Results 61 to 70 of about 2,604 (146)

Principal Component Analysis for High‐Dimensional Approximate Factor Models in Time Series: Assumptions, Asymptotic Theory, and Identification

Journal of Time Series Analysis, EarlyView.
ABSTRACT We consider estimation of large approximate factor models in high‐dimensional panels of stationary time series using Principal Component Analysis (PCA). We review the key results establishing the necessary and sufficient conditions for consistency and asymptotic normality of the estimators, which hold when both the cross‐sectional dimension n$$
Matteo Barigozzi
wiley   +1 more source

A New Physics‐Constrained Neural Network Approach to Retrieve CH4 Vertical Profiles From Hyperspectral Infrared Data

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 21, 16 November 2026.
Abstract Methane (CH4 ${\text{CH}}_{4}$) is a critical greenhouse gas, and accurate monitoring of its vertical distribution is essential for understanding its radiative impact and identifying emission sources. This paper introduces a novel methodology using a physics‐constrained neural network based on soft constraints to retrieve CH4 ${\text{CH}}_{4}$
Rocco Giosa, Marco D’Emilio, Pamela Pasquariello, Guido Masiello, Carmine Serio, Maria Ragosta, Francesco Carbone, Christian Natale Gencarelli, Italia De Feis, Diana Carolina Fonnegra Mora, Lorenzo Cassini, Raffaele Inglese, Giuliano Liuzzi   +12 more
wiley   +1 more source

An Ascorbic‐Acid Containing Poly(Carbonate) Urethane With Antioxidant Bioactivity for Application in Heart Valve Scaffold Development

Journal of Biomedical Materials Research Part A, Volume 114, Issue 11, November 2026.
ABSTRACT Prosthetic heart valve development consists of several branching, innovative strategies to mediate the complex native environment that wears down valve durability. Anti‐calcification treatments are being applied to pericardial tissue, durable polymers are being developed that mitigate oxidative degradation and stress cracking, and heart valve ...
Drake D. Pedersen, Keishi Kohyama, Taro Fujii, Marianna Barbuto, Sangho Ye, Sujeong Park, Flaviana Falci, Jooyoun Park, Keun Seok Seo, William Long, Antonio D'Amore, Seungil Kim, William R. Wagner   +12 more
wiley   +1 more source

Internet traffic data recovery via a low-rank spatio-temporal regularized optimization approach without d-th order T-SVD

Frontiers in Applied Mathematics and Statistics
Accurate recovery of Internet traffic data can mitigate the adverse impact of incomplete data on network task processes. In this study, we propose a low-rank recovery model for incomplete Internet traffic data with a fourth-order tensor structure ...
Yuxuan Duan, Chen Ling, Jinjie Liu, Xinmin Yang   +3 more
doaj   +1 more source

Low-Rank Tensor Completion for Image and Video Recovery via Capped Nuclear Norm

IEEE Access, 2019
Inspired by the robustness and efficiency of the capped nuclear norm, in this paper, we apply it to 3D tensor applications and propose a novel low-rank tensor completion method via tensor singular value decomposition (t-SVD) for image and video recovery.
Xi Chen, Jie Li, Yun Song, Feng Li, Jianjun Chen, Kun Yang   +5 more
doaj   +1 more source

Structural brain network measures are superior to vascular burden scores in predicting early cognitive impairment in post stroke patients with small vessel disease

NeuroImage: Clinical, 2019
Objectives: In this cross-sectional study, we aimed to explore the mechanisms of early cognitive impairment in a post stroke non-dementia cerebral small vessel disease (SVD) cohort by comparing the SVD score with the structural brain network measures ...
Jing Du, Yao Wang, Nan Zhi, Jieli Geng, Wenwei Cao, Ling Yu, Jianhua Mi, Yan Zhou, Qun Xu, Wei Wen, Perminder Sachdev   +10 more
doaj   +1 more source

Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change

NeuroImage: Clinical, 2017
Cerebral small vessel disease (SVD) is the primary cause of vascular cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS).
Owen A. Williams, Eva A. Zeestraten, Philip Benjamin, Christian Lambert, Andrew J. Lawrence, Andrew D. Mackinnon, Robin G. Morris, Hugh S. Markus, Rebecca A. Charlton, Thomas R. Barrick   +9 more
doaj   +1 more source

On‐Chip Photonic Neural Network Architectures

Advanced Optical Materials, Volume 14, Issue 39, 23 October 2026.
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong, Berkay Neseli, Seungyeon Cho, Seungsoo Lee, Yeonjun Kim, Seungyoon Choi, Hyo‐Hoon Park, Hamza Kurt   +7 more
wiley   +1 more source

AI‐Powered Personalization Across Digital Ecosystems: A Trust‐Centric Perspective on Intelligent, Ethical, and Adaptive User‐Centric Systems

Applied AI Letters, Volume 7, Issue 3, October 2026.
Hybrid and deep learning recommenders achieve high personalization accuracy, but sustainable adoption depends on trust: fairness, privacy, explainability and user control must be embedded across the entire personalization pipeline. ABSTRACT Personalization based on Artificial Intelligence (AI) has become a paradigm shift in user‐focused experiences in ...
Mohd Munazzer Ansari, Shailendra Kumar, Umair Tariq, Md Belal Bin Heyat   +3 more
wiley   +1 more source

A Hybrid Physics‐Informed Computational Framework for Adaptive Microrobotic Navigation and Causal Structure Discovery in Simulated Non‐Newtonian Environments

Applied Research, Volume 5, Issue 5, October 2026.
This study presents a hybrid AI framework that enables autonomous magnetic microrobots to navigate complex, non‐Newtonian tumor microenvironments. By integrating physics‐informed recurrent reinforcement learning with active persistent excitation, the system successfully infers hidden fluid rheology for precise targeted navigation and structural causal ...
Xinyuan Chen, Zanariah Abu Bakar, Mohd Nizam Husen   +2 more
wiley   +1 more source