Abstract: Principal Component Analysis (PCA) remains a fundamental technique for unsupervised dimensionality reduction. However, its traditional centralized implementation poses challenges in the ...
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 ...
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 ...
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 ...
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ABSTRACT: This study investigates the use of a decision tree classification model, combined with Principal Component Analysis (PCA), to distinguish between Assam and Bhutan ethnic groups based on ...
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