AI tools are frequently used in data visualization — this article describes how they can make data preparation more efficient ...

Abstract: cross-dimensional principal component analysis (CD-PCA). It is based on the semi-tensor product of matrices theory (STP), where a new projection rule is introduced to reduce dimensionality ...

The N’Guérédonké deposit, Faranah Province (Republic of Guinea), is part of the Leonian-Liberian crystalline shield, consisting of Archean granitoids and greenstone formations with a syn-tectonic ...

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 ...

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 ...

With the increasing complexity of analytical data nowadays, great reliance on statistical and chemometric software is quite common for scientists. Powerful open-source software, such as Python, R, and ...

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 ...

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 ...

Ensure your data are in the proper format. The first column (index 0) should consist of the species name or other identifying information. The second column (index 1) should consist of a standard body ...