Moving Human Posture Recognition Based on Joint Quaternion

Posture recognition plays an important role in many applications,such as security system and monitoring system.Joint quaternion combined with support vector machine(SVM) can solve the problem of moving human posture recognition.It is a simple and effective algorithm that only three joints are used as the feature points in the whole human skeleton.Using the quaternion of the three joints,a feature vector with five parameters in gait cycle is extracted.The efficiency of the proposed method is demonstrated through an experimental study,and walking and running postures can be distinguished accurately.

Intensity Evolution of Zonal Shear Line over the Tibetan Plateau in Summer:A Perspective of Divergent and Rotational Kinetic Energies

Based on the ERA5 reanalysis datasets during 1980-2019,a total of eleven zonal shear lines(ZSLs)that caused heavy precipitation and lasted more than 60 hours over the Tibetan Plateau in summer are selected for composite analysis.By decomposing the kinetic energy(K)near the ZSL into divergent and rotational kinetic energies(K_(D)and K_(R))and the kinetic energy of interaction between the divergent wind and the rotational wind(K_(R)D),the influence of the rotational and divergent winds on the evolution of the ZSL intensity is investigated from the perspective of K_(D)and K_(R).The main results are as follows.The ZSL is a comprehensive reflection of rotation and convergence.The intensity evolution of ZSL is essentially synchronized with those of K,K_(R),and K_(RD)but lags behind K_(D)by about three hours.The enhancement of K is mainly contributed by K_(R),which is governed by the conversion from K_(D)to K_(R).Furthermore,the increase in the conversion from K_(D)to K_(R)is controlled by the geostrophic effect term Af,which is determined by the joint enhancement of the zonal rotational and meridional divergent wind components(u_(R)and v_(D)).Therefore,the joint enhancement of u_(R)and v_(D)controls the increase of the ZSL intensity,leading to increased precipitation.

Influence of erosion voids and traffic loads on buried large-diameter reinforced concrete pipes

Geotechnical centrifuge tests were conducted to examine the influence of invert voids and surface traffic loads on 1400 mm diameter reinforced concrete pipes buried with a shallow soil cover depth of 700 mm.Void formation beneath the pipe was simulated during centrifuge testing.The test results revealed that before void formation,the surface load directly above the middle of the pipe caused a significant increase in not only the circumferential bending moments but also the longitudinal bending moments,the latter of which was considerable and could not be ignored.Void formation beneath the middle of the pipe led to a reduction in both the circumferential bending moments and longitudinal bending moments at all measuring positions,i.e.,crown,springline,and invert.The most significant reduction occurred at the invert,and there was even a reversal in the sign of the invert longitudinal bending moment.A comparison was made between centrifuge tests with erosion voids and surface loads at different horizontal positions,which had a marked influence even when the positions differed by half a pipe length.Joint rotation played an important role in relieving large bending moments of pipe barrels in a jointed pipeline when the void and surface load were located at the joint.

An adaptive beamforming algorithm based on direction vector rotation and joint iterative optimization

An adaptive beamforming algorithm named robust joint iterative optimizationdirection adaptive （RJIO-DA） is proposed for large-array scenarios. Based on the framework of minimum variance distortionless response （MVDR）, the proposed algorithm jointly updates a transforming matrix and a reduced-rank filter. Each column of the transforming matrix is treated as an independent direction vector and updates the weight values of each dimension within a subspace. In addition, the direction vector rotation improves the performance of the algorithm by reducing the uncertainties due to the direction error. Simulation results show that the RJIO-DA algorithm has lower complexity and faster convergence than other conventional reduced-rank algorithms.