Hybrid quantum key distribution (QKD) and post-quantum cryptography (PQC) systems are often described as layered security architectures, yet deployments face a basic provisioning question: how many QKD bits are needed, and where should they enter an ML-KEM-based system? This article develops a placement-aware framework...
Chavis Srichan, S. Wongthanavasu, P. Danvirutai· IEEE Access· 0 citations
HGKAN (Hyperbolic Graph-Based Kolmogorov–Arnold Network), a unified framework that combines hyperbolic representation learning, graph neural networks, and KAN-based nonlinear fusion for social recommendation, is proposed.
Nikorn Kannikaklang, S. Wongthanavasu· IEEE Access· 0 citations
GCTMR (Graph Contrastive Transformer for Multibehavior Recommendation), a framework that integrates graph-based contrastive learning with a behavior-aware Transformer architecture, is proposed, with particularly remarkable performance under sparse data conditions where traditional methods struggle most.
Nikorn Kannikaklang, S. Wongthanavasu· IEEE Access· 0 citations
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