新编民谣

到了天津才知道自己笑话讲不好到了上海才知道自己穿的过时了到了湖南才知道自己辣的吃不了到了四川才知道自己麻的受不了到了山西才知道自己喝醋滋味了到了山东才知道自己爽快有多好到了新疆才知道石油真是不愁了到了内蒙才知道大革原有多么好到了西藏才知道空气真是缺不了     

运用多媒体技术,提高小学语文课堂教学效率

科学技术的日新月异发展,推进了素质教育的进程,多媒体技术已经走进了课堂,为教师教学开辟了广阔空间。多媒体技术激发了学生浓厚的学习兴趣,化解了教学难点,创设了丰富的教学情境,有效地进行了德育渗透,突出了学生主体地位,提高了课堂教学效率。本文试就小学语文教学运用多媒体技术问题进行了探讨。     

简论多媒体技术在小学语文教学中的应用

科学技术的日新月异发展,多媒体技术已经进入了课堂,优化了课堂教学,提高了教学效率,突出了学生主体地位,激发了学生学习欲望,调动了学生学习的积极性、主动性、创造性,扩大了知识容量,促进了学生想象思维的发展,实现了课堂教学过程的最优化。本文试就多媒体技术在小学语文教学中的应用进行了探讨。     

蠕动的钱程系列报道之二——内忧外患

普遍服务赔本了,报刊自办发行了,商业信函空间缩小了土速递自动发展了,WTO进来了,中国邮政不转型不行了     

多媒体技术在小学数学教学中的作用

科学技术的日新月异发展,推动了素质教育的进程,多媒体技术已经走进了课堂,本文阐述了小学数学教学应用多媒体技术,激发了学生浓厚的学习兴趣,化解了教学重点难点,营造了良好的氛围,优化了课堂教学,提高了课堂教学效率。     

时代抛弃落伍者

整个社会仿佛是在一夜之间发生了翻天覆地的变化。我们刚刚经历了主机、个人计算机时代,又一下子迈入今天的云计算、物联网时代。我们有了互联网、有了苹果、有了Android、有了Facebook、有了微博、有了搜索引擎、     

PC变了——微软领跑Media Center

PC变了，变得平易近人了，变得讨大家欢心了，变得没有以前那么刻板了，就连父亲也喜欢上了它，开始用它看大片了。媒体中心电脑的成熟打破了PC传统的操作理念，使它变成了家庭娱乐中心，成为全家人的新宠。     

展望未来的通信 寻找明日的商机——2003年中国国际通信(设备)技术展览会火线报道

我们看到了3G,看到了PHS,看到了IPv6,看到了DSL,看到了各式各样的新鲜装备。此外,我们还看到了设备商献媚运营商,看到了运营商取悦消费者,看到了消费者痴迷新装备……2003年中国乃至亚洲最大规模的通信展会在向我们传递着来自明日通信的全新理念。     

《软件工程》教学改革的探讨与实践

分析了软件工程课程的教学特点,结合遵义师范学院学生学习现状,整合了教学内容、组建了多种教学方式、进行了教学评价改革与实践,提高了学生学习主动性和积极性,培养了学生分析问题、解决问题的能力,提高了教学质量。     

IT融资：冬去春来，谁当领跑

地震震动了人心,奥运鼓舞了人心,金融海啸席卷了人心。 失业了,郁闷;降息了,还银行贷款少了,高兴。人们在悲喜交织中动荡着。     

成品油调和建模及优化方法研究

炼油企业生产调度的优化因能提高资源利用效率、增加生产收率、满足需求和最大化利润而成为近年来的研究热点。本文以生产调度中的油品调和为例,分析和描述了调度过程建模所需的模型元素及其数学表达,其中涉及炼油企业典型的物料平衡及物性计算方法。针对生产操作规则对汽油和柴油的调和分别进行建模,求得在经济效益最大时各调和组分的质量以及主要性能指标,由此提出了一种针对成品油调和的优化方法。     

N320润滑油污染度传感器标准油样配置与实验标定的研究 庞政铎 孟国营 于功江 牛雪峰 汪爱民

为了研制油污染传感器，首先要配置不同污染度的油液，并用颗粒计数器对所配置的油液进行实验标定，本文以矿山机械减速器常用的N320润滑油为对象，首先讨论了新油的过滤以及注意事项；其次按照NAS1638污染度等级标准配置了不同污染度等级的油样，本文总共配置了污染度等级从10级到22级共13油样，叙述了配制油液的方法和具体步骤，最后对所配置的油液进行了试验标定，详细介绍了标定前的准备工作、标定的方法和标定的步骤，最后通过实验数据，进一步确定了我们所配油液的污染度，从而为下一步标定传感器做了前期准备工作。     

船舶动力与传动装置润滑油状态监测

针对目前舰船动力系统故障定位难、预判不准确的现状,提出了一种应用于船舶动力与传动装置的油液在线监测技术。通过分析舰船动力系统的故障源,阐述了船舶动力与传动装置滑油状态监测的内容,包含油液黏度检测、油液水分检测与油液金属磨粒检测。结合黏度、水分与磨粒检测原理,设计了滑油状态监测试验。通过实船试验,验证了油液在线监测技术在船舶动力与传动装置状态监测中应用的可行性和有效性。     

Daily prediction of short-term trends of crude oil prices using neural networks exploiting multimarket dynamics

This paper documents a systematic investigation on the predictability of short-term trends of crude oil prices on a daily basis. In stark contrast with longer-term predictions of crude oil prices, short-term prediction with time horizons of 1–3 days posits an important problem that is quite different from what has been studied in the literature. The problem of such short-term predicability is tackled through two aspects. The first is to examine the existence of linear or nonlinear dynamic processes in crude oil prices. This sub-problem is addressed with statistical analysis involving the Brock-Dechert-Scheinkman test for nonlinearity. The second aspect is to test the capability of artificial neural networks (ANN) for modeling the implicit nonlinearity for prediction. Four experimental models are designed and tested with historical data: (1) using only the lagged returns of filtered crude oil prices as input to predict the returns of the next days; this is used as the benchmark, (2) using only the information set of filtered crude oil futures price as input, (3) combining the inputs from the benchmark and second models, and (4) combing the inputs from the benchmark model and the intermarket information. In order to filter out the noise in the original price data, the moving averages of prices are used for all the experiments. The results provided sufficient evidence to the predictability of crude oil prices using ANN with an out-of-sample hit rate of 80%, 70%, and 61% for each of the next three days’ trends.     

Daily prediction of short-term trends or crude oil prices using neural networks exploiting multimarket dynamics

This paper documents a systematic investigation on the predictability of short-term trends of crude oil prices on a daily basis. In stark contrast with longer-term predictions of crude oil prices, short-term prediction with time horizons of 1-3 days posits an important problem that is quite different from what has been studied in the literature. The problem of such short-term predicability is tackled through two aspects. The first is to examine the existence of linear or nonlinear dynamic processes in crude oil prices. This sub-problem is addressed with statistical analysis involving the Brock-Dechert-Scheinkman test for nonlinearity. The second aspect is to test the capability of artificial neural networks (ANN) for modeling the implicit nonlinearity for prediction. Four experimental models are designed and tested with historical data: (1) using only the lagged returns of filtered crude oil prices as input to predict the returns of the next days; this is used as the benchmark, (2) using only the information set of filtered crude oil futures price as input, (3) combining the inputs from the benchmark and second models, and (4) combing the inputs from the benchmark model and the intermarket information. In order to filter out the noise in the original price data, the moving averages of prices are used for all the experiments. The results provided sufficient evidence to the predictability of crude oil prices using ANN with an out-of-sample hit rate of 80%, 70%, and 61% for each of the next three days’ trends.     

基于有限元技术滑油屑末监测器检测机理研究

针对目前滑油系统中磨粒特征计算精度不高的问题,提出了一种新型基于COMSOL和ANSYS Maxwell联合仿真的计算方法,并以外电路补偿方式修正模型提高计算精度,能有效分析传感器对不同磨粒种类、大小和位置等特征的响应.研究结果表明:该方法能够计算磨粒通过传感器时,感应电压的大小;由于检测机理不同,当分别检测铁磁性和非...     

计算机本体理论在石油勘探开发知识管理系统中的应用研究

本体论与各个领域计算机技术的发展结合产生了所谓的“领域本体”的构建及应用研究, 首先介绍了计算机本体理论的基本概念, 接着给出石油勘探开发知识管理系统的框架设计, 然后提出基于多层次业务流程的石油勘探和开发领域知识本体库的构建方法, 把石油勘探开发领域所涉及方面分为多级业务活动层次, 并以采油工程方案为例列出了对应的知识本体库构建方法的探讨.     

球罐热处理计算机监控系统

针对目前球罐整体热处理自动化程度不高的现状,采用安全性强、成本较低的内部燃烧工艺,应用德国欧科燃烧器、S7-200可编程序控制器、隔离变速模块、研华ADAM模块及研华工控机构成系统硬件体系,由组态王程序、Visual Basic程序及PLC程序构成系统软件体系,研发了一套球罐整体热处理计算机控制系统。该系统控制精度高、实用功能强、可靠性好,在国内外的多项热处理工程中,收到了很好的使用效果。     

汽轮机速关油内漏故障分析与处理

对某厂重催装置汽压机组汽轮机控制油系统进行了阐述,分析速关油内漏故障引发原因,最后给出详细的故障排查和处理方法。     

A Brazilian experience: 40 years using operations research at Petrobras

Petrobras was created as an integrated company to operate in oil and oil byproduct exploration, production, refining, marketing, and transportation. Petrobras is now the biggest Brazilian company, operating in a number of areas in the energy sector and currently present in 27 countries. This article describes the evolution of the activities and the achievements of its Operations Research group, created in the 1960s, and its work offering decision support to the most diverse segments of the company.