Modeling and multiobjective optimization of traction performance for autonomous wheeled mobile robot in rough terrain

Application of terrain-vehicle mechanics for determination and prediction of mobility performance of autonomous wheeled mobile robot(AWMR) in rough terrain is a new research area currently receiving much attention for both terrestrial and planetary missions due to its significant role in design,evaluation,optimization,and motion control of AWMRs.In this paper,decoupled closed form terramechanics considering important wheel-terrain parameters is applied to model and predict traction.Numerical analysis of traction performance in terms of drawbar pull,tractive efficiency,and driving torque is carried out for wheels of different radii,widths,and lug heights,under different wheel slips.Effects of normal forces on wheels are analyzed.Results presented in figures are discussed and used to draw some conclusions.Furthermore,a multiobjective optimization(MOO) method for achieving optimal mobility is presented.The MOO problem is formulated based on five independent variables including wheel radius r,width b,lug height h,wheel slip s,and wheel rotation angle θ with three objectives to maximize drawbar pull and tractive efficiency while minimizing the dynamic traction ratio.Genetic algorithm in MATLAB is used to obtain optimized wheel design and traction control parameters such as drawbar pull,tractive efficiency,and dynamic traction ratio required for good mobility performance.Comparison of MOO results with experimental results shows a good agreement.A method to apply the MOO results for online traction and mobility prediction and control is discussed.     

Measuring the spreadability of users in microblogs

Message forwarding (e.g.,retweeting on Twitter.com) is one of the most popular functions in many existing microblogs,and a large number of users participate in the propagation of information,for any given messages.While this large number can generate notable diversity and not all users have the same ability to diffuse the messages,this also makes it challenging to find the true users with higher spreadability,those generally rated as interesting and authoritative to diffuse the messages.In this paper,a novel method called SpreadRank is proposed to measure the spreadability of users in microblogs,considering both the time interval of retweets and the location of users in information cascades.Experiments were conducted on a real dataset from Twitter containing about 0.26 million users and 10 million tweets,and the results showed that our method is consistently better than the PageRank method with the network of retweets and the method of retweetNum which measures the spreadability according to the number of retweets.Moreover,we find that a user with more tweets or followers does not always have stronger spreadability in microblogs.     

Development of the heat treatment system for the 40 T hybrid magnet superconducting outsert

The heat treatment of Nb(3)Sn coil with the glass fabric insulation is one of the key and critical processes for the outsert solenoids of the 40 T hybrid magnet, which could be wound with cable-in-conduit conductors using the insulation-wind-and-react technique. The manufacturing of the large vertical type vacuum/Ar atmosphere-protection heat treatment system has been completed and recently installed in the High Magnetic Filed Laboratory, Chinese Academy of Sciences. The heat treatment system composed mainly the furnace, the purging gas supply system, the control system, the gas impurities monitoring system, and so on. At present, the regulation and testing of the heat treatment system has been successfully finished, and all of technical parameters meet or exceed specifications.     

Dynamic isotropic design of a class of Gough-Stewart parallel manipulators lying on a circular hyperboloid of one sheet

This paper proposes an optimal design method based on dynamic isotropy conditions of a generalized natural frequency matrix in task space for a standard Gough-Stewart parallel manipulator (GSPM). Firstly, the dynamic isotropy conditions are discussed and presented. Next, it is proved that standard GSPMs lie on a circular hyperboloid of one sheet. Further, we present a method to use a circular hyperboloid to construct 3-3-, 6-3- and 6-6-type standard GSPMs. Moreover, such novel definition is used to examine various dynamic isotropy conditions as functions of the coefficients of a hyperboloid. An optimal design method is also proposed accordingly. Finally, a numerical example is given to illustrate the design procedures. The results are very close to the complete dynamic isotropy.     

计算机实验教学改革初探

本文分析了计算机实验教学现状,并提出了若干计算机实验教学改革的建议,以期提高计算机实验教学的质量,全面提高学生的计算机应用能力.     

MongoDB数据库在网络行为分析与控制系统中的应用

在网络行为分析与控制系统中,传统的关系数据库在异构数据、海量日志的管理上难以胜任。NoSQL非关系型数据库的出现,对于解决面向文档的超大规模和高并发的问题提供了卓有成效的方案。本文在研究非关系数据库的基础上,着重分析MongoDB的特点和优势,通过性能测试,提出将MongoDB数据库应用于网络行为分析与控制系统,有效提高了大规模日志数据在网络行为分析与控制系统中的存储效率。     

Adaptive detection of range-spread targets without secondary data in multichannel autoregressive process

Adaptive detection of range-spread targets without secondary data is addressed in a multichannel autoregressive Gaussian disturbance with unknown space–time covariance matrix, by utilizing the Rao test. The proposed Rao test without secondary data is theoretically proved to be asymptotically (large-sample in the number of temporal observations) constant false alarm rate with respect to unknown space–time covariance matrix, thanks to an asymptotic equivalence between the Rao test and the generalized likelihood ratio test. Moreover, the performance loss due to no secondary data can be remedied by appropriately increasing the temporal dimension. The performance assessment conducted by Monte Carlo simulation, also in comparison with the existing detector without secondary data, confirms the effectiveness of the proposed detectors.     

Sampling average approximation method for a class of stochastic Nash equilibrium problems

We consider a class of stochastic Nash equilibrium problems (SNEP). Under some mild conditions, we reformulate the SNEP as a stochastic mixed complementarity problem (SMCP). We apply the well-known sample average approximation (SAA) method to solve the SMCP. We further introduce a semismooth Newton method to solve the SAA problems. The comprehensive convergence analysis is given as well. In addition, we demonstrate the proposed approach on a stochastic Nash equilibrium model in the wholesale gas–oil markets.     

On the Accuracy of Packet Delay Estimation in Distributed Service Networks

Packet delay (either one-way time or round-trip time) is a very important metric for measuring the performance of networks in a highly dynamic environment such as the Internet. Many network applications are also sensitive to packet delay or delay variation for ensuring an acceptable level of quality in providing network-based services such as VoIP, multimedia streaming, etc. A very important property of packet delay is that it is very dynamic and therefore should be measured frequently with measurement results being updated on a timely basis. Measurement of packet delay has thus generated a great deal of interest in the past years and a lot of research has been performed in the development of measurement architecture as well as specific measurement techniques. However, how to reduce network overhead resulting from measurement while achieving a reasonable level of accuracy still remains a challenge. In this paper, we propose to use delay estimation as an alternative to delay measurement for reducing measurement overhead and, in particular, examine the level of accuracy that delay estimation can achieve. With delay estimation, measurement nodes can be dynamically selected and activated and other nodes can share measurement results by performing delay estimation, thus reducing measurement overhead while supporting the dynamic requirement for delay measurement. Consequently, while measurement overhead can be reduced by activating only a subset of network nodes to perform actual measurement, desired accuracy can be achieved by exploring the correlation between delays as well as by sharing measurement results to do delay estimation based on such a correlation. We illustrate how packet delays of network nodes can correlate to each other based on topological properties and show how delays can be estimated based on such a correlation to meet accuracy requirements, which would make delay measurement in the Internet highly dynamic and adaptable to the accuracy requirements and measurement results highly reliable. We also show how delay estimation can be applied by presenting three application scenarios as well as an example to demonstrate the usefulness and effectiveness of delay estimation in the measurement of packet delays.     

Ricci flow-based spherical parameterization and surface registration

This paper presents an improved Euclidean Ricci flow method for spherical parameterization. We subsequently invent a scale space processing built upon Ricci energy to extract robust surface features for accurate surface registration. Since our method is based on the proposed Euclidean Ricci flow, it inherits the properties of Ricci flow such as conformality, robustness and intrinsicalness, facilitating efficient and effective surface mapping. Compared with other surface registration methods using curvature or sulci pattern, our method demonstrates a significant improvement for surface registration. In addition, Ricci energy can capture local differences for surface analysis as shown in the experiments and applications.