基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

Two-agent two-machine flowshop scheduling with learning effects to minimize the total completion time

We study a two-agent scheduling problem in a two-machine permutation flowshop with learning effects. The objective is to minimize the total completion time of the jobs from one agent, given that the maximum tardiness of the jobs from the other agent cannot exceed a bound. We provide a branch-and-bound algorithm for the problem. In addition, we present several genetic algorithms to obtain near-optimal solutions. Computational results indicate that the algorithms perform well in either solving the problem or efficiently generating near-optimal solutions.     

Enhancement of optical and electrical properties of SILAR deposited ZnO thin films through fluorine doping and vacuum annealing for photovoltaic applications

Undoped and fluorine doped ZnO thin films were deposited onto glass substrates using successive ionic layer adsorption and reaction (SILAR) technique and then annealed at 350 °C in vacuum ambience. The F doping level was varied from 0 to 15 at% in steps of 5 at%. The XRD analysis showed that all the films are polycrystalline with hexagonal wurtzite structure and preferentially oriented along the (002) plane. Crystallite sizes were found to increase when 5 at% of F is doped and then decreased with further doping. It was seen from the SEM images that the doping causes remarkable changes in the surface morphology and the annealing treatment results in well-defined grains with an improvement in the grain size irrespective of doping level. All the films exhibit good transparency (>70%) after vacuum annealing. Electrical resistivity of the film was found to be minimum (1.32×10⁻³ Ω cm) when the fluorine doping level was 5 at%.     

基于Q-learning的不确定环境BDI Agent最优策略规划研究

BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。     

The benefit of being physically present: A survey of experimental works comparing copresent robots,telepresent robots and virtual agents

The effects of physical embodiment and physical presence were explored through a survey of 33 experimental works comparing how people interacted with physical robots and virtual agents. A qualitative assessment of the direction of quantitative effects demonstrated that robots were more persuasive and perceived more positively when physically present in a user׳s environment than when digitally-displayed on a screen either as a video feed of the same robot or as a virtual character analog; robots also led to better user performance when they were collocated as opposed to shown via video on a screen. However, participants did not respond differently to physical robots and virtual agents when both were displayed digitally on a screen – suggesting that physical presence, rather than physical embodiment, characterizes people׳s responses to social robots. Implications for understanding psychological response to physical and virtual agents and for methodological design are discussed.     

移动通信系统中功率控制研究

在阐述功率控制在移动通信系统中的发展过程的基础上，着重研究了WCDMA系统的功率控制，最后对功率控制未来的研究方向做了简要的分析。     

天然气水合物和天然气脱水新工艺探讨

探讨了天然气水合物的发展过程、形成条件以及对天然气输送管道的腐蚀堵塞作用,对我国天然气脱水创新技术———膜法脱水、汽提脱水的原理与工艺过程进行了全面论述。考察了气体处理量及操作压力等对我国1.2×105m3/d天然气膜法脱水的工业试验装置的脱水过程的影响。     

Fenton试剂降低采油污水CODCr的研究与应用

针对辽河油区超稠油采油污水的特点，采用Fenton试剂催化氧化，对采油污水处理进行研究。实验研究及现场应用结果表明，此方法对污水的CODCr具有良好的去除效果。处理后污水经过简单生化，进一步降解污染物，能够实现稳定迭标排放，且具有能耗低、运行成本低和操作简单等特点。     

高导电性原油电脱盐工艺研究

南阳原油中金属含量较高,掺有部分3次采油采出原油,加工时易造成电脱盐装置原油乳化,电导率高,脱盐难度较大。装置投产十几年来脱后含盐一直不合格,经过改造仍然超标,常压塔顶腐蚀严重。为此,对原油进行了电脱盐工艺条件及破乳剂研究,研制出了高效电脱盐设备和生物复合脱盐剂及降电流剂,采用平流弓形电极进行改造,解决了该原油的电脱盐问题,使脱后含盐达到3 mg/L。