连续级联喇曼光纤激光器耦合波方程的修正

从最基本的耦合波方程出发,考虑光波正反向传输的情况下,推导出了一个全面的、准确的关于连续级联喇曼光纤激光器的理论模型,描述了各级Stokes光波功率沿光纤长度的变化.指出了相关一些文献中存在的不足,并且给出了多级斯托克斯光波相互作用的有效作用面积的表达式.此模型有助于喇曼光纤激光器的设计.     

基于中心-射线模型的印鉴识别方法及其应用

支票中的有效印鉴是支票流通有效性的重要体现。通过对支票印鉴有效性的识别来达到对支票流通有效性识别的目的。根据我国支票图像的特点提出了基于中心_射线模型的有效印鉴识别方法。该方法是通过对印鉴各成份区域之间拓扑关系的识别来达到对有效印鉴识别的目的。在将该方法用于我国支票印鉴识别的同时,还利用了印鉴的色彩特征。实验结果表明,该方法可有效地识别我国支票中的有效印鉴,有效印鉴识别的错误排除率为0%,错误接收率为23.8%。     

一种基于HSI颜色模型的目标提取方法

在工业、农业、军事以及医疗等领域中,目标识别是一个关键技术,近年来在图像处理方面已成为一个重要的研究课题。提出了一种用于除草机器人的基于HSI(色调、明度和饱和度)颜色模型的彩色图像目标提取方法。该方法首先将具有某种色彩信息的杂草与农作物从背景土壤中分离出来,然后再根据杂草与农作物形状的不同,采用腐蚀和膨胀的方法进一步将杂草与农作物分离。该方法除了用于除草机器人以外,还可用于水果采摘等。仿真结果验证了该方法的有效性。     

对地观测平台恒星敏感器离焦成像折中设计分析

从对地观测平台角秒量级姿态确定需求出发,在构建星敏感器惯性系成像模型的基础上指出,恒星在成像面上的定位误差是星敏感器姿态确定误差的主要来源。同时,结合理想光学系统离焦模型,分析了星敏感器主要性能指标间的量化关系,并给出了成像面定位误差最低限。仿真结果表明,从优化系统性能考虑,成像模糊区直径为2~3个像元的配置是利用星敏感器焦平面的“轻微离焦”来实现亚像元定位的最佳方案,定位误差可达0.2个像元,能够满足星敏感器惯性姿态确定精度4″~5″的要求。理论分析和数值仿真结果可为后续星敏感器指标的提出及仪器设计提供技术参考。     

具有反馈控制的非自治Logistic模型的正周期解

A nonautonomous delayed logistic model with linear feedback regulation is pro- posed in this paper.Sufficient conditions are derived for the existence,uniqueness and global asymptotic stability of positive periodic solution of the model.     

Traveling Wave Solutions in a Chemotaxis Model with Two Chemoattractants

In this work, we investigate the existence and non-existence of traveling wave solutions for a chemotaxis model with two chemoattractants. To prove our main results, we apply the dynamical systems theory by constructing a positively invariant set in the four-dimensional space. Particularly, we analyze the monotonicity of traveling wave solutions.     

Introduction and Analysis of a Method for the Investigation of QCD-like Tree Data

The properties of decays that take place during jet formation cannot be easily deduced from the final distribution of particles in a detector. In this work, we first simulate a system of particles with well-defined masses, decay channels, and decay probabilities. This presents the “true system” for which we want to reproduce the decay probability distributions. Assuming we only have the data that this system produces in the detector, we decided to employ an iterative method which uses a neural network as a classifier between events produced in the detector by the “true system” and some arbitrary “test system”. In the end, we compare the distributions obtained with the iterative method to the “true” distributions.     

Tumor Hypoxia Heterogeneity Affects Radiotherapy: Inverse-Percolation Shell-Model Monte Carlo Simulations

Tumor hypoxia was discovered a century ago, and the interference of hypoxia with all radiotherapies is well known. Here, we demonstrate the potentially extreme effects of hypoxia heterogeneity on radiotherapy and combination radiochemotherapy. We observe that there is a decrease in hypoxia from tumor periphery to tumor center, due to oxygen diffusion, resulting in a gradient of radiative cell-kill probability, mathematically expressed as a probability gradient of occupied space removal. The radiotherapy-induced break-up of the tumor/TME network is modeled by the physics model of inverse percolation in a shell-like medium, using Monte Carlo simulations. The different shells now have different probabilities of space removal, spanning from higher probability in the periphery to lower probability in the center of the tumor. Mathematical results regarding the variability of the critical percolation concentration show an increase in the critical threshold with the applied increase in the probability of space removal. Such an observation will have an important medical implication: a much larger than expected radiation dose is needed for a tumor breakup enabling successful follow-up chemotherapy. Information on the TME’s hypoxia heterogeneity, as shown here with the numerical percolation model, may enable personalized precision radiation oncology therapy.     

单重工作休假M/M/c排队驱动的流体模型分析

该文在M/M/c排队驱动系统中加入工作休假策略,研究了单重工作休假多服务台排队驱动的流体模型.利用拟生灭过程和矩阵几何解法得到驱动系统稳态队长分布.构建净输入率结构,导出流体模型的稳态联合分布函数满足的的矩阵微分方程组,进而利用Laplace-Stieltjes变换(LST)方法得到稳态下缓冲器库存量的空库概率及均值表...     

Structural Entropy of the Stochastic Block Models

With the rapid expansion of graphs and networks and the growing magnitude of data from all areas of science, effective treatment and compression schemes of context-dependent data is extremely desirable. A particularly interesting direction is to compress the data while keeping the “structural information” only and ignoring the concrete labelings. Under this direction, Choi and Szpankowski introduced the structures (unlabeled graphs) which allowed them to compute the structural entropy of the Erdős–Rényi random graph model. Moreover, they also provided an asymptotically optimal compression algorithm that (asymptotically) achieves this entropy limit and runs in expectation in linear time. In this paper, we consider the stochastic block models with an arbitrary number of parts. Indeed, we define a partitioned structural entropy for stochastic block models, which generalizes the structural entropy for unlabeled graphs and encodes the partition information as well. We then compute the partitioned structural entropy of the stochastic block models, and provide a compression scheme that asymptotically achieves this entropy limit.