To solve the problems of long time consuming and large space occupation in the route planning process of Unmanned Underwater Vehicle (UUV) under complex environments and multi-constraint conditions, a new route planning method based on Charged System Search (CSS) was proposed. Firstly, the UUV route planning problem model was established, and the cost function was designed. Then, a route planning method based on CSS was presented, and the charged particle was affected by the electric field force of other charged particles in the search space to achieve the purpose of iterative optimization. In addition, a method of nonlinear adjustment of speed and acceleration parameters was proposed, which could effectively balance global search and local search processes, and avoid premature convergence of algorithm. Finally, the proposed method was compared with the route planning methods based on A ^* algorithm, ant colony optimization algorithm and particle swarm optimization from two respects of the quality of planning route and the time consuming of algorithm. The experimental results show that, the proposed method has faster convergence speed and lower time complexity while ensuring the quality of planned route.

The data is usually shared by a group of users in cloud computing. The third party auditor can obtain the the identities of group members through their signatures of data blocks. In order to protect the identities of group members, the existing public audit schemes for shared data all hide the identities of group members. However, the anonymity of identity leads to the problem that a member of the group can change the shared data maliciously without being found, and the amount of computation is large for resource constrained devices in the process of generating signature for users. The existing public audit schemes have the problems that the identity of data block can not be traced and the amount of calculation of generating shared data block signature is large. In order to solve the above problems, A Scheme of sharing cloud Data Audit supporting user traceability and lightweight (ASDA) was proposed. Firstly, the security mediator was used to replace the user signature to protect the identities of group members. The information of user was saved while signing and it could be traced back that the data block was modified by which member through the above information, which could ensure the traceability of the identity of data block. Then, a new data block blinding technology was used to reduce the amount of client computing. The experimental results show that, compared with Storing shared Data on the cloud Via Security-mediator (SDVS) scheme, the proposed scheme reduces the computing time of users and realizes the traceability of shared data blocks.

Concerning the defects of fusing object information by existing visual attention models, a new visual attention method combining high-level object features and low-level pixel features was proposed. Firstly, high-level feature maps were obtained by using Convolutional Neural Network (CNN) which has strong understanding of multi-class targets. Then all object feature maps were combined by training the weights with eye fixation data. Then the saliency map was obtained by fusing pixel-level conspicuity map and object-level conspicuity map. Finally, the proposed method was compared with many popular visual attention methods on OSIE and MIT datasets. Compared with the contrast methods, the Area Under Curve (AUC) result of the proposed method is increased. Experimental results show that the proposed method can make full use of the object information in the image, and increases the saliency prediction accuracy.

The hand vein image tends to be of low contrast, which affects the recognition accuracy of the whole hand vein recognition system. The effective area of the hand vein image was extracted firstly and then the Histogram Equalization (HE) algorithm and its improved versions were employed to enhance the contrast of the extracted hand vein image. The results indicate that the Partially Overlapped Sub-block Histogram Equalization (POSHE) can enhance not only the overall contrast but also the detailed one. Meanwhile, its high efficiency is suitable to the hand vein image contrast enhancement.