Published in: Digital Scholarship in the Humanities
Nov 14, 2025
Automatic text summarization (ATS) has seen considerable development, but state-of-the-art models depend on vast training data, limiting their applicability in scholarly communication and digital knowledge management for technical and domain-specific texts where annotated datasets are scarce. This article addresses this critical gap. First, to create a controlled, data-constrained setting for study, we created two specialized datasets: CS-Summ and Geog-Summ, comprising 794 and 438 manually summ...
Published in: IEEE Access
Nov 11, 2025
With the widespread use of renewable energy sources (RES) in the smart grid, the next generation power system, short-term load forecasting (STLF) is of critical importance in grid stability and energy optimization. Traditional STLF models include issues such as high computational cost, dependency on cloud infrastructure, and latency issues, which are undesirable for real-time energy management. To solve these issues, the EdgeAI paradigm, which combines edge computing and artificial intelligence...
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