Results 131 to 140 of about 4,387,980 (294)

U‐Net‐Based Prediction of Concealed Volume Loss in AZ31 From Optical Corrosion Imprints and As‐Exposed Surface Topography

Advanced Intelligent Discovery, EarlyView.
How much material loss is concealed beneath a layer of corrosion products? This proof‐of‐concept study demonstrates how concealed volume loss is inferred from the optical appearance and as‐exposed surface topography of AZ31 corrosion imprints. By predicting postcleaning depth maps, a multimodal U‐Net model estimates hidden volume loss without chromic ...
Lars Dammann, Ci Song, Bahram Vaghefinazari, Tim Würger, Anna Lisitsyna, Shadi Albarqouni, Mikhail L. Zheludkevich, Sviatlana V. Lamaka, Christian Feiler   +8 more
wiley   +1 more source

Bubbles Acting as Micro End‐Effectors for Dexterous Manipulation and Sensing in Aqueous Environment

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Inspired by bubbles, this article proposes a low‐cost method for multifunctional manipulation and sensing using microbubbles in aqueous environments. Bubbles are easily generated in situ, enabling the safe and adaptive handling of microobjects and sensing of microforces and surface textures.
Zichen Xu, Qingsong Xu
wiley   +1 more source

NOTES ON THE ARITHMETIC-GEOMETRIC MEAN INEQUALITY FOR SINGULAR VALUES

, 2015
In this short note, we present a generalization and a new equivalent form of the arithmetic-geometric mean inequality for singular values.  Meanwhile, we also show some remarks related to generalizations of the arithmetic-geometric mean inequality ...
Ruan, Jiechang
core  

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source

Applications of Arithmetic Geometric Mean Inequality

Advances in Linear Algebra & Matrix Theory, 2017
The well-known arithmetic-geometric mean inequality for singular values, due to Bhatia and Kittaneh, is one of the most important singular value inequalities for compact operators. The purpose of this study is to give new singular value inequalities for compact operators and prove that these inequalities are equivalent to arithmetic-geometric mean ...
openaire   +2 more sources

Distributed State Estimation for Mobile Robots in LiDAR Sensor Networks With Intermittent Inertial Measurements

Advanced Intelligent Systems, EarlyView.
A scalable distributed observer framework for LiDAR sensor networks is presented for robust tracking and pose estimation of mobile robots. By combining adaptable 3D detection, clustering‐based communication reduction, and intermittent inertial fusion, accurate and efficient estimation is achieved under occlusions and sensing constraints, with formally ...
Isabella Luppi, Ehsan Hashemi
wiley   +1 more source

The arithmetic-geometric mean inequality (II)

, 2016
The arithmetic-geometric mean inequality: √ab ≤ (a+b)/2 , for a,b ≥ 0. The yellow and green triangles are similar, so b/L = L/a. Therefore L²=ab, L=√ab , and the figure shows that L ≤ (a+b)/2Ensino Médio::MatemáticaEducação Superior::Ciências Exatas e da
Rosa, Félix Martínez de la, Martínez, Soledad Mª Sáez   +1 more
core   +1 more source

The arithmetic-geometric mean inequality (I)

, 2014
The arithmetic-geometric mean inequality: √ab ≤ (a+b)/2, for a,b ≥ 0. The figure shows that (a+b)²-(a-b)²=4ab, therefore √ab = √[(a+b)²-(a-b)²]/4 ≤ √[(a+b)²]/4 = (a+b)/2Ensino Médio ...
Rosa, Félix Martínez de la, Martínez, Soledad Mª Sáez   +1 more
core  

Lab‐Scale Fabrication Process Selection for Soft Robotics: Benchmarking, Tradeoffs, and Guidelines for Formative Manufacturing of Soft Silicone Components

Advanced Intelligent Systems, EarlyView.
Fabrication shapes soft robot performance, but benchmarking data and selection guidelines remain scarce. We fabricate silicone actuators using two molding techniques and three mold types, characterizing them with cycle testing, microscopy, profilometry, and 3D imaging. Applying our lab‐scale, soft robotics‐specific fabrication evaluation criteria shows
Charlotte M. Folinus, Daniel Massimino, Cat Arase, Kaitlyn P. Becker   +3 more
wiley   +1 more source

Revealing Hidden Raman Signatures Through Attention‐Based Spectral Unmixing

Advanced Intelligent Systems, EarlyView.
Weak Raman signatures are recovered from background‐dominated spectra using a transformer‐based, reference‐free spectral unmixing AI framework. Self‐attention reconstructs substrate contribution directly from mixed data, enabling reliable extraction of previously inaccessible vibrational features.
Dmitriy A. Poteryayev, Pietro Novelli, Annalisa Coriolano, Riccardo Dettori, Valentina Tozzini, Fabio Beltram, Massimiliano Pontil, Antonio Rossi, Stiven Forti, Camilla Coletti   +9 more
wiley   +1 more source