Results 91 to 100 of about 22,588 (266)

Theoretical description of ultrasonic propagation and scattering phenomena in polycrystalline structures aiming for simulations on nondestructive materials characterization

, 2014
Beitrag 331In microscopically inhomogeneous media ultrasonic scattering at grain and/or phase boundaries causes sound velocity dispersion and attenuation.
Hirsekorn, Sigrun
core   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Computer methods and inverse problems in nondestructive testing and diagnostics Proceedings

, 1998
The aim of the Conference CM NDT is to provide a forum for the detailed discussion of fundamental computer, mathematical, and physical aspects of quantitative nndestructive evaluation and condition diagnosis.
Tillack, G.R. (comps.), Vengrinovich, V., Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin (Germany), Deutsche Gesellschaft fuer Zerstoerungsfreie Pruefung e.V., Berlin (Germany), American Society for Nondestructive Testing, Inc. (ASNT), Columbus, OH (United States), Belorussian Association on Nondestructive Testing and Technical Diagnostics, Minsk (Belarus), Institute of Applied Physics Problems, Minsk (Belarus), Iowa State Univ., Ames, IA (United States). Center for Nondestructive Evaluation   +7 more
core  

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

A Novel Deep Learning Model for Motor Imagery Classification in Brain–Computer Interfaces

Information
Recent advancements in decoding electroencephalogram (EEG) signals for motor imagery tasks have shown significant potential. However, the intricate time–frequency dynamics and inter-channel redundancy of EEG signals remain key challenges, often limiting ...
Wenhui Chen, Shunwu Xu, Qingqing Hu, Yiran Peng, Hong Zhang, Jian Zhang, Zhaowen Chen   +6 more
doaj   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Philosophy for nondestructive testing of fiber composites

, 1977
A discussion of a nondestructive testing philosophy for fiber composites is presented. The position is taken that the nondestructive test indications must be quantitatively correlated to the required engineering performance properties of the composite ...
Hamstad, M. A.
core   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Cast Iron Inspection by Means of Micromagnetic Procedures

, 2022
S.1094-1101Chilled areas - that means ledebuitic and cementite phases - in cast iron components lead to a dreduction of loadability and causes problems during machining. The micromagnetic procedure described here allows the determination of chilled areas
Altpeter, I., Laub, U.
core