Distributed and Collaborative Visualization

Visualization is a powerful tool for analyzing data and presenting results in science, engineering and medicine. This paper reviews ways in which it can be used in distributed and/or collaborative environments. Distributed visualization addresses a number of resource allocation problems, including the location of processing close to data for the minimization of data traffic. The advent of the Grid Computing paradigm and the link to Web Services provides fresh challenges and opportunities for distributed visualization—including the close coupling of simulations and visualizations in a steering environment. Recent developments in collaboration have seen the growth of specialized facilities (such as Access Grid) which have supplemented traditional desktop video conferencing using the Internet and multicast communications. Collaboration allows multiple users—possibly at remote sites—to take part in the visualization process at levels which range from the viewing of images to the shared control of the visualization methods. In this review, we present a model framework for distributed and collaborative visualization and assess a selection of visualization systems and frameworks for their use in a distributed or collaborative environment. We also discuss some examples of enabling technology and review recent work from research projects in this field.     

3ds max中创建Camera Match点方法的探讨

通过创建一辅助长方体并对其进行变换，用其变换后的方向来反映3ds max中背景图像的透视方向，并利用其对场景与背景图像匹配的Camera Match点进行定位，为进行摄像机匹配提供了一种方便快捷、实用的新途径。     

Explaining Paradoxical Relations Between Academic Self-Concepts and Achievements: Cross-Cultural Generalizability of the Internal/External Frame of Reference Predictions Across 26 Countries.

The internal/external frame of reference (I/E) model explains a seemingly paradoxical pattern of relations between math and verbal self-concepts and corresponding measures of achievement, extends social comparison theory, and has important educational implications. In a cross-cultural study of nationally representative samples of 15-year-olds from 26 countries (total N = 55,577), I/E predictions were supported in that (a) math and verbal achievements were highly correlated, but math and verbal self-concepts were nearly uncorrelated; (b) math achievement had positive effects on math self-concept, but negative effects on verbal self-concept; and (c) verbal achievement had positive effects on verbal self-concept, but negative effects on math self-concept. Supporting the cross-cultural generalizability of predictions, multigroup structural equation models demonstrated good support for the generalizabilify of results across 26 countries participating in the Programme for International Student Assessment project sponsored by the Organisation for Economic Co-operation and Development. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

双闭环复合控制在轮胎硫化机中的应用

以硫化过程为研究对象,提出了一种分别控制扰动和系统参数变化的新型复合控制方法,并用遗传算法对控制参数进行了优化。通过对其在Matlab/Simulink中进行仿真,与模型参考自适应控制相比较,结果表明该控制方案具有更优良的鲁棒性和可靠性,控制方案简单且可实现在线整定,便于在轮胎企业推广应用。     

建议增用主曲线实验方法提高我国核电安全的可靠性

日本福岛核事故后,各国政府对核电厂的安全更加重视了。提高核电厂安全要求非常重要,予以实现更加重要。毫无疑问,为安全所采取的新措施必须满足标准要求,并被世界公认和各国共同采用后,才会被核电厂接受和推行。本文的建议符合此原则并在文中说明了原因和根据。     

基准模型跟随控制在热镀锌机组张力控制中的应用

为更好地减少带钢张力的波动,确保带钢张力的稳定,宝钢分公司五冷轧工程新建热镀锌机组张力控制采用了一种最新控制策略,即基准模型跟随控制。在分析基准模型跟随控制原理的基础上,运用MATLAB仿真软件对基准模型跟随控制的应用效果进行模拟仿真试验;比照实际设备调试时的数据,基准模型跟随控制解决了机组不同传动辊因转动惯量不同造成的加减速不同步等问题,使机组各传动辊能够获得更好的速度控制。     

Nonlinear averaging theorems, and the determination of parameter convergence rates in adaptive control

The paper presents nonlinear averaging theorems for two-time scale systems, where the dynamics of the fast system are allowed to vary with the slow system. The results are applied to the Narendra-Valavani adaptive control algorithm, and estimates of the parameter convergence rates are obtained which do not rely on a linearization of the system around the equilibrium, and therefore are valid in a larger region in the parameter space.     

Iterative learning of model reference adaptive controller for uncertain nonlinear systems with only output measurement

In this paper, a model reference adaptive control strategy is used to design an iterative learning controller for a class of repeatable nonlinear systems with uncertain parameters, high relative degree, initial output resetting error, input disturbance and output noise. The class of nonlinear systems should satisfy some differential geometric conditions such that the plant can be transformed via a state transformation into an output feedback canonical form. A suitable error model is derived based on signals filtered from plant input and output. The learning controller compensates for the unknown parameters, uncertainties and nonlinearity via projection type adaptation laws which update control parameters along the iteration domain. It is shown that the internal signals remain bounded for all iterations. The output tracking error will converge to a profile which can be tuned by design parameters and the learning speed is improved if the learning gain is large.     

A multicomputer garbage collector for a single-assignment language

An asynchronous garbage collector for a message-passing multiprocessor (multicomputer) is described. This combines Weighted Reference Counting (WRC) interprocessor collection and tracing intraprocessor collection to permit individual processors to reclaim local storage independently. A novel feature is the integration of Weighted Reference Counting collection and the communication algorithms required to support a global address space in a single assignment language. This significantly reduces communication overhead and space requirements attributable to garbage collection. In addition, techniques are described that avoid the creation of cyclic structures that cannot be reclaimed using WRC. Experimental studies performed in a concurrent logic programming system that incorporates the collector confirm its efficiency and the benefits of integrating garbage collector and language implementation.     

对象随型粗糙面近红外单目视觉测量与基准图像自愈

针对复杂应用环境中近红外单目视觉位姿测量系统偏离预置合作目标对象后,无法完成位姿测量的特殊情况,提出一种以合作目标周边随型粗糙面图像为测量对象的单目视觉测量方法,以及图像受损后的动态自愈方法。通过将实时获取的随型粗糙面图像特征与预存基准图像特征进行匹配计算,完成特殊情况下的应急测量。同时,为减少随型粗糙面图像污染或受损后对位姿测量精度的影响,实时计算污染或受损程度并动态自愈基准图像特征。实验结果表明,以随型粗糙面为对象的位姿测量精度稍低于合作目标对象,但能够满足特殊情况下的应急使用需求,提高了测量系统的鲁棒性;当随型粗糙面图像污染或受损达到70%时,采用自愈处理与未做自愈处理相比,方位角测量误差减少72%以上,验证了基准图像自愈方法的有效性。