This study introduces an alignment-free computational framework for identifying microbial bioremediation potential, establishing a standardized, multi-domain dataset encompassing Bacteria, Protists, Archaea, and Fungi, and integrating metadata on polymer interactions to fill existing data gaps.
U. Luke, Emem Okon Abang, Etimbuk Daniel Akpan et al.· E3S Web of Conferences· 0 citations
This work proposes an intelligent, lightweight Tiny LSTM–GRU hybrid IDS on the edge to monitor device-generated behavioral patterns in real time, with minimal computational and energy overhead, and proposes an adaptive FedProx-based weighted federated learning framework.
Emmanuel Udok, B. Stephen, U. Luke et al.· E3S Web of Conferences· 0 citations
This approach combines semantic understanding of clinical narratives with structural modeling of patient-disease-treatment relationships and successfully validates synthetic EHR data utility for privacy-preserving healthcare AI development while addressing critical requirements necessary for clinical decision support s...
U. Luke, P. Asuquo, Victor Anaga et al.· E3S Web of Conferences· 0 citations
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