A new method for distributing power usage across a sensor network

We present a method for more uniformly distributing the energy burden across a wireless ground-based sensor network communicating with an overhead unmanned aerial vehicle (UAV). A subset of sensor nodes, termed a transmit cluster, receives and aggregates data gathered by the entire network, and forms a distributed antenna array, concentrating the radiated transmission into a narrow beam aimed towards the UAV. Because these duties are power-intensive, the role of transmit cluster must be shifted to different nodes as time progresses. We present an algorithm to reassign the transmit cluster, specifying the time that should elapse between reassignments and the number of hops that should be placed between successive transmit clusters in order to achieve three competing goals: first, we wish to better and more broadly spread the energy load across the sensor network while, second, minimizing the energy expended in moving the transmit cluster, all the while, third, reducing to the extent practicable the time to bring the UAV and the sensor network’s beam into alignment. Additionally, we present a method for reconfiguring the communication burden between the ground-based sensor network and the UAV. We describe and analyze two alternative strategies to bring the UAV and the sensor network’s beam into alignment, while minimizing the energy expended by the sensor network. The performance of the two strategies is compared in terms of probability of beam-UAV alignment as a function of time, and the expected time to alignment. We examine the performance tradeoff between the choice of strategy and parameters of the sensor network that affect power conservation.     

脊波域的图像数字水印算法研究

提出一种将混沌置乱加密后的水印信息嵌入到图像脊波变换域的算法。将图像分块后进行有限脊波变换,选择出图像纹理块的脊波域最大能量方向上的系数嵌入水印,水印提取只需要记录嵌入位置序列即可。实验结果表明,算法对噪声、压缩、不规则剪切、对比度等攻击有较强的鲁棒性。     

Arnold置乱在零水印中的二次复用

为了提高水印的鲁棒性和减小对应版权信息的大小,本文提出了一种基于Arnold变换、DWT和SVD的零水印算法。该算法将载体图像进行DWT变换,对低频子带进行分块SVD;比较置乱后的最大奇异值的大小,若大于则对应位为1,否则为0;将结果与预处理过的水印做异或运算,得密钥矩阵。该矩阵为检测水印提供密钥。实验证明,本算法对图像压缩、滤波、模糊、噪声及脏图具有良好的鲁棒性。     

服务器集群负载均衡的建模与仿真研究

研究服务器集群负载优化调试问题,各服务器负载能力差异较大,要求尽可能使每一个服务器的负载均衡,传统方法没有考虑负载动态变化特点,导致服务器集群负载极不均衡,系统性能差。为提高集群系统的整体性能,提出一种基于遗传算法的服务器集群负载均衡算法。首先根据负载均衡目标建立数学模型,然后采用遗传算法模型进行求解。仿真结果表明,遗传算法提高了服务器集群系统吞吐量,使系统负载更加均衡,使整个集群系统的资源得到充分利用。     

Phase transition of lithiated-spinel Li2Mn2O4 at high temperature

1 Introduction Lithium manganese oxides are the most attractive cathode materials for rechargeable lithium-ion batteries because of their low-cost and less toxicity when compared with either cobaltates or nickelates[1?3]. Among these oxides, the spinel-fr…     

对Mues，E and Steinmentz，N唯一性定理证明的改进

亚纯函数与其导数具有公共值问题是亚纯函数唯一性问题的特殊情况．1979年,Mues,E and Steinmentz,N获得了亚纯函数与其导数分担IM公共值的唯一性定理,本文对此定理的证明进行了改进．     

线性红利下带干扰的复合Poisson风险模型

在线性红利下将保单到达过程推广为Poisson过程,并通过添加Brownian运动来刻画保险公司不确定的收益和付款,建立线性红利下带干扰的复合Poisson风险模型.运用鞅方法得出了破产概率满足的Lundberg不等式和一般公式,并给出了生存概率满足的积分—微分方程。     

双球面投影几何可量测全景模型的构建

针对全景影像难以提供空间度量的问题,提出一种基于双球面投影几何的可量测立体全景模型构建方法.该方法依据球面全景投影关系与多视几何原理,采用对应变换与本质变换求取旋转及平移参数,并推导出双球面核线约束;在此基础上,建立起双球面投影几何的立体全景模型,解决了球面全景的量测问题.实验结果表明,文中方法可使全景影像在真实呈现户外场景的同时,提供满足一定应用需求的量测分析功能.     

Lag stochastic synchronization of chaotic mixed time-delayed neural networks with uncertain parameters or perturbations

This paper investigates the problem of lag synchronization for a kind of chaotic neural networks with discrete and distributed delays (mixed delays). The driver system has uncertain parameters and uncertain nonlinear external perturbations, while the response system has channel noises. A simple but all-powerful robust adaptive controller is designed to circumvent the effects of uncertain external perturbations such that the response system synchronize with the driver system. Based on the invariance principle of stochastic differential equations and some suitable Lyapunov functions, several sufficient conditions are developed to solve this problem. Moreover, under certain conditions, parameters of the uncertain master system can be estimated. Numerical simulations are exploited to show the effectiveness of the theoretical results.     

Application of BP Neural Network in Prediction of Cu-Pb Composite Plates Properties

Abstract： The artificial neural networks（ANN） , which have broad application, are proposed to develop Cu-Pb composite plates materials. Based on the back propagation（BP） algorithm of the forward muhilayer perceptron, the model to predict the shear stress under different ingredient of the third element and the hot dipping temperature for Cu-Pb composite plates are established. Then the relational model among the third element, hot dipping temperature and shear stress by using the limited data are studied, and the forecast average error is 4%. This model can satisfy the requirements of the precision of forecast in the project experiment process. The results show that the corresponding shear stress is greater when the third element in the element contains more Sn; the most appropriate temperature of hot-dip plating about is 340℃, ＇after predicted with lead/the third element/the best performance of copper composite material element of the third group is the one-element Sn, hot dip plating temperature is 335 ℃ ; two-element is 90% Sn 10% Bi, and hot dip plating temperature is 345 ℃. The prediction results can be used for a reference in instructing the further experimental design.