Results 111 to 120 of about 30,962 (265)
To address the nonlinearity and dynamics of industrial processes, an incremental isometric mapping (IISOMAP) in combination with double local density (DLD) is proposed as a fault detection method (IISOMAP-DLD) based on stream shape learning.
FENG Liwei, SUN Liwen, GU Huan, LI Yuan
doaj +1 more source
Geometry of statistical manifolds
A statistical manifold \((M,g,\nabla)\) is a Riemannian manifold \((M,g)\) equipped with torsion-free affine connections \(\nabla,\nabla^*\) which are dual with respect to \(g\). A point \(p\in M\) is said to be \(\nabla\)- isotropic if the sectional curvatures have the same value \(k(p)\), and \((M,g,\nabla)\) is said to be \(\nabla\)-isotropic when \(
openaire +2 more sources
A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle +5 more
wiley +1 more source
This perspective reframes additive manufacturing for electrical machines as a qualification‐limited materials and architecture design problem. It links process–structure–property–performance relationships to magnetic, conducting, dielectric, and thermal property windows, highlighting where AM can enable segmented magnetic circuits, permanent magnet ...
Dénes Fodor, Loránd Szabó
wiley +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
On the Relationships Between Affine Manifolds and Complex Manifolds
In this work, we study the relationships between affine manifolds and complex manifolds. We prove that a linear connection and a Riemannian metric on an affine manifold M of dimension n induce a complex structure and a Hermitian metric on both the ...
Hanzhang Yin
doaj +1 more source
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 +11 more
wiley +1 more source
Counterion Dependent Side‐Chain Relaxation Stiffens a Chemically Doped Thienothiophene Copolymer
Oxidation of a thienothiophene copolymer, p(g3TT‐T2), via different doping strategies and dopant molecules resulted in materials with similar oxidation levels and a high electrical conductivity of ≈100 S cm−1. However, mechanical properties varied significantly, with sub‐glass transition temperatures and elastic moduli spanning from –44°C to –3°C and ...
Mariavittoria Craighero +12 more
wiley +1 more source
Fisher’s legacy of directional statistics, and beyond to statistics on manifolds
19 pages,11 ...
openaire +3 more sources
Integration of Low‐Voltage Nanoscale MoS2 Memristors on CMOS Microchips
This article presents the first monolithic integration of nanoscale MoS2‐based memristors into the back‐end‐of‐line of foundry‐fabricated CMOS microchips in a one‐transistor‐one‐resistor (1T1R) architecture. The MoS2‐based 1T1R cells exhibit forming‐free, nonvolatile resistive switching with ultra‐low operating voltages, low cycle‐to‐cycle variability ...
Jimin Lee +16 more
wiley +1 more source

