Abstract: Hierarchical density based spatial clustering is a state-of-the-art clustering algorithm that is widely used by the research community for the analysis of spatial data. This popularity is in ...
Objective: This study analyzes university students’ physical fitness and, based on the results, applies cluster analysis to identify homogeneous groups with aim to optimize physical education programs ...
Background: It is still unclear whether traditional resistance training (TRT) provides the best or optimal stimulation for increasing maximum strength compared to cluster training (CT). Objective: ...
A new computational method gleans more information than its predecessors from maps showing how galaxies are clustered and threaded throughout the universe. Research led by the University of Michigan ...
Q. You explained Excel’s Scenario Manager in your November 2024 Tech Q&A article and Goal Seek in your December 2024 Tech Q&A article. Can you please explain the final What-If Analysis tool: Data ...
Background: Heart failure (HF) is a heterogeneous syndrome with high mortality. Previous work characterizing HF subgroups primarily relied on clinical data to cluster patients, an approach constrained ...
No cluster D of personality disorders is currently featured in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition, text revision (DSM-5-TR). Only clusters A, B, and C are ...
Asset tracking is crucial for businesses of all sizes to know what they own and where to find it. But not every business needs a premium solution. Starting with an asset tracking Excel template or a ...
Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...
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