Results 41 to 50 of about 324 (121)

Denoising method for partial discharge signals of high-voltage mining cables

Gong-kuang zidonghua
Currently, partial discharge (PD) signals of high-voltage mining cables are easily buried in noise and difficult to extract. Variational Mode Decomposition (VMD) is an effective method for PD denoising, but the number of decomposition layers and penalty ...
ZHANG Xiaoniu, SI Shijun, LI Junhong, WANG Anle   +3 more
doaj   +1 more source

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source

VQ‐Wave: A Physics‐Driven Spatiotemporal Deep Learning Approach for Noncontrast‐Enhanced Lung Ventilation and Perfusion MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a robust deep learning framework for noncontrast‐enhanced functional lung MRI, overcoming the limitations of spectral decomposition in the presence of physiological nonstationarity. Methods We introduce VQ‐Wave (Ventilation/Q‐perfusion Waveform‐based Assessment of Variable Evolutions), a physics‐driven spatiotemporal ...
Grzegorz Bauman, Pavlos Panos, Philipp Latzin, Oliver Bieri   +3 more
wiley   +1 more source

A Review of Mechanical Reinforcement and Piezoresistive Self‐Sensing in Carbon Nanotube Fiber Composites

Polymer Composites, EarlyView.
PSPP‐TRL mapping of CNT‐modified CFRP literature, with four recurring confusions resolved and five scale‐up problems quantified. ABSTRACT Carbon nanotube‐modified fiber composites are often presented as a route to stronger, tougher, and self‐sensing structural materials.
Sanan H. Khan
wiley   +1 more source

Detecting Plateau Zokor (Eospalax baileyi) Mounds in UAV Imagery of Alpine Meadows Using Deep Learning Algorithms

Remote Sensing in Ecology and Conservation, EarlyView.
We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang, Limin Hua, Lianguo Wang, Jiazhen Li, Rui Dong, Siwei Yang   +5 more
wiley   +1 more source

Virtual Overlay Staining With Plasmonic Oligomer Metasurface

Small, EarlyView.
A scalable plasmonic metasurface enables “virtual staining” of living cells by enhancing optical contrast from refractive index differences. Through electrostatically assembled nanoparticle oligomers on a mirror, cellular components such as nuclei, mitochondria, and lipid‐rich regions are visualized without molecular dyes. This approach simplifies cell
Doeun Kim, Juhwan Kim, Jiyeong Ma, Gyurin Kim, JuHyeong Lee, So Young Yoon, Youngsoo Jun, Young Min Song, Hyeon‐Ho Jeong   +8 more
wiley   +1 more source

WFSuite: a Python software suite for X‐ray wavefront sensing and at‐wavelength metrology

Journal of Synchrotron Radiation, EarlyView.
WFSuite is an open‐source Python suite for speckle‐based X‐ray wavefront reconstruction, offering both relative metrology and absolute phase modules. It streamlines wavefront characterization and feedback control for synchrotron and XFEL applications.WFSuite is a Python‐based software suite for X‐ray wavefront sensing and at‐wavelength metrology for ...
Xianbo Shi, Luca Rebuffi, Zhi Qiao, Yu-Chung Lin, Lahsen Assoufid   +4 more
wiley   +1 more source

Controllable Intrinsic Surface Pattern Generation Using Slime Mold Simulations

Computer Graphics Forum, EarlyView.
Abstract Surface‐based pattern simulations have proven valuable for texture design and scientific visualization, but existing methods face several limitations. Most simulations either target a narrow range of pattern types (e.g. spots, branching) or support a broad range of patterns at the cost of time‐consuming parameter tuning.
Jeffrey Layton, Faramarz Samavati, Adam Runions   +2 more
wiley   +1 more source

Leveraging modified ex situ tomography data for segmentation of in situ synchrotron X‐ray computed tomography

Journal of Microscopy, EarlyView.
Abstract In situ synchrotron X‐ray computed tomography enables dynamic material studies. However, automated segmentation remains challenging due to complex imaging artefacts – like ring and cupping effects – and limited training data. We present a methodology for deep learning‐based segmentation by transforming high‐quality ex situ laboratory data to ...
Tristan Manchester, Adam Anders, Julio Spadotto, Hannah Eccleston, William Beavan, Hugues Arcis, Brian J. Connolly   +6 more
wiley   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, Volume 45, Issue 4, Page 2059-2077, July 2026.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source