Ripples maintain time-locked occurrence across the septo-temporal axis and hemispheres while showing local phase coupling, revealing a dual mode of synchrony in CA1 network dynamics.

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...

Abstract: In a multi-source localization system, direction of arrival (DOA) estimation of angles always suffers from errors due to noise interference, sensor position inaccuracies, and other factors.

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...

The order would allow people to invest in crypto and private equity. President Donald Trump signed an executive order Thursday that will let Americans invest their 401(k) retirement savings in ...

I think this work might be interesting to the scikit-community. In this work, we discuss 2 classical algorithms for an sampling-based version of k-means, which return an epsilon-approximation of the ...

Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...

When it comes to teaching math, a debate has persisted for decades: How, and to what degree, should algorithms be a focus of learning math? The step-by-step procedures are among the most debated ...

Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering algorithms to a ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...