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Found 9 papers, 1 papers with code
Equitable Networked Microgrid Topology Reconfiguration for Wildfire Risk Mitigation
Increasing amount of wildfires in recent years consistently challenges the safe and reliable operations of power systems.
A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems
Accurate and quick identification of high-impedance faults is critical for the reliable operation of distribution systems.
LLMs may Dominate Information Access: Neural Retrievers are Biased Towards LLM-Generated Texts
We refer to this category of biases in neural retrieval models towards the LLM-generated text as the \textbf{source bias}.
Complementary and Integrative Health Lexicon (CIHLex) and Entity Recognition in the Literature
Results: From the 198 unique concepts in CIHLex, 62. 1% could be matched to at least one term in the UMLS.
Optimal Power System Topology Control Under Uncertain Wildfire Risk
Wildfires pose a significant threat to the safe and reliable operation of electric power systems.
Appliance Level Short-term Load Forecasting via Recurrent Neural Network
Accurate load forecasting is critical for electricity market operations and other real-time decision-making tasks in power systems.
Scalable Learning for Optimal Load Shedding Under Power Grid Emergency Operations
Effective and timely responses to unexpected contingencies are crucial for enhancing the resilience of power grids.
Discovering novel drug-supplement interactions using a dietary supplements knowledge graph generated from the biomedical literature
MATERIALS AND METHODS: We created SemRepDS (an extension of SemRep), capable of extracting semantic relations from abstracts by leveraging a DS-specific terminology (iDISK) containing 28, 884 DS terms not found in the UMLS.
Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: A scoping review
Keywords: Social and Behavioral Determinants of Health, Artificial Intelligence, Electronic Health Records, Natural Language Processing, Predictive Model
