This paper provides a comprehensive survey of Digital Twin Networks (DTNs) for 6G wireless systems, categorizing architectures, evaluating key enabling technologies like AI, ray-tracing, RIS, and MEC. It conducts a detailed computational feasibility analysis and maps these architectures to various 6G use cases while identifying critical open challenges.

This paper introduces Holonic Digital Twin Networks (HDT-Nets), a framework that transforms wireless networks into cognitive orchestrators for physical AI. It enables real-time collective reasoning by allowing holonic digital twins to actively perceive, infer, and act within dynamic physical environments.

This paper proposes "Precision Education," an AI-powered paradigm for higher education, aiming to shift from reactive to preventive student success by leveraging student digital twins, predictive analytics, and causal inference. It envisions a future where personalized academic and career pathways are dynamically optimized to enhance student outcomes.

This paper introduces a classification for software integration within Asset Administration Shells (AAS) based on runtime environments and functional components. It systematically analyzes different architectural approaches, evaluating their impact on software quality criteria and relevance for various digital manufacturing use cases.