The effect of the initial layer on the reversal mechanism in CoCr films

The dependence of OR, H/sub c/, and hysteresis loss is measured as functions of the angle with the applied field (H/sub a/) as a parameter. It is reported that with increasing H/sub c/ perpendicular to /H/sub k/ values the orientation direction of the magnetization gradually changes from in-plane (OR/sub perpendicular to /=0.7) to perpendicular (OR/sub perpendicular to /=3.9). The angular dependence of H/sub c/ is closely related to the value of H/sub a/. It was found that H/sub c//H/sub c perpendicular to / drastically decreases at H/sub a/=H/sub c perpendicular to max/ (159 kA/m) with decreasing H/sub a/. The influence of the demagnetizing field on the angular dependence of the magnetic behavior in CoCr films is also examined

Einstein-Gauss-Bonnet Black Strings at Large DD

We study the black string solutions in the Einstein-Gauss-Bonnet(EGB) theory at large $D$. By using the $1/D$ expansion in the near horizon region we derive the effective equations that describe the dynamics of the EGB black strings. The uniform and non-uniform black strings are obtained as the static solutions of the effective equations. From the perturbation analysis of the effective equations, we find that thin EGB black strings suffer from the Gregory-Laflamme instablity and the GB term weakens the instability when the GB coefficient is small, however, when the GB coefficient is large the GB term enhances the instability. Furthermore, we numerically solve the effective equations to study the non-linear instability. It turns out that the thin black strings are unstable to developing inhomogeneities along their length, and at late times they asymptote to the stable non-uniform black strings. The behavior is qualitatively similar to the case in the Einstein gravity. Compared with the black string instability in the Einstein gravity at large D, when the GB coefficient is small the time needed to reach to final state increases, but when the GB coefficient is large the time to reach to final state decreases. Starting from the point of view in which the effective equations can be interpreted as the equations for the dynamical fluid, we evaluate the transport coefficients and find that the ratio of the shear viscosity and the entropy density agrees with that obtained previously in the membrane paradigm after taking the large $D$ limit.Comment: 22 pages, 8 figures, some errors corrected, references adde

Correction of "Cloud Removal By Fusing Multi-Source and Multi-Temporal Images"

Remote sensing images often suffer from cloud cover. Cloud removal is required in many applications of remote sensing images. Multitemporal-based methods are popular and effective to cope with thick clouds. This paper contributes to a summarization and experimental comparation of the existing multitemporal-based methods. Furthermore, we propose a spatiotemporal-fusion with poisson-adjustment method to fuse multi-sensor and multi-temporal images for cloud removal. The experimental results show that the proposed method has potential to address the problem of accuracy reduction of cloud removal in multi-temporal images with significant changes.Comment: This is a correction version of the accepted IGARSS 2017 conference pape

Control-oriented implementation and model order reduction of a lithium-ion battery electrochemical model

The use of electrochemical models makes it computationally intractable for online implementation as the model is subject to a complicated mathematical structure including partial-differential equations (PDE). This paper is based on the single particle model with electrolyte dynamics. Methods to solve the PDEs in the governing equations are given. Model order reduction techniques are applied to the electrochemical model to reduce the order from 350 to 14. The models solved by numerical solution, residue grouping method and balanced truncation method are compared with experimental data of a coin cell for validation. The results show that the reduced order model can decrease simulation time 75 times compared with the high order model. And the accuracy of the model is kept with 2.3% root mean square error comparing with the experiment results