With the continuous development of blockchain technology， the block transmission delay has become a performance bottleneck of the scalability of the blockchain system. Remote Direct Memory Access （RDMA） technology， which supports high-bandwidth and low-delay data transmission， provides a new idea for block transmission with low latency. Therefore， a block catalogue structure for block information sharing was designed based on the characteristics of RDMA primitives， and the basic working process of block transmission was proposed and implemented on this basis. Experimental results show that compared with TCP（Transmission Control Protocol） transmission mechanism， the RDMA-based block transmission mechanism reduces the transmission delay between nodes by 44%， the transmission delay among the whole network by 24.4% on a block of 1 MB size， and the number of temporary forks appeared in blockchain by 22.6% on a blockchain of 10 000 nodes. It can be seen that the RDMA-based block transmission mechanism takes advantage of the performance of high speed networks， reduces block transmission latency and the number of temporary forks， thereby improving the scalability of the existing blockchain systems.

For the difficulty of expressing spatial context in classification of high resolution remote sensing imagery, a new multi-scale Conditional Random Field (CRF)model was proposed here. Specifically, a given image was represented as three superpixel layers respectively being region, object and scene from fine to coarse firstly. Then features were extracted layer-by-layer, and those features from the three layers were associated with each other to form a feature vector for each node in region layer. Secondly, Support Vector Machine (SVM) was adopted to define association potential function, and Potts model weighted by feature contrast function was used to define interaction potential function of CRF model, thus a layer-by-layer feature associative and multi-scale SVM-CRF model was formed. To confirm the effectiveness of the proposed model in classification, experiments on two complex scenes from Quickbird remote sensing imagery were developed. The results show that the proposed model achieves an improved accuracy averagely 2.68%, 2.37%, 3.75% higher than that of SVM-CRF model based on either region, object or scene layer, also it consumes less time in classification.

The Instruction Level Parallelism (ILP) of VLIW DSP processor is acquired through operation partitioning and software pipeline. In the previous research of operation partitioning, people always focus on reducing move operations between clusters, but rarely consider the effect of heterogeneous architecture and some registers that should be placed on reserved cluster. A method based on DataFlow Graph (DFG) for heterogeneous architecture was described to solve this problem. First, the DFG was partitioned into several sub-graphs according to the relations between operations, then the sub-graphs were refined with a heuristic method to meet the requirements of special registers. The experimental results show that this method can make the load of cluster more balanced, and achieve an average of 8% improvement over traditional method.

This paper presented an improved sequential heuristic algorithm to solve the classical One-Dimensional Cutting Stock Problem (1D-CSP). The prices of the items assigned to the current pattern were adjusted so as to make them more reasonable. The pattern, whose unit value was the maximum among those of the patterns generated from solving a bounded knapsack problem, was added to the cutting plan. Several solutions were constructed iteratively and at last the best one was selected. The heuristic algorithm can generate cutting plans of higher material utilization level, and at the same time, can consider multiple objectives such as pattern reduction and residual length increment. The computational results show the effectiveness of the presented algorithm.

The customer meaning for outlier explanation is rarely provided in the current studies. The outliers usually contain important information, and for many applications, the explanations are as important to the user as the outliers. A new definition of outlier customer meaning was given, and a new outlier customer meaning analysis algorithm named DSCM was put forward based on distance sum. The algorithm gave an explanation of every outlier, which improved the user’s understanding of the data. Then the algorithm was applied to quality management, and the results show that the algorithm is effective and practical, and more easy to use.

An anonymous authentication protocol was proposed to improve the anonymity and to control anonymity abuse in wireless communications. The protocol implemented the anonymity of Home Location Register (HLR) using Visitor Location Registers (VLRs) which had been employed to forward the authentication message by Mobile Station (MS). Through checking the authentication token, this protocol could control anonymity abuse. The probability statistics were adopted to analyze the security and anonymity of this protocol. The analysis results show that this protocol not only improves the anonymity of HLR but also defends anonymity abuse effectively.