Abstract: Principal Component Analysis (PCA) aims to acquire the principal component space containing the essential structure of data, instead of being used for mining and extracting the essential ...
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 ...
Nuclear imaging for industrial process analysis and non-destructive component testing has been around for longtime, but progression and innovation in this field has been limited and not as advanced ...
Ditch the boring resume format on LinkedIn! Craft a compelling narrative in your experience section showcasing your "why," origin story, and achievements with specific results. Use clear language, ...
1 Department of Civil Engineering, College of Engineering and Technology, Mbeya University of Science and Technology, Mbeya, Tanzania. 2 Department of Earth Sciences, College of Science and Technical ...
Abstract: Robust tensor principal component analysis (RTPCA) based on tensor singular value decomposition (t-SVD) separates the low-rank component and the sparse component from the multiway data. For ...
© 2024 American Chemical Society and Division of Chemical Education, Inc. Article Views are the COUNTER-compliant sum of full text article downloads since November ...
The authors present a critique of current usage of principal component analysis in geometric morphometrics, making a compelling case with benchmark data that standard techniques perform poorly. The ...
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