柴油加氢工艺动态仿真研究与应用

柴油加氢工艺是通过加氢反应来提高油品质量,对于环境保护和大气污染防治起着至关重要的作用.由于柴油的组成纷繁复杂,使得柴油组分难以确定,一直以来是加氢工艺动态仿真模拟中的难点问题.为解决上述问题,采用真实组分法确定了柴油组成,建立了组分分率模型,进而实现了柴油加氢工艺的全流程动态仿真.仿真结果与实际相吻合,证明了该方法用于柴油加氢工艺的动态仿真是行之有效的.     

基于ZYNQ飞艇囊体应变在线监测系统设计

针对当前高空飞艇囊体的应变实时测量装置无法同时具备体积小和实时测量的工作属性,创新性地用光学器件和感光元件配合,对工作中飞艇囊体两个固定点的相对位移量进行测量,提出了一种能够在线监测飞艇囊体应变的测量装置,能够实现应变在线测量且测量精度高;采用TCD1500C电荷耦合器件作为数据来源;主芯片采用ZYNQ处理器,ZYNQ能够具备FPGA的并行处理能力和Cortex的数据调度能力,能够处理CCD高速数据;通过自定义IP核,使用PS端与PL端互联AXI协议,实现了高速、大量数据传输;为了得到应变信号,采用了将应变信号转化为位移信号进行采集的方法,之后将位移信号采集存储至SD卡中并周期性显示到上位机上,实现地面对飞艇囊体应变的实时监控;实现了飞艇囊体应变的实时测量并把测量精度提高至0.1％.     

房地产与粮食价格对通货膨胀的影响——基于VAR模型的实证研究

为了分析研究我国房地产价格和粮食价格对通货膨胀的影响,选取2000年第1季度至2010年第4季度数据,基于VAR模型进行了实证检验。结果表明,房地产价格、粮食价格和通货膨胀之间具有长期稳定的协整关系,且房地产价格和粮食价格的上涨对通货膨胀的发生均具有推动作用。但是,相比较而言,房地产价格的上涨对通货膨胀的贡献更大;粮食价格的上涨对通货膨胀的影响持续时间更长。     

地下水监测系统电源值更电路的设计与实现

针对地下水监测系统野外工作无人值守、更换电池困难、采样时间短、待机周期长的特点,采用值更电路控制系统在不同功耗状态自动切换的方法延长电源使用寿命。考虑到系统参数配置命令复杂、野外采样情况多样、通信时序不稳定的特性,提出了硬件多触发源与软件状态字配合工作的措施实现系统逻辑控制。引入值更电路的地下水监测系统整体功耗大幅度降低。实测结果验证了值更电路的可行性-表明值更方式必将成为野外监测行业的发展方向。     

Which algorithm should I choose: An evolutionary algorithm portfolio approach

Many good evolutionary algorithms have been proposed in the past. However, frequently, the question arises that given a problem, one is at a loss of which algorithm to choose. In this paper, we propose a novel algorithm portfolio approach to address the above problem for single objective optimization. A portfolio of evolutionary algorithms is first formed. Covariance Matrix Adaptation Evolution Strategy (CMA-ES), History driven Evolutionary Algorithm (HdEA), Particle Swarm Optimization (PSO2011) and Self adaptive Differential Evolution (SaDE) are chosen as component algorithms. Each algorithm runs independently with no information exchange. At any point in time, the algorithm with the best predicted performance is run for one generation, after which the performance is predicted again. The best algorithm runs for the next generation, and the process goes on. In this way, algorithms switch automatically as a function of the computational budget. This novel algorithm is named Multiple Evolutionary Algorithm (MultiEA). The predictor we introduced has the nice property of being parameter-less, and algorithms switch automatically as a function of budget. The following contributions are made: (1) experimental results on 24 benchmark functions show that MultiEA outperforms (i) Multialgorithm Genetically Adaptive Method for Single Objective Optimization (AMALGAM-SO); (ii) Population-based Algorithm Portfolio (PAP); (iii) a multiple algorithm approach which chooses an algorithm randomly (RandEA); and (iv) a multiple algorithm approach which divides the computational budget evenly and execute all algorithms in parallel (ExhEA). This shows that it outperforms existing portfolio approaches and the predictor is functioning well. (2) Moreover, a neck to neck comparison of MultiEA with CMA-ES, HdEA, PSO2011, and SaDE is also made. Experimental results show that the performance of MultiEA is very competitive. In particular, MultiEA, being a portfolio algorithm, is sometimes even better than all its individual algorithms, and has more robust performance. (3) Furthermore, a positive synergic effect is discovered, namely, MultiEA can sometimes perform better than the sum of its individual EAs. This gives interesting insights into why an algorithm portfolio is a good approach. (4) It is found that MultiEA scales as well as the best algorithm in the portfolio. This suggests that MultiEA scales up nicely, which is a desirable algorithmic feature. (5) Finally, the performance of MultiEA is investigated on a real world problem. It is found that MultiEA can select the most suitable algorithm for the problem and is much better than choosing algorithms randomly.     

基于图像处理的锆管端面缺陷检测

对核用锆管端面缺陷进行检测是保证锆管尺寸具有高度的一致性和稳定性的重要手段之一,该文采用计算机图像处理技术对锆管端面的缺陷进行自动检测,在VC6.0的开发平台,运用mil库函数,对锆管端面的宽度,内外倒角进行了快速、实时检测,并通过实例验证了检测系统的可行性。     

Biofidelic child head FE model to simulate real world trauma

Biomechanics of human head has been widely studied since several decades. At a mechanical level, the use of engineering allowed investigating injury mechanisms developing numerical models of adult head. For children, the problem is more difficult and evaluating child injury mechanisms using data obtained from scaling adult injury criteria does not account for differences in morphology and structure between adults and children. During growth, child head undergoes different modifications in morphology and structure. The present paper compares the anthropometry and numerical simulations of a child head model based on medical CT scans to a child head model developed by scaling an adult head model using the method proposed by Mertz [H.J. Mertz, A procedure for normalizing impact response data, SAE paper 840884, 1984]. These analysis point out significant differences showing that scaling down an adult head to obtain a child head does not appear relevant. Biofidelic and specific child geometry is needed to investigate child injury mechanisms.     

Truth-Telling Reservations

We present a mechanism for reservations of bursty resources that is both truthful and robust. It consists of option contracts whose pricing structure induces users to reveal the true likelihoods that they will purchase a given resource. Users are also allowed to adjust their options as their likelihood changes. This scheme helps users save cost and the providers to plan ahead so as to reduce the risk of under-utilization and overbooking. The mechanism extracts revenue similar to that of a monopoly provider practicing temporal pricing discrimination with a user population whose preference distribution is known in advance.     

Valuing pilot projects in a learning by investing framework: An approximate dynamic programming approach

We introduce a general discrete time dynamic framework to value pilot project investments that reduce idiosyncratic uncertainty with respect to the final cost of a project. The model generalizes different settings introduced previously in the literature by incorporating both market and technical uncertainty and differentiating between the commercial phase and the pilot phase of a project. In our model, the pilot phase requires N$N$ stages of investment for completion. With this distinction we are able to frame the problem as a compound perpetual Bermudan option. We work in an incomplete markets setting where market uncertainty is spanned by tradable assets and technical uncertainty is idiosyncratic to the firm. The value of the option to invest as well as the optimal exercise policy are solved by an approximate dynamic programming algorithm that relies on the independence of the state variables increments. We prove the convergence of our algorithm and derive a theoretical bound on how the errors compound as the number of stages of the pilot phase is increased. We implement the algorithm for a simplified version of the model where revenues are fixed, providing an economic interpretation of the effects of the main parameters driving the model. In particular, we explore how the value of the investment opportunity and the optimal investment threshold are affected by changes in market volatility, technical volatility, the learning coefficient, the drift rate of costs and the time to completion of a pilot stage.     

使用静态小波变换增强与降噪真彩图像

由于几乎所有真彩图像都不同程度含有噪声,并且含有阴影和明亮光源的图像的动态范围超过了多数电子设备和人眼的感受区域,这就要求真彩图像被增强的同时还能够对噪声进行抑制.因此,在分析了噪声在HSV色彩空间分布的基础上,根据静态小波变换解释的入射-反射模型,提出了一种能够同时增强与降噪真彩图像的方法.实验表明,本方法在明显增强真彩图像的同时,还可以有效抑制图像中的噪声.