Results 71 to 80 of about 2,561,650 (296)

Unsupervised Machine Learning Identifies Shared Biomechanical and Clinical Variation in Individuals with Knee Osteoarthritis and High Body Mass Index

Arthritis Care &Research, EarlyView.
Objective High body mass index (BMI ≥ 27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck, J. Elyse Borgert, Hyeon Lee, Liubov Arbeeva, Yvonne M. Golightly, Richard F. Loeser, Leigh F. Callahan, Stephen P. Messier, Brian Pietrosimone, Amanda E. Nelson, James S. Marron   +10 more
wiley   +1 more source

A Data-Adaptive Compressed Sensing Approach to Polarimetric SAR Tomography of Forested Areas [PDF]

, 2013
Super-resolution imaging via compressed sensing (CS)-based spectral estimators has been recently introduced to synthetic aperture radar (SAR) tomography.
Nannini, Matteo, Aguilera, Esteban, Reigber, Andreas   +2 more
core   +1 more source

The Content and Reporting Completeness of Physical Therapist–Led Interventions for Glenohumeral Osteoarthritis: A Systematic Review

Arthritis Care &Research, EarlyView.
Objective This study synthesized the content and reporting completeness of published physical therapist–led interventions for glenohumeral osteoarthritis (GHOA). Methods This systematic review undertook electronic database searches in PubMed, EMBASE, Cochrane, CINAHL, and PEDro (until June 2025) for any peer‐reviewed articles or studies describing ...
Daha G. Muhammad, Nadine E. Foster, Mickylle Pelaez, Karina O'Leary, Ilana N. Ackerman, Jonathan G. Quicke   +5 more
wiley   +1 more source

Compressed point cloud classification with point-based edge sampling

EURASIP Journal on Image and Video Processing
3D point cloud data, as an immersive detailed data source, has been increasingly used in numerous applications. To deal with the computational and storage challenges of this data, it needs to be compressed before transmission, storage, and processing ...
Zhe Luo, Wenjing Jia, Stuart Perry
doaj   +1 more source

Microstructural Evolution and Vacancy Defect Formation in Mn–Mo–Ni RPV Steel Under Low Cycle Fatigue: Insights From EBSD and PALS

Advanced Engineering Materials, EarlyView.
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar, Dhanadeep Dutta, G. Bharat Reddy   +2 more
wiley   +1 more source

Image compression and recovery through compressive sampling and particle swarm [PDF]

2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
We present an application of particle swarm techniques to the problem of sparse signal recovery. Although a direct application of particle swarm is straightforward, specifics of the signal recovery problem can be incorporated into particle behavior in a way that substantially improves the quality of the recovered signal.
David Sturgill, Benjamin Van Ruitenbeek, Robert J. Marks II   +2 more
openaire   +2 more sources

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

Compressed Sensing-Based MRI Reconstruction Using Complex Double-Density Dual-Tree DWT

International Journal of Biomedical Imaging, 2013
Undersampling k-space data is an efficient way to speed up the magnetic resonance imaging (MRI) process. As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS) allows signal acquisition using fewer samples ...
Zangen Zhu, Khan Wahid, Paul Babyn, Ran Yang   +3 more
doaj   +1 more source

Wavelet-Based Compressed Sensing for Polarimetric SAR Tomography [PDF]

, 2013
Tomographic synthetic aperture radar (SAR) imaging has been recently formulated in a wavelet-based compressed sensing (CS) framework. This paper reviews the underlying sparsity-driven algorithms for single-channel as well as polarimetric tomography, and ...
Nannini, Matteo, Aguilera, Esteban, Andreas, Reigber   +2 more
core  

Thermodynamic Pathways of Nonequilibrium Solidification in Wire‐Arc Additive Manufacturing Fe‐Based Multicomponent Alloy Structures

Advanced Engineering Materials, EarlyView.
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios, Anthony Gonzalez, Aleksander Aleman, Tyler Dolmetsch, Tanaji Paul, Arvind Agarwal   +5 more
wiley   +1 more source