The natural exponential potential (Ce^R/λ0) widely exists at micro/nanoscales;this paper studies the interaction potential between a curved-surface body and an outside particle base on the natural exponential potenti...The natural exponential potential (Ce^R/λ0) widely exists at micro/nanoscales;this paper studies the interaction potential between a curved-surface body and an outside particle base on the natural exponential potential. Mat hematical derivation proves t hat the int er act ion potential can be expressed as a function of curvatures. Then, idealized numerical experiments are designed to verify the accuracy of the curvature-based potential. The driving forces exerted on the particle are discussed and confirmed to be a function of curvatures and the gradient of curvatures, which may explain some abnormal movements at micro/nanoscales.展开更多
Curvature-driven diffusion (CDD) principles were used to develop a novel gradient based image restora- tion algorithm. The algorithm fills in blocks of missing data in a wireless image after transmission through the n...Curvature-driven diffusion (CDD) principles were used to develop a novel gradient based image restora- tion algorithm. The algorithm fills in blocks of missing data in a wireless image after transmission through the network. When images are transmitted over fading channels, especially in the severe circum- stances of a coal mine, blocks of the image may be destroyed by the effects of noise. Instead of using com- mon retransmission query protocols the lost data is reconstructed by using the adaptive curvature-driven diffusion (ACDD) image restoration algorithm in the gradient domain of the destroyed image. Missing blocks are restored by the method in two steps: In step one, the missing blocks are filled in the gradient domain by the ACDD algorithm; in step two, and the image is reconstructed from the reformed gradients by solving a Poisson equation. The proposed method eliminates the staircase effect and accelerates the convergence rate. This is demonstrated by experimental results.展开更多
基金by the Natural Science Foundation of Jiangsu Province (Nos. BK20180411, BK20180416)the start-up funding awarded by Nanjing University of Aeronautics and Astronautics (Nos. 56SYAH17065, 90YAH17065).
文摘The natural exponential potential (Ce^R/λ0) widely exists at micro/nanoscales;this paper studies the interaction potential between a curved-surface body and an outside particle base on the natural exponential potential. Mat hematical derivation proves t hat the int er act ion potential can be expressed as a function of curvatures. Then, idealized numerical experiments are designed to verify the accuracy of the curvature-based potential. The driving forces exerted on the particle are discussed and confirmed to be a function of curvatures and the gradient of curvatures, which may explain some abnormal movements at micro/nanoscales.
基金supported by the National High-Tech Research and Development Program of China (No. 2008AA062200)the National Natural Science Foundation of China (No.60802077)the Fundamental Research Funds for the Central Universities (No. 2010QNA43)
文摘Curvature-driven diffusion (CDD) principles were used to develop a novel gradient based image restora- tion algorithm. The algorithm fills in blocks of missing data in a wireless image after transmission through the network. When images are transmitted over fading channels, especially in the severe circum- stances of a coal mine, blocks of the image may be destroyed by the effects of noise. Instead of using com- mon retransmission query protocols the lost data is reconstructed by using the adaptive curvature-driven diffusion (ACDD) image restoration algorithm in the gradient domain of the destroyed image. Missing blocks are restored by the method in two steps: In step one, the missing blocks are filled in the gradient domain by the ACDD algorithm; in step two, and the image is reconstructed from the reformed gradients by solving a Poisson equation. The proposed method eliminates the staircase effect and accelerates the convergence rate. This is demonstrated by experimental results.
