基于ASP技术的高校办公自动化系统的分析与设计

对高校办公自动化系统需求进行了分析,并且介绍了系统设计的主要内容和一些实际开发经验,以及在具体实现中的关键技术.     

配合煤选择性粉碎工艺的应用

介绍了配和煤选择性粉碎工艺的原理、特点及应用情况。结果表明该工艺投用后，配合煤质量明显改善。     

2001年绵阳科学城地区辐射环境监测与质量评价

2001年绵阳科学城地区主要环境介质(大气、河水、土壤和沉降等)中放射性水平与科学城开工前天然本底辐射没有显著性差别。通过对每个核设施烟囱流出物的测量与估算,获得了烟囱排放源项数据。利用该地区的大气扩散模式和多烟囱排放的剂量叠加原理,在评价坐标系中计算了叠加剂量分布。辐射环境质量评价表明80km范围内最大个人有效剂量是公众剂量限值的十万分之四,健康危害是危害约束值的千万分之二。表明环境影响是微弱的,是人们可以接受的。     

基于以太网的工业控制远程访问的研究

NAT是一项专门用于网络互联的技术，可以用来解决工业控制网络的互联及远程访问的问题。探讨了利用NAT技术实现基于以太网的远程访问的实现，并给出了具体的实例。     

Neutronic Comparison of Tritium－Breeding Performance of Candidate Tritium－Breeding Materials

Tritium self-sustainment, which will meet the fuel requirement of fusion reactor, is one of the key issues of fusion power development. The tritium breeding performances of various tritium-breeding materials are compared based on a series of neutronics calculations using three-dimensional Monte Carlo neutron-photon transport code MCNP/4C with the IAEA FENDL-2 data library. The effects of the dimensions of the tritium-breeding zone and the enrichment of 6Li on Tritium Breeding Ratio (TBR) are analyzed. The effects of Be as a neutron multiplier on TBR are also calculated.     

防失败签字安全性的理论分析

防失败签字是一种十分安全的签字体制,即使攻击者得到签字密钥后也难以伪造签字。论文首先简要介绍了该签字方案的签字过程和验证过程,然后根据这些过程利用矩阵方程等对该签字体制进行理论分析并证明了该体制的安全性。最后得出结论:攻击者得到签字者密钥后成功伪造签字的可能仅为1/q。     

神经网络控制器用于永磁电机的伺服驱动

提出用一种遗传算法（ＧｅｎｅｔｉｃＡｌｇｏｒｉｔｈｍ，简称ＧＡ）训练的多层神经网络结构（ＮＮ），并把它用于交流直线永磁同步电动机（简称ＬＰＭＳＭ）的辩识与控制，使其运行在伺服驱动环境．ＮＮ可随时辩识被控系统的动态待性，而不需要ＬＰＭＳＭ的精确的数学模型．仿真结果令人满意     

一种新的多维稀疏规则模糊插值推理方法

经典的插值理论针对一维稀疏规则库的条件，提出了各种不同的插值方法，取得了很多很好的经验．但对多维稀疏规则条件的近似推理，研究很少，仅有的几种插值方法，存在着难以保证推理结果的凸性和正规性等问题．为了在多维稀疏规则条件下能得到好的插值推理结果。提出了一种基于几何相似的插值推理方法．该方法能较好地保证推理结果隶属函数的凸性和正规性，为智能系统中的模糊推理提供了一个十分有用的工具．     

安装卸载程序技术要点简述

简要论述构造安装卸载程序的技术难点及其解决办法,并给出可行的软件实现方法.     

An effective hybrid genetic algorithm for flow shop scheduling with limited buffers

As a typical manufacturing and scheduling problem with strong industrial background, flow shop scheduling with limited buffers has gained wide attention both in academic and engineering fields. With the objective to minimize the total completion time (or makespan), such an issue is very hard to solve effectively due to the NP-hardness and the constraint on the intermediate buffer. In this paper, an effective hybrid genetic algorithm (HGA) is proposed for permutation flow shop scheduling with limited buffers. In the HGA, not only multiple genetic operators based on evolutionary mechanism are used simultaneously in hybrid sense, but also a neighborhood structure based on graph model is employed to enhance the local search, so that the exploration and exploitation abilities can be well balanced. Moreover, a decision probability is used to control the utilization of genetic mutation operation and local search based on problem-specific information so as to prevent the premature convergence and concentrate computing effort on promising neighbor solutions. Simulation results and comparisons based on benchmarks demonstrate the effectiveness of the HGA. Meanwhile, the effects of buffer size and decision probability on optimization performances are discussed.