Structure Analysis of Network Traffic Matrix Based on Relaxed Principal Component Pursuit
Zhe Wang, Kai Hu, Ke Xu, Baolin Yin
openalex +1 more source
ABSTRACT This article explores how artificial intelligence (AI) can support online adult learning by aligning with Knowles’ four principles of andragogy: involvement, experience, problem‐centeredness, and relevance. Three activities were analyzed using a comparative case study (CCS) method.
Xi Lin, Steve W. Schmidt
wiley +1 more source
Pattern Recognition of Pyrolysis Bio-Oils by GC×GC-TOFMS with Tile-Based Feature Selection and Principal Component Analysis. [PDF]
Couto ACF +8 more
europepmc +1 more source
ABSTRACT Objective Cognitive impairment (CI) affects the quality of life in multiple sclerosis (MS). Identifying influencing factors is key to improving CI monitoring. This systematic review and meta‐analysis examines clinical and sociodemographic variables impacting the cognitive screening Symbol Digit Modalities Test (SDMT) performance across MS ...
Katalin Lugosi +8 more
wiley +1 more source
Designing a multidimensional vulnerability index for supervising dengue cases from 2015 to 2020 in a low/middle-income country: A spatial principal component analysis. [PDF]
Moreno-López S +2 more
europepmc +1 more source
Pre‐Diagnostic Features of Multiple Sclerosis in a Diverse UK Cohort: A Nested Case–Control Study
ABSTRACT Background Many patients with Multiple Sclerosis (MS) experience nonspecific symptoms prior to diagnosis. This period—the 'MS prodrome'—has been described in socio‐economically homogeneous cohorts to date. It remains unclear to what extent events prior to an MS diagnosis differ according to social determinants of health. Methods We conducted a
Pooja Tank +3 more
wiley +1 more source
Longitudinal changes in salivary biomarkers in Parkinson’s disease (PD) from early (T0) to 4‐year follow‐up (T1), quantified by ELISA: oligomeric and total α‐synuclein, total and phosphorylated tau, MAP1LC3B (autophagy), and TNFa (inflammation). Blue arrows indicate direction of change at T1 vs T0 (up = increase; down = decrease).
Maria Ilenia De Bartolo +13 more
wiley +1 more source
Feature level quantitative ultrasound and CT information fusion to predict the outcome of head & neck cancer radiotherapy treatment: Enhanced principal component analysis. [PDF]
Moslemi A +4 more
europepmc +1 more source
Phenotyping Chronic Obstructive Pulmonary Disease Through Principal Component Analysis: Identification of Clinical Clusters. [PDF]
Mekov EV +6 more
europepmc +1 more source

