This research provides density functions and descriptive statistics for the distance between points for basic shapes in Cartesian space. Both Euclidean and Rectilinear Distances are determined for ...

Abstract: Log-Euclidean distances are commonly used to quantify the similarity between positive definite matrices using geometric considerations. This paper analyzes the behavior of this distance when ...

When it comes to a driver fitting, the guiding principle is: “Ball speed is the most important factor.” This seems obvious. Make the ball go faster, and it’s always going to go farther. Generally, ...

It's an expensive proposition to build cars, especially when you've got to make sure every part of it complies with every letter of the law. That's why, sometimes, automakers will decide to use an off ...

Calculating the distance between two points is a fundamental concept in mathematics, often applied in various fields such as geometry, physics, and engineering. Understanding how to compute the ...

The identity of sensory stimuli is encoded in the spatio-temporal patterns of responses of the encoding neural population. For stimuli to be discriminated reliably, differences in population responses ...

Hi, I’m using pre-computed distances between points (euclidean distances) for training the hdbscan clustering model (by passing metric='precomputed'). But when I want to predict the clusters and ...

Frequent Student-Faculty contact in and out of the classroom is the single most important factor in student motivation and engagement. The attention of the faculty helps the student in hard times and ...