AI Learns When to Hold Off: Smarter Water Maintenance Cuts Service Failures
A new digital twin framework uses ensemble forecasting and a fast, explainable confidence index to defer non-critical water maintenance during ...
A new digital twin framework uses ensemble forecasting and a fast, explainable confidence index to defer non-critical water maintenance during ...
Researchers have developed a dual-path attention-augmented ResNet that recognizes radar jamming signals with 97.07 percent accuracy even at jamming-to-noise ratios ...
Researchers developed optimized hybrid XGBoost models that accurately predict blast-induced flyrock distances at Iran's Sungun Copper Mine while identifying powder ...
A rapid review of twelve studies finds that artificial intelligence can sharpen health predictions from weather data, but poor reporting ...
A new perspective argues that human factors and ergonomics methods are essential to fixing agriculture's stubbornly low adoption of Industry ...
A sensorized ink pen developed by Politecnico di Milano and the University of Insubria accurately detected writing difficulties in more ...
Researchers have developed CropFusionNet, an interpretable deep learning framework that forecasts wheat, barley, and maize yields across Germany with benchmark-beating ...
Researchers have developed UbiQVision, a framework that fuses explainable AI attributions from deep learning ensembles using Dempster–Shafer evidence theory to ...
Researchers have developed an explainable AI framework that combines reflective listening, large language models, and knowledge graph reasoning to support ...
Researchers have developed P2CE, a model-agnostic algorithm that generates counterfactual explanations for machine learning decisions that are both plausible and ...
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© 2025 Scienmag - Science Magazine