Symmetry, Volume 17, Issue 5

Mixing time, as a key parameter for evaluating ladle refining efficiency, has long attracted extensive attention from researchers. In typical experimental studies, salt solution tracers are introduced into ladle water models to assess the degree of m...

This study proposes a novel two-dimensional hyperchaotic map model based on an orthogonal feedback mechanism, exhibiting dynamic behaviors with multistable characteristics and high complexity. By analyzing the homogeneous multistability of the system...

This study introduces a novel fractional-order derivative, termed the Mittag-Leffler–Caputo–Fabrizio (MLCF) fractional derivative, which is characterized by a singular kernel. Symmetry plays a key role in the structure and behavior of fra...

In the Heisenberg group Hn, we establish the local regularity theory for weak solutions to non-homogeneous degenerate nonlinear parabolic equations of the form ∂tu−∑i=12nXiAi(Xu)=K(x,t,u,Xu), where the nonlinear structure is modeled on...

Low-light image enhancement remains a challenging task in computer vision due to the complex interplay of noise, asymmetrical artifacts, illumination non-uniformity, and detail preservation. Existing methods such as traditional histogram equalization...

This study investigates the closed forms of Lucas matrices, with a particular emphasis on the nth powers of the tridiagonal symmetric Toeplitz matrix S4(x,y), whose entries are associated with Lucas numbers Ln. The analysis extends Filipponi’s...

Existing few-shot learning models leverage vision-language pre-trained models to alleviate the data scarcity problem. However, such models usually process visual and text information separately, which causes still inherent disparities between cross-m...

This article constructs all the anisotropic spaces of four-dimensional numbers in which the commutative and associative operations of addition and multiplication are defined. In this case, so-called “zero divisors” appear in these spaces....

Electrocardiogram (ECG) interpretation using deep learning models holds immense potential for improving cardiac diagnosis. However, existing models often suffer from overconfident predictions and lack the capability to directly quantify uncertainty,...

Although some progress has been made in deep learning-based remote sensing image change detection, the complexity of scenes and the diversity of changes in remote sensing images lead to challenges related to background interference. For instance, rem...