The complexity of an elastic wavefield increases the nonlinearity of inversion, To some extent, multiscale inversion decreases the nonlinearity of inversion and prevents it from falling into local extremes. A multisca...The complexity of an elastic wavefield increases the nonlinearity of inversion, To some extent, multiscale inversion decreases the nonlinearity of inversion and prevents it from falling into local extremes. A multiscale strategy based on the simultaneous use of frequency groups and layer stripping method based on damped wave field improves the stability of inversion. A dual-level parallel algorithm is then used to decrease the computational cost and improve practicability. The seismic wave modeling of a single frequency and inversion in a frequency group are computed in parallel by multiple nodes based on multifrontal massively parallel sparse direct solver and MPI. Numerical tests using an overthrust model show that the proposed inversion algorithm can effectively improve the stability and accuracy of inversion by selecting the appropriate inversion frequency and damping factor in low- frequency seismic data.展开更多
Synthetic dry adhesives inspired by the nano-and micro-scale hairs found on the feet of geckos and some spiders have beendeveloped for almost a decade. Elastomeric single level micro-scale mushroom shaped fibres are c...Synthetic dry adhesives inspired by the nano-and micro-scale hairs found on the feet of geckos and some spiders have beendeveloped for almost a decade. Elastomeric single level micro-scale mushroom shaped fibres are currently able to function evenbetter than natural dry adhesives on smooth surfaces under normal loading. However, the adhesion of these single level syntheticdry adhesives on rough surfaces is still not optimal because of the reduced contact surface area. In nature, contact area ismaximized by hierarchically structuring different scales of fibres capable of conforming surface roughness. In this paper, weadapt the nature’s solution arid propose a novel dual-level hierarchical adhesive design using Polydimethylsiloxane (PDMS),which is tested under peel loading at different orientations. A negative macro-scale mold is manufactured by using a laser cutterto define holes in a Poly(methyl methacrylate) (PMMA) plate. After casting PDMS macro-scale fibres by using the obtainedPMMA mold, a previously prepared micro-fibre adhesive is bonded to the macro-scale fibre substrate. Once the bondingpolymer is cured, the micro-fibre adhesive is cut to form macro scale mushroom caps. Each macro-fibre of the resulting hierarchicaladhesive is able to conform to loads applied in different directions. The dual-level structure enhances the peel strengthon smooth surfaces compared to a single-level dry adhesive, but also weakens the shear strength of the adhesive for a given areain contact. The adhesive appears to be very performance sensitive to the specific size of the fibre tips, and experiments indicatethat designing hierarchical structures is not as simple as placing multiple scales of fibres on top of one another, but can requiresignificant design optimization to enhance the contact mechanics and adhesion strength.展开更多
Dual-level stress plateaus (i.e., relatively short peak stress plateaus, followed by prolonged crushing stress plateaus) in metallic hexagonal honeycombs subjected to out-of-plane impact loading are characterized usin...Dual-level stress plateaus (i.e., relatively short peak stress plateaus, followed by prolonged crushing stress plateaus) in metallic hexagonal honeycombs subjected to out-of-plane impact loading are characterized using a combined numerical and analytical study, with the influence of the strain-rate sensitivity of the honeycomb pare nt material accounted for. The predicti ons are validated against existing experimental measurements, and good agreement is achieved. It is demonstrated that honeycombs exhibit dual-level stress plateaus when bucklewaves are initiated and propagate in cell walls, followed by buckling and progressive folding of the cell walls. The abrupt stress drop from peak to crushing plateau in the compressive stress versus strain curve can be explained in a way similar to the quasi-static buckling of a clamped plate. The duration of the peak stress plateau is more evident for strain-rate insensitive honeycombs.展开更多
Existing Transformer-based image captioning models typically rely on the self-attention mechanism to capture long-range dependencies,which effectively extracts and leverages the global correlation of image features.Ho...Existing Transformer-based image captioning models typically rely on the self-attention mechanism to capture long-range dependencies,which effectively extracts and leverages the global correlation of image features.However,these models still face challenges in effectively capturing local associations.Moreover,since the encoder extracts global and local association features that focus on different semantic information,semantic noise may occur during the decoding stage.To address these issues,we propose the Local Relationship Enhanced Gated Transformer(LREGT).In the encoder part,we introduce the Local Relationship Enhanced Encoder(LREE),whose core component is the Local Relationship Enhanced Module(LREM).LREM consists of two novel designs:the Local Correlation Perception Module(LCPM)and the Local-Global Fusion Module(LGFM),which are beneficial for generating a comprehensive feature representation that integrates both global and local information.In the decoder part,we propose the Dual-level Multi-branch Gated Decoder(DMGD).It first creates multiple decoding branches to generate multi-perspective contextual feature representations.Subsequently,it employs the Dual-Level Gating Mechanism(DLGM)to model the multi-level relationships of these multi-perspective contextual features,enhancing their fine-grained semantics and intrinsic relationship representations.This ultimately leads to the generation of high-quality and semantically rich image captions.Experiments on the standard MSCOCO dataset demonstrate that LREGT achieves state-of-the-art performance,with a CIDEr score of 140.8 and BLEU-4 score of 41.3,significantly outperforming existing mainstream methods.These results highlight LREGT’s superiority in capturing complex visual relationships and resolving semantic noise during decoding.展开更多
基金supported by the Natural Science Foundation of China(No.41374122)
文摘The complexity of an elastic wavefield increases the nonlinearity of inversion, To some extent, multiscale inversion decreases the nonlinearity of inversion and prevents it from falling into local extremes. A multiscale strategy based on the simultaneous use of frequency groups and layer stripping method based on damped wave field improves the stability of inversion. A dual-level parallel algorithm is then used to decrease the computational cost and improve practicability. The seismic wave modeling of a single frequency and inversion in a frequency group are computed in parallel by multiple nodes based on multifrontal massively parallel sparse direct solver and MPI. Numerical tests using an overthrust model show that the proposed inversion algorithm can effectively improve the stability and accuracy of inversion by selecting the appropriate inversion frequency and damping factor in low- frequency seismic data.
基金Finallcial support was provided by the Natural Sciences and Engineering Research Council of Canada(NSERC)the European Space Agency(ESA)
文摘Synthetic dry adhesives inspired by the nano-and micro-scale hairs found on the feet of geckos and some spiders have beendeveloped for almost a decade. Elastomeric single level micro-scale mushroom shaped fibres are currently able to function evenbetter than natural dry adhesives on smooth surfaces under normal loading. However, the adhesion of these single level syntheticdry adhesives on rough surfaces is still not optimal because of the reduced contact surface area. In nature, contact area ismaximized by hierarchically structuring different scales of fibres capable of conforming surface roughness. In this paper, weadapt the nature’s solution arid propose a novel dual-level hierarchical adhesive design using Polydimethylsiloxane (PDMS),which is tested under peel loading at different orientations. A negative macro-scale mold is manufactured by using a laser cutterto define holes in a Poly(methyl methacrylate) (PMMA) plate. After casting PDMS macro-scale fibres by using the obtainedPMMA mold, a previously prepared micro-fibre adhesive is bonded to the macro-scale fibre substrate. Once the bondingpolymer is cured, the micro-fibre adhesive is cut to form macro scale mushroom caps. Each macro-fibre of the resulting hierarchicaladhesive is able to conform to loads applied in different directions. The dual-level structure enhances the peel strengthon smooth surfaces compared to a single-level dry adhesive, but also weakens the shear strength of the adhesive for a given areain contact. The adhesive appears to be very performance sensitive to the specific size of the fibre tips, and experiments indicatethat designing hierarchical structures is not as simple as placing multiple scales of fibres on top of one another, but can requiresignificant design optimization to enhance the contact mechanics and adhesion strength.
基金the National NaturalScience Foundation of China (Grants 11472209 and 11472208)the China Postdoctoral Science Foundation (Grant 2016M600782)+4 种基金thePostdoctoral Scientific Research Project of Shaanxi Province (Grant2016BSHYDZZ18)the Zhejiang Provincial Natural Science Foundationof China (Grant LGG18A020001)the Fundamental ResearchFunds for Xi'an Jiaotong University (Grant xjj2015102)the JiangsuProvince Key Laboratory of High-end Structural Materials (Granthsm1305)and the Natural Science Basic Research Plan in ShaanxiProvince of China (Grant 2018JQ1078).
文摘Dual-level stress plateaus (i.e., relatively short peak stress plateaus, followed by prolonged crushing stress plateaus) in metallic hexagonal honeycombs subjected to out-of-plane impact loading are characterized using a combined numerical and analytical study, with the influence of the strain-rate sensitivity of the honeycomb pare nt material accounted for. The predicti ons are validated against existing experimental measurements, and good agreement is achieved. It is demonstrated that honeycombs exhibit dual-level stress plateaus when bucklewaves are initiated and propagate in cell walls, followed by buckling and progressive folding of the cell walls. The abrupt stress drop from peak to crushing plateau in the compressive stress versus strain curve can be explained in a way similar to the quasi-static buckling of a clamped plate. The duration of the peak stress plateau is more evident for strain-rate insensitive honeycombs.
基金supported by the Natural Science Foundation of China(62473105,62172118)Nature Science Key Foundation of Guangxi(2021GXNSFDA196002)+1 种基金in part by the Guangxi Key Laboratory of Image and Graphic Intelligent Processing under Grants(GIIP2302,GIIP2303,GIIP2304)Innovation Project of Guang Xi Graduate Education(2024YCXB09,2024YCXS039).
文摘Existing Transformer-based image captioning models typically rely on the self-attention mechanism to capture long-range dependencies,which effectively extracts and leverages the global correlation of image features.However,these models still face challenges in effectively capturing local associations.Moreover,since the encoder extracts global and local association features that focus on different semantic information,semantic noise may occur during the decoding stage.To address these issues,we propose the Local Relationship Enhanced Gated Transformer(LREGT).In the encoder part,we introduce the Local Relationship Enhanced Encoder(LREE),whose core component is the Local Relationship Enhanced Module(LREM).LREM consists of two novel designs:the Local Correlation Perception Module(LCPM)and the Local-Global Fusion Module(LGFM),which are beneficial for generating a comprehensive feature representation that integrates both global and local information.In the decoder part,we propose the Dual-level Multi-branch Gated Decoder(DMGD).It first creates multiple decoding branches to generate multi-perspective contextual feature representations.Subsequently,it employs the Dual-Level Gating Mechanism(DLGM)to model the multi-level relationships of these multi-perspective contextual features,enhancing their fine-grained semantics and intrinsic relationship representations.This ultimately leads to the generation of high-quality and semantically rich image captions.Experiments on the standard MSCOCO dataset demonstrate that LREGT achieves state-of-the-art performance,with a CIDEr score of 140.8 and BLEU-4 score of 41.3,significantly outperforming existing mainstream methods.These results highlight LREGT’s superiority in capturing complex visual relationships and resolving semantic noise during decoding.
