BIOMECHANICAL ANALYSIS OF BADMINTON DIFFERENT FORWARD STEPS

[[abstract]]The purpose of this study was to compare the biomechanical variables between 2-step and 3-step forward steps in badminton. Eight collegiate elite male badminton players participated in this study. Eight Vicon T-20 cameras (300 Hz) were used to record the 3D kinematics data and a Kistler force plate (1500 Hz) was used to collect the GRF data of the last steps. A Wilcoxon matched-pairs signed-rank nonparametric statistical test was conducted to compare the differences between two kinds of forward step movements. The results showed that the movement time for 3-step movement was significantly faster than 2-step. We recommend that the badminton players should practice 3-step forward footwork technique. The additional strength and power training for lower limbs should be carried out for the footwork training.[[notice]]補正完畢[[conferencetype]]國際[[conferencedate]]20150629~20150703[[booktype]]紙本[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Franc

Kinematic Analysis of a Novel Vibratory Bowl Feeder

This study aims to propose a kinematic analysis approach for a novel vibratory bowl feeder, and verify its feasibility by kinematic simulation. First, the novel design is presented, and its advantages compared with conventional feeders are described. Moreover, the equations for kinematic analysis are derived. Finally, the solid model for the proposed design is established, and then kinematic simulation is performed by ADAMS software. The simulation results indicate that the proposed design can effectively advances the part with high efficiency

A Robust Hessian-based Trust Region Algorithm for Spherical Conformal Parameterizations

Surface parameterizations are widely applied in computer graphics, medical imaging and transformation optics. In this paper, we rigorously derive the gradient vector and Hessian matrix of the discrete conformal energy for spherical conformal parameterizations of simply connected closed surfaces of genus-$0$. In addition, we give the sparsity structure of the Hessian matrix, which leads to a robust Hessian-based trust region algorithm for the computation of spherical conformal maps. Numerical experiments demonstrate the local quadratic convergence of the proposed algorithm with low conformal distortions. We subsequently propose an application of our method to surface registrations that still maintains local quadratic convergence