To satisfy the requirement of real-time and rapid processing of Scale-Invariant Feature Transform(SIFT) algorithm for remote sensing images of large-scale Unmanned Aerial Vehicle (UAV) network on the scene, an implementation scheme of the algorithm by using the hardware multiplier of Digital Signal Processor(DSP)kernel was proposed to process the multiplication of single-precision floating-point pixel data. Firstly,according to the characteristics of data input and output of the hardware multiplier with DSP kernel,the image data structure and the image function of SIFT algorithm were reconstructed in order to make the hardware multiplier perform the multiplication calculation of single-precision floating-point pixel data of SIFT algorithm. Secondly,the software pipelining technology was adopted to rearrange the iterative computation,so as to enhance the parallel computing ability of the algorithm. Finally,the dynamic data produced in the algorithm calculation process were transferred to the Double Data Rate 3 synchronous dynamic random access memory(DDR3)to enlarge the storage space of the algorithm data. Experimental results show that the SIFT algorithm on DSP platform is able to achieve high-precision and fast processing for 1 000×750 remote sensing images of UAV,and the scheme satisfies the requirement of real-time and rapid processing of SIFT algorithm for remote sensing images of UAV network on the scene.

Aiming at the integrity threat of Android systems at present brought by kernel-level attacks, a method for dynamic measurement of Android kernel, namely DIMDroid (Dynamic Integrity Measurement of Android), was proposed. The hardware-assisted virtualization technology was used to provide the isolation between the measurement module and the measured Android system. First of all, the static and dynamic measurement objects were obtained by analyzing the kernel elements that affect kernel integrity in the running of the Android system. Secondly, these measurement objects were semantically reconstructed at the measurement layer. Finally, an integrity analysis was performed to determine whether the Android kernel is under attack or not. At the same time, the boot protection based on hardware-based trust chain and the runtime protection based on memory isolation were performed to ensure the security of DIMDroid itself. The experimental results show that DIMDroid can detect the rootkit which breaks Android kernel integrity in time, and the performance loss of the method is within an acceptable range.

At present, most social networking systems recommend potential friends mainly according to the existed friend relationship, and users' interests are not emphasized. Furthermore, it is a very difficult task to find users' interests with high precision from a large amount of data. A Friend Recommendation Based on user Tagging (FRBT) algorithm was proposed to find potential friends with the same interests by mining users' interests in tagging behavior data. First, Term Frequency-Inverse Document Frequency (TF-IDF) was used to cluster the similar semantic tags into topics. A new formula for calculating the users' similarity of topics was described. Combined with the user similarity based on topic and item, the proposed algorithm could recommend the users with high similarities as potential friends. The experimental results on tagging dataset of Delicious validate, compared wtih the algorithms of item, tag and tri-graph, FRBT has better performance in terms of precision and recall.

To resolve the problem that underground pipe network of plant is large, complex and difficult to manage, the C/S+B/S mixed development model based on the ArcGIS platform was used. This paper aimed to transfer the spatial analysis of the traditional Geographic Information System (GIS) from C/S to B/S. Collision detection algorithm and efficient linear interpolation method were used in B/S client, and moreover an optimized relational database management model was proposed. The system running results show that the system could make spatial analysis of the invisible underground pipe network better and more effective, and achieve the digital management of underground pipe network in large plant.