linear, moist, shallow‐water equations with stochastic forcing.
H. Reed Ogrosky, Alfredo N. Wetzel, Leslie M. Smith, Samuel N. Stechmann   +3 more
wiley   +1 more source

Statistical Complexity of Quantum Learning

Advanced Quantum Technologies, EarlyView.
The statistical performance of quantum learning is investigated as a function of the number of training data N$N$, and of the number of copies available for each quantum state in the training and testing data sets, respectively S$S$ and V$V$. Indeed, the biggest difference in quantum learning comes from the destructive nature of quantum measurements ...
Leonardo Banchi, Jason Luke Pereira, Sharu Theresa Jose, Osvaldo Simeone   +3 more
wiley   +1 more source

What can we Learn from Quantum Convolutional Neural Networks?

Advanced Quantum Technologies, EarlyView.
Quantum Convolutional Neural Networks have been long touted as one of the premium architectures for quantum machine learning (QML). But what exactly makes them so successful for tasks involving quantum data? This study unlocks some of these mysteries; particularly highlighting how quantum data embedding provides a basis for superior performance in ...
Chukwudubem Umeano, Annie E. Paine, Vincent E. Elfving, Oleksandr Kyriienko   +3 more
wiley   +1 more source

Discrete Transforms and Orthogonal Polynomials of (Anti)symmetric Multivariate Sine Functions. [PDF]

Entropy (Basel), 2018
Brus A, Hrivnák J, Motlochová L.
europepmc   +1 more source

Critical Energies and Wigner Functions of the Stationary States of the Bose Einstein Condensates in a Double‐Well Trap

Advanced Quantum Technologies, EarlyView.
The critical parameters and energies, at which the wave function of the Bose Einstein Condensate in a double well trap exhibit the symmetry breaking, are estimated. The phase space representation of the states is obtained trough the Wigner function and the trends of the negativities are analyzed.
D. J. Nader, E. Serrano‐Ensástiga
wiley   +1 more source

Boundary characteristic orthogonal polynomials method in the vibration analysis of multi-span plates acting upon a moving mass. [PDF]

Heliyon, 2019
Kashani Rad H, Ghalehnovi M, Shariatmadar H.   +2 more
europepmc   +1 more source

Multiple Population Genetic Algorithm‐Based Inverse Kinematics Solution for a 6‐DOF Manipulator

Journal of Field Robotics, EarlyView.
ABSTRACT Compared to traditional fixed configuration manipulators, modular manipulators occupy less space, offer greater flexibility, and demonstrate stronger adaptability to diverse environments. These characteristics make them particularly suitable for operating in unknown environments, such as disaster rescue and pipeline inspection.
Shuhuan Wen, Jiatai Min, Zhanqi Yu, Yunxiao Li, Xin Liu, Hamid Reza Karimi   +5 more
wiley   +1 more source

Recurrence relations for orthogonal polynomials for PDEs in polar and cylindrical geometries. [PDF]

Springerplus, 2016
Richardson M, Lambers JV.
europepmc   +1 more source

3D Temperature Mapping During Photothermal Therapy in Cellular Assemblies

Small Structures, EarlyView.
3D temperature mapping and control during photothermal therapy are achieved with temperature‐sensitive iron selenide nanoparticles, combined with low‐cost and portable magnetic resonance imaging scanners. This strategy overcomes 2D measurement limitations, and facilitates real‐time temperature monitoring, allowing more effective therapy outcomes ...
Joana F. Soeiro, Rute A. Pereira, Rui Oliveira‐Silva, Filipa L. Sousa, Vítor M. Gaspar, João F. Mano, Ángel Millán, Claudia Innocenti, Manuel Mariani, Alessandro Lascialfari, Nuno J. O. Silva   +10 more
wiley   +1 more source