Transport mean free path tensor and anisotropy tensor in anisotropic diffusion equation for optical media

2020 ◽  
Vol 22 (7) ◽  
pp. 075606
Author(s):  
Sang Eon Han
1999 ◽  
Author(s):  
Per G. Sverdrup ◽  
Y. Sungtaek Ju ◽  
Kenneth E. Goodson

Abstract The temperature rise in compact silicon devices is predicted at present by solving the heat diffusion equation based on Fourier’s law. The validity of this approach needs to be carefully examined for semiconductor devices in which the region of strongest electronphonon coupling is narrower than the phonon mean free path, Λ, and for devices in which Λ is comparable to or exceeds the dimensions of the device. Previous research estimated the effective phonon mean free path in silicon near room temperature to be near 300 nm, which is already comparable with the minimum feature size of current generation transistors. This work numerically integrates the phonon Boltzmann transport equation (BTE) within a two-dimensional Silicon-on-Insulator (SOI) transistor. The BTE is coupled with the classical heat diffusion equation, which is solved in the silicon dioxide layer beneath a transistor with a channel length of 400 nm. The sub-continuum simulations yield a peak temperature rise that is 159 percent larger than predictions using only the classical heat diffusion equation. This work will facilitate the development of simpler calculation strategies, which are appropriate for commercial device simulators.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Liyuan Guo

On the basis of studying the basic theory of anisotropic diffusion equation, this paper focuses on the application of anisotropic diffusion equation in image recognition film production. In order to further improve the application performance of P-M (Perona-Malik) anisotropic diffusion model, an improved P-M anisotropic diffusion model is proposed in this paper, and its application in image ultrasonic image noise reduction is discussed. The experimental results show that the model can effectively suppress the speckle noise and preserve the edge features of the image. Based on the image recognition technology, an image frame testing system is designed and implemented. The method of image recognition diffusion equation is used to extract and recognize the multilayer feature points of the test object according to the design of artificial neural network. To a certain extent, it improves the accuracy of image recognition and the audience rating of film and television. Use visual features of the film and television play in similarity calculation for simple movement scene segmentation problem, at the same time, the camera to obtain information, use the lens frame vision measuring the change of motion of the camera, and use weighted diffusion equation and the visual similarity of lens similarity calculation and motion information, by considering the camera motion of image recognition, effectively solve the sports scene of oversegmentation problem such as fighting and chasing.


Author(s):  
Donatella Giuliani

This chapter presents a method to compute the skeletal curve of shapes extracted by images derived by the real world. This skeletonization approach has been proved effective when applied to recognize biological forms, regardless of their complexity. The coloured and grayscale images have been pre-processed and transformed in binary images, recurring to segmentation. Generally the resulting binary images contain bi-dimensional bounded shapes, not-simply connected. For edge extraction it has been performed a parametric active contour procedure with a generalized external force field. The force field has been evaluated through an anisotropic diffusion equation. It has been noticed that the field divergence satisfies an anisotropic diffusion equation as well. Moreover, the curves of positive divergence can be considered as propagating fronts that converge to a steady state, the skeleton of the extracted object. This methodology has also been tested on shapes with boundary perturbations and disconnections.


2015 ◽  
Vol 44 (9) ◽  
pp. 910002 ◽  
Author(s):  
周慧鑫 ZHOU Hui-xin ◽  
赵营 ZHAO Ying ◽  
秦翰林 QIN Han-lin ◽  
殷世民 YIN Shi-min ◽  
刘刚 LIU Gang ◽  
...  

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