Principal component analysis (PCA) integrates multiple clinical indicators into a single score, providing a holistic assessment. Existing clinical indicators often fail to fully reflect health ...
Abstract: In semiconductor manufacturing, virtual metrology (VM) leverages high-dimensional sensor data for real-time quality estimation. However, excessive sensor deployment leads to increased ...
Computation of training set (X^T * W * X) and (X^T * W * Y) or (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm and Jensen (2025). FELBuilder is an automated ...
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 ...
ABSTRACT: Most studies on the relationship between lexical sophistication and writing quality operationalize lexical sophistication as distributional property of words and focus on argumentative ...
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 ...
Abstract: As a classic data processing tool, Principal Component Analysis (PCA) has been widely applied in various data analysis applications. To mitigate the high computational complexity of PCA on ...
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