The existing network spread model ignores the information attenuation in the process of information spread, and the traditional influence maximization algorithm cannot effectively use the community structure to improve the influence spread range. To solve these problems, an algorithm of Influence Maximization on Internal Decay (IMID) based on community structure was proposed. Firstly, the community structure of a whole social network was divided and the influence range of nodes in the community was evaluated. Then, with spread probability of association points between the communities considered, the attenuation degree of information spread between nodes was calculated. Experimental and analysis results show that the proposed algorithm not only reduces the time complexity, but also obtains the influence transmission range near that of greedy algorithm, with influence coverage over 90%. Therefore, with several nodes selected as the initial nodes between the core seed node set and connected communities, information will be widely spread in the network at the minimum cost.

In the transportation field, analyzing passengers' travel destinations brings a lot of commercial value. However, research on the passengers' travel destinations is difficult because of its uncertainty. In order to solve this problem, in existing studies, entropy is used to measure the uncertainty of human mobility to describe individuals' travel features, and the spatiotemporal correlation of individual trajectories is taken into account simultaneously, which can not achieve the desired accuracy. Therefore, an algorithm for airline prediction based on improved Markov chain was proposed to predict passengers' travel destinations. First, the distance distribution, site distribution and temporal regularity on history records of passengers' travels were analyzed. Then, the dependence of human mobility on historical behavior and current location was analyzed. Finally, the characteristics of passengers' permanent residence and the exploration probability of new airlines were added into the calculation transition matrix, and an algorithm based on improved Markov chain was proposed and realized to predict passengers' next travels. The experimental results show that the average prediction accuracy of the proposed model can reach 66.4%. Applying in the field of customer travel analysis, airline company can benefit from the research to predict passenger travel better and provide personalized travel services.

In order to alleviate the problem of energy hole in the Wireless Sensor Network (WSN), a Multi-level Energy Heterogeneous algorithm (MEH) was proposed. The energy consumption's characteristics of WSN were analyzed. Then the nodes with different initial energies were deployed according to the energy consumption's characteristics. To balance the energy consumption rate of each region, alleviate the energy hole problem and prolong the network lifecycle, nodes in the heavy communication load region would be configured with higher initial energy. The simulation results show that, compared with Low-Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy-Balanced Unequal Clustering routing protocol (DEBUC), and Nonuniform Distributed Strategy (NDS), the utilization rate of network energy, network lifecycle and period ratio of network energy of MEH were increased nearly 10 percentage points respectively. The proposed MEH has a good balance of energy consumption as well. The experimental results show that, the proposed MEH can effectively prolong the network lifecycle and ease the energy hole problem.

For the unique environment of the Underwater Wireless Sensor Network (UWSN) in river, the model was built by method of fluid dynamics to obtain the real-time position of sensor nodes and simulate the movement law of sensor nodes in real river environment. Furthermore, on the problem of data transmission in UWSN, a Routing Algorithm based on Layered Mechanism (RALM) was proposed for river environment. The topology information was calculated and updated by each node periodically based on the receiving speed from sink. The node to transmit data would choose the neighbor node in upper layer which has the most residual energy to be the next hop. If the node has no neighbor node in upper layer, the next hop would be the neighbor node in the same layer which has the most residual energy. The simulation results show that, compared with DBR (Depth-Based Routing) and Layered-DBR (Layered-Depth Based Routing), RALM algorithm can effectively reduce the network redundancy and packet loss rate, and the network life cycle is raised by 71% and 45%.

To improve the accuracy of Centroid Localization (CL) algorithm in Wireless Sensor Network (WSN), an Optimal Beacon nodes-based Centroid Localization (OBCL) algorithm was proposed. In this algorithm, four mobile beacon nodes were used. First, the path for each mobile beacon node was planned. Second, the optimal beacon nodes were selected from the candidate beacon nodes by each unknown node to estimate location according to Set Deviation Degree (SDD). Besides, a role-change mechanism that an unknown node can assist other unknown nodes to locate as the expectant beacon node after it got its estimated location was adopted to solve the problem of beacon nodes' shortage. At last, to ensure that each unknown node could get its location, a relocation procedure was executed after the completion of the initial locating. The simulation results show that, the average locating error is respectively reduced by 67.7%, 39.2%, 24.4% comparing with the CL, WCL (Weighted Centroid Localization), RR-WCL (Weighted Centroid Localization based on Received signal strength indication Ration) algorithms. For the reason that OBCL can achieve better locating results using only four mobile beacon nodes, it is suitable for scenes which require low network cost and high locating accuracy.

video-based human action recognition has received much attention recently in computer vision while it is a very challenging research with many applications such as automatic behavior analysis, visual surveillance and human-computer interaction. A human action recognition method based on cascaded structure is proposed in this paper. Firstly, a trajectory-based method is proposed to select the interest points detected by the Dollar detector, which is sensitive to image noise, camera movement and zooming. Therefore, the pseudo interest points in the background can be effectively excluded and the extracted features will be more relevant to action recognition. Secondly, an automatic feature selection method based on the combination of normalized cuts and mRMR criteria is used to determine a subset of the words generated by the Bag-of-Words model and construct a cascaded structure for action recognition. The purpose is to make the feature used by the cascaded structure more distinctive. Lastly, the promising experimental results validate our contribution to the improvement of accuracy in human action recognition.

GPU-based volume rendering has become an active research area in the domain of volume visualization. Large volume data cannot be uploaded directly due to the limitation of GPU memory, which has been a bottleneck of the application of GPU. Bricking method could not only solve this problem, but also maintain the quality of original volume-rendered image. However, the data exchange via the graphics bus is really time consuming and will definitely degrade the render performance. As for these difficulties, the optimal bricking for large volume data was calculated by establishing the model for optimal bricking, and also a 3D texture named node code texture was constructed and distance template was improved to accelerate the octree-based bricking volume rendering. The experimental results illustrate that the proposed method can significantly accelerate the bricking-based volume rendering for large volume data.

Based on the implements of the secure mobile auction system, the paper analysed the security requirements of this system, introduced the special encryption and sign techniques in mobile auction system, these techniques contained the making, storing and updating of the secret key, the encryption, decryption and the self-sign certificate model of SOAP message in server, the implement of the encryption engine and the sign engine in client. This system can be successfully transplanted to mobile devices in order to improve the security of the wireless Web Services.