Nondestructive testing of fiber array with multiple missing fibers

National audienceOur goal is to detect defects in composite materialscomposed by multilayer planar plates with a periodicset of circular cylindrical fibers embedded in each layer. As astarter, the work presented is electromagnetic (EM) modelingand imaging of missing fibers within a fiber array standingin air. The multiple scattering method is utilized to analyzethe electromagnetic behavior, and the corresponding imagingmodel is established directly from Lippman-Schwinger integralformulation. Standard MUltiple SIgnal Classification (MUSIC)and the proposed joint sparsity which borrows the idea ofsparse theory are applied to retrieve the locations of missingfibers. Numerical results are provided to confirm availabilityand accuracy of EM modeling and defect imaging

Shifted Diffusion for Text-to-image Generation

We present Corgi, a novel method for text-to-image generation. Corgi is based on our proposed shifted diffusion model, which achieves better image embedding generation from input text. Unlike the baseline diffusion model used in DALL-E 2, our method seamlessly encodes prior knowledge of the pre-trained CLIP model in its diffusion process by designing a new initialization distribution and a new transition step of the diffusion. Compared to the strong DALL-E 2 baseline, our method performs better in generating image embedding from the text in terms of both efficiency and effectiveness, resulting in better text-to-image generation. Extensive large-scale experiments are conducted and evaluated in terms of both quantitative measures and human evaluation, indicating a stronger generation ability of our method compared to existing ones. Furthermore, our model enables semi-supervised and language-free training for text-to-image generation, where only part or none of the images in the training dataset have an associated caption. Trained with only 1.7% of the images being captioned, our semi-supervised model obtains FID results comparable to DALL-E 2 on zero-shot text-to-image generation evaluated on MS-COCO. Corgi also achieves new state-of-the-art results across different datasets on downstream language-free text-to-image generation tasks, outperforming the previous method, Lafite, by a large margin

Study on Stability and Control of Pre-excavated Withdrawal Channel under Mining Influence

AbstractPre-excavated withdrawal channel (PWC) is an effective means to shorten the withdrawal time of fully mechanized working face and improve the efficiency, safety, and reliability during the withdrawal. However, the key to the success of the withdrawal method is the influence of mining on the stability of PWC, taking the III32upper1 working face of Zhuzhuang Coal Mine as the engineering background. By theoretical analysis and numerical simulation, the deformation of the PWC is analyzed and the mechanical model of the influence of the instability of the main roof fracture on the PWC is established. And the effect of the fracture and rotation of the main roof on the PWC is analyzed. The result shows that the instability of the coal pillar leads to the fracture and rotary deformation of the main roof as the width of the coal pillar gradually decreases, which further aggravates the deformation of the PWC and the degree of ground pressure behavior. Based on the influence of mining on the PWC, a control method is proposed. This method uses hydraulic fracturing technology to weaken the mining stress and prevent the fracture of the main roof above the PWC. The control effect of hydraulic fracturing on PWC is analyzed through the establishment of numerical calculation model. The result of engineering practice demonstrates that the mining stress is significantly reduced, and the deformation of surrounding rock in the PWC is effectively controlled after hydraulic fracturing