宽温变环境的空间反射镜结构分析与研究

相机在从地面到太空的过程中,需要经历重力、温度、气压、辐射等多种环境因素的变化,而这些因素都可能导致空间相机分辨率下降、像质变坏、功能失效甚至系统破坏。所描述的系统工作于18±15℃的温度环境,要求光学反射镜在30℃温度变化范围内仍能正常成像。经优化设计,应用计算机仿真手段进行了静、动态及热特性的分析,提出了一种采用中心粘接结合Bipod柔性支撑形式,解决了在大跨度环境温度范围下的反射镜结构支撑问题。     

基于综合监控的设备状态修方案研究

随着工业控制领域的不断发展,综合监控系统已经日趋成熟并于工业现场运行较长时间。而基于综合监控系统获取的大量历史数据的分析和实时数据的使用并没有开展深入的探讨。本方案提出了一种基于综合监控系统的状态修方案,把综合监控系统的历史数据经过一定的清洗,建模导入到大数据平台,通过相应的算法分析,从而改善维修决策模型并建立设备评价体系;把实时数据实时的传递到设备状态页面,减轻了传统巡检工作,保证了设备检查效果;把设备报警数据通过分类,分项,直接派生检修工单,实现了设备维修的自动化。     

Traffic-Aware Green Cognitive Radio

Cognitive Radio Network (CRN) has emerged as an effective solution to the spectrum under-utilization problem, by providing secondary users (SUs) an opportunistic access to the unoccupied frequency bands of primary users (PUs). Most of the current research on CRN are based on the assumption that the SU always has a large amount of data to transmit. This leads to the objective of SU throughput maximization with a constraint on the allowable interference to the PU. However, in many of the practical scenarios, the data arrival process of the SU closely follows an ON–OFF traffic model, and thus the usual throughput optimization framework may no longer be suitable. In this paper, we propose an intelligent data scheduling strategy which minimizes the average transmission power of the SU while maintaining the transmission delay to be sufficiently small. The data scheduling problem has been formulated as a finite horizon Markov Decision Process (MDP) with an appropriate cost function. Dynamic programming approach has been adopted to arrive at an optimal solution. Our findings show that the average transmitted power for our proposed approach can be as small as 36.5% of the power required for usual throughput maximization technique with insignificant increase in average delay.     

基于选择性支持向量机集成的混沌时间序列预测

提出了一种基于聚类的选择性支持向量机集成预测模型.为提高支持向量机集成的泛化能力，采用自组织映射和K均值聚类算法结合的聚类组合算法，从每簇中选择出精度最高的子支持向量机进行集成，可以保证子支持向量机有较高精度并提高了子支持向量机之间的差异度.该方法能以较小的代价显著提高支持向量机集成的泛化能力.采用该方法对Mackey-Glass混沌时间序列和Lorenz系统生成的混沌时间序列进行预测实验，结果表明可以对混沌时间序列进行准确预测，验证了该方法的有效性. 关键词： 支持向量机 集成 混沌时间序列 聚类     

Fabrication of BDD quantum node switches on embedded GaAs quantum wires grown by selective MBE

In view of applications to hexagonal binary decision diagram (BDD) LSIs, a first attempt is made to form quantum BDD node switches on selectively grown (SG) embedded quantum wires (QWRs) by molecular beam epitaxy (MBE). SG branch switches controlled by a Schottky wrap gate (WPG) were successfully fabricated by MBE growth and subsequent device processing. Gate control characteristics were studied by gate-dependent Shubnikov–de-Haas measurements, and the behavior was found to be similar to that of devices fabricated on wires by etching. The switch exhibited clear conductance quantization at low temperature, and temperature dependence of the voltage slope of conductance jump was clarified. A Y-branch BDD node device using two SG branch switches was successfully fabricated, and realized clear path switching characteristics.     

基于SVM的固化土无侧限抗压强度模型

为实现较少试验次数下固化土无侧限抗压强度(qu)的准确预测, 提出了基于支持向量机(SVM)的固化土qu的预测模型. 以固化剂各组分掺入比、龄期、初始含水量、固化剂掺量等因素为输入量, 固化土的qu作为输出量, 以径向基为核函数, 采用网格搜索法和交叉验证法进行参数优化, 建立了基于SVM的固化土qu的预测模型. 算例分析表明: 该模型适用于任意条件下固化土qu的精确预测, 且在较小试验成本下实现与响应面法相当的预测精度.     

镁铝复合氧化物负载铜催化剂上甘油选择性氢解合成丙二醇

我们通过乙醇溶液浸渍法合成出了具有高分散度金属Cu 的Cu/MgO-Al₂O₃ (Mg/Al 原子比=1/1, 3/1, 4/1)、Cu/MgO 和Cu/Al₂O₃ 等催化剂. 在200℃, 6.0 MPa H₂ 和二氧六环溶剂中, 这些催化剂高选择性地将甘油氢解为1,2-丙二醇(选择性>90%), 而单位表面Cu 原子的甘油转化速率则随催化剂表面碱中心与Cu 原子比例的提高而增大. N₂O 化学吸附-H₂ 程序升温还原实验表明Cu 粒子的本征氢解能力不随其负载量以及载体中的Mg/Al 原子比发生明显改变, 加之碱性MgO-Al₂O₃ 载体本身不催化甘油的转化, 我们推测在甘油氢解反应中金属Cu 粒子与载体界面处的碱中心辅助Cu 粒子活化甘油分子的α 位C-H键, 从而加速甘油脱氢为甘油醛步骤以及甘油氢解反应的进行. CO₂程序升温脱附实验以及对甘油氢解反应中Cu/MgO-Al₂O₃ 催化剂稳定性的考察结果暗示在甘油氢解反应中起主要作用的碱中心是载体表面上与Mg²⁺键连的羟基基团(即B 碱OH^-). 这些对甘油氢解反应中金属中心与碱性中心协同作用的认识对进一步理性设计高效的甘油或其它多元醇分子氢解催化剂具有重要指导意义.     

Modelling decision making and learning by low latitude hunter gatherers

Recent anthropological studies have demonstrated that low latitude ‘encounter’ foragers exploit their environments in energetically very efficient manners and closely track the environment as it changes. The paper begins to investigate how they manage to do this by proposing a simple decision making and learning rule developed from an evolutionary ecological basis. Having described the mathematical model the paper refers to simulation studies exploring this model which suggest that some of the seemingly complex aspects of hunter gatherer behaviour may result from the use of simple decision making and learning processes.     

需求弹性在价格决策中的应用

将着眼点由总收益改变为总利润,对于需求弹性用于价格决策,利用微积分方法,分5种情况进行推导,得到的结论修正和补充了现行"经济数学"、"市场营销学"和"管理经济学"等教科书里讲的内容,并在此基础上进一步研究了最佳调价量问题.     

An overview on available models and techniques for the multicriteria reliability problem with emphasis on a potential use in a DSS for this problem type

The paper reviews available models and techniques covering three classes of the multi-criteria reliability problem. These classes include allocation of reliabilities in presence of multiple goals, reliability optimization with several kinds of failures and allocation of resources to optimize multiattribute systems. Optimization techniques are also suggested. The models and techniques are also evaluated with respect to their potential use in a DSS for reliability optimization.