Security networks as one of the biggest issue for network managers with the exponential
growth of devices connected to the internet. Kee** a big and diverse network running …

This study seeks to explain why telecom customers would continue to use mobile value-
added services (MVAS), including information, communication, entertainment, and …

The Internet of Things (IoT) is rapidly growing and is projected to develop in future years.
The IoT connects everything from Closed Circuit Television (CCTV) cameras to medical …

Human activity recognition (HAR) using wearable sensors enables continuous monitoring
for healthcare applications. However, the conventional centralised training of deep learning …

Federated Learning (FL) enhances predictive accuracy in load forecasting by integrating
data from distributed load networks while ensuring data privacy. However, the …

Increased demand for fast edge computation and privacy concerns have shifted researchers'
focus towards a type of distributed learning known as federated learning (FL). Recently …

As data become increasingly abundant and diverse, their potential to fuel machine learning
models is increasingly vast. However, traditional centralized learning approaches, which …

The integration of artificial intelligence (AI) into energy networks significantly advanced short-
term forecasting, particularly in smart meter applications. However, as distributed energy …

Predicting signal blockages in millimetre-wave and terahertz networks is essential for
enabling proactive handover (PHO) and ensuring seamless connectivity. Existing …

Federated Learning (FL) in load forecasting improves predictive accuracy by leveraging
data from distributed load networks while preserving data privacy. However, the …