Adapting Memory Hierarchies for Emerging Datacenter Interconnects

E?cient resource utilization requires that emerging datacenter interconnects support both high performance communication and e?cient remote resource sharing. These goals require that the network be mor...     

高级氧化-IC-曝气工艺处理克林霉素生产废水实例

某药业股份有限公司克林霉素生产废水采用高级氧化-IC-曝气工艺处理,重点介绍了工程的调试启动。工程运行结果表明,出水水质稳定,COD为112mg/L,BOD5为23mg/L,SS为48mg/L,NH3-N为37.1mg/L,TN为49.6mg/L,硫化物为0.72mg/L,急性毒性(以HgCl2毒性当量计)为0.05mg/L,pH为8.22,处理后出水毒性和有机物浓度都大大降低,各项水质指标符合《化学合成类制药工业水污染物排放标准》(GB 21904-2008)的要求。     

FTTH资源管理的研究与实现

随着PON技术的不断完善发展,FTTH逐渐成为运营商的主推宽带用户接入方案。ONT的数据配置比较’繁琐,且由于PON接入网络的无源性特点,给分光器的管理带来了一定困难。通过ONT的营业系统预配置,预先定义用户归属关系,可以解决ONT的配置问题和分光器的资源管理问题。     

关于无线传感器网络MAC层协议的研究

当前,无线传感器网络(WSN)是国内外备受关注的一个新兴前沿热点领域,已经吸引了许多研究者和机构的广泛关注.本文简单介绍了无线传感器网络以及MAC协议,对MAC协议进行了分类、分析,比较和总结了这些协议的核心机制、性能和特点,最后得出结论,展望了今后无线传感器网络MAC协议的研究重点及策略.     

基于PRI谱的双门限雷达信号分选算法及其硬件平台设计

针对修正的PRI变换法无法分选重频参差雷达信号的缺点,提出了一种基于PRI谱的双门限雷达信号分选算法.该算法先对PRI谱设定双门限检测各个准PRI,再结合组合查看及序列搜索提取各个PRI.同时,构建了一种预分选、主分选结合的新型分选平台.预分选利用带有PowerPC的FPGA构架片上系统,完成对脉冲雷达信号的实时测量、AOA分类及数据存储;主分选采用DSP专职完成其他维参数的分选算法.谊分选新算法在保留抑制PRI子谐波优点的同时,对重频固定、抖动和参差的雷达脉冲信号都有较好的检测结果.视频信号源的大量测试表明,谊分选平台对普通雷达、PRI抖动和参差雷达、频率捷变雷达及一些特殊雷达均具有较好的分选能力.     

基于词汇语义特征的中文语义角色标注研究

语义角色除了受句法结构限制之外,同词汇的语义特征也有着紧密的内在联系。对于一些仅依靠句法分析不能很好解决的角色标注问题,如句法结构相同的两个成分所对应的角色分别为完全不同的施事、受事角色的情况,可以通过引入一些词汇语义特征来进行处理。该文基于北京大学的语义词典CSD,引入了配价数、主客体语义类等词汇语义特征来进行语义角色标注研究。10折交叉验证的结果显示,通过引用词汇语义特征,所有角色标注的总体评价F值比单纯使用句法特征上升了1.11%,而其中Arg0和Arg1角色标注的F值达到93.85%和90.60%,比仅使用句法特征进行角色标注分别提高了1.10%和1.26%。     

一种多模冗余结构存储器系统的容错设计研究

某型飞机代码转换器存储器用于存储ARINC419总线数据的地址,针对存储器数据易丢失影响数据传输的故障,提出了采用多模冗余结构的存储器系统容错设计方案;首先研究了三模冗余结构的可靠性,分析了存储器采用冗余结构设计的可行性,在此基础上,给出了多模冗余结构存储器实现方法和逻辑电路,并对其容错性进行了分析;实际工程应用表明,采用多模冗余结构存储器设计提高了国产化代码转换器的可靠性,降低了该设备的故障率。     

转子系统早期碰摩故障特征提取方法研究

航空发动机转子系统是发动机的核心部件,针对发动机转子系统早期碰摩故障难以检测的特点,通过对碰摩机理分析及早期故障特征的研究,提出了基于小波变换对原始信号降噪和虚拟仪器对转子系统振动数据采集相结合的方法,对转子系统早期碰摩故障特征进行提取,并在转子试验台上进行了实验验证。结果表明,采用LabVIEW程序采集转子系统振动数据并存储,然后应用小波变换进行数据分析和处理,能够对转子早期碰摩故障特征进行有效地提取。     

Intelligent Optimal-Setting Control for Grinding Circuits of Mineral Processing Process

During the operation of a grinding circuit (GC) in mineral processing plant the main purpose of control and optimal operation is to control the product quality index, namely the product particle size, into its technically desired ranges. Moreover, the grinding production rate needs to be maximized. However, due to the complex dynamic characteristics between the above two indices and the control loops, such control objectives are difficult to achieve using existing control methods. The complexity is reflected by the existence of process heavy nonlinearities, strong coupling and large time variations. As a result, the lower level loop control with human supervision is still widely used in practice. However, since the setpoints to the involved control loops cannot be accurately adjusted under the variations of the boundary conditions, the manual setpoints control cannot ensure that the actual production indices meet with technical requirements all the time. In this paper, an intelligent optimal-setting control (IOSC) approach is developed for a typical two-stage GC so as to optimize the production indices by auto-adjusting on line the setpoints of the control loops in response to the changes in boundary conditions. This IOSC approach integrates case-based reasoning (CBR) pre-setting controlling, neural network (NN)-based soft-sensor and fuzzy adjusting into one efficient control model. Although each control element is well known, their innovative combination can generate better and more reliable performance. Both industrial experiments and applications show the validity and effectiveness of the proposed IOSC approach and its bright application foreground in industrial processes with similar features.