To improve the error detection efficiency and the benefit of regression testing of test case sequence， a test case prioritization approach based on historical data and multi-objective optimization was proposed. Firstly， the test case set was clustered according to the text topic similarity and code coverage similarity of test cases， and the association rules were mined for execution failure relationships between test cases according to the historical execution information， thereby preparing for the subsequent process. Then， the multi-objective optimization algorithm was used to sort the test cases in each cluster. After that， the final sorting sequence was generated to separate the similar test cases. Finally， the association rules between test cases were used to dynamically adjust the execution order of test cases， so that the test cases that may fail were executed with priority， so as to further improve the efficiency of defect detection. Compared with random search approach， the approach based on clustering， the approach based on topic model， the approach based on association rules and multi-objective optimization， the proposed approach has the average value of Average Percentage of Faults Detected （APFD） increased by 12.59%， 5.98%， 3.01% and 2.95%， respectively， and has the average value of APFD cost-cognizant （APFDc） increased by 17.17%， 5.04%， 5.08% and 8.21%， respectively. Experimental results show that the proposed approach can improve the benefit of regression testing effectively.

Since the existing adaptive neighborhood based multi-view clustering algorithms do not consider the noise and the loss of consensus graph information, a Robust Multi-View Graph Clustering(RMVGC) algorithm based on adaptive neighborhood was proposed. Firstly, to avoid the influence of noise and outliers on the data, the Robust Principal Component Analysis(RPCA) model was used to learn multiple clean low-rank data from the original data. Secondly, the adaptive neighborhood learning was employed to directly fuse multiple clean low-rank data to obtain a clean consensus affinity graph, thus reducing the information loss in the process of graph fusion. Experimental results demonstrate that the Normalized Mutual Informations(NMI) of the proposed algorithm RMVGC is improved by 5.2, 1.36, 27.2, 4.66 and 5.85 percentage points, respectively, compared to the current popular multi-view clustering algorithms on MRSCV1, BBCSport, COIL20, ORL and UCI digits datasets. Meanwhile, in the proposed algorithm, the local structure of data is maintained, the robustness against the original data is enhanced, the quality of affinity graph is improved, and such that the proposed algorithm has great clustering performance on multi-view datasets.

Since the methods of multiple kernel subspace spectral clustering do not consider the problem of noise and relation graph structure, a novel Joint Low-rank and Sparse Multiple Kernel Subspace Clustering algorithm (JLSMKC) was proposed. Firstly, with combination of low-rank and sparse representation for subspace learning, the relation graph obtained the attribute of low-rank and sparse structure. Secondly, a robust multiple kernel low-rank and sparsity constraint model was constructed to reduce the influence of noise on the relation graph and handle the nonlinear structure of data. Finally, the quality of relation graph was enhanced by making full use of the consensus kernel matrix by multiple kernel approach. The experimental results on seven datasets show that the proposed JLSMKC is better than five popular multiple kernel clustering algorithms in ACCuracy (ACC), Normalized Mutual Information (NMI) and Purity. Meanwhile, the clustering time is reduced and the block diagonal quality of relation graph is improved. JLSMKC has great advantages in clustering performance.

Concerning the NP (Nondeterministic Polynomial)-hard problem of localizing link failures from end-to-end measurement in communication network, a new tomography method which relaxes the Boolean constraints was proposed. Firstly, the relationship between path state and link state in a network was modeled as Boolean algebraic equations, and the essence of localizing failures was treated as an optimization problem under the constraints of these equations. Then the NP property was derived from the binary states (normal/failed) of link state in the optimization problem. Therefore, by relaxing the Boolean constraints, the proposed method simply transformed the problem into a Linear Programming (LP) problem, which can be easily solved by any LP solver to get the set of failed links. Simulation experiments were conducted to identity link failures in real network topologies. The experimental results show that the false negative rate of the proposed method is 5%-30% lower than that of the classical heuristic algorithm TOMO (TOMOgraphy).

Concerning the problems that Two-Dimensional Multiple-Input Multiple-Output (2D MIMO) systems only consider the effects of horizontal radiation pattern, ignoring the effects of vertical radiation pattern, and the closed-form on the sum rate of 2D MIMO system over K (Rayleigh/Gamma) fading channels involves special functions, two closed-form upper bounds on achievable sum rate of Three Dimensional Distributed Multiple-Input Multiple-Output (3D D-MIMO) systems with Zero-Forcing (ZF) receivers over K composite fading channels were proposed. The upper bounds considered Rayleigh multipath fading, Gamma shadow fading, geometric path-loss, 3D antenna radiation loss, and user distribution. The experimental results show that the obtained expressions accurately match with the Monte Carlo simulation conclusions.

In the IPv4/IPv6 transition process, since some legacy IPv4 networks still need to communicate with the IPv6 Internet, the stateless communication mechanism between an IPv4 network and the IPv6 Internet, which complements the current IPv4/IPv6 translation framework, was proposed. First, the communication procedures in two related scenarios were demonstrated. The two scenarios include IPv6 Internet clients accessing IPv4 servers and IPv4 clients accessing IPv6 Internet servers. The one-way IPv6-IPv4 address mapping function is the key component of the mechanism. Therefore, the requirements and three quantitative criteria of the one-way mapping function were discussed. Afterwards, multiple Hash functions as the candidates of the one-way mapping function were compared and analyzed with the real user data of large IPv6 websites and real IPv6 server addresses. The simulation results show that the FarmCity Hash function is suitable to be deployed in the above two scenarios because it has short average processing time, low collision rate and low reverse query complexity. It also verifies the validity of the stateless communication mechanism. Compared with current stateful communication mechanisms, the stateless mechanism has better scalability and traceability. Moreover, the capacity for bidirectional communication facilitates a smooth migration path towards the IPv6 Internet.

In Dynamically Tuned Gyroscope (DTG) system, traditional identification methods, including least square identification method and traditional frequency domain identification method, could not achieve acceptable identification fitness degree. To deal with this problem, outlier-eliminated frequency identification method was proposed. In consideration of the characteristics of DTG model structure and intrinsic colored noise, outlier-eliminated method was applied to DTG frequency domain identification. The experimental results indicate that outlier-eliminated frequency identification method, with a fitness degree above 90%, compared with both least square identification method and traditional frequency domain identification method, has a better performance. In addition, outlier-eliminated frequency identification method possesses of good repeatability and stability. Outlier-eliminated frequency identification method could improve the identification fitness degree of DTG system.

To carry out lens distortion correction of unknown camera parameters, a method calibrating distortion center first and distortion coefficient second was proposed. First, with target imaged at two different focal lengths, distortion center could be positioned using relative position relation of the same target points in two pictures; then according to the invariance of line perspective projection, distortion coefficient could be searched by variable step optimization method. The simulation experiment showed that the average error of distortion center was (0.2243,0.1636) pixel, and the distortion coefficient error was 0.28% when target point number was 25, the noise level was 0.2 pixel. Real image experiment shows that distortion center and distortion coefficient obtained by the proposed method can correct the image well. The method is easy to implement, the calibration of camera's internal and external parameters and the knowledge of line grid's world coordinates can be neglected.

In this paper, considering the Web service composition model described by DAG (Directed Acrylic Graph), a new Quality of Service (QoS) computing method for the composition service based on topological sequence reduction (QCMTSR) was proposed. Based on the basic structures and their QoS computing formulas of iterative reduction method two kinds of basic structures (i.e. serial reduction structure and parallel reduction structure) were defined in graph DAG, and their QoS calculation formulas were also given. During accessing each node step by step in the topology sequence for DAG. Repeating this process until the last node in this queue, then the QoS measure results of the last node were the computing results of the composition service. It has been proved that the algorithm can be applied to all the composition services described by DAG, and the experimental results show that the algorithm QCMTSR is more accurate in the measurement of reliability and availability.

As the correlation between color components in color image is not considered in the traditional edge detection algorithms, and the detection results will be affected by the threshold value, a new kind of edge detection method for color image was proposed combining quaternion with Self-Organizing Map (SOM). Based on the quaternionic Cauchy integral formula and vector product, the edge characteristic vector was constructed. Then the SOM was trained by the vector and used for edge detection. The experimental results show that the proposed method has stronger retention capacity of the details.

The detected data often appear redundant, which affects the actual application of traffic models. A method of recognizing and reducing redundant data was proposed. Redundant data were recognized based on rank-based weights and packet method. Firstly, each of traffic parameters was endowed with certain weight according to rank-based weights method. Secondly, in terms of group thought, large data sets were divided into many non-intersecting small data sets. Finally, redundant data were detected and eliminated in each small data set. To avoid missing, the above steps can be repeated. And the recognized redundant data were reduced by average method. An application example shows that, the proposed recognition method of redundant data has a good detection precision, the recall and the precision decreased with the threshold increasing, but still over 93%. The reduced data have a high fitting degree, up to 0.938. The results indicate that, the problem of single data source can be solved effectively.

The TMS320DM642 Digital Media Processor is based on the C64x CPU, a member of the C6000 DSP family. The DM642 integrates a number of peripherals to address the development of video and imaging applications. The development process and implementation methods of the multi-level bootloader for bulk Flash memory bootloading on DM642 Platform was introduced in detail,and a new way to develop top multimedia embedded system based on TMS320DM642 Digital Media Processor was given. It is proved that the way introduced here is practical and has a good prospect.

 Internet2 Commons is a next generation application framework that encourages deployment of tools for large scale distributed collaborative environment for the research and education community in U.S. The general architecture of design and managing large-scale, distributed videoconference collaborative environment was proposed. Key techniques of H 323-based videoconference system in Internet2 Commons were studied. Ordinary videoconference applications and special videoconference-based applications developed on Internet2 were also introduced. Migration policies of videoconference application from IPv4 network to IPv6 testbed were analyzed and Conclusions were given.

 Aimed at image watermark robustness, an evaluative method based on synergetic order parameter and its usage was first advanced. Many kinds of robust experiment of Image carrier were done. After procession, the synergetic original order parameter of patterns in the set were calculated and compared. Through validation by the order parameter evolvement curves, their robust conclusions were gotten. This method is more convenient and applied than the correlative coefficient method, although the two methods have same conclusion.