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This papers studies a high-performance node-level service grid model, which aims to solve the problem that the current pod-level service grid model affects the service operation and consumes many computing resources. The main method of the node-level service grid model is to improve pod-accompanied service grid sidecar with the node-accompanied service grid sidecar sharing of multiple pods, combined with the cut-through of user mode protocol stack and scaling of node-level service grid sidecar. By the performance comparison of pod-level service grid model and node-level service grid, we can conclude that node-level service grid model can isolate pod services without affecting service operation, significantly reduce memory consumption without multiplying with the number of pods, and largely reduce end-to-end network delay about 30% but the overall CPU consumption as the same as that of the pod service grid model. It indicates that the node service grid model can obtain better business benefits than the pod service grid model in container cloud, cloud service providers can provide grid services for more tenants with less memory resources and network latency, and adding grid services has no impact on the operation of user applications.

N owadays, medical plastic gloves are sorted into the left and the right hands manually with low efficiency during productive process. In this paper, an automated way is proposed to improve this situation through establishing a convolutional neural network model for image recognition. The back propagation process of learning and training is analyzed in order to optimize the weight by adopting the combination of different activation layers and different loss functions. For the same learning times, there are two evaluation indexes. One is the result of recognition accuracy in the training set, the other is the convergence curve and oscillation amplitude of the loss function. Finally, the adaptability of the combinations is discussed, which plays an important role in improving the recognition accuracy of the left and the right hand.

This document proposes an IP multicast fast convergence method based on differentiating primary and backup PIM(Protocol Independent Multicast) join. The multicast stream is only sent along one of the multicast primary and backup path, which enables the efficient multicast delivery under both normal and abnormal conditions. The Single stream FRR(Fast Re-Route) solution has the advantages of implementing fast multicast protection and of avoiding double multicast bandwidth occupation in both normal and abnormal situations.

The printing speed and print quality are depending on the dynamic characteristics of paper transferring system for a sheet-fed press. Because of the complexity of a sheet-fed press and printing technique, it is difficulty to get the real dynamic response by FEM separately, thus the boundary condition is not ease to determine while modeling. Taking the experimental platform of printing press' paper transferring system as the studying object, the experimental modal analysis was carried out with hammer pulse excitation method. The modal parameters including modal frequency, modal damping and modal shape were obtained by the result of the experimental modal analysis. The conclusion shows that the vibration characteristics of the exciting source (i.e. cam driving mechanism and gear transmission mechanism) and the compelled vibration components(i.e. the wallboard and transverse beam) need to be improved. The result of the experiment establishes a foundation of the dynamic characteristics modification for high speed paper transferring system. (6 pages)