Conservation of mass and momentum equations for the solid and for the gas phases was used to compute the hydrodynamics of flow of fluidized catalytic cracking particles in a vertical pipe (riser) for the 1995 benchmark modeling contest. The computer code predicted a new phenomenon:  an off-center maximum flux. The computed time-average radial fluxes and particle concentrations agree with PSRI experimental data. The computer code also predicted the observed core-annular flow regime. For the lowest gas velocity and highest solids flux, the code predicted low-frequency, snakelike density oscillations.

Gait identification is a valuable approach to identify humans at a distance. In this paper, gait characteristics are analyzed based on an iPhone's accelerometer and gyrometer, and a new approach is proposed for gait identification. Specifically, gait datasets are collected by the triaxial accelerometer and gyrometer embedded in an iPhone. Then, the datasets are processed to extract gait characteristic parameters which include gait frequency, symmetry coefficient, dynamic range and similarity coefficient of characteristic curves. Finally, a weighted voting scheme dependent upon the gait characteristic parameters is proposed for gait identification. Four experiments are implemented to validate the proposed scheme. The attitude and acceleration solutions are verified by simulation. Then the gait characteristics are analyzed by comparing two sets of actual data, and the performance of the weighted voting identification scheme is verified by 40 datasets of 10 subjects.

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