Physicists have for the first time observed light drifting sideways in discrete, quantized steps, reproducing a quantum Hall ...

GF2L is a self-supervised graph learning framework that operates in the frequency domain. It decomposes graph signals into low-, mid-, and high-frequency components, and integrates them through ...

ABSTRACT: Let G=( V,E ) be a graph. The first Zagreb index of a graph G is defined as ∑ u∈V d G 2 ( u ) , where d G ( u ) is the degree of vertex u in G . In this paper, we obtain two lower bounds ...

Update (Nov 20th, 2023): Working with large graphs (more than 100-200 nodes)? Consider using SparseDiff, a sparse version of DiGress: https://github.com/qym7 ...

Abstract: Deep learning models have shown great potential for fault location and classification tasks in distribution systems. Emerging multi-scale data sources such as waveform measurement units, ...

Abstract: The Wigner-Ville distribution (WVD) is a high-resolution time-frequency analysis method. However, the discrete WVD (DWVD) has the problem of a narrow frequency observation range. This is ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Quartz crystal microbalance with dissipation monitoring (QCM-D) has become a major ...

ABSTRACT: Although there are many measures of variability for qualitative variables, they are little used in social research, nor are they included in statistical software. The aim of this article is ...