Called Torque Clustering, this method could pave the way for truly autonomous AI. Unlike traditional methods that rely on ...

Linear normalization, which is most common, involves shifting the number axis so the data is balanced around zero, and then ...

About every 10 minutes, it seems, a new article about a "revolutionary breakthrough" in AI hits my screen. A new approach, a ...

Researchers have developed Torque Clustering, a new AI algorithm that mimics natural intelligence, enabling unsupervised ...

This paper proposed an energy-efficient adaptive clustering routing algorithm named MPDE&VSSLS-SIACR to minimize the energy consumption of WSNs and prolong the network lifespan. Here, SIACR is a swarm ...

This valuable study presents a mouse gastruloid model that can be used to generate hematopoietic progenitors as well as leukemic cells. However, in its current form, the manuscript is inadequate ...

This R package (Hahsler, Piekenbrock, and Doran 2019) provides a fast C++ (re)implementation of several density-based algorithms with a focus on the DBSCAN family for clustering spatial data. The ...