In view of the huge risks brought by transaction fraud， handover irregularities and other issues in bulk stock online trading， a long-term traceable online trading mechanism was proposed to achieve more reliable bulk stock trading， in order to realize the authenticity and anti-tampering of information and the credibility and anti-fraud of process. Firstly， combined with blockchain， an online trading framework based on the idea of "application-verification-record" was proposed， and the smart contracts were used for multi-party supervision and detailed records for each stage of the trading process. Secondly， to guarantee the authenticity of commodity information， for bulk stock with texture features on its appearance， the commodity fingerprints of the bulk stock were extracted and verified based on the Local Binary Pattern （LBP） algorithm. Finally， to ensure the credibility of the handover process， a standardized handover method of commodities was proposed on the basis of environmental fingerprints. The above trading framework， commodity appearance fingerprint extraction and verification algorithm， and standardized commodity handover method were used jointly to constitute the online trading mechanism. The analysis results show that the proposed trading framework can avoid most of the frauds from the perspectives of user selection and process specification and can identify single-party and two-party frauds occurring in the transactions. The experiment results based on the real log image data show that the proposed commodity appearance fingerprint extraction and verification algorithm can judge different images of the same commodity with 94.00% accuracy and distinguish images of different commodities with 78.30% accuracy. The system performance test shows that the delay of each stage of the proposed trading mechanism is within an acceptable range， and meets the requirements of online trading.

The acoustic signal waveform of vehicle through the deceleration zone is different from that of the normal running on the road, the extraction of its feature parameters is crucial to the automatic judgment of number, speed and type of vehicles, and the acoustic signal envelope curve has many advantages in extracting its feature parameters compared with the original signal. However, the traditional envelope extraction algorithm has the problems that there are many burrs and it is difficult for the feature parameters to truly reflect the signal properties and features in the envelope extraction of acoustic signals in such traffic domain. In order to solve the problems, combined with the characteristics of acoustic signals of vehicles through the deceleration zone, a new envelope extraction algorithm for acoustic signal of vehicle pressing line based on variable step size was proposed. Different step sizes were set to traverse the signal. The curve was plotted by using the maximum point in each step and compared with the original signal waveform. The sharp definition and error of feature point extraction were taken as the judgment basis to realize the effective extraction of the acoustic signal envelope. The experimental results show that, under the same number of sampling points, the extracted envelope curve by the proposed algorithm is more clear and has less burrs than that by the traditional envelope extraction algorithm, and the extraction error of feature parameters is smaller.

With the increasing amount of data and expanding of application demand, the efficient organizational management and rapid processing speed of remote sensing data have become a bottleneck in the application of remote sensing technology. The earth partition theory and high performance computing provide a possible way to solve the above problem. Combined with global partition model, the conceptual model and data model of partition facet template were proposed based on partition facet of remote sensing image. A computing mode of partition facets based on templates was designed, and a small partition template database was established. A specific example of partition image data template applications was also given for validation. The experimental results demonstrate the feasibility of the data model and improve the efficiency of targets retrieval.

This paper investigated the limited feedback technology based on the Multiple Input Multiple Output Orthogonal Frequency Division Multiple (MIMO-OFDM) system in LTE-Advanced applications. A new limited feedback method based on recursive feedback was proposed. The method utilized the correlation between the subcarrier channels. The codewords for the current subcarrier could be determined by ordering the result of the inner product with respect to the codewords of the previous subcarrier. Then the variable length encoding method was used to code the index of the new codewords. The experimental results show that the recursive feedback algorithm based on variable length coding can reduce the feedback bits effectively in LTE-Advanced systems.

The method of differential analysis on collision attacks against MD5 was analyzed. Considering the increase of message blocks to be hashed via message pre-processing, a new method of modifying the step function of MD5 was proposed. The method can raise the resistibility of collision attack by preventing choosing a good differential path and limiting the use of message modification techniques. The efficiency of the improved algorithm is higher than that of method via message pre-processing.