A Filtered Back-Projection （FBP） ultrasonic tomography reconstruction algorithm based on sparse representation was proposed to solve the difficulty of traditional ultrasonic Lamb wave in detecting and vividly describing the delamination defects composite materials. Firstly， the Lamb wave time-of-flight signals in the composite plate with defect were used as the projection values， the one-dimensional Fourier transform of the projection was equivalent to the two-dimensional Fourier transform of the original image， and the FBP reconstructed image was obtained by convolution with the filter function and projection along different directions. Then， the sparse super-resolution model was constructed and jointly trained by constructing a dictionary of low-resolution image blocks and high-resolution image blocks in order to strengthen the sparse similarity between low- and high-resolution blocks and real image blocks， and a complete dictionary was constructed using low- and high-resolution blocks. Finally， the images obtained by FBP were substituted into the constructed dictionary to obtain the complete high-resolution images. Experimental results show that the proposed algorithm improves Peak Signal-to-Noise Ratio （PSNR）， Structural Similarity （SSIM）， and Edge Structural Similarity （ESSIM） values in the reconstructed image by 9.22%， 2.90%， 80.77%， and 4.75%， 1.52%， 16.5%， respectively compared with the linear interpolation and bicubic spline interpolation algorithms. The proposed algorithm can detect delamination defects in composite materials， improve the resolution of the obtained images with delamination defects and enhance the edge details of the images.

The research on the evolutionary mechanisms and models of Protein-Protein Interaction (PPI) network is significant for understanding the evolution of the biological systems as well as the formation process of the organisms. So far, there have been kinds of models based on different evolutionary mechanisms. All of these models exhibit certain topological characteristics emerging from the protein-protein interaction networks, while some limitations exist simultaneously. This paper focused on several classic protein-protein interaction network models, analyzing the main ideas of these models and comparing the topological characteristics derived from them with those of real protein-protein interaction networks. A summary of the features for each model was given based on the experiments. At last, several viewpoints for the future research of protein-protein interaction network models were also proposed to provide a useful reference for further studies.

Concerning the poor positioning rate and localization precision of Grid-Scan algorithm, an improved Grid-Scan localization algorithm based on virtual beacon nodes was proposed. Three related works were mentioned as follows: Firstly, the unknown nodes which have neighbor beacon nodes located themselves by using the beacon nodes, and the located unknown nodes were upgraded to virtual beacon nodes. Secondly, the unknown nodes that do not have neighbor beacon nodes got their location through virtual beacon nodes. Finally, different communication radiuses were set between beacon nodes, virtual beacon nodes and unknown nodes to scan in order to accomplish the localization. The simulation results show that the improved algorithm’s positioning accuracy and positioning rate increase by 6.35% and 23.37% on average respectively.

An efficient Morphological Un-Decimated Wavelet (MUDW) transform with more delicate and accurate multi-scale decomposition performance that suites real-time image fusion was proposed. It took the average of dilation and erosion as the analysis operator, and the difference of adjacent scale images as the detail image. Size-increasing structure elements were adopted to get better fusion result. Due to the simplicity of dilation and erosion operator, computation time is shorter than other real-time algorithms. Furthermore, a factor was added during reconstruction, to obtain an obvious enhancement effect. The experimental results show that the new method outperforms other real-time algorithms.