Results 71 to 80 of about 605,541 (277)

Bio‐Inspired Molecular Events in Poly(Ionic Liquids)

Advanced Functional Materials, EarlyView.
Originating from dipolar and polar inter‐ and intra‐chain interactions of the building blocks, the topologies and morphologies of poly(ionic liquids) (PIL) govern their nano‐ and micro‐processibility. Modulating the interactions of cation‐anion pairs with aliphatic dipolar components enables the tunability of properties, facilitated by “bottom‐up ...
Jiahui Liu, Marek W. Urban
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  

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

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Extreme Learning Machine for Multi-Label Classification

Entropy, 2016
Extreme learning machine (ELM) techniques have received considerable attention in the computational intelligence and machine learning communities because of the significantly low computational time required for training new classifiers.
Xia Sun, Jingting Xu, Changmeng Jiang, Jun Feng, Su-Shing Chen, Feijuan He   +5 more
doaj   +1 more source

Illuminance prediction through Extreme Learning Machines

2012 IEEE Workshop on Environmental Energy and Structural Monitoring Systems (EESMS), 2012
Planning, managing, and operating power grids using mixed traditional and renewable energy sources requires a reliable forecasting of the contribution of the renewable sources, due to their variable nature. Besides, the short-term prediction of the climatic conditions finds application in other fields (e.g., Climate Sensitive Buildings). In particular,
S. Ferrari, M. Lazzaroni, V. Piuri, A. Salman, L. Cristaldi, M. Rossi, T. Poli   +6 more
openaire   +4 more sources

A Fast Reduced Kernel Extreme Learning Machine [PDF]

Neural Networks, 2016
In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the ...
Deng, Wan-Yu, Ong, Yew-Soon, Zheng, Qing-Hua   +2 more
openaire   +3 more sources

Disordered Carbon Shells Enable Shape Dependent Fluorescence Enhancement in Nanodiamond Quantum Sensors Revealed by Correlative TEM–Fluorescence Microscopy

Advanced Functional Materials, EarlyView.
Molten KNO2 treatment induces a lowrefractive index disordered carbon shell on fluorescent nanodiamonds, enhancing fluorescence emission while preserving spin coherence. Machine learningassisted correlative TEMPL enables direct single‐particle resolution of this enhancement relative to air‐oxidized nanodiamonds of similar morphology, establishing a ...
Parkarsh Kumar, Tom Vaillant, Mehran Kianinia, Haotian Wen, Adam Stewart, Peter J. Reece, Hugues A. Girard, Jean‐Charles Arnault, Huan‐Cheng Chang, Igor Aharonovich, Shery L. Y. Chang   +10 more
wiley   +1 more source

Deep information-extreme machine learning for autonomous UAV based on decursive data structure for semantic segmentation of digital image of a region

Радіоелектронні і комп'ютерні системи
The subject of the research is functional categorical models of deep information-extreme machine learning based on linear and hierarchical data structures, methods for optimizing machine learning parameters based on information criteria and constructing ...
Valerii Cheranovskyi, Mykyta Myronenko, Serhii Kovalevskyi, Roman Kraskovskyi, Mykhailo Otroshchenko   +4 more
doaj   +1 more source

Toward Stable Multivalent Metal Batteries: Understanding the Interfacial Chemistry for Magnesium and Calcium Metal Anodes

Advanced Functional Materials, EarlyView.
Interphase chemistry governs the stability of multivalent metal batteries. We summarize state‐of‐the‐art developments in calcium and magnesium metal batteries by focusing on the correlation among electrolytes, interphase layers, and the electrochemical performance of corresponding metal anodes.
Huijun Lin, Qi Meng, Juncai Long, Chuheng Cao, Zheng‐Long Xu   +4 more
wiley   +1 more source