Results 71 to 80 of about 2,032,630 (292)

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Bio-inspired artificial neurons

Scheme of the origin of artificial neurons, inspired form biological ...
Andrea Navas-Olive (18126109)
core   +1 more source

Developmental Regulation of Small-Conductance Ca²⁺-Activated K⁺ Channel Expression and Function in Rat Purkinje Neurons [PDF]

, 2002
Calcium transients play an important role in the early and later phases of differentiation and maturation of single neurons and neuronal networks. Small-conductance calcium-activated potassium channels of the SK type modulate membrane excitability and ...
Stocker, M, Pedarzani P., Stocker, M., Pedarzani, P, Cingolani, L., Cingolani L, Gymnopoulos, M., Boccaccio, A, Cingolani, L. A., Gymnopoulos M, Boccaccio A, Gymnopoulos, Marco, Boccaccio, A., Cingolani, LA, Gymnopoulos, M, Pedarzani, P., Stocker M   +16 more
core   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

The Gini differential test for neural network analysis of small biometric data samples

Известия высших учебных заведений. Поволжский регион:Технические науки
Backgroud. Training of artificial neural networks in accordance with the algorithms for recognizing biometric patterns described in GOST R 52633.5-2011 should be performed on small samples.
S.A. Guzhova
doaj   +1 more source

A Self‐Organizing Map Spiking Neural Network Based on Tin Oxide Memristive Synapses and Neurons

Advanced Electronic Materials
Neuromorphic computing systems are promising alternatives in areas such as pattern recognition and image processing. This work focuses on the fabrication of tin oxide memristors (Ag/SnO2/Pt) to emulate artificial synapses and neurons.
Yu Wang, Yanzhong Zhang, Yanji Wang, Xinpeng Wang, Hao Zhang, Rongqing Xu, Yi Tong   +6 more
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Using software support for quantum superposition effects to speed up the solution of the targeted enumeration issue in biometric data when extracting knowledge from a neural network

Известия высших учебных заведений. Поволжский регион:Технические науки
Background. The continuum/discrete processing of information by natural neurons and artificial neurons is considered. The purpose of the work is to demonstrate the possibilities of unlimitedly long-term support of the effects of quantum superposition ...
V.I. Volchikhin, A.I. Ivanov, M.A. Shcherbakov   +2 more
doaj   +1 more source