基于遗传算法的静态Ad-hoc拓扑结构控制

将遗传算法引入到了静态Ad—hoc无线网络的拓扑结构控制中，突破了网络中所有节点辐射半径都相同的固有思路，通过调节各无线节点的辐射半径，在相邻节点对之间形成有向路径，从而达到节省节点能源消耗和网络拓扑结构优化的目的，并取得了较好的实验结果。     

MDP－PROLOG~（＋＋）语言的实现

给出了ＭＤＰ－ＰＲＯＬＯＧ＋＋语言的预编译技术，详细论述了预编译程序ＰＰＰ的总体设计、数据结构、扫描处理以及进程文本创建．该语言已在多层分布并行处理系统Ｗｕｄｐ－９１上实现     

DYNAMICS MODELING,SIMULATION, AND CONTROL OF ROBOTS WITH FLEXIBLE JOINTS AND FLEXIBLE LINKS$^{\bf 1)}$

本文探究了铰柔性对机器人动力学响应和动力学控制的影响. 首先, 建立由$n$个柔性铰和$n$个柔性杆组成的空间机器人模型, 运用递推拉格朗日动力学方法, 得到柔性机器人系统的刚柔耦合动力学方程. 在动力学建模过程中, 除了考虑杆件的拉伸变形、弯曲变形、扭转变形以及非线性耦合变形对机器人系统动力学行为的影响, 还考虑了铰的柔性对机器人动力学响应和控制的影响. 其中, 柔性铰模型是基于Spong的柔性关节简化模型, 将柔性铰看成线性扭转弹簧, 不仅考虑了铰阻尼的存在, 还考虑了柔性铰的质量效应. 其次, 编写了空间柔性铰柔性杆机器人仿真程序, 研究铰的刚度系数和阻尼系数对系统动力学响应的影响. 研究表明: 随着柔性铰刚度系数的增大, 柔性机器人的动态响应幅值减小, 振动频率变大. 随着柔性铰阻尼系数的增大, 柔性机器人的动态响应幅值减小, 振动幅值的衰减速度变快. 可通过调节柔性铰的刚度和阻尼来减小柔性铰柔性杆机器人的振动, 因此铰阻尼的研究具有重要工程意义. 最后, 研究了铰柔性在机器人系统动力学控制中的影响. 在刚性铰机械臂和柔性铰机械臂完成相同圆周运动时, 通过逆动力学方法求解得到两种情况下的关节驱动力矩. 研究表明: 引入柔性铰会使控制所需的驱动力矩变小, 对机器人控制的影响显著.     

Great circle links and virtually fibered knots

We show that all two-bridge knot and link complements are virtually fibered. We also show that spherical Montesinos knot and link complements are virtually fibered. This is accomplished by showing that such manifolds are finitely covered by great circle link complements.     

Power and reversal power links for binary regressions: An application for motor insurance policyholders

In binary regression, symmetric links such as logit and probit are usually considered as standard. However, in the presence of unbalancing of ones and zeros, these links can be inappropriate and inflexible to fit the skewness in the response curve and likely to lead to misspecification. This is the case of covering some type of insurance, where it can be observed that the probability of a given binary response variable approaches zero at different rates than it approaches one. Furthermore, when usual links are considered, there is not a skewness parameter associated with the distribution chosen that, regardless of the linear predictor, is easily interpreted. In order to overcome such problems, a proposal for the construction of a set of new skew links is developed in this paper, where some of their properties are discussed. In this context, power links and their reversal versions are presented. A Bayesian inference approach using MCMC is developed for the presented models. The methodology is illustrated considering a sample of motor insurance policyholders selected randomly by gender. Results suggest that the proposed link functions are more appropriate than other alternative link functions commonly used in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

Co-authorship model with link strength

We generalize a network formation model for co-authorship introducing the possibility of the connections having different link strengths. Different link strengths represent the fact that authors may put different efforts into different collaborations. To evaluate the model, we consider the notions of efficiency and pairwise stability, which are based on a utility function that measures the benefits for an author to belonging to a certain network structure. We divide the analysis in two cases, considering that link strengths are unbounded or bounded. In the first case, we show that if there are more than two authors in the network, then there is no pairwise stable network. In the second case, we show that the pairwise stable networks consist of completely connected disjoint components where essentially all link strengths are maximal. Regarding efficiency, in both cases, if the number of authors is even, then the unique efficient network structure consists of pairs of connected authors.     

以提升创新能力为目标的基础力学实践教学初探

创新型基础力学人才的培养既要注重专业知识的学习,又要重视学生思辨、质疑与应用能力的提升。受限于不断削减的学时,传统基础力学课程仍以讲授为主,难以开展有效的实践教学环节。这种重理论轻实践的模式易导致学生学习兴趣下降、综合能力不足。为弥补实践短板,国内高校正逐步开展各类型大学生实践项目。本文以大学生创新训练项目为例,系统介绍项目实施期间教师有效的引导方式,以期为新时期力学人才培养贡献力量。

     

Relative Entropy of Distance Distribution Based Similarity Measure of Nodes in Weighted Graph Data

Many similarity measure algorithms of nodes in weighted graph data have been proposed by employing the degree of nodes in recent years. Despite these algorithms obtaining great results, there may be still some limitations. For instance, the strength of nodes is ignored. Aiming at this issue, the relative entropy of the distance distribution based similarity measure of nodes is proposed in this paper. At first, the structural weights of nodes are given by integrating their degree and strength. Next, the distance between any two nodes is calculated with the help of their structural weights and the Euclidean distance formula to further obtain the distance distribution of each node. After that, the probability distribution of nodes is constructed by normalizing their distance distributions. Thus, the relative entropy can be applied to measure the difference between the probability distributions of the top d important nodes and all nodes in graph data. Finally, the similarity of two nodes can be measured in terms of this above-mentioned difference calculated by relative entropy. Experimental results demonstrate that the algorithm proposed by considering the strength of node in the relative entropy has great advantages in the most similar node mining and link prediction.     

Control of multi-node mobile communications networks with time-varying channels via stability methods

Consider a communications network consisting of mobiles and random external data processes, each destined to a particular destination. Each mobile can serve as a node in the multi-hop path from source to destination. At each mobile the data is queued according to the source destination pair. The quality of the connecting channels are randomly varying. Time is divided into small scheduling intervals. At the beginning of each interval, the channels are estimated and this information is used for the decisions concerning allocation of transmission power and/or time, bandwidth, and perhaps antennas, in a queue and channel-state dependent way. Under a natural (and “almost” necessary) “average flow” condition, stochastic stability methods are used to develop scheduling policies that assure stability. The policies are readily implementable and allow a range of tradeoffs between current rates and queue lengths, under very weak conditions. Because of the non-Markovian nature of the problem, we use the perturbed Stochastic Liapunov function method. The choice of Liapunov function allows a choice of the effective performance criteria. All essential factors are incorporated into a “mean rate” function, so that the results cover many different systems. Extensions concerning acknowledgments, multicasting, non-unique routes, and others are given to illustrate the versatility of the method, and a useful method for getting the a priori routes is discussed.