Stop letting AI pick your passwords. They follow predictable patterns instead of being truly random, making them easy for hackers to guess despite looking complex. Two independent research programs, ...

I stumbled upon an excellent LinkedIn article by Sergio Albea titled "Applying Shanon Entropy to SenderDomains via Kusto" this morning where he built a heuristic measurement function to detect ...

Image segmentation is a fundamental process in digital image analysis, with applications in object recognition, medical imaging, and computer vision. Traditional segmentation techniques often struggle ...

Monoallelic gene expression is a pivotal phenomenon in developmental biology, notably through the influence of imprinted genes. Our model predicts that monoallelic expression generates expression ...

In this study, we analyze the changes over time in the complexity and structure of words used in article titles and the connections between articles in citation networks, focusing on the topic of ...

Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. Article Views ...

The tendency of many cellular proteins to form protein-rich biomolecular condensates underlies the formation of subcellular compartments and has been linked to various physiological functions.

A. A. B. Pessa, H. V. Ribeiro, ordpy: A Python package for data analysis with permutation entropy and ordinal network methods, Chaos 31, 063110 (2021). arXiv:2102. ...

The entropy function takes as input a vector of frequency counts (the observed frequencies for a set of classes or states) and an alphabet size (the number of classes ...