7 天前 - … over data sharing access.This study uses ensemble deep learning architectures
to suggest new methods for identifying malevolent users accessing healthcare data in EHRs. …

23 天前 - … Techniques for machine learning and measurable … study proposes a novel method
for a deep learning-based fog computing-based privacy-preserving healthcare application. …

45 天前 - … In this study, a novel approach to cyberphysical system analysis based on 6G mobile
edge networks and machine learning modelling of smart healthcare systems is proposed. …

61 天前 - … , and RAN (Radio Access Network) and core. … network slicing technology exhibits
compatibility with emerging technologies such as deep learning, machine learning, and cloud …

86 天前 - … applications with high bandwidth and low latency. This is in spite of the O-RAN vision
to endow radio access networks (… analytics and machine learning application of another …

102 天前 - … The solution assigns apps by priority using a machine learning-based prediction
model … in Cloud Radio Access Networks (C-RANs) by addressing the Joint Radio Processing (…

111 天前 - … uses of 6G and beyond. It promotes openness and standardisation, increased flexibility
through the disaggregation of Radio Access Network (RAN) … Networking (SDN), Network …

126 天前 - … This is where new technologies such as machine learning and/or Deep learning
can help parsing Terabytes of data to predict better behavior for the 4.0 Industry. Regarding IIoT…

129 天前 - … Access Network (O-RAN) networks where we have a shared database within the
… machine learning (ML) models for spectrum sharing and interference mitigation applications …

173 天前 - … as deep neural networks, with state st serving as their input. Specifically, ϕ and
β represent the parameters for the Actor and Critic networks, respectively. The actor …