Digital Twin (DT) ecosystems integrate heterogeneous computational models to represent complex systems under evolving, purpose-specific objectives. Systematic reuse of existing high-quality models and datasets is essential for scalable DT development, yet is constrained by heterogeneity in semantic intent, data structu...
N. Soveizi, Milan Kopp, Parinaz Rashidi et al.· 0 citations
LLMCrater is a lifecycle-aware metadata generation framework that combines Large Language Models (LLMs) with stage-specific RO-Crate metadata profiles that progressively enriches metadata across four research lifecycle stages while remaining compatible with RO-Crate~1.1 and EOSC metadata recommendations.
Dani Termaat, N. Soveizi, Zhi-Ming Zhao et al.· 0 citations
Experimental results demonstrate that the proposed CNASIM approach achieves good performance in terms of modeling flexibility, simulation accuracy, and applicability to complex scenarios, making it a practical aid for system designers and researchers to evaluate and optimize cloud-native applications efficiently.
Zeng-Yi Wang, Paul Daniëlse, Zhi-Ming Zhao· International Conference on...· 0 citations
A lifecycle-aware framework that integrates quantitative software quality assessment with Large Language Model (LLM)-based code refinement is proposed and the potential of metric-driven LLM feedback for research software quality improvement is demonstrated while highlighting its inherently multi-objective nature.
Nafis Tanveer Islam, N. Soveizi, Yutong Li et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.