Composite registers

Summary We introduce a shared data object, called acomposite register, that generalizes the notion of an atomic register. A composite register is an array-like shared data object that is partitioned into a number of components. An operation of a composite register either writes a value to a single component or reads the values of all components. A composite register reduces to an ordinary atomic register when there is only one component. In this paper, we show that multi-reader, singlewriter atomic registers can be used to implement a composite register in which there is only one writer per component. In a related paper, we show how to use the composite register construction of this paper to implement a composite register with multiple writers per component. These two constructions show that it is possible to implement a shared memory that can be read in its entirety in a single snapshot operation, without using mutual exclusion. James H. Anderson received the B.S. degree in Computer Science from Michigan State University in 1982, the M.S. degree in Computer Science from Purdue University in 1983, and the Ph.D. degree in Computer Sciences from the University of Texas at Austin in 1990. Since August 1990, he has been with the University of Maryland at College Park, where he is now an Assistant Professor of Computer Science. Since January 1992, he has been a staff scientist at NASA's Center of Excellence in Space Data and Information Sciences, located at the Goddard Space Flight Center in Greenbelt, Maryland. Professor Anderson's primary research interests are within the area of concurrent and distributed computing.Preliminary version presented at theNinth Annual ACM Symposium on Principles of Distributed Computing [2]Work supported, in part, at the University of Texas at Austin by Office of Naval Research Contract N00014-89-J-1913, and at the University of Maryland by an award from the University of Maryland General Research Board     

Composite convex programs

A duality theory using conjugate functions is established for mathematical programs that involve the composition of two convex functions. This generalizes our earlier work in quadratic and composite geometric programs. A specific application to minimax programs is given.     

Composite kernel learning

The Support Vector Machine is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning enables to learn the kernel, from an ensemble of basis kernels, whose combination is optimized in the learning process. Here, we propose Composite Kernel Learning to address the situation where distinct components give rise to a group structure among kernels. Our formulation of the learning problem encompasses several setups, putting more or less emphasis on the group structure. We characterize the convexity of the learning problem, and provide a general wrapper algorithm for computing solutions. Finally, we illustrate the behavior of our method on multi-channel data where groups correspond to channels.     

复合材料固化传感器

对复合材料现有固化监测传感器的工作原理、结构特点进行了具体分析,展望了固化传感器的发展。     

Composite Flow Maps

Flow maps are widely used to provide an overview of geospatial transportation data. Existing solutions lack the support for the interactive exploration of multiple flow components at once. Flow components are given by different materials being transported, different flow directions, or by the need for comparing alternative scenarios. In this paper, we combine flows as individual ribbons in one composite flow map. The presented approach can handle an arbitrary number of sources and sinks. To avoid visual clutter, we simplify our flow maps based on a force‐driven algorithm, accounting for restrictions with respect to application semantics. The goal is to preserve important characteristics of the geospatial context. This feature also enables us to highlight relevant spatial information on top of the flow map such as traffic conditions or accessibility. The flow map is computed on the basis of flows between zones. We describe a method for auto‐deriving zones from geospatial data according to application requirements. We demonstrate the method in real‐world applications, including transportation logistics, evacuation procedures, and water simulation. Our results are evaluated with experts from corresponding fields.     

Composite Texture Synthesis

Many textures require complex models to describe their intricate structures. Their modeling can be simplified if they are considered composites of simpler subtextures. After an initial, unsupervised segmentation of the composite texture into the subtextures, it can be described at two levels. One is a label map texture, which captures the layout of the different subtextures. The other consists of the different subtextures. This scheme has to be refined to also include mutual influences between textures, mainly found near their boundaries. The proposed composite texture model also includes these. The paper describes an improved implementation of this idea. Whereas in a previous implementation subtextures and their interactions were synthesized sequentially, this paper proposes a parallel implementation, which yields results of higher quality.     

可信的服务组合框架研究

Web服务环境下功能相似的质量不同的服务很多,为了更好地让消费者发现并使用其所提供的服务,服务商不惜造假欺骗客户。针对这种服务不可信等问题,提出了一种可信的服务组合框架,该框架整合了业务过程定义与服务组合,利用业务过程柔性定义来支撑服务组合的灵活选择,通过组合服务设计、组合服务选择、服务绑定这三个阶段来最终实现服务的优化选择。最后,通过一个案例来验证了该技术的有效性。     

Injectivity of Composite Functions

The problem of deciding injectivity of functions is addressed. The functions under consideration are compositions of more basic functions for which information about injectivity properties is available. We present an algorithm which will often be able to prove that such a composite function is injective. This algorithm constructs a set of propositional Horn clause axioms from the function specification and the available information about the basic functions. The existence of a proof of injectivity is then reduced to the problem of propositional Horn clause deduction. Dowling and Gallier have designed several very fast algorithms for this problem, the efficiency of which our algorithm inherits. The proof of correctness of the algorithm amounts to showing soundness and completeness of the generated Horn clause axioms.     

复合固体推进剂细观力学模型研究

为了建立复合固体推进剂的细观力学模型,首要的问题是建立一个能够真实描述推进剂细观形态结构的颗粒填充模型.文中将推进剂看作是颗粒与基体组成的复合材料,详细地给出了应用分子动力学生成推进剂颗粒填充模型的方法,得到了推进剂颗粒在基体中随机分布的颗粒填充模型.在此基础上,采用细观有限元方法进行了分析,获得了推进剂颗粒与基体内的应力分布情况.研究表明:分子动力学方法可以有效地生成推进剂的细观颗粒填充模型,在此基础上进行的细观力学分析可以有效地考虑固体推进剂细观结构对其力学性能的影响.     

Composite system controllability and observability

A differential operator approach to modeling the dynamical behavior of linear, time-invariant, multivariable systems is employed in order to develop some new techniques for determining the controllability and observability properties of series, parallel, and feedback composite systems. The tests outlined involve polynomial matrix manipulations and rely on some recent results which deal with the controllability and observability of systems in differential operator form.     

改进的组合差分进化优化算法

组合差分进化算法CoDE是一新的具有竞争力的算法,但收敛速度和寻优性能仍有待改进。为解决上述问题,提出对组合差分进化算法CoDE从生成策略和控制参数两个方面进行改进,提出了两种改进的CoDE版本MCoDE和MCoDE-P,并利用6个典型的测试函数对改进性能进行检验。结果表明结合了最好个体信息的MCoDE方法能够改善CoDE的寻优性能,而采用控制参数扩展的MCoDE-P方法却难以达到期望的效果。     

一种混合式的指针分析算法

指针的指向分析在检测C语言多线程程序的数据竞争中占有重要的地位。Steensgaard提出的流非敏感上下文非敏感的指针别名分析算法,因其执行效率极高的优点被广泛的应用于快速的指针指向分析。但该算法计算结果精度不高,得到的指针指向集往往有误差。针对该不足,引入了Vineet Kahlon的用求最大更新序列来求指针别名的思想,对Steensgaard算法计算出的结果进行了修正。并通过一个实例证明了改进后的算法比先前的算法更精确。     

夏普黑白高端数码复合机

世界著名的综合电器制造商夏普公司向中国市场正式发售按照次时代标准设计的黑白高端数码复合机[MX-M363N/453N/503N]系列。作为夏普最新技术的代表,该系列产品均可选购搭载业内首创的主机一体型键盘、并标配8.5英寸彩色W-VGA液晶触摸屏和前置USB接口,使其操作更加简便快捷,为商务人士带来PC化的操作体验。与此同时,夏普还同时发售保留了N系列主要功能、而价格更具亲民性的[MX-M363U/453U/503U]的U系列。     

Composite performance and dependability analysis

Composite performance and dependability analysis is gaining importance in the design of complex, fault-tolerant systems. Markov reward models are most commonly used for this purpose. In this paper, an introduction to Markov reward models including solution techniques and application examples is presented. Extensions of Markov reward models to semi-Markov reward models are also mentioned. A brief discussion of how task completion time models and models of queues with breakdowns and repairs relate to Markov reward models is also given.     

一种新型的双闭环复合控制系统

针对常规PID控制器不能满足系统结构参数变化的控制要求,并且传统的单一控制器无法实现非结构参数变化和参数变化的分时控制。文章将自适应控制思想与PID控制器相结合,提出了一种分别控制扰动和系统参数变化的新的复合控制方法。通过Simulink仿真,结果表明该控制方案具有更加优良的鲁棒性和可靠性,实现了对受控对象的扰动和参数变化的分时控制。     

Composite modeling of transfer functions

The problem under consideration is how to estimate the frequency function of a system and the associated estimation error when a set of possible model structures is given and then one of them is known to contain the true system. The “classical” solution to this problem is to, first, use a consistent model structure selection criterion to discard all but one single structure, second, estimate a model in this structure and, third, conditioned on the assumption that the chosen structure contains the true system, compute an estimate of the estimation error. For a finite data set, however, one cannot guarantee that the correct structure is chosen, and this “structural” uncertainty is lost in the previously mentioned approach. In this contribution a method is developed that combines the frequency function estimates and the estimation errors from all possible structures into a joint estimate and estimation error. Hence, this approach bypasses the structure selection problem. This is accomplished by employing a Bayesian setting. Special attention is given to the choice of priors. With this approach it is possible to benefit from a priori information about the frequency function even though the model structure is unknown     

Bijective Composite Mean Value Mappings

We introduce the novel concept of composite barycentric mappings and give theoretical conditions under which they are guaranteed to be bijective. We then focus on mean value mappings and derive a simple procedure for computing their Jacobians, leading to an efficient GPU‐assisted implementation for interactively designing composite mean value mappings which are bijective up to pixel resolution. We provide a number of examples of 2D image deformation and an example of 3D shape deformation based on a natural extension of the concept to spatial mappings.     

故障特征组合选择方法

特征选择方法主要包括过滤方法和绕封方法。为了利用过滤方法计算简单和绕封方法精度高的优点,提出一种组合过滤和绕封方法的特征选择新方法。该方法首先利用基于互信息准则的过滤方法得到满足一定精度要求的子集后,再采用绕封方法找到最后的优化特征子集。由于遗传算法在组合优化问题上的成功应用,对特征子集寻优采用了遗传算法。在数值仿真和轴承故障特征选择中,采用新方法在保证诊断精度的同时,可以节省大量选择时间。组合特征选择方法有较好的寻优特征子集的能力,能够节省选择时间,具有高效、高精度的双重优点。