智能测温仪表的研究与实现

文章介绍了一种以8098单片机为核心、以铂铑一铂为测温元件研制的智能化测温仪表，它与传统的接触式温度传感器相比具有价格低、性能高、应用范围广、人机界面好等特点。     

美国的灭火与救援机器人研发综述

设想某一个城镇生产木材调色板的流水线车间里 ,由于电器原因引发了一场火灾 ,致使建筑物坍塌。没有人能够确切地说出有多少工人被埋压在里面 ,更糟的是 ,当毗邻墙体坍塌时 ,隔壁的旧轮胎储藏室也被埋压在下面。于是市消防局派遣一批机器人去现场救援。第一个到达的机器人进入现场调查情况 ,该机器人能忍耐80 0℃的高温炙烤 ,身上安装了摄像机 ,可以给 90 m外的控制室发送图片 ,控制室的指挥人员就可以根据图片决定是否派消防队员冒险进入现场。第二个机器人是无人驾驶卡车 ,进入后便从 75 m远的地方以2 6 gal/ s的速度往火场喷水 ,并用它所…     

我国车用无铅汽油的质量状况及分析

对1998－2001年间生产领域和流通领域的近500批次汽油产品检验数据进行了总结和分析，表明我国汽油的实物质量正在不断提高，但从环保要求出发还需不断向国际水平靠扰，尤其应进一步降低烯烃含量，硫含量。     

High Temperature Solid Oxide Fuel Cells(SOFC)

The history and the state of the art of solid oxide fuel cells(SOFC)is reviewed in this paper.Itdescribes mainly on the material selection,structure design and technological economics of SOFC.The appli-cation of great amount of rare earth materials in SOFC may well extend the market potential of rare earthmaterials in the world.A research project to be carried out as early as possible in China on the SOFC tech-nology will be far-reaching.     

RADIOACTIVE OR NATURAL TRACER。TECHNIQUES FOR LEAK DETERMINING OF DAM ABUTMENT

Infiltration and localization of preferential infiltration zones at the dam abutment are measured using radioactive tracer tests of flow in boreholes,meanwhile interconnection between boreholes and the energing water points is analysed.The theory and practice of radioactive tracer synthetic detective method are described to give methods and calculation formulae used under the condition of stable flow in single well to measure permeability coefficient and hydrostatic heads.Major single hole techniques including measurement for seepage line,velocity,rate of seepage flow and relationship of recharge of groundwater in aquifers are introduced briefly.The possibilities offered by natureal tracers are analysed,uincluding electric-conduct,pH-value and temperature of water as well as stable isotopes(D,^18O) and tritium.Furthermore,the sensibilities of this theory and methods were confirmed by detecting seepage flow field of Xinanjiang Dam.     

民国时期书刊封面设计的发展

民国时期[1]书刊封面中的汉字设计风格丰富多样,兼具了传达功能与艺术美感,具有鲜明的民族性与时代特征。如杉浦康平先生所说,"为了前进一步,回首过去。"[2]民国时期的书刊封面的设计,在中国书籍发展史及平面设计史上具有重要的历史地位,归纳与梳理这一时期的发展脉络,对于研究封面中的汉字设计有着重要意义。所以本文以时间为线索,归纳从1912年至1949年之间的民国书籍封面。     

三网融合的技术现状和未来发展

三网融合是网络发展的主要方向,无线网络是接入有线网络的一个重要途径。本文主要概述了因特网、电信网络、有线电视网络和无线网络的技术现状;分析在三网融合的形势下,它们各自都可以为发展未来包含现在由三种网络提供的所有服务的综合业务网提供核心技术的能力;指出没有单个网络技术能够成为无争议的赢家:融合的网络将具有异构网络集合的特征,提供多种多样的服务;然后在更广阔的视野上阐明了在三网融合之后的未来全局多媒体网络的特征以及建立具有这样的特征的网络所面临的挑战和所需要的变革和创新。     

网站及网络自动检测告警系统的实现

介绍了利用微软ASP.NET技术进行网站和网络无人值守自动告警系统的研发,实现了利用编写的程序自动对网络中部署的网站系统和网络连通情况进行实时的监控。     

Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.