Results 111 to 120 of about 19,982 (307)
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee +17 more
wiley +1 more source
Lagrangian predictability of high-resolution regional models: the special case of the Gulf of Mexico [PDF]
The Lagrangian prediction skill (model ability to reproduce Lagrangian drifter trajectories) of the nowcast/forecast system developed for the Gulf of Mexico at the University of Colorado at Boulder is examined through comparison with real drifter ...
P. C. Chu +6 more
doaj
Relative Entropy and Inductive Inference
We discuss how the method of maximum entropy, MaxEnt, can be extended beyond its original scope, as a rule to assign a probability distribution, to a full-fledged method for inductive inference.
Caticha, Ariel
core +1 more source
Mesoporous Carbon Thin Films with Large Mesopores as Model Material for Electrochemical Applications
Mesoporous carbon thin films possessing 70 nm mesopores are prepared on titanium substrates by soft templating of resol resins with a self‐synthesized poly(ethylene oxide)‐block‐poly(hexyl acrylate) block copolymer. A strategy to avoid corrosion of the metal substrate is presented, and the films are extensively characterized in terms of morphology ...
Lysander Q. Wagner +9 more
wiley +1 more source
Thermodynamic Exercises for the Kinetically Controlled Hydrogenation of Carvone
Carvone belongs to the chemical family of terpenoids and is the main component of various plant oils. Carvone and its hydrogenated products are used in the flavouring and food industries.
Artemiy A. Samarov +3 more
doaj +1 more source
A new class of living liquid metal composites is introduced, embedding Bacillus subtilis endospores into eutectic gallium–indium (EGaIn). The spores enhance droplet coalescence, strengthen interfacial conductivity, and provide on‐demand electrogenic functionality after germination. The composites exhibit high conductivity, self‐healing, patternability,
Maryam Rezaie, Yang Gao, Seokheun Choi
wiley +1 more source
Localizing the latent structure canonical uncertainty: Entropy profiles for hidden Markov models [PDF]
Ce rapport concerne l'inférence sur les états de modèles de Markov cachés. Ces modèles se fondent sur des états non observés, qui ont en général une interprétation, dans le contexte d'une application donnée. Ceci rend nécessaire la conception d'outils de
Durand, Jean-Baptiste, Guédon, Yann
core
Electron–Matter Interactions During Electron Beam Nanopatterning
This article reviews the electron–matter interactions important to nanopatterning with electron beam lithography (EBL). Electron–matter interactions, including secondary electron generation routes, polymer radiolysis, and electron beam induced charging, are discussed.
Camila Faccini de Lima +2 more
wiley +1 more source
Dual‐atom catalysts featuring varying spatial configurations of metal sites (Pt1Fe1 DACs) are employed to systematically investigate the influence of spatial arrangements on the electronic structure and catalytic activity of active sites. Notably, the 3D asymmetric Pt1Fe1‐TAC dimer, featuring strong interatomic interactions, demonstrates superior ...
Yi Guan +8 more
wiley +1 more source
An innovative medium entropy alloy (MEA) composite material was fabricated via micro laser powder bed fusion (μ‐LPBF) with appropriate nano‐ceramic particles doping and exhibited markedly improved overall performance, including synergistically enhanced strength and ductility, increased hardness and compressive strength, improved wear resistance and ...
Zhonglin Shen, Mingwang Fu
wiley +1 more source

