The vertex shader needs an extra generating pattern and the calculation of subdivision level is complicated when subdividing terrain grid. A Level of Detail (LOD) terrain rendering algorithm using subdivision shader was put forward for the insufficiency. The proposed method used block quad tree organization to build a rough terrain grid hierarchical structure, and filtrated the activity terrain blocks by LOD discrimination function. A subdivision factor calculation method was proposed based on viewpoint in a three-dimensional continuous distance in tessellation control shader and cracks of the external factor segment was eliminated. As a result, displacement mapping on tessellation evaluation shader and displacement of height component in fine grid blocks were achieved. Meanwhile, the quadtree was saved to vertex buffer, and the exchange of resource between Central Processing Unit (CPU) and Graphic Processing Unit (GPU) was decreased. The subdivision process was accelerated by bringing in subdivision queue. The experimental results show that the proposed algorithm has a smooth detail level transition and good subdivision effect, and it can increase the utilization ratio of GPU and terrain rendering efficiency.

Question classification is one of the tasks in question answering system. Since questions often have rare words and colloquial expressions, especially in the application of voice interaction, the traditional text classifications perform poorly in short question classification. Thus a short question classification algorithm was proposed, which was based on semantic extensions and used the search engine to extend knowledge for short questions, the question's category was got by selecting features with the topic model and calculating the word similarity. The experimental results show that the proposed method can get F-measure value of 0.713 in a set of 1365 real problems, which is higher than that of Support Vector Machine (SVM), K-Nearest Neighbor (KNN) algorithm and maximum entropy algorithm. Therefore, the accuracy of the question classification can be improved by above method in question answering system.

As an important part of the urban vehicle network, bus vehicle network provides supports for a wide range of urban-vehicle communication network due to cyclical movement law. However, the complex urban road environment brings great challenges to highly efficient and reliable routing protocols for bus vehicle network. In bus vehicle network with the characteristics of cyclical movement, a new protocol named SRMHR (Single & Realmending-Multi Hop Routing) was proposed to ensure the single hop link's life time and multi-hop submission probability in limited delay. According to the signal propagation attenuation model and vehicle mobility model, a single hop selection mechanism and a multi-hop delay probability forwarding mechanism were proposed to ensure the reliability and effectiveness of bus-assistant forwarding. On the urban traffic simulation platform, using real road traffic data of slight adjustment, the performance of signal attenuation model, single hop selection mechanism and light correction model under different traffic densities were tested. The results prove the validity of each link of the scheme. Comparison with SF (Spray and Focus) and SW (Spray and Wait) proves that SRMHR protocol has a higher successful rate of data transmission and lower delivery delay.

Concerning the lack of research on User Datagram Protocol (UDP) flow detection, and its low accuracy and efficiency, an adaptive UDP flow detection based on multi-granularity was proposed. Two different dynamic timeout strategies based on different granularity were designed by analyzing the characteristics of UDP flow. Compared with other timeout strategies, the accuracy of the proposed method was similar to the fixed timeout strategy, and the memory usage was only about 75% of the others. The experimental results show that the proposed method is suitable to the UDP flow detection.