Abstract: Principal Component Analysis (PCA) is a workhorse of modern data science. While PCA assumes the data conforms to Euclidean geometry, for specific data types, such as hierarchical and cyclic ...
ABSTRACT: Pyrethrum (Chrysanthemum cinerariaefolium L.) is an industrial crop with complex morphology and diverse physico-mechanical properties that jeopardize the optimal design of precision ...
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 ...
PCA, CPCA and PBA all identified three dietary patterns, with a common “traditional southern Chinese” pattern high in rice and animal-based foods and low in wheat products and dairy. Only this pattern ...
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 ...
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 ...
ABSTRACT: Man is always in search of knowledge; the discoveries of fire, animals’ domestication and agricultural procedures, astronomy or navigation, all allowed at their time important leaps in ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results