An Analysis of Citation Counts of ETRI‐Invented US Patents

From its foundation until 2004, ETRI has registered over 1,000 US patents. This letter analyzes the characteristics of these patents and addresses the explanatory factors affecting their citation counts. For explanatory variables, research team related variables, invention specific variables, and geographical domain related variables are suggested. Zero‐altered count data models are used to test the impact of independent variables. A key finding is that technological cumulativeness, the scale of invention, outputs in the electronic field, and the degree of dependence on the US technology domain positively affect the citation counts of ETRI‐invented US patents. The magnitude of international presence appears to negatively affect the citation counts of ETRI‐invented US patents.     

The Intellectual Development of Science and Engineering Students. Part 2: Teaching to Promote Growth

As college students experience the challenges of their classes and extracurricular activities, they undergo a developmental progression in which they gradually relinquish their belief in the certainty of knowledge and the omniscience of authorities and take increasing responsibility for their own learning. At the highest developmental level normally seen in college students (which few attain before graduation), they display attitudes and thinking patterns resembling those of expert scientists and engineers, including habitually and skillfully gathering and analyzing evidence to support their judgments. This paper proposes an instructional model designed to provide a suitable balance of challenge and support to advance students to that level. The model components are (1) variety and choice of learning tasks; (2) explicit communication and explanation of expectations; (3) modeling, practice, and constructive feedback on high‐level tasks; (4) a student‐centered instructional environment; and (5) respect for students at all levels of development.     

人工智能的原理及应用

介绍了人工智能的发展，并对改进的神经网络专家系统的优越性做了介绍，指出了神经网络专家系统广阔的应用前景及实现。     

在基于MPLS的层次化移动IP网络中支持DiffServ的研究

MPLS支持DiffServ、流量工程,能为网络提供较好的QoS保证,而移动IP(MIP)能为移动设备提供较好的移动性支持。文章探讨了在无线接入网中MPLS和MIP结合实现DiffServ的方案,并给出了一种在基于MPLS的层次化MIP网络结构中支持DiffServ的体系结构,设计了其节点功能模型和关键协议。方案中利用了层次化结构的区域注册和重路由机制,减少了切换时延和网络的信令负荷。     

DSR的一种自适应路由自动缩短机制

动态源路由协议是无线自组织网络众多路由协议中被广泛关注的一种按需路由协议，目前，关于该协议的优化措施有很多。本文先分析了动态源路由协议的一种优化机制——路由自动缩短，该机制能动态缩短处于工作状态路由的跳数，但不保证缩短路由的质量，在此基础上，提出一种自适应路由自动缩短机制，新机制既可缩短路由．又能保证缩短路由质量．理论分析及仿真结果表明，自适应路由缩短机制的各项性能优于原路由缩短机制。     

热管传热性能对小型热管换热器散热效能影响

在零重力辅助下,小热管热阻是小型热管换热器散热效能的重要影响因素之一。基于集总参数法对于换热器系统数值计算的高效性思想,建立了热管、热管换热器的集总参数模型。对同一热管换热器选用不同传热性能的热管,在不同传热温差和流体质量流速下,就其散热效能进行了数值计算。计算结果表明,在零重力辅助下,热管换热器管内热阻存在一临界值Rcri。当热阻RHP≤Rcri时,管外热阻起主导作用,热管换热器的散热效能εh几乎不随热管管内热阻的值而变化。     

三网互联的几个关键技术

对三网互联的几个关键技术进行分析与研究，介绍利用IP技术解决有线电视网地址选择问题，探讨怎样将ATM技术与IP技术相互融合，使真正的信息高速公路成为现实，阐述利用H．323标准全面解决视频网络方案。     

电力系统谐波检测的现状与发展

准确、实时地对电力系统谐波进行检测有着重要的意义。本文根据电力系统谐波测量的基本方法，对近年来电力系统谐波检测的新方法进行了分析和评述。最后对电力系统的谐波测量进行了总结并提出了看法。     

结构化编程实现Sniffer

随着各高校校园网络规模的不断扩大和各种应用的急剧增加,各种新的网络问题也在不断出现。Sniffer是网络管理员进行网络管理的有效工具,可以有效地对网络进行实时监控,及时发现网络中存在的各种问题。本文首先介绍了Sniffer的工作原理,其次给出了实现Sniffer功能的编程流程图,并用C语言给出了编程所需的关键代码。     

A Study on Turbo—rotor Multi—fault Diagnosis Based on a Neural Network

The multi-fault phenomena are common in the turbo-rotor system of a liquid rocket engine.As it has many excellent qualities,the neural network might be used to solve the problems of multi-fault diagnasis of a turbo-rotor system.First,the feature expression of a common turbo-rotor fault was studied in order to build up the standard fault pattern and satisfy the need of neural network studying and diagnosing.Then.the turbo-rotor fault identification and diagnosis problems were investigated by using a BP(back-propaga-tion)neural network.According to the BP neural network problems,the parallel BP neural network method of multi-fault diagnosis and classification was presented and investigated.The results indicated that the parallel Bp neural network method could solve the turbo-rotor multi-fault diagnosis problems.