Results 71 to 80 of about 181,397 (258)
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
CT‐based finite element simulations combined with in situ X‐ray computed tomography are used to analyze insert pull‐out in nickel‐coated polymer foams. Despite variations in material parameters, deformation consistently concentrates within a narrow annular region around the insert.
Yannik Bautz +4 more
wiley +1 more source
We investigate the impact of the wireless network's physical layer (PHY) security and reliability on demand-side management operation in the smart grid.
Ahmed El Shafie +3 more
doaj +1 more source
Fabrication Routes for Ionic Conducting Fiber Strain Sensors
Ionic conducting fiber strain sensors (ICFSs) offer compliant, textile‐integrable sensing. Thus far, the commercialization of ICFSs has been constrained by fiber fabrication routes. This review provides a fabrication‐centric analysis of ICFSs correlating processing strategies with material properties and scalability.
Leo John Kershaw +3 more
wiley +1 more source
Engine Noise and Artificial Intelligence:Babbage's London [PDF]
Williams describes Charles Babbage as he neared the end of his life: living on Dorset Street in Marylebone alongside an old Difference Engine and an incomplete Analytical Machine, one working automated dancer (purchased from the remnants of Merlin’s Mechanical Exhibition, and restored), and – by Babbage’s own furious account – many hundreds of noisy ...
openaire +3 more sources
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 more
wiley +1 more source
Secure D2D underlaying cellular communication based on artificial noise assisted
A secure communication scheme based on artificial noise assisted from base station(BS)was proposed to improve the system secrecy rate of the D2D underlaying cellular.Firstly,the system secrecy rate was modeled.Then the BS with multi-antennas added ...
Xiao-lei KANG +2 more
doaj
FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin +16 more
wiley +1 more source
Full duplex secret transmission scheme based on user cooperation
Full-duplex artificial noise scheme can achieve a limited improvement while the interference power keeps increasing and the full-duplex gain is null.To solve these two problems,a full-duplex secure transmission scheme based on user cooperation was ...
Xiao-lei KANG +3 more
doaj

