A grid-based clustering algorithm for wild bird distribution

Advanced satellite tracking technologies provide biologists with long-term location sequence data to understand movement of wild birds then to find explicit correlation between dynamics of migratory birds and the spread of avian influenza. In this paper, we propose a hierarchical clustering algorithm based on a recursive grid partition and kernel density estimation (KDE) to hierarchically identify wild bird habitats with different densities. We hierarchically cluster the GPS data by taking into account the following observations: 1) the habitat variation on a variety of geospatial scales; 2) the spatial variation of the activity patterns of birds in different stages of the migration cycle. In addition, we measure the site fidelity of wild birds based on clustering. To assess effectiveness, we have evaluated our system using a large-scale GPS dataset collected from 59 birds over three years. As a result, our approach can identify the hierarchical habitats and distribution of wild birds more efficiently than several commonly used algorithms such as DBSCAN and DENCLUE.     

企业网的安全管理与对策探讨

为推动企业进一步发展,促进企业在激烈的市场竞争中占据先驱地位,越来越多的企业开始重视企业网络的建设。而由于网络的开放性,必然导致企业在进行网络建设的过程中会带来一系列安全问题。网络安全成为企业网络建设过程中必然考虑的因素。     

Enhanced security in internet voting protocol using blind signature and dynamic ballots

In this paper, we introduce an internet voting protocol which satisfies desired security requirements of electronic voting. In the newly proposed protocol, we allow the adversaries to get more power than in any previous works. They can be coercers or vote buyers outside, and corrupted parties inside our system. These adversaries also have ability to collude with each other to ruin the whole system. Our main contribution is to design an internet voting protocol which is unsusceptible to most of sophisticated attacks. We employ the blind signature technique and the dynamic ballots instead of complex cryptographic techniques to preserve privacy in electronic voting. Moreover, we also aim at the practical system by improving the blind signature scheme and removing physical assumptions which have often been used in the previous works.     

Path planning in complex 3D environments using a probabilistic roadmap method

This paper presents a 3D path planning algorithm for an unmanned aerial vehicle （UAV） in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, free space is represented by free voxels, which have enough space margin for the UAV to pass through. A bounding box array is created in the whole 3D space to evaluate the free voxel connectivity. The probabilistic roadmap method （PRM） is improved by random sampling in the bounding box array to ensure a more efficient distribution of roadmap nodes in 3D space. According to the connectivity evaluation, the roadmap is used to plan a feasible path by using A＊ algorithm. Experimental results indicate that the proposed algorithm is valid in complex 3D environments.     

基于免疫粒子群算法的参数估计方法

针对污水生化反应模型参数估计问题,提出一种基于免疫粒子群算法的估计方法。该方法采用免疫算法保持粒子群的多样性,避免粒子群算法的过早收敛而降低寻优能力。利用估计的参数值对实验数据进行拟合,仿真结果表明,拟合误差率低于标准的粒子群和遗传算法,进一步提高了污水生化反应模型参数估计精度。     

基于免疫粒子群神经网络的污水水质预测

针对污水处理过程所具有的多变量、非线性和大时滞的特点, 利用出水水质参数与多个可测过程参数间的相关关系,给出了基于RBF神经网络的出水水质参数预测模型.采用免疫粒子群优化算法来训练网络的隐层节点、径向基函数的中心点和网络权值.以反应时间、DO浓度、ORP和pH值作为输入参数,实现对COD,NH3-N,TP等水质参数的预测.仿真试验表明,该预测模型对污水处理出水水质参数COD,NH3-N,TP具有理想的预测效果.     

面向安全生产综合监管系统的工作流引擎

针对安全生产监管系统中关键业务应用的开发离不开工作流技术支持的特点,通过对安全生产监管领域中关键业务的实际开发需求的分析,引进了工作流技术,设计并实现了一个轻量级嵌入式工作流引擎;本文首先对安全生产综合监管系统整体架构进行分析,然后提出该工作流引擎的设计方案,并详细阐述了引擎设计的关键环节;最后把此工作流引擎应用到安全生产综合监管系统中,不仅显著地缩短关键业务的开发周期,同时也规范了各种关键业务处理流程。     

基于肤色特征的AdaBoost人脸检测方法①

针对人脸检测准确率和实时性问题,提出了一种基于肤色特征的AdaBoost检测方法。通过将肤色特征应用到AdaBoost检测算法中,提高AdaBoost算法的检测率。实验结果表明,该算法能更好地实现多人脸检测,且减少计算量,保障了实时性的要求。     

基于专家评价信息的军校课堂教学质量评价的统计融合方法

以现代军事教育教学理论为指导,结合军校课堂教学质量评价指标体系和军校课堂教学评价的实际,提出了一种基于专家评价信息的军校课堂教学质量评价的统计融合方法。通过实例分析和计算,验证了该方法的有效性。