Results 91 to 100 of about 1,175,505 (360)

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

Coking energy consumption radial basis function prediction model improved by differential evolution algorithm

Measurement + Control, 2019
This paper presents a radial basis function prediction model improved by differential evolution algorithm for coking energy consumption process, which is very difficult to get online and real time because of the complex process. In the energy consumption
Wenhua Tao, Jiao Chen, Yunjin Gui, Pingping Kong   +3 more
doaj   +1 more source

Compactly supported radial basis functions: how and why? [PDF]

, 2012
The use of radial basis functions have attracted increasing attention in recent years as an elegant scheme for high-dimensional scattered data approximation, an accepted method for machine learning, one of the foundations of mesh-free methods, an ...
Zhu, S.
core   +3 more sources

Double Helical Plasmonic Antennas

Advanced Functional Materials, EarlyView.
Plasmonic double helical antennas funnel circularly polarized light to the nanoscale, offering strong chiroptical interaction and directional light emission. Extending a single helix design tool, this study combines numerical modeling with experimental validation, revealing large, broadband dissymmetry factors in the visible range.
Aleksei Tsarapkin, Luka Zurak, Krzysztof Maćkosz, Lorenz Löffler, Victor Deinhart, Ivo Utke, Thorsten Feichtner, Katja Höflich   +7 more
wiley   +1 more source

Back to the Future: Radial Basis Function Network Revisited

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016
Radial Basis Function (RBF) networks are a classical family of algorithms for supervised learning. The most popular approach for training RBF networks has relied on kernel methods using regularization based on a norm in a Reproducing Kernel Hilbert Space
Qichao Que, M. Belkin
semanticscholar   +1 more source

Decoupling Size and Electronic Effects in Doped SrTiO3 Photocatalysts Through Surface Area–Normalized CO2 Hydrogenation Rates

Advanced Functional Materials, EarlyView.
Exploring the photocatalytic reverse water–gas shift (RWGS) reaction on doped SrTiO3 nanoparticle films, reveals that normalizing catalytic rates by the catalyst's specific surface area (SSA) disentangled surface area effects from the catalyst's intrinsic material properties.
Dikshita Bhattacharyya, Baliana Shani, Isaac Holmes‐Gentle, Gerardo T Martinez, Martyn McLachlan, Nicola Seriani, Ludmilla Steier   +6 more
wiley   +1 more source

Machine Learning Application of Generalized Gaussian Radial Basis Function and Its Reproducing Kernel Theory

Mathematics
Gaussian Radial Basis Function Kernels are the most-often-employed kernel function in artificial intelligence for providing the optimal results in contrast to their respective counterparts.
Himanshu Singh
doaj   +1 more source

Radial Basis Function Networks for Conversion of Sound Spectra

EURASIP Journal on Advances in Signal Processing, 2001
In many advanced signal processing tasks, such as pitch shifting, voice conversion or sound synthesis, accurate spectral processing is required. Here, the use of Radial Basis Function Networks (RBFN) is proposed for the modeling of the spectral changes ...
Carlo Drioli
doaj   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

Organisms modeling: The question of radial basis function networks

ITM Web of Conferences, 2014
There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are ...
Muzy Alexandre, Massardier Lauriane, Coquillard Patrick   +2 more
doaj   +1 more source