Cloud computing data are vulnerable to be theft illegally and tampered maliciously. To solve these problems, a Dynamic Updating Ciphertext-Policy Attribute-Based Encryption (DU-CPABE) scheme which enables both data dynamic updating and security protection was proposed. Firstly, by using linear partitioning algorithm, data information was divided into fixed size blocks. Secondly, the data blocks were encrypted by using Ciphertext-Policy Attribute-Based Encryption (CP-ABE) algorithm. Finally, based on conventional Merkle Hash Tree (MHT), an Address-MHT (A-MHT) was proposed for the operation of dynamically updating data in cloud computing. The theoretical analysis proved the security of the scheme, and the simulation in ideal channel showed that, for five updates, compared with CP-ABE method, the average time overhead of data update was decreased by 14.6%. The experimental results show that the dynamic updating of DU-CPABE scheme in cloud computng services can effectively reduce data update time and system overhead.

Since the gesture signals in gesture interaction are similar and instable, an acceleration gesture recognition method based on Random Projection (RP) was designed and implemented. The system incorporated two parts, one was the training stage and the other was the testing stage. In the training stage, the system employed Dynamic Time Warping (DTW) and Affinity Propagation (AP) algorithms to create exemplars for each gesture; in the testing stage, the method firstly calculated the distance between the unknown trace and all exemplars to find the candidate traces, then used the RP algorithm to translate all the candidate traces and the unknown trace onto the same lower dimensional subspace, and by formulating the whole recognition problem as an l₁-minimization problem, the unknown trace was recognized. The experimental results on 2400 gesture traces show that the proposed algorithm achieves an accuracy rate of 98.41% for specific individuals and 96.67% for unspecific individuals, and it can effectively identify acceleration gestures.

In order to effectively improve the recognition accuracy of the speech emotion recognition system, an improved speech emotion recognition algorithm based on Support Vector Machine (SVM) was proposed. In the proposed algorithm, the SVM parameters, penalty factor and nuclear function parameter, were optimized with genetic algorithm. Furthermore, an emotion recognition model was established with SVM method. The performance of this algorithm was assessed by computer simulations, and 91.03% and 96.59% recognition rates were achieved respectively in seven-emotion recognition experiments and common five-emotion recognition experiments on the Berlin database. When the Chinese emotional database was used, the rate increased to 97.67%. The obtained results of the simulations demonstrate the validity of the proposed algorithm.

A new algorithm for Boolean operation of two simple polygons based on minimum circle was presented. Polygon P and Q were initialized to counterclockwise direction, and the edges connecting to each intersection point of P and Q were arranged in sequential order. Then, all minimum circles were found using the minimum turning angle rule. These minimum circles were classified according to edges direction in P and Q. Intersection, union, and difference of the two polygons are corresponding to different kinds of minimum circles. The algorithm run in time O((n+m+k)logd) in a worst presented case, where n and m were the vertex numbers of the two polygons respectively, k was the numbers of intersection points, and d was the number of polygon’s monotonic chain. The algorithm has explicit geometric significance, and well resolves the problems in special cases，such as overlapped edges, and operation edges intersection at the vertex of edges.