Results 81 to 90 of about 1,557,577 (150)
SPARK‐ICA: Guided Frequency‐Resolved Dynamic Spatial ICA Reveals Fine‐Scale fMRI Network Dynamics
Human Brain Mapping, Volume 47, Issue 16, November 2026.SPARK–ICA is a frequency‐resolved dynamic spatial ICA framework that decomposes time‐varying fMRI network maps into multiple spatial frequency bands. Applied to schizophrenia resting‐state data, it reveals complementary abnormalities in stable connectivity and rapid high‐frequency network interactions that are not captured by conventional dynamic ...
N. Behzadfar, A. Iraji, V. Calhoun
wiley +1 more source
Computational Models of the Foreign Body Response: A Focus on Biomaterial Properties
Journal of Biomedical Materials Research Part A, Volume 114, Issue 11, November 2026.ABSTRACT The foreign body response (FBR) is the main biological process governing the long‐term performance and safety of implantable biomaterials. As the FBR is complex, multifactorial, and unfolds over extended time scales, making in vitro replication challenging, standard biological evaluation frameworks continue to rely primarily on in vivo testing
Matilde Marradi +5 more
wiley +1 more source
High‐Dimensional Cumulative Sum Control Charts for Industrial Measurement Systems
Quality and Reliability Engineering International, Volume 42, Issue 7, Page 4342-4361, November 2026.ABSTRACT High dimensional sensing in modern factories and energy assets produces thousands of correlated signals. Detecting small process shifts is challenging because many classical multivariate charts lose power or become unstable. We present two cumulative sum procedures for two sample monitoring that remain effective when the number of variables is
Osama Alhadi +3 more
wiley +1 more source
Transactions in GIS, Volume 30, Issue 7, November 2026.ABSTRACT Digital elevation models (DEMs) are widely used to characterize terrain and support applications ranging from geomorphology to environmental management. While traditional analyses rely on handcrafted geomorphometric features, advances in machine learning enable richer, data‐driven representations of topographic surfaces.
Thomas Schneidergruber, Johannes Scholz
wiley +1 more source
Journal of Geophysical Research: Atmospheres, Volume 131, Issue 20, 28 October 2026.Abstract Urban methane emissions remain highly uncertain due to the complexity of overlapping anthropogenic sources and limitations in current bottom‐up inventories. In this study, we apply a synthesis inversion framework to refine sector‐specific methane emissions for the Melbourne region in Australia, using in situ atmospheric observations and a ...
N. Shahrokhi +13 more
wiley +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
Advanced Engineering Materials, Volume 28, Issue 20, 21 October 2026.High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
, 2017 Multiscale entropy (MSE) is a widely-used tool for the analysis of biomedical signals. It was proposed to overcome the deficiencies of conventional entropy methods when quantifying the complexity of time series.
Edinburgh Neuroscience +3 more
core +1 more source
Multivariate Multiscale Symbolic Entropy Analysis of Human Gait Signals
, 2017 The complexity quantification of human gait time series has received considerable interest for wearable healthcare. Symbolic entropy is one of the most prevalent algorithms used to measure the complexity of a time series, but it fails to account for the ...
Jian Yu +5 more
core +1 more source
Multivariate Multiscale Complexity Analysis of Self-Reproducing Chaotic Systems
, 2018 Designing a chaotic system with infinitely many attractors is a hot topic. In this paper, multiscale multivariate permutation entropy (MMPE) and multiscale multivariate Lempel–Ziv complexity (MMLZC) are employed to analyze the complexity of those ...
Shaobo He +3 more
core +1 more source
Multiscale complex network for analyzing experimental multivariate time series
, 2015 The multiscale phenomenon widely exists in nonlinear complex systems. One efficient way to characterize complex systems is to measure time series and then extract information from the measurements.
Yong Zou +5 more
core +1 more source