Subsequently to the problem of performance and energy overhead, the reliability problem of the system caused by soft error has become a growing concern. Since register file（RF） is the hottest component in processor, if not well protected, soft errors occurring in it will do harm to the system reliability greatly. In order to reduce soft error occurrence rate of register file, this paper presents a method to reallocate the register based on the fact that different live variables have different contribution to the register file vulnerability（RFV）. Our experimental results on benchmarks from MiBench suite indicate that our method can significantly enhance the reliability.
梳理健康信息素养评估问题的研究进展、发展脉络,把握其研究前沿,为我国健康信息素养评估研究提供借鉴和参考。以Web of ScienceTM核心合集收录的有效文献为来源,综合运用文献计量和知识图谱等分析方法,从研究现状分析、引文时序分析、主路径分析和前沿追踪4个方面,对健康信息素养评估的进展和前沿进行可视化分析。结果发现:1健康信息素养评估问题自1997年开始日益受到各国学者的关注,诞生了很多经典的健康信息素养评估工具,美国在健康信息素养评估研究中遥遥领先于其他国家,我国在研究热度与研究成果上尚需很大的努力。21993-2004年健康信息素养的评估研究经历了从临床视角到公共卫生视角的转变,再到两者结合的发展轨迹。3健康信息素养评估的前沿主题主要集中在针对于特定年龄人群、特定疾病患者的健康信息素养评估,评估方式的多元化,以及评估范畴的全面化、规范化。
Microblog is a social platform with huge user community and mass data. We propose a semantic recommendation mechanism based on sentiment analysis for microblog. Firstly, the keywords and sensibility words in this mechanism are extracted by natural language processing including segmentation, lexical analysis and strategy selection. Then, we query the background knowledge base based on linked open data （LOD） with the basic information of users. The experiment result shows that the accuracy of recommendation is within the range of 70% -89% with sentiment analysis and semantic query. Compared with traditional recommendation method, this method can satisfy users＇ requirement greatly.
Aiming at the fact that traditional cache replacement strategy lacks pertinence to the semantic cache in the process of extensible markup language （XML） algebra query, a replacement strategy based on the semantic cache contribution value is proposed. First, pattern matching rules for XML algebra query and semantic caches are given. Second, the method of calculating the semantic cache contribution value is proposed. In XML documents with four different sizes, the experimental results of time efficiency show that this strategy supports environment of the XML algebra query and it has better time efficiency than both least frequency used （LFU） and least recently used （LRU）.
文章以Web of Science TM核心集中图书情报学科的"大数据""数据驱动"文献为数据源,分析大数据驱动下图书情报学科研究的现状和进展;借助SATI和SPSS软件对507篇文献的关键词进行共词分析和聚类分析。研究表明:大数据驱动下的图书情报学科研究热点主题主要集中在数字图书馆知识组织与语义互联、社会网络大数据、科研大数据管理与共享、云计算与信息安全、政府数据开放与共享、大数据驱动的知识发现、E-learning与高等教育、数据挖掘与数字人文等方面。
