ⅡB型LBO光参量振荡器

二极管泵浦的Nd:YAG激光器美国加州圣克拉拉的Continuum公司推出的HPO-300型高功率二极管泵浦Nd:YAG激光器,在1064nm波长输出3mJ.该激光器重复率在1～300Hz可产生接近衍射极限的脉冲。     

与国际综合业务数字网连接的京,沪,穗国际交换机工程

本文介绍了在新建的北京、上海、广州、国际交换机工程中采用新一代程控交换技术接通国际综合业务数字网，以及本工程采用的中继方式。     

On the capacity of packet reservation multiple access with capturein personal communication systems

A new Markovian model is developed to analyze the packet reservation multiple access (PRMA) protocol over Rician fading channels with lognormal shadowing. The packet dropping probability and the voice user capacity are defined as the performance measures. A new formula is derived to evaluate the dropping probability in the fading environment. The analytical results from our new formula show close agreement with those from computer simulations. The capture effect on the PRMA system performance is also studied. We found that, with capture, the user capacity will be improved and the service quality will degrade gracefully when the number of active users in the system increases. Using the dropping probability as the criterion, we also determine the optimal permission probability in a microcellular environment     

智能电视,电话信息查询系统

本文阐述了在ＷＩＮＤＯＷＳ环境下开发电脑，电视、电话信息查询系统系统的基本思想、硬软件环境和具体实施方法，并介绍了软件流程。     

准连续Ti~(3+):Al_2O_3可调谐激光的研究

本文给出了Ti~(3+):Al_2O_3的准连续可调谐激光的实验结果。采用Nd:YAG内腔倍频532nm的准连续输出作为泵浦源,得到Ti~(3+):Al_2O_3的连续可调谐输出。波长覆盖范围为685nm到821nm。最大输出功率为293mW,斜率效率为20％,在805nm处的窄谱输出功率达240mW,总体转换效举为26％。     

新疆西达里亚油气藏精细描述研究

从构造、沉积、储层及流体4方面对新疆西达里亚T—Ⅱ油藏进行了精细描述研究。在构造研究中结合地震及测井对比成果进行了重新解释，分析了圈闭特征；在三维地质模型研究中，首先进行沉积微相研究，利用测井解释成果，采用先建砂岩格架后建属性模型的方法，应用地质统计学方法确立了精细的储层参数三维模型，实现油藏三维可视化。     

隔壁精馏塔分离芳烃混合物的模拟研究

采用隔壁精馏塔分离苯-甲苯-对二甲苯物系,用Aspen Plus软件模拟了隔壁精馏塔内温度分布及液相组成分布,考察了汽相和液相分配比对产品纯度的影响。对隔壁精馏塔模拟得到的优化操作条件为:隔壁精馏塔的理论板数为30块,侧线采出在第14块理论板,进料段为15块理论板,在进料段的第7块理论板进料,进料组成n(苯)∶n(甲苯)∶n(对二甲苯)为1∶3∶1,回流比为8.8,液相分配比为2.96,汽相分配比为0.83。在此条件下,各组分的摩尔分数大于98.5%,与实验结果基本吻合。当进料组成n(苯)∶n(甲苯)∶n(对二甲苯)为1∶3∶1时,采用隔壁精馏塔可比常规两塔流程节能27.18%。     

A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system.

This paper presents a new method for learning Bayesian networks from functional dependencies (FD) and third normal form (3NF) tables in relational databases. The method sets up a linkage between the theory of relational databases and probabilistic reasoning models, which is interesting and useful especially when data are incomplete and inaccurate. The effectiveness and practicability of the proposed method is demonstrated by its implementation in a mobile commerce system.