Climb-enabled discrete dislocation plasticity

A small strain two-dimensional discrete dislocation plasticity framework coupled to vacancy diffusion is developed wherein the motion of edge dislocations is by a combination of glide and climb. The dislocations are modelled as line defects in a linear elastic medium and the mechanical boundary value problem is solved by the superposition of the infinite medium elastic fields of the dislocations and a complimentary non-singular solution that enforces the boundary conditions. Similarly, the climbing dislocations are modelled as line sources/sinks of vacancies and the vacancy diffusion boundary value problem is also solved by a superposition of the fields of the line sources/sinks in an infinite medium and a complementary non-singular solution that enforces the boundary conditions. The vacancy concentration field along with the stress field provides the climb rate of the dislocations. Other short-range interactions of the dislocations are incorporated via a set of constitutive rules. We first employ this formulation to investigate the climb of a single edge dislocation in an infinite medium and illustrate the existence of diffusion-limited and sink-limited climb regimes. Next, results are presented for the pure bending and uniaxial tension of single crystals oriented for single slip. These calculations show that plasticity size effects are reduced when dislocation climb is permitted. Finally, we contrast predictions of this coupled framework with an ad hoc model in which dislocation climb is modelled by a drag-type relation based on a quasi steady-state solution. © 2013 Elsevier Ltd. All rights reserved.

Gaussian processes for POMDP-based dialogue manager optimization

A partially observable Markov decision process (POMDP) has been proposed as a dialog model that enables automatic optimization of the dialog policy and provides robustness to speech understanding errors. Various approximations allow such a model to be used for building real-world dialog systems. However, they require a large number of dialogs to train the dialog policy and hence they typically rely on the availability of a user simulator. They also require significant designer effort to hand-craft the policy representation. We investigate the use of Gaussian processes (GPs) in policy modeling to overcome these problems. We show that GP policy optimization can be implemented for a real world POMDP dialog manager, and in particular: 1) we examine different formulations of a GP policy to minimize variability in the learning process; 2) we find that the use of GP increases the learning rate by an order of magnitude thereby allowing learning by direct interaction with human users; and 3) we demonstrate that designer effort can be substantially reduced by basing the policy directly on the full belief space thereby avoiding ad hoc feature space modeling. Overall, the GP approach represents an important step forward towards fully automatic dialog policy optimization in real world systems. © 2013 IEEE.

基于模糊行为分析的移动自组网入侵检测

移动自组网络是一种不需要基础设施的网络．在这种网络中，移动节点是自组织的，并且需要互相提供网络路由服务．自组网络非常容易受到攻击，特别是内部攻击．提出了一个基于模糊行为分析的入侵检测方案，以检测网络内部的路由攻击．利用邻接节点监测，通过分析节点路由行为与路由规范的偏差，发现恶意行为．在数据分析的过程中引入了模糊路由行为分析的方法，大大降低了误报率．仿真实验表明，该方案能有效地检测出路由入侵行为，而将误报率控制在一个较低的水平．

无线自组网络中基于簇结构的安全方案

无线自组网络是一种不需要基础通信设施的自组织网络，正得到越来越多的应用．当前自组网络的安全性研究正成为一个热点．对基于簇结构的自组网络进行了安全分析，并且针对存在的安全问题提出了新的安全解决方案．主要贡献在于：①提出了一个保护簇首的安全机制；②针对节点簇间漫游的安全隐患，提出一个基于请求的节点信息共享机制，并给出了相应的算法．对该方案进行了仿真实验，结果显示，该方案具有充分的可行性．与已有方案相比，该方案具有较完善的安全机制，网络性能也较好．

移动自组网中感知拓扑失配的P2P覆盖网构建

对等计算主要关注构造在应用层的虚拟覆盖网络.在上层的覆盖网络和底层的物理网络之间,通常都存在着拓扑失配.这种失配会导致P2P应用耗费相当大的通信开销.在移动自组网中,由于资源(比如带宽,电池能量等)和节点移动性的限制,拓扑失配问题变得更加严重.而已有工作对这一问题没有进行充分的研究.本文研究了移动自组网中的拓扑失配问题对非结构化P2P覆盖网中目标搜索的影响,并提出一个分布式的、能感知拓扑失配的覆盖网络构建算法D-TAOC.分析和实验表明在D-TAOC构建的拓扑失配感知的覆盖网中,P2P应用能够在较少牺牲目标搜索效率的前提下,明显地降低网络中的通信负载.

一种基于信任度的自组安全互操作方法

提出了基于信任度的自组安全互操作方法,引入信任度描述自治域和用户正确参与协作的概率.自治域对用户的信任度由二者的直接交互经验以及其他域对用户的评价共同决定,满足信任策略要求的用户允许执行角色.用户的恶意历史行为将会降低其信任度,从而影响执行角色的范围.自治域对其他域的信任度由对用户的评价与直接经验的偏差根据加权主要算法反馈更新.自治域的恶意评价影响其推荐信息的可信程度.实验结果表明,该方法能够有效地抵御欺骗和恶意行为.

移动卫星网络资源发现技术研究

资源发现技术是根据给定的资源描述，在网络中自动找到相应资源的技 术，该技术能够智能地满足网络中应用和指挥任务执行时对资源信息的需求， 并且能够为资源的管理和监控提供一定支持。 现有的资源发现技术研究主要针对地面的网格、P2P网络和移动Ad hoc 网络等。卫星网络作为一种特殊的移动网络，其中节点的星载CPU 处理能力 和存储能力都无法与地面设备相提并论。同时，由于卫星网络具有拓扑结构 动态变化、空间无线信道时延长、误码率较高等特性，使得现有的地面网络 资源发现协议不能直接应用于卫星网络，因此设计高效的卫星网络资源发现 协议将有助于促进卫星网络的复杂应用和智能控制。 本文提出了一种针对移动卫星网络的分布式资源发现协议SatRDP， 针对 卫星网络中节点的移动性、星间链路时延和不同星座组网结构等情况，设计 了协议的体系结构以及相应的分布式资源信息存储和广告策略、需求路由和 回溯策略。经过分析，SatRDP 能够更好地适应移动卫星网络，提高资源发现 成功率，节省卫星节点的存储资源，在一定程度上降低协议开销。 最后，设计了仿真实验平台，对算法进行了初步的实验，并与传统的分 布式资源发现协议 FLOOD 进行比较。实验结果表明，SatRDP 协议更适合卫 星网络环境，有更高的发现成功率、发现效率和更小的需求包开销。最后总 结并指出了移动卫星网络资源发现技术进一步的研究方向。

MANET中TCP Vegas拥塞控制的端到端改进方法

TCP Vegas通过往返时间的最小值baseRTT来进行拥塞控制,因此获取准确baseRTT的值至关重要.在MANET中,不断变化的网络拓扑会导致baseRTT的测量出现严重偏差,从而降低了吞吐量,而TCP Vegas在拥塞避免阶段发生路由变化但没有引起丢包或失序现象时,已有的端到端启发式方案很难进行识别.采用回落探测方法识别路由变化,进而调节往返时间的最小值以改善TCP Vegas拥塞控制算法在MANET中的性能.

水下机器人神经网络自适应逆控制

水下环境的复杂性以及自身模型的不确定性,给水下机器人的控制带来很大困难。针对水下机器人的特点和控制方面所存在的问题,提出了基于预测 校正控制策略的水下机器人神经网络自适应逆控制结构及训练算法。通过在线辨识系统的前向模型,估计出系统的Jacobian矩阵,然后采用预报误差法实现控制器的自适应。同时,为了提高系统对于外扰的鲁棒性,在伪线性回归算法的基础上,在评价函数中引入微分项。理论分析和仿真结果表明,与原来的算法相比,微分项的引入改善了系统对于外扰的鲁棒性和动态性能。

大规模多数据库系统的互操作机制

Sharing data among disparate databases has so far mostly been achieved through some form of ad-hoc schema integration. This approach becomes less tractable as the number of participating database increases. In this paper,we first present the primary problems to be resolved in large multidatabase systems and discuss the autonomy and heteroheneity of large multidatabase systems and then describe a coalition agent mechanism to implement large multidatabase systems interoperation.

Resolving Ambiguity in Nonmonotonic Inheritance Hierarchies

This paper describes a theory of inheritance theories. We present an original theory of inheritance in nonmonotonic hierarchies. The structures on which this theory is based delineate a framework that subsumes most inheritance theories in the literature, providing a new foundation for inheritance. * Our path-based theory is sound and complete w.r.t. a direct model-theoretic semantics. * Both the credulous and the skeptical conclusions of this theory are polynomial-time computable. * We prove that true skeptical inheritance is not contained in the language of path-based inheritance. Because our techniques are modular w.r.t. the definition of specificity, they generalize to provide a unified framework for a broad class of inheritance theories. By describing multiple inheritance theories in the same "language" of credulous extensions, we make principled comparisons rather than the ad-hoc examination of specific examples makes up most of the comparative inheritance work.

Specialization of Perceptual Processes

In this report, I discuss the use of vision to support concrete, everyday activity. I will argue that a variety of interesting tasks can be solved using simple and inexpensive vision systems. I will provide a number of working examples in the form of a state-of-the-art mobile robot, Polly, which uses vision to give primitive tours of the seventh floor of the MIT AI Laboratory. By current standards, the robot has a broad behavioral repertoire and is both simple and inexpensive (the complete robot was built for less than $20,000 using commercial board-level components). The approach I will use will be to treat the structure of the agent's activity---its task and environment---as positive resources for the vision system designer. By performing a careful analysis of task and environment, the designer can determine a broad space of mechanisms which can perform the desired activity. My principal thesis is that for a broad range of activities, the space of applicable mechanisms will be broad enough to include a number mechanisms which are simple and economical. The simplest mechanisms that solve a given problem will typically be quite specialized to that problem. One thus worries that building simple vision systems will be require a great deal of {it ad-hoc} engineering that cannot be transferred to other problems. My second thesis is that specialized systems can be analyzed and understood in a principled manner, one that allows general lessons to be extracted from specialized systems. I will present a general approach to analyzing specialization through the use of transformations that provably improve performance. By demonstrating a sequence of transformations that derive a specialized system from a more general one, we can summarize the specialization of the former in a compact form that makes explicit the additional assumptions that it makes about its environment. The summary can be used to predict the performance of the system in novel environments. Individual transformations can be recycled in the design of future systems.