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Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...

Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Abstract Detecting epileptic seizures from electroencephalogram (EEG) signals presents a significant challenge due to the nonlinear and non-stationary nature of brain activity. In this study, we propose a hybrid classifi...

Abstract The increasing number of Internet of Things (IoT) devices demands a rigid and adaptive routing methodologies to ensure the reliable communication especially for the low-power and lossy networks. The Routing Prot...

Abstract Smart home networks are a rapidly evolving part of the Internet of Things (IoT), where connected devices exchange information to automate energy use, enhance comfort, and improve user safety. Despite their benef...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

Abstract With the evolution of interactive art installations towards 4 K/8 K ultra-high-definition streaming and large-scale multi-point interaction, existing 5G networks face challenges in maintaining the "flow state"...

Abstract The current English grammar error correction model still has low accuracy when dealing with complex sentences and long sentence dependencies. Therefore, this study proposes a Sequence-to-Sequence (Seq2Seq) model...