对1983年夏季热带大气环流异常的分析

本文利用1980—1983年夏季 ECMRWF 资料,分析了1983年夏季热带大气环流的异常;指出1983年夏季大气对1982—1983ElNino 事件的响应,主要发生在北半球热带夏季风区,并且以东亚季风区最显著;引起1983年亚洲夏季异常减弱的主要因子是赤道印度洋至“海洋陆地”之间的纬向热力对比的异常减弱.     

基于在线百科的大规模人物社会网络抽取与分析

在线百科词条中蕴含着海量的人物间关系信息,基于这些信息可以抽取出大规模社会网络,为数字人文和社会计算研究提供数据支撑。本研究以百度百科为例,首次对面向中文在线百科的大规模社会网络抽取进行探索,提出一种新的人物社会网络抽取方法。该方法利用排序学习综合多种特征计算人物关系权重,通过估计人物生存时空来发现人物间的时空耦合关系。由此,从百度百科中抽取出一个带权重的跨时空人物社会网络和一个时空耦合的人物网络。这两个人物网络具有良好的小世界和无标度特性,并存在清晰的社区结构。最后,通过可视化分析展示了百科人物网络在数字人文研究中的应用模式和应用价值。图8。表6。参考文献39。     

浅析二版主题词升级过程中书目数据替换规则

以国家图书馆二版主题词升级为背景,介绍升级中书目数据更新的整体情况,分析书目数据替换产生的依据及规则,并针对每种书目数据替换进行程序实现说明。     

基于SOA架构的术语注册和服务系统设计与应用

术语注册和服务系统是各种知识组织系统共建共享的重要平台,是网络知识组织系统（NKOS）由理论走向实际应用的关键环节。 通过对国内外术语注册与服务系统及相关研究的调研分析,指出当前我国在术语注册与术语服务方面的研究与应用与国外相比还有较大的差距,提出了一个基于SOA（ServiceOriented Architecture）构建术语注册和服务系统的解决方案。整个系统的架构从上至下分为四层,分别为任务服务层、工具服务层、组件层和数据层。设计的术语注册和服务系统主要支持基于RDF的语义化词表表示格式,并且支持以关联数据的形式显示词表内容数据。此外,本文还详细描述了实现该系统的关键技术,列举了术语注册和术语服务的一些典型应用案例。指出下一步的研究将具体实现一个术语注册和服务原型系统及术语服务客户端,并尝试将客户端程序集成在数字图书馆系统或编目系统中,通过调用术语服务对信息检索和编目提供术语支持。图4。表1。参考文献22。     

基于建构主义理论种子市场营销学课程教学改革与实践

从种子市场营销学这门学科的特点和教学要求出发,重点阐述了该门课程在教学过程中存在的问题,并基于建构主义理论阐述讨论了课程教学改革的主要内容.以促进种子市场营销学课程教学活动的改革.     

本体与关联数据驱动的图书馆信息资源语义整合方法及其测评

探索语义网技术在图书馆信息资源整合中的应用。 首先,提出一个本体与关联数据驱动的资源语义整合框架, 实现：①图书馆中不同格式、不同类型文献资源的整合;②不同数据集合中信息资源的语义整合;③图书馆馆藏资源与外界相关资源的链接与集成, 从而构成一个可无限延伸与扩展的开放的资源整合体系。其次,构建一个资源整合演示系统。 最后,将该系统与使用传统资源整合方式的CALIS OPAC系统和CNKI进行实验对比。     

Mobile Agents for Distributed and Heterogeneous Information Retrieval

The heterogeneous, distributed and voluminous nature of many government and corporate data sources impose severe constraints on meeting the diverse requirements of users who analyze the data. Additionally, communication bandwidth limitations, time constraints, and multiple data formats impose further restrictions on users of these distributed data sources. In this paper, we present an Agent-based Complex QUerying and Information Retrieval Engine (ACQUIRE) for large, heterogeneous, and distributed data sources. ACQUIRE acts as a softbot or interface agent by presenting users with a view of a single, unified, homogenous data source, against which users can pose high-level declarative queries. ACQUIRE translates each such user query into a set of sub-queries by employing a combination of planning and traditional database query optimization techniques. ACQUIRE then spawns a set of mobile agents corresponding to these sub-queries, which in turn retrieve the data from various distributed data sources by dynamically optimizing the retrieval strategy as it is carried out. These mobile agents carry with them data-processing code that can be executed at the remote site, thus reducing the size of data returned by the agent. When all mobile agents have returned, ACQUIRE filters and merges the retrieved data and presents the results to the user. While the system is still very much a work in progress, current validation experiments on simulated NASA Distributed Active Archive Centers (DAACs) have demonstrated that complex queries can be effectively decomposed and retrieved by this approach.     

Dynamic harmonic balance principle and analysis of rocking block motions

The harmonic balance (HB) principle is a powerful and convenient tool for finding periodic solutions in nonlinear systems. In the present paper, this principle is extended to transient processes in systems with one single-valued odd-symmetric nonlinearity and linear plant not having zeros in the transfer function, and named the dynamic HB. Based on the dynamic HB, first the equations for the amplitude, frequency, and amplitude decay of an oscillatory process in the Lure system are derived. It is then applied to analysis of rocking block decaying motions. An example is provided.     

Stabilization of artificial gas-lift process using nonlinear predictive generalized minimum variance control

Artificial gas-lift (AGL) is one of the most widely used methods in oil production to maintain acceptable oil flow to the processing equipment and sales when the reservoir pressure is not high enough. In spite of its popularity, the AGL process is prone to casing-heading instability, which is revealed as significant flow oscillation. This is undesirable as it results in production losses and unstable behavior that has negative impact on the downstream equipment. Controller design for such a process is very challenging as it exhibits highly nonlinear dynamics. In this work, the predictive generalized minimum variance control (NPGMV) is employed to derive a robust controller based on the state estimation to stabilize AGL process when casing-heading phenomenon occurs. A closed-form optimal control law is obtained based on the Taylor series approximation. Further, a nonlinear state observer is produced and combined with the controller to ensure closed-loop control through variables that are most beneficial to the system performance, which are unmeasurable and can be obtained only via estimation. Through simulation studies, the effectiveness of the proposed controller is demonstrated.