A high accuracy flow segmentation method in crowded scenes based on streakline

Flow segmentation based on similar motion patterns in crowded scenes remains an open problem in computer vision due to inherent complexity and vast diversity found in such scenes. To solve this problem, the streakline framework based on Lagrangian fluid dynamics had been proposed recently. However, this framework computed optical flow field using conventional optical flow method (Lucas Kanade method) which has poor anti-interference performance, and serious deviation would be brought to the computation of optical flow field. Moreover, our experimental results show that using the formulation of streak flow similarity in this framework can result in incorrect flow segmentation. Therefore, we combine this framework with a high accurate variational model, and modify the corresponding formulation of streak flow similarity after analyzing the streakline framework in detail. Finally, an improved method is proposed to solve flow segmentation in crowded scenes. Experiments are done to compare these two methods and results verify the validity and accuracy of our method.     

Numerical simulation of indoor suspension particles based on v-f model

This paper presents a new algorithm for the prediction of indoor suspension particle dispersion based on a v²-f model. In order to handle the near-wall turbulence anisotropy properly, which is significant in the dispersion of fine particles, the particle eddy diffusivity is calculated using different formulae among regions of the turbulent core and in the vicinity of walls. The new algorithm is validated by several cases performed in two ventilated rooms with various air distribution patterns. The simulation results reveal that v²-f nonlinear turbulence model combined with a particle convective equation gives satisfactory agreement with the experimental data. It is generally found that the dynamic equation combined with the v²-f model can properly handle low Reynolds number (LRN) flows which are usually encountered in indoor air flows and fine particle dispersion.     

Control of Ionization in the Interaction of Strong Laser Fields with Dense Nanoplasmas

Different experimental methods to maximize the yield of highly charged ions in silver and xenon clusters interacting with intense and ultra‐short optical laser pulses are discussed. Theoretically, the interaction of strong laser fields with clusters is investigated within the nanoplasma model. The time evolution of the laser intensity has been parametrized. The free optimization of the parameters with a genetic algorithm is an effective but expensive tool to control the plasma dynamics. Comparison is given to the parametric control method in which pulse separation and relative intensity ratio of double‐pulses are varied. This method delivers in the case of silver and xenon clusters pulses quite close to the optimal pulse shape (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Approximate and efficient calculation of dominant Lyapunov exponents of high-dimensional nonlinear dynamic systems

This short communication presents an efficient method for calculating dominant Lyapunov exponents (LEs) of high-dimensional nonlinear dynamic systems based on their reduced-order models obtained from the linear model reduction theory. Mathematical derivation shows that the LEs of the reduced-order models correspond to the dominant LEs of the original systems. Two numerical examples are provided to demonstrate the effectiveness of the method.     

C_(2~6)烯烃在H-ZSM-5分子筛周期性模型上吸附的理论研究

采用密度泛函理论中的PBE-D方法研究了C2~6直链烯烃以及丁烯异构体在H-ZSM-5分子筛周期性模型上的吸附行为。结果表明,对于C2~6直链烯烃,随着碳数的增加,烯烃的吸附能以-12 kJ/mol的常数线性增大,体系中色散校正能ED以-13 kJ/mol的常数线性增大,而不考虑范德华力的能量E*随碳数增加变化不大,只在C5和C6时由于空间阻力凸显而减小。ED显著大于E*,说明烯烃在分子筛孔道中吸附时范德华力起主要作用,且碳数增加其影响增大。丁烯异构体吸附能大小顺序为:反式-2-丁烯顺式-2-丁烯正丁烯异丁烯。正丁烯的3种异构体ED相近且都比正丁烯的大,3种异构体的吸附能差异由E*不同引起。差分电荷密度分析表明,烯烃双键与酸性中心之间有电子聚集,且聚集程度与π配位作用相一致,而且酸性中心H原子有质子化趋向,O原子及其周围电子增加。     

No optimal 1‐planar graph triangulates any nonorientable closed surface

Suzuki [Discrete Math. 310 (2010), 6–11] proved that for any orientable closed surface F² other than the sphere, there exists an optimal 1‐planar graph which can be embedded on F² as a triangulation. However, for nonorientable closed surfaces, the existence of such graphs is unknown. In this article, we prove that no optimal 1‐planar graph triangulates a nonorientable closed surface.     

Conditionally Specified Space-Time Models for Multivariate Processes

This article proposes a class of conditionally specified models for the analysis of multivariate space-time processes. Such models are useful in situations where there is sparse spatial coverage of one of the processes and much more dense coverage of the other process(es). The dependence structure across processes and over space, and time is completely specified through a neighborhood structure. These models are applicable to both point and block sources; for example, multiple pollutant monitors (point sources) or several county-level exposures (block sources). We introduce several computational tricks that are integral for model fitting, give some simple sufficient and necessary conditions for the space-time covariance matrix to be positive definite, and implement a Gibbs sampler, using Hybrid MC steps, to sample from the posterior distribution of the parameters. Model fit is assessed via the DIC. Predictive accuracy, over both time and space, is assessed both relatively and absolutely via mean squared prediction error and coverage probabilities. As an illustration of these models, we fit them to particulate matter and ozone data collected in the Los Angeles, CA, area in 1995 over a three-month period. In these data, the spatial coverage of particulate matter was sparse relative to that of ozone.     

Estimating Precision in Functional Images

Abstract

Functional imaging of biologic parameters like in vivo tissue metabolism is made possible by Positron Emission Tomography (PET). Many techniques have been suggested for extracting such images from dynamic time-course sequences of reconstructed PET scans. Quantitating the precision of these estimates is important for drawing inferences on the biologic parameters. Analytic variance formulas are not immediate owing to the nonlinear methods used in extraction. The usual resampling approach is infeasible because each image reconstruction in PET is a computationally demanding solution to a high-dimensional linear inverse problem. We suggest an alternative simulation approach that approximates the distribution of reconstructed PET scans and performs a parametric bootstrap in the imaging domain. Results on a simplified model chosen to match the characteristics of PET reconstruction are very encouraging. Mixture analysis is used to estimate functional images; however, the suggested approach is general enough to extend to other techniques or imaging methods.     

Differential equation dynamical system based assessment model in GNSS interoperability

With the development of Global Navigation Satellite System (GNSS),the idea of GNSS interoperability is born and has become the focus of study in the field of satellite navigation.The popularity for GNSS to augment the interoperability with the existing ones necessitates the study of the assessment algorithm of this idea.In this paper,an assessment algorithm for interoperability comprehensive benefits based on the differential equation dynamical system is discussed.There are two important aspects in GNSS tha...