Results 101 to 110 of about 5,139 (262)

Nonlinear Fractal Interpolation Functions Induced by General Integral Contractions

Fractal and Fractional
The development of fractal set theory has been strongly driven by the introduction of new classes of fractal sets, among which the attractors of iterated function systems (IFSs) play a central role.
Taoufik Moulahi, Najmeddine Attia
doaj   +1 more source

Evaluation of Plasticity and Creep Parameters From Tensile Stress–Strain Data for a Range of Strain Rates

Advanced Engineering Materials, EarlyView.
This plot compares experimental tensile stress–strain curves (with 4 different strain rates) and corresponding modelled curves (obtained using the optimised sets of Voce and Miller–Norton parameter values shown). The inferred M‐N values, characterizing the creep, are very similar to those obtained via conventional creep testing.
S. Ooi, R. P. Thompson, T. W. Clyne
wiley   +1 more source

Multivariate error function based neural network approximations

Journal of Numerical Analysis and Approximation Theory, 2014
Here we present multivariate quantitative approximations of real and complex valued continuous multivariate functions on a box or \(\mathbb{R}^{N},\) \(N\in \mathbb{N}\), by the multivariate quasi-interpolation, Baskakov type and quadrature type neural ...
George A. Anastassiou
doaj   +2 more sources

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Positive‐Tone Nanolithography of Antimony Trisulfide with Femtosecond Laser Wet‐Etching

Advanced Functional Materials, EarlyView.
A butyldithiocarbamic acid (BDCA) etchant is used to fabricate various micro‐ and nanoscale structures on amorphous antimony trisulfide (a‐Sb2S3) thin film via femtosecond laser etching. Numerical analysis and experimental results elucidate the patterning mechanism on gold (reflective) and quartz (transmissive) substrates.
Abhrodeep Dey, Uwe Hübner, Albane Benardais, Xiaofei Wu, Andrea Dellith, Jan Dellith, Torsten Wieduwilt, Henrik Schneidewind, Markus A Schmidt, Virginie Nazabal, Volker Deckert, Jer‐Shing Huang, Wei Wang   +12 more
wiley   +1 more source

Mining Dynamics: Using Data Mining Techniques to Analyze Multi-agent Learning

Journal of Intelligent Systems, 2017
Analyzing the learning dynamics in multi-agent systems (MASs) has received growing attention in recent years. Theoretical analysis of the dynamics was only possible in simple domains and simple algorithms.
Sherief Abdallah
doaj   +1 more source

Mechanical Properties of Architected Polymer Lattice Materials: A Comparative Study of Additive Manufacturing and CAD Using FEM and µ‐CT

Advanced Functional Materials, EarlyView.
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker, Thierry Roland, Damien Favier, Antoine Egele, Michael Heymann, Cosima Stubenrauch   +5 more
wiley   +1 more source

Formally Verified Approximate Policy Iteration

Proceedings of the AAAI Conference on Artificial Intelligence
We present a methodology based on interactive theorem proving that facilitates the development of verified implementations of algorithms for solving factored Markov Decision Processes. As a case study, we formally verify an algorithm for approximate policy iteration in the proof assistant Isabelle/HOL.
Schäffeler, Maximilian, Abdulaziz, Mohammad   +1 more
openaire   +2 more sources

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Multivariate Approximation by Overactivated and Spiked Multivariate Convolutions as Positive Linear Operators

Axioms
This study quantitatively approximates the unit operator using three types of multivariate, overactivated, and spiked convolution operators. The core of these operators is a multivariate “cusp” kernel, which acts as a novel, compact-support activation ...
George A. Anastassiou
doaj   +1 more source