Aiming at the problem of scattered initial labels and large randomness of label propagation, an overlapping community detection algorithm fusing label preprocessing and node influence was proposed. Firstly, the influence value of each node was calculated, and the node with the largest influence value was selected as the central node gradually. Secondly, the label of the central node was used to preprocess the labels of the homogeneous neighbor nodes, so as to reduce the number of initial labels as well as the randomness of subsequent label propagation, and preliminarily identify the overlapping nodes. Thirdly, the overlapping nodes were identified by the label belonging coefficient, and the labels of non-overlapping nodes were selected by the node influence values, improving the stability and accuracy of the proposed algorithm. Finally, in order to maximize the increment of the adaptive function, the communities with weak cohesion were merged together to improve the quality of communities. The simulation experimental results show that the proposed algorithm has the largest extended modularity value on 50% datasets of the six real networks, and has the best performance in Normalized Mutual Information (NMI) index on the artificial benchmark networks with different mixing degrees, overlapping degrees of node and the maximum numbers of communities to which the node belongs. In conclusion, the algorithm has good adaptability to all kinds of networks, and has nearly linear time complexity.

Deep neural networks tend to suffer from overfitting problem because of the high complexity of the model. To reduce the adverse eeffects of the problem on the network performance, an improved elastic network model based deep learning optimization method was proposed. Firstly, considering the strong correlation between the variables, the adaptive weights were assigned to different variables of L1-norm in elastic network model, so that the linear combination of the L2-norm and the adaptively weighted L1-norm was obtained. Then, the solving process of neural network parameters under this new regularization term was given by combining improved elastic network model with the deep learning optimization model. Moreover, the robustness of this proposed model was theoretically demonstrated by showing the grouping selection ability and Oracle property of the improved elastic network model in the optimization of neural network. At last, in regression and classification experiments, the proposed model was compared with L1-norm, L2-norm and elastic network regularization term, and had the regression error decreased by 87.09, 88.54 and 47.02 and the classification accuracy improved by 3.98, 2.92 and 3.58 percentage points respectively. Thus, theory and experimental results prove that the improved elastic network model can effectively improve the generalization ability of deep neural network model and the performance of optimization algorithm, and solve the overfitting problem of deep learning.

According to the idea of manually drawing a train diagram of the express and slow, the different proportions modularization thought of express and slow trains was proposed. Under the condition to satisfy the requirements of trains,the transitions and adjustments between different modules were added to meet the entrance/exit tracks of depot, so that the automatically generated diagram could meet the needs of designers. It can draw different full-day operation plans of different lines in particular proportions. Besides it can convert train diagram into CAD scripts and realize automatic drawing in CAD software. Finally, taking line 18 of Chengdu Metro as an example, the proposed method is implemented and its feasibility is proved.

A new tags anti-collision algorithm was proposed for the reader collision problems in the Radio Frequency IDentification (RFID) technology. It divided tags into groups based on the coset partition theory, and restricted each group to response in a fixed timeslot. According to the query codes and collision flag bits, the reader could identify a group of tags in one slot. The Matlab simulation results show that, compared with the binary search algorithm and dynamic frame timeslot algorithm, the proposed algorithm improves the slot utilization and throughput when the number of tags is large.

In order to protect Android platforms from the application-level privilege escalation attacks, this paper analyzed the XManDroid access control model, which has better ability on fighting these attacks, especially the collusion attack on the covert channel. To address the problem that XManDroid could not detect the multi-application and multi-permissions collusion attacks, this paper proposed an improved mandatory access control model which recorded the communication history of applications by building an IPC links colored diagram. At last, the test result on the prototype system show that the new model can solve the problem in the XManDroid well.

The template-based feature in Threading Building Blocks (TBB) simplifies parallel design and is suitable for efficient design of multi-core parallelism. Since fractal computing is CPU-intensive, it is practicable to parallelize fractal computation under TBB. As to the workload unbalance problem in parallelism, a balance method based on sampling execution time was presented to estimate workload. The proposed method realized the task partition through the workload estimate from sampling execution time, and TBB task scheduler was invoked for parallel process. The experimental results show that the proposed method has high estimation accuracy and low time rate so as to effectively achieve workload balance, and good speedups are available through TBB design.

Embedded operating systems become increasingly significant, which run on the resource-limited home appliances and industry instruments. Meanwhile people pay more and more attention to 3D technique. Therefore it is necessary to transplant Direct3D to embedded operating systems. The transplant and research of Direct3D based on CAR component technique on ElastOS were analyzed. The realization of ElaD3D interfaces on ElastOS and Windows synchronously and the exertion of CAR component programming ideas in the transplant of Direct3D were expatiated. So client programs can register some or other event handling function solely so as to predigest programming greatly.

A solution to data mining service design based on EJB technology was introduced to meet the requirement and environment status for enterprises. The DAA application system was developed according to the solution. Several key technologies in system implementation including coarse grained accessing method, intermediate data management, asynchronous communication in mining and data browsing were discussed. A mining example based on C4.5 algorithm in DAA system was presented.

The advantages of media player using component technique, such as automatic replacing decoders and dynamic upgrading, were analysed. With an example of DirectShow, how a media player with component technique works was illuminated. Afterwards, by analysing DirectShow in detail(on synchronization and controlling), DirectShow was simplified and improved, and a new set of interface definition was shown, a scheme of media player was implemented as well. This scheme was proved to be able to support hardware decoder, and be expanded to media capture.