Microgravity experiments on the collisional behavior of Saturnian ring particles

In this paper we present results of two novel experimental methods to investigate the collisional behavior of individual macroscopic icy bodies. The experiments reported here were conducted in the microgravity environments of parabolic flights and the Bremen drop tower facility. Using a cryogenic parabolic-flight setup, we were able to capture 41 near-central collisions of 1.5-cm-sized ice spheres at relative velocities between 6 and $22 \mathrm{cm s^{-1}}$. The analysis of the image sequences provides a uniform distribution of coefficients of restitution with a mean value of $\overline{\varepsilon} = 0.45$ and values ranging from $\varepsilon = 0.06$ to 0.84. Additionally, we designed a prototype drop tower experiment for collisions within an ensemble of up to one hundred cm-sized projectiles and performed the first experiments with solid glass beads. We were able to statistically analyze the development of the kinetic energy of the entire system, which can be well explained by assuming a granular `fluid' following Haff's law with a constant coefficient of restitution of $\varepsilon = 0.64$. We could also show that the setup is suitable for studying collisions at velocities of $< 5 \mathrm{mm s^{-1}}$ appropriate for collisions between particles in Saturn's dense main rings.Comment: Accepted for publication in the Icarus Special Issue "Cassini at Saturn

PulSync:the heart rate variability as a unique fingerprint for the alignment of sensor data across multiple wearable devices

Abstract Most off-the-shelf wearable devices do not provide reliable synchronization interfaces, causing multi-device sensing and machine learning approaches, e.g. for activity recognition, still to suffer from inaccurate clock sources and unmatched time. Instead of using active online synchronization techniques, such as those based on bidirectional wireless communication, we propose in this work to use the human heartbeat as a reference signal that is continuously and ubiquitously available throughout the entire body surface. We introduce PulSync, a novel approach that enables the alignment of sensor data across multiple devices utilizing the unique fingerprint-like character of the heart rate variability interval function. In an evaluation on a dataset from 25 subjects, we demonstrate the reliable alignment of independent ECG recordings with a mean accuracy of -0.71±3.44 samples, respectively -2.86±11.43 ms at 250 Hz sampling rate