Soft-MSM is a smooth, gradient-enabled version of the context-aware MSM distance for time series alignment that outperforms Soft-DTW alternatives in clustering and nearest-centroid classification.
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QQMR applies Q-learning with priority queuing and fuzzy C-means clustering to select multipath routes in IoMT body area networks, raising packet delivery while cutting delay, overhead, and energy use.
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Soft-MSM: Differentiable Context-Aware Elastic Alignment for Time Series
Soft-MSM is a smooth, gradient-enabled version of the context-aware MSM distance for time series alignment that outperforms Soft-DTW alternatives in clustering and nearest-centroid classification.
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A Q-learning-based QoS-aware multipath routing protocol in IoMT-based wireless body area network
QQMR applies Q-learning with priority queuing and fuzzy C-means clustering to select multipath routes in IoMT body area networks, raising packet delivery while cutting delay, overhead, and energy use.