The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has ...
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 ...
Spectral speech features may serve as noninvasive biomarkers for monitoring attention and executive function in major depressive disorder.
Abstract: Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover the dominant patterns of variability within a population. Despite its ability to represent a ...
Suzanne is a content marketer, writer, and fact-checker. She holds a Bachelor of Science in Finance degree from Bridgewater State University and helps develop content strategies. The term notional ...
ABSTRACT: This article examines the effect of economic vulnerability on inclusive growth across 49 developing countries from 1991 to 2020, focusing on the mitigating role of agricultural structural ...
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 ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Mass spectrometry imaging (MSI) is constantly improving in spatial resolving power, ...
This paper develops a procedure for uncovering the common cyclical factors that drive a mix of stationary and nonstationary variables. The method does not require knowing which variables are ...
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