A multi-technology approach to identifying the reasons for lateral drift in professional and recreational darts

This work performs an extensive charterisation of precision targeted throwing in professional and recreational darts. The goal is to identify the contributing factors for lateral drift or throwing inaccuracy in the horizontal plane. A multitechnology approach is adopted whereby a custom built body area network of wireless inertial measurement devices monitor tilt, force and timing, an optical 3D motion capture system provides a complete kinematic model of the subject, electromyography sensors monitor muscle activation patterns and a force plate and pressure mat capture tactile pressure and force measurements. The study introduces the concept of constant throwing rhythm and highlights how landing errors in the horizontal plane can be attributable to a number of variations in arm force and speed, centre of gravity and the movements of some of the bodies non throw related extremities.

A probabilistic approach to user mobility prediction for wireless services.

Mobile and wireless networks have long exploited mobility predictions, focused on predicting the future location of given users, to perform more efficient network resource management. In this paper, we present a new approach in which we provide predictions as a probability distribution of the likelihood of moving to a set of future locations. This approach provides wireless services a greater amount of knowledge and enables them to perform more effectively. We present a framework for the evaluation of this new type of predictor, and develop 2 new predictors, HEM and G-Stat. We evaluate our predictors accuracy in predicting future cells for mobile users, using two large geolocation data sets, from MDC [11], [12] and Crawdad [13]. We show that our predictors can successfully predict with as low as an average 2.2% inaccuracy in certain scenarios.