For healthcare datasets, it is often impossible to combine data samples from multiple sites
due to ethical, privacy, or logistical concerns. Federated learning allows for the utilization of …

Multiple organizations in social manufacturing can collaborate on high-quality product defect
detection with social networks. Federated learning (FL) is an emerging paradigm where …

In recent years, the epidemic of communicable diseases has boosted the prevalence of
online teaching activities. But how to make smart evaluation towards teaching effect has …

In recent times, there has been a notable rise in the utilization of Internet of Medical Things
(IoMT) frameworks particularly those based on edge computing, to enhance remote …

The utilization of intelligent computing in digital teaching quality evaluation has been a
practical demand in smart cities. Currently, related research works can be categorized into …

Distributed learning empowers social media platforms to handle massive data for image
sentiment classification and deliver intelligent services. However, with the increase of …

Heart disease is a leading global cause of death, while federated learning (FL) is an
effective way to predict it. Due to patient privacy concerns and the centralized nature of …

The application of 3D reconstruction technology in building images has been a novel
research direction. In such scenes, the reconstruction with proper building details remains …

This work is confronted with hospital accounting management systems where business
volume is usually large and trivial. While designing system prototype and processing …

With a high proportion of distributed source–grid–load–storage resources penetrating into
the distribution network, multi-flow aggregated energy dispatch is essential to enhance …