板壳式换热器设置膨胀节的判定

介绍板壳式换热器的主要特点和应用。当壳体与板束温差较大时,笔者通过对产品开发的生产实践,提出解决板壳式换热器要否设置膨胀节的类似判定方法。     

Tripartite entanglement of a spin star model with Dzialoshinski–Moriya interaction

The effect of Dzialoshinski–Moriya (DM) interaction on the tripartite thermal entanglement of a spin-star model with four spins has been analyzed by an entanglement measure of the tripartite negativity. Our results imply that the tripartite thermal entanglement can be established among the three surrounding parties which do not interact with each other but interact with the central party independently. From the results, we find that the strong DM interaction can enhance the tripartite thermal entanglement while the high temperature can shrink it. The effect of the inhomogeneous coupling on the tripartite thermal entanglement is also discussed.     

RBF neural network based on q-Gaussian function in function approximation

To enhance the generalization performance of radial basis function (RBF) neural networks, an RBF neural network based on a q-Gaussian function is proposed. A q-Gaussian function is chosen as the radial basis function of the RBF neural network, and a particle swarm optimization algorithm is employed to select the parameters of the network. The non-extensive entropic index q is encoded in the particle and adjusted adaptively in the evolutionary process of population. Simulation results of the function approximation indicate that an RBF neural network based on q-Gaussian function achieves the best generalization performance.     

Robust clusterwise linear regression through trimming

The presence of clusters in a data set is sometimes due to the existence of certain relations among the measured variables which vary depending on some hidden factors. In these cases, observations could be grouped in a natural way around linear and nonlinear structures and, thus, the problem of doing robust clustering around linear affine subspaces has recently been tackled through the minimization of a trimmed sum of orthogonal residuals. This “orthogonal approach” implies that there is no privileged variable playing the role of response variable or output. However, there are problems where clearly one variable is wanted to be explained in terms of the other ones and the use of vertical residuals from classical linear regression seems to be more advisable. The so-called TCLUST methodology is extended to perform robust clusterwise linear regression and a feasible algorithm for the practical implementation is proposed. The algorithm includes a “second trimming” step aimed to diminishing the effect of leverage points.     

Dual FastSLAM: Dual Factorization of the Particle Filter Based Solution of the Simultaneous Localization and Mapping Problem

The process of building a map with a mobile robot is known as the Simultaneous Localization and Mapping (SLAM) problem, and is considered essential for achieving true autonomy. The best existing solutions to the SLAM problem are based on probabilistic techniques, mainly derived from the basic Bayes Filter. A recent approach is the use of Rao-Blackwellized particle filters. The FastSLAM solution factorizes the Bayes SLAM posterior using a particle filter to estimate over the possible paths of the robot and several independent Kalman Filters attached to each particle to estimate the location of landmarks conditioned to the robot path. Although there are several successful implementations of this idea, there is a lack of applications to indoor environments where the most common feature is the line segment corresponding to straight walls. This paper presents a novel factorization, which is the dual of the existing FastSLAM one, that decouples the SLAM into a map estimation and a localization problem, using a particle filter to estimate over maps and a Kalman Filter attached to each particle to estimate the robot pose conditioned to the given map. We have implemented and tested this approach, analyzing and comparing our solution with the FastSLAM one, and successfully building feature based maps of indoor environments.     

A Case Study on Applying a Tool for Automated System Analysis Based on Modular Specifications Written in TRIO

An effective means for analyzing and reasoning on software systems is to use formal specifications to simulate their execution. The simulation traces can be used for specification testing and reused for functional testing of the system later in the development process. It is widely acknowledged that, to deal with the complexity of industrial-size systems, specifications must be structured into modules providing abstraction mechanisms and clear interfaces. In our past work, we defined and implemented a method for simulating specifications written in the TRIO temporal logic language, and applied it to functional testing of time-critical industrial systems. In the present paper, we report on a case study with a tool that analyzes TRIO specifications by taking advantage of their modular structure, so as to overcome the well-known state-explosion problem and make the proposed method really scalable. We discuss the fundamental operations and the algorithms on which the tool is based. Then, we illustrate its use in a realistic case study, inspired from an industrial application. Finally, we comment on the overall results in terms of usability of the tool and effectiveness of the approach, and we outline future improvements.     

圆环面上纤维轨迹的计算机辅助设计

曲面上的曲线造型是计算机图形领域的一个新的研究热点,而且它们在纤维织物编织,三维服装裁剪以及复合材料的纤维缠绕轨迹设计等领域有十分广泛的应用,为了解决圆环面上纤维轨迹的计算机辅助设计问题,研究了圆环面上测地线的解析解以及拟测地线数值求解的具体算法并给出了其表达式,测地线是曲面上两点之间最短距离的曲线段,在一般曲面上没有解析解,但是在圆环面上却可求出其精确的解析解,但在曲面的边沿部分,测地线因不能实现自然的折返过渡,于是拟测地线就被引进到曲面上的曲线造型设计之中,在拟测地线分析研究基础上,给出了圆环面上拟测地线的方程及数值解法,通过其在一个实例中的应用结果证明,该方法可获得织物的纺织条纹以及缠绕物体的纤维轨迹。     

以存储器为中心的路由器MRouter

并行系统的互连技术一直是高性能计算机的一个关键研究领域。在本文作者1999年中提出了一种基于多端口快速存储器的新型互连体系结构MCIM,并在此基础上构造出规模为16－128个CPU的结点系统。该文将MCIM原理应用在互连网络通信技术上,实现了一种以存储器系统为中心 的路由器MRouter。它采用流水操作和穿通传输技术,可用于构成低延时、高带宽的高性能互连网络。这将种互连网络与上述结点系统结合,可以实现更大规模的并行系统。而且其无论在板级或是结点级都采用同一种互连技术,有利于系统的模块化实现。文中介绍了以存储器为中心的互连机制MCIM的原理,同时描述了以存储器为中心的路由器MRouter的结构及数据传输流程,在仿真实验中作者对MCIM的互连通信技术和其它互连技术进行了测试和比较。     

A new DSATUR-based algorithm for exact vertex coloring

This paper describes a new exact algorithm PASS for the vertex coloring problem based on the well known DSATUR algorithm. At each step DSATUR maximizes saturation degree to select a new candidate vertex to color, breaking ties by maximum degree w.r.t. uncolored vertices. Later Sewell introduced a new tiebreaking strategy, which evaluated available colors for each vertex explicitly. PASS differs from Sewell in that it restricts its application to a particular set of vertices. Overall performance is improved when the new strategy is applied selectively instead of at every step. The paper also reports systematic experiments over 1500 random graphs and a subset of the DIMACS color benchmark.