Graph theory within power electronics, developed over a 50-year span, is continually
evolving, necessitating ongoing research endeavors. Facing with the never-been-seen …

Machine learning (ML) and deep learning (DL), in particular, are common tools for anomaly
detection (AD). With the rapid increase in the number of Internet-connected devices, the …

Solar panels are exposed to various pollutants in outdoor environments, such as dust,
sediment, and bird excrement, which can cause the power generated by the panels to drop …

Compared with time-domain simulation (TDS), data-driven models show great advantage in
time consumption of the power system security analysis. This paper proposes a novel graph …

Human-oriented and machine-generated data in cyber-physical-social systems are often
complicated graph-structured. Graph-powered learning methods are conducive to …

Social networks, functioning as core platforms for modern information dissemination,
manifest distinctive user clustering behaviors and state transition mechanisms, thereby …

Knowledge graph builds the bridge from massive data generated by the interaction and
communication between various objects to intelligent applications and services in Internet of …

Nowadays, users can personalize Internet of Things (IoT) devices/web services via trigger-
action programming (TAP). As the number of connected entities grows, the relations of …

The segmentation of multiple sclerosis (MS) lesions from MR imaging sequences remains a
challenging task, due to the characteristics of variant shapes, scattered distributions and …

The automation of hand hygiene monitoring is critical in healthcare for ensuring clean hands
and preventing infectious disease spread. While advancements have been made, existing …