Automatic evaluation of X-ray weld image quality is an important foundation for automatic evaluation of weld image defects. A digital blackness meter model was proposed to realize the automatic evaluation of X-ray weld image quality. Firstly, in order to obtain the physical blackness by numerical calculation, the physical illumination model and the weld blackness model were combined by the digital blackness meter model. Then, through the analysis of the correlation between the physical blackness value of the sample image and the corresponding grayscale value, a method for obtaining the parameters of the digital blackness meter model was given. Finally, an X-ray weld film blackness automatic evaluation algorithm was proposed. The experiments on the actual X-ray weld images show that, the accuracy of the proposed algorithm can reach 99% without manual intervention. The cross-validation experiments show that the sensitivity of the proposed method is 98.5% and the specificity of the method can reach 100%. The digital blackness meter model based on illumination model and blackness model as well as the solving algorithm can replace the commonly used physical blackness meter and realize the automation of weld image quality evaluation.

Currently, two vectorization methods which exploit Simple Instruction Multiple Data (SIMD) parallelism are loop-based method and Superword Level Parallel (SLP) method. Focusing on the problem that the current compiler cannot realize function level vectorization, a method of function level vectorization based on static single assignment was proposed. Firstly, the variable properties of program were analysed, and then a set of compiling directives including SIMD function annotations, uniform clauses, linear clauses were used to realize function level vectorization. Finally, the vectorized code was optimized by using the variable attribute result. Some test cases from the field of multimedia and image processing were selected to test the function and performance of the proposed function level vectorization on Sunway platform. Compared with the scalar program execution results, the execution of the program after the function level vectorization is more efficient. The experimental results show that the function level vectorization can achieve the same effect of task level parallelism, which is instructive to realize the automatic function level vectorization.

Concerning that the upper, lower bounds and stride of the non-normalized loop are uncertain, some issues were normalized based on a transform method such as that loop conditions were logical expression, increment-reduction statement and do-while. An unroll-jam method was proposed to deal with the loops that cannot be normalized, which mined the unroll-jam results by Superword Level Parellelism (SLP) vectorization. Compared with the existing Single Instruction Multiple Data (SIMD) vectorization method for non-normalized loops, the experimental results show that the transform method and unroll-jam method are better to explore the parallelism of the non-normalized loops, which can improve the performance by more than 6%.

This paper represented the information of each vertex in ontology graph as a vector. According to its structure of ontology graph, the vertices were divided into k parts. It chose vertices from each part, and chose the ranking loss function. It used k-partite ranking learning algorithm to get the optimization ranking function, mapped each vertex of ontology structure graph into a real number, and then calculated the relative similarities of concepts by comparing the difference between real numbers. The experimental results show that the method for calculating the relative similarity between the concepts of ontology is effective.

The work relevant to the Grid Database was introduced. According to one practical application of an enterprise, author discussed the design and implementation of real-time data replicate system in Grid Databases, which based on OGSA-DAI and publish/subscribe model. The overall architecture and the key technologies of data partition strategy were presented. Test results demonstrate that the model that bases on the Publish/Subscribe has higher efficiency and good real time property against the pull-method model that bases on the Oracle data linkage.