Neural network-based sliding mode adaptive control for robot manipulators

This paper addresses the robust trajectory tracking problem for a robot manipulator in the presence of uncertainties and disturbances. First, a neural network-based sliding mode adaptive control (NNSMAC), which is a combination of sliding mode technique, neural network (NN) approximation and adaptive technique, is designed to ensure trajectory tracking by the robot manipulator. It is shown using the Lyapunov theory that the tracking error asymptotically converge to zero. However, the assumption on the availability of the robot manipulator dynamics is not always practical. So, an NN-based adaptive observer is designed to estimate the velocities of the links. Next, based on the observer, a neural network-based sliding mode adaptive output feedback control (NNSMAOFC) is designed. Then it is shown by the Lyapunov theory that the trajectory tracking errors, the observer estimation errors asymptotically converge to zero. The effectiveness of the designed NNSMAC, the NN-based adaptive observer and the NNSMAOFC is illustrated by simulations.     

一种融合多种定位精度改进策略的实时定位中间件

无论是普适计算还是物联网,实时定位均是其关键技术之一。在建筑物、洞室等复杂环境中,由于无线信号的不规则衰减、非视距传播,使得常用的一些定位算法(如接收信号强度、到达角度等)无法达到较高的定位精度。为了解决复杂环境中定位精度不足的问题,设计并实现了一个定位精度改进中间件。它集成了平滑、传感器融合、卡尔曼滤波、粒子滤波等多种精度改进策略,可以根据用户对定位精度的需求动态地选择相应的策略。通过实验分析了不同精度改进策略的性能,结果表明,该中间件能够较好地满足用户对不同精度的需求。     

Remoting技术在工业远程测控系统中的应用研究

在工业分布式测控通信系统中,Microsoft.NET Remoting技术可以在应用程序内部或应用程序域之间传输数据.采用Remoting技术结合二进制流的方法,通过远程对象和数据接口的建立,以及服务器端和客户端的设置,可以在软件各个结构层之间进行快速高效的远程对象访问,达到实时控制的目的.该方案使测控仪表具有更好的开放性和可集成能力,有一定的参考和实用价值.     

基于P2P的语义Web服务发现机制

分析集中式语义Web服务发现机制存在的问题,利用P2P和本体技术,提出一种基于P2P的语义Web服务发现机制。将服务的部署与发布无缝地绑定在一起,按应用领域和服务目标将整个P2P网络组织成3层结构,基于该结构建立3阶段服务发现算法,达到优化网络结构、提高服务发现效率的目的。     

Discovery of probabilistic nearest neighbors in traffic-aware spatial networks

Travel planning and recommendation have received significant attention in recent years. In this light, we study a novel problem of discovering probabilistic nearest neighbors and planning the corresponding travel routes in traffic-aware spatial networks (TANN queries) to avoid potential time delay/traffic congestions. We propose and study four novel probabilistic TANN queries. Thereinto two queries target at minimizing the travel time, including a congestion-probability threshold query, and a time-delay threshold query, while another two travel-time threshold queries target at minimizing the potential time delay/traffic congestion. We believe that TANN queries are useful in many real applications, such as discovering nearby points of interest and planning convenient travel routes for users, and location based services in general. The TANN queries are challenged by two difficulties: (1) how to define probabilistic metrics for nearest neighbor queries in traffic-aware spatial networks, and (2) how to process these TANN queries efficiently under different query settings. To overcome these challenges, we define a series of new probabilistic metrics and develop four efficient algorithms to compute the TANN queries. The performances of TANN queries are verified by extensive experiments on real and synthetic spatial data.     

Continuous-variable quantum homomorphic signature

Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold.     

人群运动中的视觉显著性研究

在公共场所中人们都倾向于以分组的形式进行运动,本文把这种以分组形式运动的若干个行人称为运动群组,具有视觉显著性的人群运动群组是场景理解的重点,其对人群的整体运动也影响最大。本文对运动群组的视觉显著性展开了研究,分别从规模、速度、组内紧致度和变化度４个方面来对运动群组的视觉显著性进行度量,并基于该度量给出了视觉显著性运动群组检测方法。首先,利用光流法对运动人群进行分析得到光流向量;然后通过层次聚类算法对运动人群进行分组;最后,基于本文所给出的度量计算每个群组的视觉显著性,以检测出视觉显著性最高的运动群组。实验表明该方法能够有效地对视觉显 著性运动群组进行检测,该研究成果可应用于人群场景理解、人群运动分析和人群场景分类等计算机视觉研究领域。     

A shape prior constraint for implicit active contours

We present a shape prior constraint to guide the evolution of implicit active contours. Our method includes three core techniques. Firstly, a rigid registration is introduced, using a line search method within a level set framework. The method automatically finds the time step for the iterative optimization processes. The order for finding the optimal translation, rotation and scale is derived experimentally. Secondly, a single reconstructed shape is created from a shape distribution of a previously acquired learning set. The reconstructed shape is applied to guide the active contour evolution. Thirdly, our method balances the impact of the shape prior versus the image guidance of the active contour. A mixed stopping condition is defined based on the stationarity of the evolving curve and the shape prior constraint. Our method is completely non-parametric and avoids taking linear combinations of non-linear signed distance functions, which would cause problems because distance functions are not closed under linear operations. Experimental results show that our method is able to extract the desired objects in several circumstances, namely when noise is present in the image, when the objects are in slightly different poses and when parts of the object are invisible in the image.     

新型核序列自相关函数用于非同源蛋白质结构类预测

从天然氨基酸的50个性质参数中经主成分分析得出1种新的氨基酸描述子:氨基酸特征性质得分.并在此基础上通过定义基于向量形式的自相关函数以及引入Mercer核技术将该函数运算空间进行非线性变换,最终提出了1种新的蛋白质序列表征方法:核序列自相关函数.采用该函数对632个已知晶体结构的非同源蛋白分类研究结果表明:KSACF能...     

三维荧光二阶校正法直接快速测定血浆样中川芎嗪和阿魏酸含量

本文将三维荧光光谱与二阶校正方法相结合用于人体血浆样中的中药药理活性成分川芎嗪和阿魏酸含量的直接测定.尽管预测样存在血浆内源荧光物质的基体干扰,但由于该方法基于“数学分离”的思路和具有“二阶优势”,仍能对荧光光谱严重重叠的血浆样中的目标分析物进行直接同时定量测定,为川芎嗪和阿魏酸在体内的代谢监控及其药效研究提供了一种新思路.获得的预测样中川芎嗪和阿魏酸的平均回收率分别为(95.7±2.2)％和(100.8±2.5)％.该方法简单、快速,结果可靠.