Step sequence planning for a biped robot by means of a cylindrical shape model and a high-resolution 2.5D map

A novel step sequence planning (SSP) method for biped-walking robots is presented. The method adopts a free space representation custom-designed for efficient biped robot motion planning. The method rests upon the approximation of the robot shape by a set of 3D cylindrical solids. This feature allows efficient determination of feasible paths in a 2.5D map, comprising stepping over obstacles and stair climbing. A SSP algorithm based on A^∗-search is proposed which uses the advantages of the aforementioned environment representation. The efficiency of the proposed approach is evaluated by a series of simulations performed for eight walking scenarios.     

Miniaturized ceramic differential scanning calorimeter with integrated oven and crucible in LTCC technology

A miniaturized ceramic differential scanning calorimeter (MC-DSC) with integrated oven and crucible is presented. Despite its small size of only 11 mm × 39 mm × 1.5 mm, all functions of a conventional DSC apparatus are integrated in this novel device - including the oven. The MC-DSC is fully manufactured in thick-film and green glass ceramic tape-based low temperature co-fired ceramics (LTCC) technology. Therefore, production costs are considered to be low. Initial results using indium as a sample material show a good dynamic performance of the MC-DSC. Full width at half maximum of the melting peak is 2.4 °C (sample mass approx. 11 mg, heating rate approx. 50 °C/min). Repeatability of the indium melting point is within ±0.02 °C. The melting peak area increases linearly with the sample mass up to at least 26 mg. Simulations of a strongly simplified finite element model of the MC-DSC are in a good agreement with measurement results allowing a model-based prediction of its basic characteristics.     

Mean square exponential stability in high-order stochastic impulsive BAM neural networks with time-varying delays

In this paper, a class of stochastic impulsive high-order BAM neural networks with time-varying delays is considered. By using Lyapunov functional method, LMI method and mathematics induction, some sufficient conditions are derived for the globally exponential stability of the equilibrium point of the neural networks in mean square. It is believed that these results are significant and useful for the design and applications of impulsive stochastic high-order BAM neural networks.     

基于Improved-HMM的进程行为异常检测

针对传统隐马尔可夫模型(HMM)状态转移概率仅与前一状态有关的不足,提出了一种改进的隐马尔可夫模型(Im-proved-HMM),该模型考虑到状态转移概率与前两时刻状态相关,旨在提高异常检测准确率。用基于Improved-HMM的Baum-Welch(BW)算法对正常进程行为进行建模,并采用滑动窗口的方法,检测进程行为是否处于异常状态。实验结果表明,该模型的检测准确率高于传统的HMM模型,能及时、准确检测到进程行为的异常。     

基于电子白板的远程实时答疑系统

为解决现场答疑受时间和地点限制的问题,分析了现有答疑系统的不足,构建了一种以答疑双方为对等客户端的远程实时答疑系统。将TCP协议和UDP协议相结合,采用双协议三线程方法,实现了客户端动态IP地址的自动获取及通讯连接。引入电子白板技术,实现文本与图形模式的同步交流,体现了传统板书讲解特点。提出教师答疑评价方法,为教师和教学管理部门提供考核依据。在Internet中测试的结果表明,该系统能够提供远程在线答疑,具有较好的方便性和实用性。     

非超递增序列背包加密算法研究

为了提高背包加密体制的安全性,对基于超递增序列的背包加密算法进行了分析,指出了利用非超递增序列构造背包所存在的难题,提出一种无冲突非超递增序列的构造方法,并给出严格的证明。依据该方法提出了一种基于无冲突非超递增序列的背包公钥加密算法,有效地避免了利用非超递增序列构造背包的过程中出现的难题。理论分析和仿真实验结果表明,该算法具有高的安全性能,在抵抗Shamir攻击和低密度攻击方面都具有良好的性能。     

面向用户柔点的设计模型

为了提高软件适应需求变化的能力,设计出具有良好柔性的软件,提出了一种基于面向用户柔点的设计模型.给出面向用户柔点的概念和特征,指出柔点与需求变化的密切联系.在此基础上,通过归纳需求变化的分类,抽象出柔点的分类.利用MVC(模型-视图-控制器)框架和软件设计模式给出通用的柔点设计模型,根据柔点的分类将模型细化.通过一个网...     

基于参考点和投票规则的多目标粒子群优化群体决策

针对巨量可选方案的群体决策问题,提出了一个新的基于参考点和投票规则的多目标粒子群优化算法。该算法把个体与参考点的支配关系或者距离作为一个重要因素,在选择引导者的锦标赛方法,局部最优更新规则,以及外部种群档案剪枝规则中都嵌入了基于支配关系或距离因素的投票规则,以找到群体决策解,并且提高搜索效率。仿真结果表明该算法有效。     

基于能效优化的两足机器人步态控制方法

针对高能耗导致的两足机器人实用化障碍,提出了一种全新的、系统化的步态能效优化控制方法.基于两足机器人运动的重要能耗指标(平均功率、平均功率偏差、平均力矩损耗),提出了能耗预估策略和能效优化算法,获取了零力矩点(ZMP)稳定区域内的能耗极小值.沿着能耗极小值所对应的上体轨迹对机器人步态实施能效优化控制,最终获得满足ZMP稳定判据的低能耗步态.仿真结果证明,该方法能够有效降低机器人能耗并保持其稳定性.     

Moving objects forecast in image sequences using autoregressive algorithms

The objective of this paper is to present an overall approach to forecasting the future position of the moving objects of an image sequence after processing the images previous to it. The proposed method makes use of classical techniques such as optical flow to extract objects’ trajectories and velocities, and autoregressive algorithms to build the predictive model. Our method can be used in a variety of applications, where videos with stationary cameras are used, moving objects are not deformed and change their position with time. One of these applications is traffic control, which is used in this paper as a case study with different meteorological conditions to compare with.