Techniques used in high-scoring and low-scoring 'Roche' vaults performed by elite male gymnasts

The 16 highest-scored Roche vaults (G1) performed during the 2000 Olympic Games were compared with those receiving the 16 lowest-scores (G2). A 16-mm motion picture camera operating at 100 Hz recorded the vaults during the competition. The results of t tests (p < .05) indicated G1, compared to G2, had (a) shorter time of board support, greater normalised average upward vertical force and backward horizontal force exerted by the board, greater change in the vertical velocity while on the board, and greater vertical velocity at board take-off, (b) comparable linear and angular motions in pre-flight, (c) smaller backward horizontal impulse exerted by the horse, smaller loss of the horizontal velocity while on the horse, and greater horizontal and vertical velocities at horse take-off, (d) greater height and larger horizontal distance of post-flight, (e) higher body mass centre at knee release, and (f) higher mass centre, greater normalised moment of inertia, and smaller vertical velocity at mat touchdown. Therefore, gymnasts and coaches should focus on sprinting the approach; blocking and pushing-off the take-off board rapidly and vigorously; departing the board with a large vertical velocity; exerting large downward vertical force and small forward horizontal force from the hand-stand position while on the horse; departing the horse with large horizontal and vertical velocities; and completing the majority of the double salto forward near the peak of trajectory and releasing the knees above the top of the horse to prepare for a controlled landing.     

Direction of arrival tracking for signals with known waveforms based on block least squares techniques

In this paper, we address the problem of tracking DOA of multiple moving targets with known signal source waveforms and unknown gains in the presence of Gaussian noise using a nonuniform linear array. Herein, we make use of the fact that the output of each sensor can be described as a linear regression model whose coefficients each contain a pair of DOA and gain information corresponding to one target. These coefficients are determined by solving a linear least squares (LS) problem and then updated recursively based on a block QR decomposition recursive least squares (QRD-RLS) technique or a block regularized LS technique. Since the coefficients from different sensors have the same amplitude but variable phase information for the same signal, along with simple algebraic manipulations the well-known generalized least squares (GLS) are used to obtain an asymptotically-optimal DOA estimate without requiring a search over a large region of the parameter space. Computer simulations show that the proposed DOA tracking techniques when applied to a sparse antenna array can provide a better tracking performance than some of the existing methods do.