ALICE实验中光子谱仪的触发选判机制的模拟研究

对ALICE实验光子谱仪的触发选判机制进行了模拟研究, 内容包括: 1) 对光子谱仪的能量重建性能进行了研究, 通过计算机模拟检验光子谱仪探测器对大横动量范围的入射粒子的能量重建性能; 2) 对光子谱仪探测器的事件触发效率进行了研究, 通过计算机模拟分析触发阈值的选取并计算触发效率; 3) 对光子谱仪探测器的事件触发频率进行了研究, 通过计算机模拟对p-p和Pb-Pb两种碰撞模式下的触发频率分别进行了估算和讨论.     

基于联合变换相关器的Dempster-Shafer理论计算

提出了用联合变换相关器(JTC)来实现证据理论概率分配函数正交和的光学计算,在理论上对于如何用联合变像相关器实现证据理论分配函数正交和作了详细的讨论,并作了相应的仿真测试,结果显示该方法是可行的。与John Caulfield提出的用声光器件矢量外积实现的正交和计算相比,在该结构中由于采用二进制编码的数值计算,因此其计算精度得到了提高,同时对联合变换相关器输入端二进制编码的数值空间位置的适当调整可以直接得到所需要的证据理论正交和矢量,在处理步骤上得到了简化。     

光码分多址系统中光学相关接收机判决阈值的分析

介绍了光码分多址系统中常用地址码（一维扩时码、二维码和三维码）的特点，并对它们各自的互相关均值和方差进行了理论分析。基于非相干光码分多址系统中光学相关接收机的基本原理，结合不同的用户地址码，对系统误码率性能进行了分析，得到了接收机最佳判决阈值与地址码基本特性参数和系统同时用户数间的关系。最后，给出了数值仿真结果。结果表明，对于采用特定地址码的光码分多址系统，只有选择合适的接收机判决阈值，系统的误码率性能才能达到最佳。研究结果对光码分多址系统中接收机判决阈值的选取具有一定的参考作用。     

基于状态指标的更新决策方法研究

针对设备在实际运行和执行任务时经常涉及到维修、更新报废等管理活动缺乏定量模型支撑的问题,提出了利用典型部件的预测寿命和非典型部件的历史寿命对设备系统级的健康状态进行综合评估的方法,建立了一种以状态指标为决策序列的动态规划更新决策方法。该方法能综合考虑维修费用和更新费用,确定最优更新决策,降低保障费用,有效的提高了设备的经济效益。最后经过案例分析证明了该方法的有效性,对于提高设备的保障能力和经济效益提供了理论支撑和方法指导。     

一种识别病毒和蠕虫的算法

对现有的恶意软件检测算法进行研究之后发现,某些检测算法只能检测一种恶意软件,并且部分传统的检测算法在检测恶意程序时漏检率偏高。针对目前现有的检测算法缺乏综合性检测能力的短板,在此文中提出了一种新的检测算法,该检测算法具有一定的综合检测能力。新算法的思路如下：第一步区分某种软件是恶意软件还是非恶意软件,如果是恶意软件则提取其特征码,然后使用决策树根据恶意软件的特征码对恶意软件进行识别和分类,如果存在特征码不能识别的恶意软件,那么再根据病毒和蠕虫的特征使用相似性计算算法对未知的恶意软件进行相似性计算,最后使用决策系统对相似性算法计算的结果进行决策,该恶意软件是病毒还是蠕虫。将相似性计算算法,决策树和决策系统在检测恶意软件算法中进行应用是本文的创新之处。     

加热炉热过程动态操作数学模型

根据加热炉生产特点,建立了钢坯加热过程的动态操作数学模型,分析了待轧时间变化时炉内钢坯温度分布情况。并针对加热炉待轧的灰色性,采用多目标灰色局势决策方法,得出了相应合理的待轧优化控制策略。模拟结果表明:该方法具有良好的动态性能,适合于在线控制。     

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.     

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.     

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.