Lightweight convolutional neural network (CNN) models have proven effective in
recognizing common pest species, yet challenges remain in enhancing their nonlinear …

Background Identifying the cell types using unsupervised methods is essential for scRNA-
seq research. However, conventional similarity measures introduce challenges to single-cell …

Within the teaching-learning process, evaluation involves various mechanisms generated by
the teacher for its execution, such as identifying the elements to be evaluated, defining the …

Cluster analysis can be perceived as a problem of grouping data points according to their
mutual similarity. Clustering quality largely depends on choosing an effective distance …

This study explored the clustering based on arithmetic optimization algorithm (CAOA) and its
potential for addressing challenging clustering problems. CAOA is based on the arithmetic …

Ferroptosis is a regulated form of cell death that involves iron-dependent lipid peroxidation.
Ferroptosis-related genes (FRGs) play an essential role in the tumorigenesis of gastric …

The traditional K-means clustering method is often affected by the initial selection of center
points, as well as the presence of outliers and edge points during the iterative process. To …

This study uses information technologies to analyze the lifestyles of Cubans. Cluster
analysis is used to identify similarities in habits and lifestyles. Clustering results are …

The system in construction project management is constantly improving and increasing, and
the traditional method is no longer applicable to the nature of construction engineering …