The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods [1] are considered th...The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods [1] are considered the preferred methods. Selecting an effective preconditioner with appropriate parameters for a specific sparse linear system presents a challenging task for many application scientists and engineers who have little knowledge of preconditioned iterative methods. The purpose of this paper is to predict the parameter solvability space of the preconditioners with two or more parameters. The parameter solvability space is usually irregular, however, in many situations it shows spatial locality, i.e. the parameter locations that are closer in parameter space are more likely to have similar solvability. We propose three spatial data mining methods to predict the solvability of ILUT which make usage of spatial locality in different ways. The three methods are MSC （multi-points SVM classifier）, OSC （overall SVM classifier）, and OSAC （overall spatial autoregressive classifier）. The experimental results show that both MSC and OSAC can obtain 90% accuracy in prediction, but OSAC is much simpler to implement. We focus our work on ILUT preconditioner [2], but the proposed strategies should be applicable to other preconditioners with two or more parameters.展开更多
To solve the problems with coronary stent implantation, coronary artery stent surface was directly modified by three-beam laser interference lithography through imitating the water-repellent surface of lotus leaf, and...To solve the problems with coronary stent implantation, coronary artery stent surface was directly modified by three-beam laser interference lithography through imitating the water-repellent surface of lotus leaf, and uniform micro-nano structures with the controllable period were fabricated. The morphological properties and contact angle(CA) of the microstructure were measured by scanning electron microscope(SEM) and CA system. The water repellency of stent was also evaluated by the contact and then separation between the water drop and the stent. The results show that the close-packed concave structure with the period of about 12 μm can be fabricated on the stent surface with special parameters(incident angle of 3°, laser energy density of 2.2 J·cm^(-2) and exposure time of 80 s) by using the three-beam laser at 1 064 nm, and the structure has good water repellency with CA of 120°.展开更多
文摘The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods [1] are considered the preferred methods. Selecting an effective preconditioner with appropriate parameters for a specific sparse linear system presents a challenging task for many application scientists and engineers who have little knowledge of preconditioned iterative methods. The purpose of this paper is to predict the parameter solvability space of the preconditioners with two or more parameters. The parameter solvability space is usually irregular, however, in many situations it shows spatial locality, i.e. the parameter locations that are closer in parameter space are more likely to have similar solvability. We propose three spatial data mining methods to predict the solvability of ILUT which make usage of spatial locality in different ways. The three methods are MSC （multi-points SVM classifier）, OSC （overall SVM classifier）, and OSAC （overall spatial autoregressive classifier）. The experimental results show that both MSC and OSAC can obtain 90% accuracy in prediction, but OSAC is much simpler to implement. We focus our work on ILUT preconditioner [2], but the proposed strategies should be applicable to other preconditioners with two or more parameters.
基金supported by the National Natural Science Foundation of China(No.81470024)
文摘To solve the problems with coronary stent implantation, coronary artery stent surface was directly modified by three-beam laser interference lithography through imitating the water-repellent surface of lotus leaf, and uniform micro-nano structures with the controllable period were fabricated. The morphological properties and contact angle(CA) of the microstructure were measured by scanning electron microscope(SEM) and CA system. The water repellency of stent was also evaluated by the contact and then separation between the water drop and the stent. The results show that the close-packed concave structure with the period of about 12 μm can be fabricated on the stent surface with special parameters(incident angle of 3°, laser energy density of 2.2 J·cm^(-2) and exposure time of 80 s) by using the three-beam laser at 1 064 nm, and the structure has good water repellency with CA of 120°.
