基于RBAC模型的权限管理改进研究与实现

针对传统RBAC模型无法满足业务审批系统要求的权限可分级、能动态管理的新需求,提出一种改进后的基于角色的控制访问模型。该模型能够动态地创造权限、分配权限、撤销权限,达到资源分离、多级权限管理的目的。结合一个实际项目,采用脚本语言JS （JavaScript）和主流的SSH框架,给出该模型的实现过程,增强各类角色对权限的分级、动态管理,该模型的可行性由此得到验证。     

一种视频流畅度优先的带宽自适应方法

由于现有基于平均接收质量的带宽自适应方法,在自适应过程中会出现视频质量振荡,且在可用带宽急剧恶化时会出现中断的问题,提出了一种流畅度优先的带宽自适应方法。该方法引入了图着色优先级算法,在带宽自适应过程中,在保证视频的流畅播放的前提下,通过判断是否振荡调整,改变平均质量范围,以达到减少视频振荡次数的效果。仿真结果表明,该方法在自适应调整传输速率、有效利用带宽的同时,保证了流畅度并减少视频质量振荡,符合预期目标。     

p53抑癌基因电化学阻抗传感器研究

基于电化学阻抗技术构建了一种检测p53抑癌基因的电化学传感器.首先利用自组装作用将末端带巯基的探针p53抑癌基因(p53-DNA)固定于金电极表面,根据传感器结合前后电子转移阻抗值的变化,对目标p53-DNA进行了测定.以pH =7.4的5mmol/L K3[Fe(CN)6]-5mmol/L K4[Fe(CN)6]平衡电对溶液作为检测液,检测目标p53-DNA的线性浓度范围为1.0×10-8～ 1.0×10-6 mol/L,其检出限为3.0×10-9 mol/L(S/N =3).对5.0×10-8 mol/L的目标p53-DNA进行11次平行测定,其RSD为3.4％.该传感器制作简单、灵敏高、选择性好,且无需标记,易于操作.     

一种用户需求感知的无线接入点关联策略

在无线局域网中,接入点(access point,简称AP)的稠密部署使得AP的关联策略成为一个重要的研究问题.目前,用户与AP的关联仅依据AP的信号强度,然而,这种方法未能考虑到网络中AP的异构性,以及不同用户对资源(例如带宽、安全性、时延等)的不同需求,并且分布式的AP关联会造成网络中AP负载的不均衡.针对以上问题,基于软件定义网络(software defined network,简称SDN)技术提出一种集中式的AP关联策略模型.该模型同时考虑了网络管理员和用户的目标,对网络负载均衡和用户资源满足度同时进行优化.采用蚁群算法对模型进行求解,并通过仿真实验对算法进行验证.实验结果表明,针对随机生成的数据集,用户资源满足度可由54.5%分别提升至86.8%(重负载时)和94.1%(轻负载时),并且管理员目标(负载均衡)得到了明显的改善.     

一种差动放大器输出转换电路的研究

设计了一种差动放大器的教学电路,研究了电阻负载和恒流源负载的差动放大器的特性。实验电路切换简单,测量方便,便于实践。使用Multisim 10对电路进行仿真,测算了两种差动放大器电路的静态工作点、差模电压放大倍数、共模电压放大倍数以及共模抑制比等。实验结果表明,该电路实现了双端输出转单端输出路,达到电路转换目的。     

Fuzzy Identification Based on Tire/Road Adhesion Feature

For identifying the tire/road friction coefficient accurately in real-time to meet the needs of automobile electronic control system and then improving the active safety performance of automobile, the road recognition method based on fuzzy control algorithm was studied in this paper. Adopt a 7-DOF vehicle dynamic model, wheel slip ratio λ and longitudinal forces Fx as the input of fuzzy controller with fuzzy rules was proposed. The output is the weight coefficient of μ-λ functional expression which is related to c1, c2 and c3 proposed by Burckhardt etc. By a simulation experiment of automobile brake on the condition of driving straight or veering on a single road and docking pavement, to some extent, indicates that this method is able to guarantee the real-time and accuracy of the road identification.     

基于奇异谱分析的DGPS浮标海面高测量误差研究

在高度计绝对定标实验中,利用差分GPS(Differential GPS,DGPS)浮标进行现场海面高测量得到的海面高(Sea Surface Height,SSH)序列之中,除了包含有由风浪引起的高频噪声外,还包括了仪器误差造成的影响。前者可通过低通滤波方式消除,而后者由于是全频段的白噪声,不能通过低通滤波的方式消除。通过研究奇异谱分析(Singular Spectrum Analysis,SSA)的方法,确定了嵌入维数和截断长度的选取准则,并对其进行仿真,验证了该方法在消除海面高序列的仪器误差噪声中的有效性,同时也验证了嵌入维数和截断长度选取准则的有效性。最后,利用该方法处理了某次DGPS浮标实验获得的海面高序列,处理结果与原始序列相比较为平滑,且在精度上有一定的改善,验证了奇异谱分析方法的有效性。     

结合阴影抑制的混合高斯模型改进算法

混合高斯模型背景法作为运动目标检测的一种经典方法,已经广泛应用于智能视频监控系统中。但是,传统的混合高斯模型背景法容易将阴影误检测为运动目标的一部分。因此,针对该方法在区分阴影和运动目标方面的不足,提出了一种将混合高斯模型背景法和HSV空间阴影抑制相结合的运动目标检测算法。这种改进算法首先将颜色空间转换到HSV空间,初步提取运动目标,然后再利用阴影的灰度值比背景中的灰度值小,而前景的灰度值比背景中灰度值大的特性,检测出运动目标中的阴影。实验结果表明,这种改进的算法明显提高了检测效果,有效抑制了阴影对运动目标检测的干扰,算法实时性也较好。     

Exact and approximate flexible aggregate similarity search

Aggregate similarity search, also known as aggregate nearest-neighbor (Ann) query, finds many useful applications in spatial and multimedia databases. Given a group Q of M query objects, it retrieves from a database the objects most similar to Q, where the similarity is an aggregation (e.g., \({{\mathrm{sum}}}\), \(\max \)) of the distances between each retrieved object p and all the objects in Q. In this paper, we propose an added flexibility to the query definition, where the similarity is an aggregation over the distances between p and any subset of \(\phi M\) objects in Q for some support \(0< \phi \le 1\). We call this new definition flexible aggregate similarity search and accordingly refer to a query as a flexible aggregate nearest-neighbor ( Fann ) query. We present algorithms for answering Fann queries exactly and approximately. Our approximation algorithms are especially appealing, which are simple, highly efficient, and work well in both low and high dimensions. They also return near-optimal answers with guaranteed constant-factor approximations in any dimensions. Extensive experiments on large real and synthetic datasets from 2 to 74 dimensions have demonstrated their superior efficiency and high quality.