氨基磺酸系高效减水剂应用性能研究     

贺凤伟 《辽宁科技学院学报》2010,12(3):38-40

研究了氨基磺酸系高效减水剂（ASP）对水泥净浆流动度、新拌砼硬化性能及力学性能影响以及ASP减水率、ASP与水泥适应性：ASP与萘系减水剂复合性能。试验表明：ASP与萘系减水剂相比,具有低掺量、高减水率,以及控制坍落度损失的功能,而且与水泥具有很好的适应性,与萘系减水剂具有很好的相容性。  相似文献   

基于智能代理的混合学习支持系统设计     

景红娜  陈琳 《江苏广播电视大学学报》2010,21(4):10-13

混合学习提倡将传统学习与网络学习方式优势结合。将智能代理技术应用到混合学习之中,可以部分替代教师的工作,引导学生有效获取信息资源,简化教学设计和课程开发,同时能实现科学合理的评价。基于智能代理的混合学习支持系统的模型是通过学生代理、教师代理、教学代理、信息代理四个模块的功能设计,完成复杂、智能的工作及信息交换,实现混合学习的目的。  相似文献   

二次插值对称点算法求解一维搜索问题     

杨爽  贾礼平 《乐山师范学院学报》2013,(12):3-5,9

插值法是一类用插值多项式来逼近未知或复杂函数的方法。本文基于二次插值,将插值多项式的极小点和其对称点作为搜索区间的两个探索点,通过不断缩小搜索区间,求解一维搜索问题的最优解。本文给出了二次插值对称点的算法,并用0.618法进行了数值比较。结果表明,新算法比0.618法效果好。  相似文献   

基于MAS的混合智能故障诊断模型研究     

游张平  朱晓虹  王克刚 《丽水学院学报》2013,(5):55-59

针对复杂设备故障的复杂性和不确定性等特点,以起重设备为研究对象,提出了一种基于多Agent的混合智能故障诊断模型,并构建了模型的诊断工作过程及每一功能Agent的内部结构和功能。模型根据各子系统并行感知外界环境,动态地组建Agent诊断组,共同完成诊断任务。最后,通过实例验证了模型的有效性。该模型在某企业的设备远程维护平台应用中,能快速、准确地进行故障成因分析,并给出合理的决策意见,提高了设备的安全运行效率。  相似文献   

基于位置信息的分簇传感网数据汇聚方案     

陈德礼  郭江鸿 《嘉应学院学报》2013,(11):9-13

数据汇聚是降低传感器网络传输能耗的重要手段.分簇传感网数据汇聚通常包括簇内汇聚及传递汇聚结果到基站两个阶段,现有方案大多关注第二阶段数据汇聚结果传递到基站的效率.现提出一种基于位置信息的分簇传感网数据汇聚方案,通过利用位置信息选择代理点,仅与代理点有不同测量值的节点进行数据发送,有效减少了第一阶段中的数据传输.理论分析与模拟试验表明,方案簇内消息发送数优于相关方案,减少了通信开销,延长了网络生命期.  相似文献   

环境友好型润滑防锈剂研究进展     

周石柔  陈雷 《岳阳职业技术学院学报》2013,(6):78-80

随着传统润滑剂对环境造成的污染愈来愈多的受到社会关注,环境友好润滑防锈剂的研究、开发和利用已成为可持续发展战略的需要。目前使用中的防锈剂大多使用浓度高且效率低,导致防锈产品成本高,单一组分防锈效果都不好,开展高效、低成本、易生物降解防锈剂的研究和使用是以后发展的方向。  相似文献   

试论管理层收购(MBO)在我国的应用     

吴剑雄  陈移柏 《长江工程职业技术学院学报》2004,21(1):62-64

从当前国有企业改革和公有制企业的产权明晰过程中出现的管理层收购(MBO)现象出发,分析了MBO的特点以及产生的动因,提出了在我国现阶段实施MBO的利弊,并且希望随着改革的深化,MBO能在我国作出应有的贡献.  相似文献   

Search tactics used in solving everyday how-to technical tasks: Repertoire,selection and tenacity     

Sophie Rutter  Verena Blinzler  Chaoyu Ye  Max L. Wilson  Michael D. Twidale 《Information processing & management》2019,56(3):919-938

With greater access to computational resources, people use search to address many everyday challenges in their lives, including solving technology problems. Although there are now many useful ‘how-to’ resources online (especially videos on YouTube), it can still be difficult to identify, understand, and resolve certain kinds of technical problem. While research tasks have been studied for many years and we know the tactics people use, we know far less about searchers’ tactics for how-to technical tasks that involve actually being able to apply found information to resolve a problem. Crucial to our study was developing and studying a highly realistic, how-to technical task, for which there was no single guidance resource: making a phone safe for a child. After providing 39 participants with an actual phone to fix, and a search engine to perform the task, we analysed their search tactics using retrospective cued think aloud interviews. Our primary contribution is a set of 77 tactics used, in three categories, along with detail of how common they were. We conclude that people had a lot of tactics in their repertoire. Although it was not hard for participants to find relevant information, what was hard was for participants to find information they could use; indeed only 23% of participants successfully completed the entire task. Domain knowledge affected the choice of tactics used (although not necessarily towards better task success). We discuss these influences and make design recommendations for how future search systems can support those in resolving how-to technical tasks.  相似文献   

Information retrieval in the workplace: A comparison of professional search practices     

Tony Russell-Rose  Jon Chamberlain  Leif Azzopardi 《Information processing & management》2018,54(6):1042-1057

Legal researchers, recruitment professionals, healthcare information professionals, and patent analysts all undertake work tasks where search forms a core part of their duties. In these instances, the search task is often complex and time-consuming and requires specialist expertise to identify relevant documents and insights within large domain-specific repositories and collections. Several studies have been made investigating the search practices of professionals such as these, but few have attempted to directly compare their professional practices and so it remains unclear to what extent insights and approaches from one domain can be applied to another. In this paper we describe the results of a survey of a purposive sample of 108 legal researchers, 64 recruitment professionals and 107 healthcare information professionals. Their responses are compared with results from a previous survey of 81 patent analysts. The survey investigated their search practices and preferences, the types of functionality they value, and their requirements for future information retrieval systems. The results reveal that these professions share many fundamental needs and face similar challenges. In particular a continuing preference to formulate queries as Boolean expressions, the need to manage, organise and re-use search strategies and results and an ambivalence toward the use of relevance ranking. The results stress the importance of recall and coverage for the healthcare and patent professionals, while precision and recency were more important to the legal and recruitment professionals. The results also highlight the need to ensure that search systems give confidence to the professional searcher and so trust, explainability and accountability remains a significant challenge when developing such systems. The findings suggest that translational research between the different areas could benefit professionals across domains.  相似文献   

A knowledge-based semantic framework for query expansion     

Jamal Abdul Nasir  Iraklis Varlamis  Samreen Ishfaq 《Information processing & management》2019,56(5):1605-1617

Searching for relevant material that satisfies the information need of a user, within a large document collection is a critical activity for web search engines. Query Expansion techniques are widely used by search engines for the disambiguation of user’s information need and for improving the information retrieval (IR) performance. Knowledge-based, corpus-based and relevance feedback, are the main QE techniques, that employ different approaches for expanding the user query with synonyms of the search terms (word synonymy) in order to bring more relevant documents and for filtering documents that contain search terms but with a different meaning (also known as word polysemy problem) than the user intended. This work, surveys existing query expansion techniques, highlights their strengths and limitations and introduces a new method that combines the power of knowledge-based or corpus-based techniques with that of relevance feedback. Experimental evaluation on three information retrieval benchmark datasets shows that the application of knowledge or corpus-based query expansion techniques on the results of the relevance feedback step improves the information retrieval performance, with knowledge-based techniques providing significantly better results than their simple relevance feedback alternatives in all sets.  相似文献