Results 121 to 130 of about 1,072,724 (364)
Assessment of regional development level in Romania through Principal component analysis [PDF]
Journal of Central European AgricultureThis paper primarily aims to address aspects related to regional development in Romania, which has become a challenge both at the national and global level. The way regional development is approached is different, depending on the particularities of each
Ancuta Rotaru +5 more
doaj +1 more source
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis
, 2014 We propose a new high dimensional semiparametric principal component analysis (PCA) method, named Copula Component Analysis (COCA). The semiparametric model assumes that, after unspecified marginally monotone transformations, the distributions are ...
Han, Fang, Liu, Han
core +1 more source
The rs10191329 Risk Allele Is Associated With Pronounced Retinal Layer Atrophy in Multiple Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate whether the rs10191329 risk allele in the DYSF–ZNF638 locus, which is implicated in central nervous system resilience rather than immune‐mediated pathology, is associated with retinal layer thinning, a biomarker of neuroaxonal damage in relapsing multiple sclerosis (RMS). Methods From a prospective observational study,
Gabriel Bsteh +22 more
wiley +1 more source
SIAM Journal on Imaging Sciences, 2013 We describe a method for analyzing the shape variability of images, called geometric PCA. Our approach is based on the use of deformation operators to model the geometric variability of images around a reference mean pattern. This leads to a new algorithm for estimating shape variability.
Bigot, Jérémie +2 more
openaire +8 more sources
Optimizing Face Recognition Using PCA
, 2012 Principle Component Analysis PCA is a classical feature extraction and data representation technique widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has drawback of high computational especially
Abdullah, Manal +2 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective The optimal treatment for neurosarcoidosis myelitis is uncertain. We characterize incident neurosarcoidosis myelitis and assess treatment response by MRI and clinical scales. Methods Incident probable or definite neurosarcoidosis myelitis in adults was retrospectively identified from 13 academic medical centers.
Giovanna S. Manzano +39 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Epilepsy is increasingly associated with immune dysregulation and inflammation. The T cell receptor (TCR), a key mediator of adaptive immunity, shows repertoire alterations in various immune‐mediated diseases. The unique TCR sequence serves as a molecular barcode for T cells, and clonal expansion accompanied by reduced overall TCR ...
Yong‐Won Shin +12 more
wiley +1 more source
Clinical Characteristics and Outcomes of Early‐Onset Versus Late‐Onset LGI1‐Antibody Encephalitis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Leucine‐rich glioma‐inactivated 1 antibody (LGI1‐Ab) encephalitis predominantly affected older individuals, but has also been reported in younger patients. However, the demographic, clinical, and prognostic characteristics of early‐onset LGI1‐Ab encephalitis have yet to be systematically elucidated. This study aims to systematically
Yu Kong +7 more
wiley +1 more source
Qualitative and quantitative evaluation of surface water using statistical analysis in Azna River, Lorestan [PDF]
محیط زیست و مهندسی آب, 2016 Water pollution in recent decades is as serious threat to the human and natural ecosystem so that assessing changes water quality are one of the most important topics for desirable use .
Artimes Ghassemi Dehnavi +4 more
doaj
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source