Results 61 to 70 of about 602,374 (329)

Synchrotron Radiation for Quantum Technology

Advanced Functional Materials, EarlyView.
Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader, Sakura Pascarelli, Klaus Attenkofer, Anna A. Makarova, Karsten Holldack, Kai Rossnagel, Kristiaan Temst, George Kourousias, Stefano Carretta, Caterina Biscari, Helmut Dosch   +10 more
wiley   +1 more source

Hybrid regression model via multivariate adaptive regression spline and online sequential extreme learning machine and its application in vision servo system

International Journal of Advanced Robotic Systems, 2022
To solve the problems of slow convergence speed, poor robustness, and complex calculation of image Jacobian matrix in image-based visual servo system, a hybrid regression model based on multiple adaptive regression spline and online sequential extreme ...
Zhiyu Zhou, Jiangfei Ji, Yaming Wang, Zefei Zhu, Ji Chen   +4 more
doaj   +1 more source

Atomic Size Misfit for Electrocatalytic Small Molecule Activation

Advanced Functional Materials, EarlyView.
This review explores the application and mechanisms of atomic size misfit in catalysis for small molecule activation, focusing on how structural defects and electronic properties can effectively lower the energy barriers of chemical bonds in molecules like H2O, CO2, and N2.
Ping Hong, Changfan Xu, Huaping Zhao, Yong Lei   +3 more
wiley   +1 more source

An Algorithm, Based on Extreme Machine Learning, for Modeling Rate of Material Transfer in EDC Process [PDF]

فناوری در مهندسی هوافضا, 2019
In this paper, Extreme Learning Machine method is used to model the rate of material transfer as an effective parameter in process speed and surface quality.
Moohamadreza Maraki, Hadi Tagimalek, Majid Azargoman, Ramin Karami   +3 more
doaj  

Multiple-Instance Learning Approach via Bayesian Extreme Learning Machine

IEEE Access, 2020
Multiple-instance learning (MIL) can solve supervised learning tasks, where only a bag of multiple instances is labeled, instead of a single instance.
Peipei Wang, Xinqi Zheng, Junhua Ku, Chunning Wang   +3 more
doaj   +1 more source

Evolutionary Voting‐Based Extreme Learning Machines

Mathematical Problems in Engineering, 2014
Voting‐based extreme learning machine (V‐ELM) was proposed to improve learning efficiency where majority voting was employed. V‐ELM assumes that all individual classifiers contribute equally to the decision ensemble. However, in many real‐world scenarios, this assumption does not work well.
Nan Liu, Jiuwen Cao, Zhiping Lin, Pin Pin Pek, Zhi Xiong Koh, Marcus Eng Hock Ong   +5 more
openaire   +1 more source

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Robust kernel-based model reference adaptive control for unstable aircraft

Advances in Mechanical Engineering, 2016
In this article, a robust kernel-based model reference adaptive control is proposed for an unstable nonlinear aircraft. The heart of the proposed kernel-based model reference adaptive control scheme comprises an offline neural identifier and an online ...
Zhao-Xu Yang, Guang-She Zhao, Rong-Jing Bao, Hai-Jun Rong, Lei-Tao Gao   +4 more
doaj   +1 more source

A Fault Diagnosis Method of Rolling Bearing Based on Attention Entropy and Adaptive Deep Kernel Extreme Learning Machine

Energies, 2022
To address the difficulty of early fault diagnosis of rolling bearings, this paper proposes a rolling bearing diagnosis method by combining the attention entropy and adaptive deep kernel extreme learning machine (ADKELM).
Weiyu Wang, Xunxin Zhao, Lijun Luo, Pei Zhang, Fan Mo, Fei Chen, Diyi Chen, Fengjiao Wu, Bin Wang   +8 more
doaj   +1 more source

Bimetallic Nanoparticles as Cocatalysts for Photocatalytic Hydrogen Production

Advanced Functional Materials, EarlyView.
Recent developments have introduced bimetallic nanoparticles as effective cocatalysts for photocatalytic systems. This review explores the rapidly expanding research on bimetallic cocatalysts for photocatalytic production of hydrogen, emphasizing the creation of carrier‐selective contacts, localized surface plasmon resonance effects, methodologies for ...
Yufen Chen, Asier Agrelo‐Lestón, Ignasi Burgués‐Ceballos, Jordi Llorca, Lluís Soler   +4 more
wiley   +1 more source