The impact of certain separate characteristics, including the porosity parameter, reaction rate parameter, and viscoelastic parameters of steady convective diffusion across a rectangular channel, has been investigated...The impact of certain separate characteristics, including the porosity parameter, reaction rate parameter, and viscoelastic parameters of steady convective diffusion across a rectangular channel, has been investigated in this article. The model’s momentum and concentration equations were developed using the similarities technique, and the numerically finite volume method was combined with the Beavers and Joseph slip conditions. Various graphs have been used to get insight into various parameters of the problem on velocity and concentration. The cartilage surfaces are assumed to be porous, and the viscosity of synovial fluid varies with hyaluronate (HA) content.展开更多
Meta-learning provides a framework for the possibility of mimicking artificial intelligence.How-ever,data distribution of the training set fails to be consistent with the one of the testing set as the limited domain d...Meta-learning provides a framework for the possibility of mimicking artificial intelligence.How-ever,data distribution of the training set fails to be consistent with the one of the testing set as the limited domain differences among them.These factors often result in poor generalization in existing meta-learning models.In this work,a novel smoother manifold for graph meta-learning(SGML)is proposed,which derives the similarity parameters of node features from the relationship between nodes and edges in the graph structure,and then utilizes the similarity parameters to yield smoother manifold through embedded propagation module.Smoother manifold can naturally filter out noise from the most important components when generalizing the local mapping relationship to the global.Besides suiting for generalizing on unseen low data issues,the framework is capable to easily perform transductive inference.Experimental results on MiniImageNet and TieredImageNet consistently show that applying SGML to supervised and semi-supervised classification can improve the performance in reducing the noise of domain shift representation.展开更多
The thermodynamic suppression effect on cavitation can improve the suction performance of hydraulic machinery.In the present study,tip leakage vortex cavitation,which is the primary type of cavitation in pumps,is repr...The thermodynamic suppression effect on cavitation can improve the suction performance of hydraulic machinery.In the present study,tip leakage vortex cavitation,which is the primary type of cavitation in pumps,is reproduced using a twisted hydrofoil with tip clearance in high-temperature water,and the thermodynamic suppression effect on cavity length is evaluated.First,a similarity parameter is identified from room-temperature experiments to extract the pure thermodynamic suppression effect.Second,the cavitation number for a critical cavity length is examined in terms of similarity parameters and correlated with the conventional thermodynamic parameter.It is found that none of the existing parameters fully predict the degree of cavity suppression under high-temperature conditions.展开更多
文摘The impact of certain separate characteristics, including the porosity parameter, reaction rate parameter, and viscoelastic parameters of steady convective diffusion across a rectangular channel, has been investigated in this article. The model’s momentum and concentration equations were developed using the similarities technique, and the numerically finite volume method was combined with the Beavers and Joseph slip conditions. Various graphs have been used to get insight into various parameters of the problem on velocity and concentration. The cartilage surfaces are assumed to be porous, and the viscosity of synovial fluid varies with hyaluronate (HA) content.
基金Supported by the National Natural Science Foundation of China(No.61171131)the Key R&D Program of Shandong Province(No.YD01033)the China Scholarship Council Project(No.021608370049).
文摘Meta-learning provides a framework for the possibility of mimicking artificial intelligence.How-ever,data distribution of the training set fails to be consistent with the one of the testing set as the limited domain differences among them.These factors often result in poor generalization in existing meta-learning models.In this work,a novel smoother manifold for graph meta-learning(SGML)is proposed,which derives the similarity parameters of node features from the relationship between nodes and edges in the graph structure,and then utilizes the similarity parameters to yield smoother manifold through embedded propagation module.Smoother manifold can naturally filter out noise from the most important components when generalizing the local mapping relationship to the global.Besides suiting for generalizing on unseen low data issues,the framework is capable to easily perform transductive inference.Experimental results on MiniImageNet and TieredImageNet consistently show that applying SGML to supervised and semi-supervised classification can improve the performance in reducing the noise of domain shift representation.
基金supported by JST SPRING Grant No.JPMJSP2114 and JSPC KAKENHI Grant No.25KJ0601.
文摘The thermodynamic suppression effect on cavitation can improve the suction performance of hydraulic machinery.In the present study,tip leakage vortex cavitation,which is the primary type of cavitation in pumps,is reproduced using a twisted hydrofoil with tip clearance in high-temperature water,and the thermodynamic suppression effect on cavity length is evaluated.First,a similarity parameter is identified from room-temperature experiments to extract the pure thermodynamic suppression effect.Second,the cavitation number for a critical cavity length is examined in terms of similarity parameters and correlated with the conventional thermodynamic parameter.It is found that none of the existing parameters fully predict the degree of cavity suppression under high-temperature conditions.
