Group activity recognition is a challenging task in complex scenes， which involves the interaction and the relative spatial position relationship of a group of people in the scene. The current group activity recognition methods either lack the fine design or do not take full advantage of interactive features among individuals. Therefore， a network framework based on partitioned attention mechanism and interactive position relationship was proposed， which further considered individual limbs semantic features and explored the relationship between interaction feature similarity and behavior consistency among individuals. Firstly， the original video sequences and optical flow image sequences were used as the input of the network， and a partitioned attention feature module was introduced to refine the limb motion features of individuals. Secondly， the spatial position and interactive distance were taken as individual interaction features. Finally， the individual motion features and spatial position relation features were fused as the features of the group scene undirected graph nodes， and Graph Convolutional Network （GCN） was adopted to further capture the activity interaction in the global scene， thereby recognizing the group activity. Experimental results show that this framework achieves 92.8% and 97.7% recognition accuracy on two group activity recognition datasets （CAD （Collective Activity Dataset） and CAE （Collective Activity Extended Dataset））. Compared with Actor Relationship Graph （ARG） and Confidence Energy Recurrent Network （CERN） on CAD dataset， this framework has the recognition accuracy improved by 1.8 percentage points and 5.6 percentage points respectively. At the same time， the results of ablation experiment show that the proposed algorithm achieves better recognition performance.

For precision control problem of multi-resolution fairing, specific impact of fairing precision caused by fairing scale was studied on the basis of the researches of multi-resolution fairing algorithm and software. Taking semicircular curve as a calibration object, this method revealed the internal relations between selection of fairing scale and fairing precision. The experimental results show that the smaller the fairing scale is, the larger the fairing error is. Secondly, multi-resolution fairing can reflect original curves with less control vertexes and own a strong ability of data compression. Finally, fairing error would be larger at the place of curves with larger curvature.

Concerning the problem that existing blind road recognition method has low recognition rate, simplistic handling, and is easily influenced by light, or shadow, an improved blind road recognition method was proposed. According to the color and texture features of blind road, the algorithm used two segmentation methods respectively including color histogram feature threshold segmentation combined with improved region growing segmentation and fuzzy C-means clustering segmentation for gray level co-occurrence matrix feature. And combined with Canny edge detection and Hough transform algorithm, the proposed algorithm made the blind area separated from the pedestrian area and determines the migration direction for the blind. The experimental results show that the proposed algorithm can segment several kinds of blind road more accurately, detect the boundary and direction of blind road and solve the light and shadow problem partly. It can choose the fastest and the most effective segmentation method adoptively, and can be used in a variety of devices, such as electronic guide ones.

In order to realize aircraft optimal target aiming in the situation of combat duel, a control method based on Gauss Pseudospectral Method (GPM) was proposed. Taking agility and multi-constraint into consideration, the dynamic equation of the aircraft was modeled, the two-stage target aiming condition expression was deduced, and the optimal index was designed. Afterwards, the aircraft optimal aiming control was described as the multi-stage optimal control problem with constraint and unknown final time. The GPM was used to equally convert the continuous optimal boundary value problem to a discrete Nonlinear Programming (NLP) problem and the initial solution was preprocessed through Genetic Algorithm (GA), then, the Sequential Quadratic Programming (SQP) algorithm was applied to solve it. The simulation results show that it can realize target aiming effectively and satisfy weapon launch condition.

Concerning that most Web video categorization researches just focus on the basic simple fusion of the information from text model and visual model, a Web video classification method based on the bidirectional propagation of heterogeneous attributes was proposed. Firstly, the method adopted K-means clustering to divide key frames into multiple clusters, and modeled videos at the level of frame. For each cluster, a part of key frames were randomly chosen to propagate their text information to the cluster. For each key frame, the text explanation of the corresponding cluster was transferred to this frame. Finally, the Web video was classified based on the extended text information from dual propagation by using Support Vector Machine (SVM) classifiers. The method integrates heterogeneous attributes well based on the dual propagation. The experimental results demonstrate the effectiveness of the method in the Web video classification.

An embedded control system development methodology based on modeldriven development method was studied, the basic features and architecture of the embedded control system were analyzed and summarized, and the key elements of this specific domain were identified and extracted. Afterwards, a visible element modeling technique was used to build a directly graphical model system, and this embedded modeling technique based on modeldriven was applied to realize a model of embedded voice control system design. As a result, the visual source model of this system was obtained.

Allowing for the shortcomings of existing network security management, a network security management platform based on XMLRPC was designed. The problems of the standardization and combination of log and data in network security management platform were analyzed, a solution method was put forward and the process of implementation was discussed in details. This platform can manage all kinds of network security products running on different operating systems. Moreover, all kinds of log data can be analyzed identically by this platform.