Trust for Ubiquitous,Transparent Collaboration

In this paper, trust-based recommendations control the exchange of personal information between handheld computers. Combined with explicit risk analysis, this enables unobtrusive information exchange, while limiting access to confidential information. The same model can be applied to a wide range of mobile computing tasks, such as managing personal address books and electronic diaries, to automatically provide an appropriate level of security. Recommendations add structure to the information, by associating categories with data and with each other, with degrees of trust belief and disbelief. Since categories also in turn confer privileges and restrict actions, they are analogous to rôles in a Rôle-Based Access Control system, while principals represent their trust policies in recommendations. Participants first compute their trust in information, by combining their own trust assumptions with others' policies. Recommendations are thus linked together to compute a considered, local trust assessment. Actions are then moderated by a risk assessment, which weighs up costs and benefits, including the cost of the user's time, before deciding whether to allow or forbid the information exchange, or ask for help. By unifying trust assessments and access control, participants can take calculated risks to automatically yet safely share their personal information.     

可编程光学二值双轨逻辑门

基于双轨逻辑,本文提出一种可级联的并行二值逻辑门。所有十六种二值逻辑运算可以采用偏振半波相延编程来实现。也提出了用电光晶体实现实时编程的方法。本文中给出了实验结果。     

光纤传感器在海洋环境监测中的应用

海洋是个特殊的环境,为许多光纤传感器提供了一个极好的应用领域。对于海洋这个特殊的“敌对”环境,光纤传感器将面临许多挑战。 本文着重介绍应用于海水温度、浊度、盐份浓度、浮游生物和溶解物光吸收量以及环境湿度等海洋环境参数监测的光纤传感器的原理、结构和特性,展望光纤传感器在海洋环境监测方面的美好前景。     

A comparison of two algorithms for the assignment problem

State-of-the-art computational results have shown that the shortest augmenting path (SAP) methods are more efficient than other primal-dual and primal-simplex based methods for solving the linear assignment problem on uniprocessor computers. There is, however, some controversy concerning their merits when compared with Bertsekas' auction algorithm on multiprocessor computers. In this study we investigate the performance of these competing methods on the Alliant FX/8. For each method, theoretical motivation, sources of parallelism and computational results are presented.     

Solving large-scale semidefinite programs in parallel

We describe an approach to the parallel and distributed solution of large-scale, block structured semidefinite programs using the spectral bundle method. Various elements of this approach (such as data distribution, an implicitly restarted Lanczos method tailored to handle block diagonal structure, a mixed polyhedral-semidefinite subdifferential model, and other aspects related to parallelism) are combined in an implementation called LAMBDA, which delivers faster solution times than previously possible, and acceptable parallel scalability on sufficiently large problems. This work was supported in part by NSF grants DMS-0215373 and DMS-0238008.     

随机环境中分枝过程的等价定理

给定了随机环境中分枝过程(BPRE)的精确定义,讨论了有关的可测性问题和BPRE的基本性质．在此基础上,证明了BPRE的一个等价定理．     

论浮力的计算

通过讨论物体下表面不与液体接触时浮力的计算,总结浮力计算的一般方法.     

随机环境下的对称零程过程的大偏差原理

利用相对熵方法及鞅方法给出了随机环境下的对称零程过程的经验测度的收敛速度函数.     

Computing Aviation Sparing Policies: Solving a Large Nonlinear Integer Program

Deployed US Navy aircraft carriers must stock a large number of spare parts to support the various types of aircraft embarked on the ship. The sparing policy determines the spares that will be stocked on the ship to keep the embarked aircraft ready to fly. Given a fleet of ten or more aircraft carriers and a cost of approximately 50 million dollars per carrier plus the cost of spares maintained in warehouses in the United States, the sparing problem constitutes a significant portion of the Navy’s resources. The objective of this work is to find a minimum-cost sparing policy that meets the readiness requirements of the embarked aircraft. This is a very large, nonlinear, integer optimization problem. The cost function is piecewise linear and convex while the constraint mapping is highly nonlinear. The distinguishing characteristics of this problem from an optimization viewpoint are that a large number of decision variables are required to be integer and that the nonlinear constraint functions are essentially “black box” functions; that is, they are very difficult (and expensive) to evaluate and their derivatives are not available. Moreover, they are not convex. Integer programming problems with a large number of variables are difficult to solve in general and most successful approaches to solving nonlinear integer problems have involved linear approximation and relaxation techniques that, because of the complexity of the constraint functions, are inappropriate for attacking this problem. We instead employ a pattern search method to each iteration of an interior point-type algorithm to solve the relaxed version of the problem. From the solution found by the pattern search on each interior point iteration, we begin another pattern search on the integer lattice to find a good integer solution. The best integer solution found across all interations is returned as the optimal solution. The pattern searches are distributed across a local area network of non-dedicated, heterogeneous computers in an office environment, thus, drastically reducing the time required to find the solution.     

一种适用于高数据速率和高速移动环境的新型信道估计方法——双正交通道信道估计方法

本文给出了一种适用于高数据速率和高速移动环境下的新型有效的信道估计方法-双正交通道信道估计方法(CETOC,Channel Estimation by using Two Orthogonal Channels),这种信道估计方法通过采用两个独立通道的联合估计,可以有效的克服快衰落的影响,从而使得在快衰落信道下应用多维状态调制成为可能.