Results 81 to 90 of about 25,782,438 (282)

How many separable sources? Model selection in independent components analysis.

PLoS ONE, 2015
Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent ...
Roger P Woods, Lars Kai Hansen, Stephen Strother   +2 more
doaj   +1 more source

High‐Resolution MRI Revealed Different Etiology‐Specific Associations With Cerebral Infarction in Adult Moyamoya Vasculopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective High‐resolution MRI enables detailed assessment of intracranial vessel wall pathology in moyamoya vasculopathy. We aimed to classify adult moyamoya vasculopathy etiologies using high‐resolution MRI and to examine subtype‐specific associations between high‐resolution MRI features and ischemic infarction.
Guangsong Han, Jiachun Pan, Yuehui Hong, Xiaoyuan Fan, Ming Yao, Lixin Zhou, Yicheng Zhu, Feng Feng, Jun Ni   +8 more
wiley   +1 more source

A Principal Component Analysis Framework for Evaluating Mining-Induced Risk: A Case Study of a Chilean Underground Mine

Applied Sciences
Mining-induced seismicity presents significant challenges to the safety and operational continuity of underground mines, particularly in deep and highly stressed environments.
Felipe Muñoz, Rodrigo Estay, Claudia Pavez-Orrego, Gonzalo Nelis   +3 more
doaj   +1 more source

Using principal component analysis to identify the component affecting skull weight of Japanese Quail [PDF]

Basrah Journal of Veterinary Research
Principal Component Analysis (PCA) is a powerful statistical tool used to reduce the complexity of large datasets while preserving significant variations.
israa Abd Alsada
doaj   +1 more source

Generalized power method for sparse principal component analysis [PDF]

In this paper we develop a new approach to sparse principal component analysis (sparse PCA). We propose two single-unit and two block optimization formulations of the sparse PCA problem, aimed at extracting a single sparse dominant principal component of
Journée, Michel, Nesterov, Yurii, Richtarik, Peter, Sepulchre, Rodolphe   +3 more
core  

Understanding Further the Phenotypic Spectrum of Central Nervous System Inflammatory Demyelinating Disorders Using Unsupervised Clustering

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec, Elif Everest, Melih Tutuncu, Ugur Bilge, Sabahattin Saip, Ugur Uygunoglu, Aksel Siva   +6 more
wiley   +1 more source

Designing a Hybrid Approach to Predict the Performance of Decision Making Units Based on Fuzzy Stochastic DEA and PCA [PDF]

چشم‌انداز مدیریت صنعتی, 2014
Data Envelopment Analysis is a management method which applied to performance analysis for decision making units. This paper presents a new hybrid approach based on fuzzy stochastic DEA (FSDEA) and principal component analysis (PCA) to predict efficiency
Ali Yaghoubi, Maghsoud Amiri, Azamdokht Safi Samghabadi   +2 more
doaj  

Plasma EV Proteomics Identifies ECM Remodeling and Inflammatory Proteins LUM and C7 as Candidate Biomarkers in FSHD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit, Chiranth K. Nagaraj, Jackson S. Newell, Kim Truc Nguyen, Xilal Y. Rima, Jacob Doon‐Ralls, Eduardo Reátegui, Jeffrey M. Statland, Rabi Tawil, Kevin M. Flanigan, Scott Q. Harper, Nizar Y. Saad   +11 more
wiley   +1 more source

Performance monitoring of MPC based on dynamic principal component analysis

, 2011
A unified framework based on the dynamic principal component analysis (PCA) is proposed for performance monitoring of constrained multi-variable model predictive control (MPC) systems.
Chen, Sheng, Tian, Xuemin, Cao, Yuping, Chen, Gongquan   +3 more
core   +2 more sources

Hyperspectral Dimensionality Reduction Based on Multiscale Superpixelwise Kernel Principal Component Analysis

Remote Sensing, 2019
Dimensionality reduction (DR) is an important preprocessing step in hyperspectral image applications. In this paper, a superpixelwise kernel principal component analysis (SuperKPCA) method for DR that performs kernel principal component analysis (KPCA ...
Lan Zhang, Hongjun Su, Jingwei Shen
doaj   +1 more source