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LTE with large capacity and high speed is the most promising standard of wireless data communications technology to be used in Chinese high-speed rail(HSR). Because of over-frequent handover in HSR, the experience of passengers is highly degraded. Wireless Quality of Service (QoS) provisioning in such high speed movement is more difficult to be tackled than in a fixed-wired environment. Seamless handover attempts to provide a given QoS during the process of migration from one cell to another. It can reduce the interruption period to nearly zero. In this paper, we revised an existent seamless dual-link handover scheme where the Train Relay Station relays the data of users in the train and two antennas are mounted in the top of the train and designed a set of new handover procedures suitable for HSR communications. We defined a velocity threshold(VT). If the speed of train exceeds VT, two target base stations are prepared for user equipment(UE) when handover is triggered. The simulation results show that in the proposed scheme the communication interruption probability is under 0.01 when the train is at speed of 350 kilometers per hour.

A new method, called 3D growing deformable B-surface model, is proposed for object detection which works in 3D space directly. First, the coarse boundary of the subject is extracted. The 3D external force field of the subject is generated based on this coarse boundary using modified GVF (gradient vector flow). After the initialization of a surface patch, growing B-surface model starts to deform it to locate the boundary of the object. Next, this surface patch is anchored to the surface of the subject and a new surface patch grows up based it. This process is repeated until a closed surface of the subject is obtained. 3D growing deformable B-surface model overcomes the difficulty that comes from analyzing 3D volume image slice by slice. And the computation load of B-surface is reduced since the internal force is not necessary in every iteration deformation step. Next, the geometric information on every surface point can be calculated easily. And it has the ability Io achieve high compression ratio (the ratio of data to parameters) by presenting the whole surface with only a relatively small number of control points. Growing B-surface model simplifies the initialization step of the surface model.