Results 111 to 120 of about 34,052 (223)

Gaussian Mixture Model Based Bayesian Learning for Sparse Channel Estimation in Orthogonal Time Frequency Space Modulated Systems

IEEE Open Journal of Vehicular Technology
A novel Gaussian mixture model (GMM)–aided sparse Bayesian learning (SBL) framework is proposed for channel state information (CSI) estimation in orthogonal time-frequency space (OTFS) modulated systems. The key attribute of the proposed algorithm
Surbhi Gehlot, Suraj Srivastava, Sandeep Kumar Yadav, Lajos Hanzo   +3 more
doaj   +1 more source

Ground‐Motion Characterization for the 2025 U.S. National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands

Earthquake Spectra, Volume 42, Issue 2, May 2026.
We develop the ground‐motion characterization (GMC) for the 2025 U.S. National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands (NSHM‐PRVI) for earthquakes in active crustal, subduction interface, and subduction intraslab regimes. Using ground‐motion models (GMMs) from the Next‐Generation Attenuation (NGA)‐West2 and NGA‐Subduction ...
Morgan P. Moschetti, Brad T. Aagaard, Kyle B. Withers, Kevin Milner, Jason Altekruse, Julie Herrick, Peter M. Powers, Sanaz Rezaeian, Allison M. Shumway, William Stephenson   +9 more
wiley   +1 more source

2025 U.S. Geological Survey National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands: Overview of Model and Hazard Results

Earthquake Spectra, Volume 42, Issue 2, May 2026.
The U.S. Geological Survey recently updated the National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The first version of the PRVI NSHM was released in 2003, and therefore this 2025 update includes over 20 years of new geologic, geophysical, and engineering data, methods, and models.
Allison M. Shumway, Kevin R. Milner, Peter M. Powers, Morgan P. Moschetti, Jason M. Altekruse, Julie A. Herrick, Andrea L. Llenos, Kyle B. Withers, Edward H. Field, Brad T. Aagaard, Richard W. Briggs, Alexandra E. Hatem, Kirstie L. Haynie, Andrew J. Michael, Jessica A. Thompson Jobe, Kishor S. Jaiswal, Brandon S. Clayton, Nicolas Luco, Mark D. Petersen, Sanaz Rezaeian, Thomas L. Pratt, Yuehua Zeng   +21 more
wiley   +1 more source

From Low Field to High Value: Robust Cortical Mapping From Low‐Field MRI

Human Brain Mapping, Volume 47, Issue 7, May 2026.
Recon‐any processes a brain MRI acquired with arbitrary contrast, resolution, and field strength to generate morphometric measurements comparable to FreeSurfer's recon‐all, including cortical (parcellation, thickness, etc.) and volumetric (segmentation, regional volumes) outputs.
Karthik Gopinath, Annabel Sorby‐Adams, Jonathan Williams‐Ramirez, Dina Zemlyanker, Jennifer Guo, David Hunt, Christine L. Mac Donald, C. Dirk Keene, Timothy Coalson, Matthew F. Glasser, David Van Essen, Matthew S. Rosen, Oula Puonti, W. Taylor Kimberly, Juan Eugenio Iglesias, Alzheimer's Disease Neuroimaging Initiative   +15 more
wiley   +1 more source

Unsupervised Work Behavior Pattern Extraction Based on Hierarchical Probabilistic Model

IEEJ Transactions on Electrical and Electronic Engineering, Volume 21, Issue 5, Page 693-703, May 2026.
In this study, we address the challenge of analyzing worker behaviors in high‐mix, low‐volume production environments, where traditional supervised learning methods struggle owing to the lack of labeled data and task variability among workers. To overcome these issues, we propose a novel hierarchical approach for unsupervised behavior pattern ...
Issei Saito, Tomoaki Nakamura, Toshiyuki Hatta, Wataru Fujita, Shintaro Watanabe, Shotaro Miwa   +5 more
wiley   +1 more source

Electrochemical CO2 Reduction on a Bi–Sn Eutectic Alloy in Acidic Media for Formic Acid Production

ChemSusChem, Volume 19, Issue 8, 28 April 2026.
Acidic CO2 electrolysis enables direct formic acid production with minimal (bi)carbonate formation. A eutectic Bi–Sn gas‐diffusion electrode achieves 81.3% faradaic efficiency (FE) at −100 mA cm−2 and pH 3, retaining selectivity up to −400 mA cm−2 and stable operation for 100 h with < 10% FE loss.
Avni Guruji, Alejandro Cañete‐Arché, Yuvraj Y. Birdja, Ranjith Prasannachandran, Max García‐Melchor, Deepak Pant   +5 more
wiley   +1 more source

A Measurement Error Model Based on Finite Mixture of the Skew-Normal Distributions for Brain MR Image Segmentation

IEEE Access
The accuracy of medical image segmentation plays a crucial role in assisting with diagnosis. One commonly used method is the Gaussian mixture model (GMM) due to its high accuracy and low complexity.
Kaili Zhang, Xiaoxu Zhu
doaj   +1 more source

A feature restoration for machine learning on anti-corrosion materials

Case Studies in Chemical and Environmental Engineering
Materials informatics often struggles with small datasets. Our study introduces the Gaussian Mixture Model Virtual Sample Generation (GMM-VSG) approach to enhance feature correlation by generating virtual samples.
Supriadi Rustad, Muhamad Akrom, Totok Sutojo, Hermawan Kresno Dipojono   +3 more
doaj   +1 more source

Enhanced diagnosis of diabetic retinopathy: integrating advanced algorithms for automated detection and classification. [PDF]

Int J Ophthalmol
Murali E, Prasad T, Hari Krishna J, Sharief AH, Nandini P.   +4 more
europepmc   +1 more source

Clustering ensemble method integrating Gaussian mixture model and three-way decision (GMM-3WD-CE). [PDF]

Sci Rep
Ma Y, Li Z.
europepmc   +1 more source