曾坑水库大坝安全鉴定分析

在长期复杂的自然环境条件和各种荷载作用下,土石坝容易产生安全隐患,尤其是国内早期修建的土石坝,因为设计考虑不周、施工质量差、运行管理不当,大坝安全受到严重影响.该文结合曾坑水库工程实例,从水库的工程质量、防洪标准、渗流安全及结构安全等主要方面,对该水库工程的安全性进行全面复核和评价,对大坝结构、渗流稳定等做了详细的分析...     

调亏灌溉条件下甘蔗耗水规律试验研究

通过大棚内的甘蔗盆栽试验,研究了不同生育期调亏灌溉条件下甘蔗的耗水规律。结果表明:甘蔗的耗水强度因土壤含水量的不同而不同,各生育期内,土壤含水量大的甘蔗耗水强度就大;甘蔗各生育期的阶段耗水量因生育期的长短而不同,萌芽期的甘蔗耗水量最小,伸长期的耗水量最大。在不考虑降雨因素影响的条件下,研究了甘蔗生长的耗水规律参数。     

从设计软件中获取明细表信息技术研究

机械机电行业中大量使用设计软件制作的工程图纸,如何从这些图纸中有效和快速的获取其中的明细表信息是一个关键环节.本文针对目前明细表信息提取过程繁琐、效率不高的问题,通过对明细表信息提取方法的阐述,实现了从设计软件图纸中简洁、快速的读取信息的目标.在此基础上还可以把这些信息集成到一个软件中,以便实现和其他软件系统的集成.     

失事潜艇高压援救快速减压控制仿真研究

研究快速对失事潜艇救生问题,高压援救/饱和减压技术是目前援潜救生领域的研究重点.针对现有失事潜艇通风系统不具备高压环境快速减压控制功能,且通风量无法满足破损状况下艇内实际需求.为改善失事潜艇通风条件,实现快速减压技术建模,开发了基于MPTT的减压模型和基于混杂Petri网(HPN)理论的失事潜艇高压援救过程控制系统.通过对系统的一系列仿真研究,结果证明系统能够稳定地维持失事潜艇艇内生存环境,能够执行快速减压操作保障艇员安全返回水面.     

PowerBuilder中目录树的探讨

在管理信息系统中,经常会用到无限级的树形结构,如学校班级管理、物品分类等等。它看起来很像窗口形状,在此通过一个案例,加深对TreeView理解。     

基于读写任务分发的数据库集群服务器的实现

该文在LVS基础之上将网络中传送的数据包变成SQL语句,通过负载均衡器把任务均衡分发到数据库集群服务器中,从而提高了查询、更新效率和芸现了负载均衡、数据同步;同时通过替换策略和更新策略消除了单负载均衡器的瓶颈问题。     

计算机网络安全分析研究

随着计算机网络技术的发展,信息化的程度越来越高,网络逐步承载着越来越多的关键应用,随之而来的网络安全问题也越来越突出。黑客的攻击和计算机病毒等的侵害,严重地威胁了计算机信息的安全,引起全社会共同关注。如何保护计算机信息的问题显的越来越重要。该文旨在分析计算机网络面临的威胁和存在的安全隐患,并提出防范技术,提高计算机网络安全。     

基于信任模型的安全应用层多播协议

针对ALM(application layer multicast)安全性方面存在的问题,设计了一种新的ALM协议.节点加入多播组时,协议对节点的信任度进行认证检测.在交互过程中动态计算节点信任度,以便准确识别覆盖网中的恶意节点.同时,通过标签机制,有效防止了节点对信任信息的恶意篡改.仿真实验结果表明,该协议能有效区分恶意节点并对其进行控制,对多播安全性方面存在的问题有较大改进.     

DECODE: a new method for discovering clusters of different densities in spatial data

When clusters with different densities and noise lie in a spatial point set, the major obstacle to classifying these data is the determination of the thresholds for classification, which may form a series of bins for allocating each point to different clusters. Much of the previous work has adopted a model-based approach, but is either incapable of estimating the thresholds in an automatic way, or limited to only two point processes, i.e. noise and clusters with the same density. In this paper, we present a new density-based cluster method (DECODE), in which a spatial data set is presumed to consist of different point processes and clusters with different densities belong to different point processes. DECODE is based upon a reversible jump Markov Chain Monte Carlo (MCMC) strategy and divided into three steps. The first step is to map each point in the data to its mth nearest distance, which is referred to as the distance between a point and its mth nearest neighbor. In the second step, classification thresholds are determined via a reversible jump MCMC strategy. In the third step, clusters are formed by spatially connecting the points whose mth nearest distances fall into a particular bin defined by the thresholds. Four experiments, including two simulated data sets and two seismic data sets, are used to evaluate the algorithm. Results on simulated data show that our approach is capable of discovering the clusters automatically. Results on seismic data suggest that the clustered earthquakes, identified by DECODE, either imply the epicenters of forthcoming strong earthquakes or indicate the areas with the most intensive seismicity, this is consistent with the tectonic states and estimated stress distribution in the associated areas. The comparison between DECODE and other state-of-the-art methods, such as DBSCAN, OPTICS and Wavelet Cluster, illustrates the contribution of our approach: although DECODE can be computationally expensive, it is capable of identifying the number of point processes and simultaneously estimating the classification thresholds with little prior knowledge.     

基于单片机控制的等精度频率计设计制作

用D触发器控制两个计数器count1和count2的同步工作,以保证count1和count2计数时间的一致性;将count1和count2与单片机的定时器T0和T1相结合构成两个20位的高精度计数器,分别对标准频率脉中和被测频率脉中进行计数;利用单片机串行口完成输出显示.从而克服了传统测频原理的频率计的测量精度随被测信号频率的下降而降低的局限性,提高了频率测量的精度.