In this paper, taking its turbulent exchange coefficient as a function of the Lagrangian time scale and standard variance of the turbulence in atmosphere, the atmospheric dispersion PDF models are obtained on the basi...In this paper, taking its turbulent exchange coefficient as a function of the Lagrangian time scale and standard variance of the turbulence in atmosphere, the atmospheric dispersion PDF models are obtained on the basis of atmospheric diffusion K-theory. In the model the statistics of wind speed are directly used as its parameters instead of classic dispersion parameters. The bi- Gaussian PDF is derived in convective boundary layer (CBL), from the statistics of vertical velocity in both of the downdraft and updraft regions that are investigated theoretically in the other part of this paper. Giving the driven parameters of the CBL (including the convective velocity scale w* and the mixing depth h_i) and the time-averaged wind speed at release level, the PDF model is able to simulate the distribution of concentration released at any levels in the CBL. The PDF's simulations are fairly consistent with the measurements in CONDORS experiment or the results brought out by some numerical simulations.展开更多
Developing a watermarking method that is robust to cropping attack is a challenging task in image watermarking. The moment-based watermarking schemes show good robustness to common signal processing attacks and some g...Developing a watermarking method that is robust to cropping attack is a challenging task in image watermarking. The moment-based watermarking schemes show good robustness to common signal processing attacks and some geometric attacks but are sensitive to cropping attack. In this paper, we modify the moment-based approach to deal with cropping attack. Firstly, we find the probability density function （PDF） of the pixel value distribution from the original image. Secondly, we reshape and normalize the pdf of the pixel value distribution （PPVD） to form a two dimensional image. Then, the moment invariants are calculated from the PPVD image. Since PPVD is insensitive to cropping, the proposed method is robust to cropping attack. Besides, it also has high robustness against other common attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.展开更多
The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly ...The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms search the pose space exhaustively with the pose space itself being limited to a set of hierarchical manifolds that represent, respectively, surfaces, curves and points with unique geometric and energetic properties. These algorithms promise to be es- pecially valuable for the docking of fragments and small compounds as well as for virtual screening.展开更多
基金This paper supported by the National Natural Science Foundation of China under Grant No.49475247.
文摘In this paper, taking its turbulent exchange coefficient as a function of the Lagrangian time scale and standard variance of the turbulence in atmosphere, the atmospheric dispersion PDF models are obtained on the basis of atmospheric diffusion K-theory. In the model the statistics of wind speed are directly used as its parameters instead of classic dispersion parameters. The bi- Gaussian PDF is derived in convective boundary layer (CBL), from the statistics of vertical velocity in both of the downdraft and updraft regions that are investigated theoretically in the other part of this paper. Giving the driven parameters of the CBL (including the convective velocity scale w* and the mixing depth h_i) and the time-averaged wind speed at release level, the PDF model is able to simulate the distribution of concentration released at any levels in the CBL. The PDF's simulations are fairly consistent with the measurements in CONDORS experiment or the results brought out by some numerical simulations.
基金partially funded by the Australian Research Council(No.DP110102076)
文摘Developing a watermarking method that is robust to cropping attack is a challenging task in image watermarking. The moment-based watermarking schemes show good robustness to common signal processing attacks and some geometric attacks but are sensitive to cropping attack. In this paper, we modify the moment-based approach to deal with cropping attack. Firstly, we find the probability density function （PDF） of the pixel value distribution from the original image. Secondly, we reshape and normalize the pdf of the pixel value distribution （PPVD） to form a two dimensional image. Then, the moment invariants are calculated from the PPVD image. Since PPVD is insensitive to cropping, the proposed method is robust to cropping attack. Besides, it also has high robustness against other common attacks. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.
文摘The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms search the pose space exhaustively with the pose space itself being limited to a set of hierarchical manifolds that represent, respectively, surfaces, curves and points with unique geometric and energetic properties. These algorithms promise to be es- pecially valuable for the docking of fragments and small compounds as well as for virtual screening.
