Abstract: As a widely used method in signal processing, Principal Component Analysis (PCA) performs both the compression and the recovery of high dimensional data by leveraging the linear ...

Inside living cells, mitochondria divide, lysosomes travel, and synaptic vesicles pulse—all in three dimensions (3Ds) and constant motion. Capturing these events with clarity is vital not just for ...

AI search tools are on the rise, but SEO fundamentals remain critical. Learn how the two intersect and what it means for your strategy. The explosive rise of ChatGPT and other generative AI tools has ...

Background/objectives: Dietary patterns play an important role in regulating serum uric acid (SUA) levels in the body. Recently, compositional data analysis (CoDA) has been proposed as an alternative ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...

Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, College of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China. With the ...

Introduction: This study investigates an approach for defect characterization in non-ferromagnetic materials by combining Pulsed Alternating Current Field Measurement (PACFM) with Principal Component ...

ABSTRACT: This study applies Principal Component Analysis (PCA) to evaluate and understand academic performance among final-year Civil Engineering students at Mbeya University of Science and ...

📌 This repository provides the official MATLAB implementation of the PCSSI algorithm proposed in our preprint. Stochastic Subspace Identification (SSI) is widely used in modal analysis of engineering ...

Abstract: Principal component analysis (PCA) stands as one of the most extensively utilized techniques in dimensionality reduction. However, PCA uses least squares (LS) loss which may yield poor ...