The inverse relationship between track rebound rate and negative acceleration peaks for all hooves reflects the most important dynamic property of a track. Any factor that reduces negative acceleration of the hooves will increase stride efficiency by allowing smoother transition from retardation to propulsion and therefore may be important in determining the safety of racing surfaces.

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The characteristics of the acoustic emission signal during the tool wear process in end milling are analyzed, and a signal processing scheme for abstracting the mean time domain averaging deviation of the signal to monitor tool wear is proposed. Experiments indicate that the mean deviation value is sensitive to flank wear and its normalized value is not as dependent on milling parameters as the acoustic emission root mean square signal.

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