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Testing learning-enabled cyber-physical systems with Large-Language Models: A Formal Approach
The integration of machine learning (ML) into cyber-physical systems (CPS) offers significant benefits, including enhanced efficiency, predictive capabilities, real-time responsiveness, and the enabling of autonomous operations.
PPG-based Heart Rate Estimation with Efficient Sensor Sampling and Learning Models
Moreover, our analysis showed that DT models with 10 to 20 input features usually have good accuracy, while are several magnitude smaller in model sizes and faster in inference time.
Efficient and Direct Inference of Heart Rate Variability using Both Signal Processing and Machine Learning
With this dataset, we developed HRV models that combine signal processing and ML to directly infer HRV.
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