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  • Standard Digital Governance Strategy: Opportunities, Challenges, and Countermeasures

    Subjects: Other Disciplines >> Synthetic discipline submitted time 2024-03-28 Cooperative journals: 《文献与数据学报》

    Abstract: [Purpose/Significance]Digitalization of standards can deeply explore the potential knowledge of standards and unleash their potential value. The Chinese standard digital governance strategy is directly related to the development of China’s digital economy and China’s international competitive discourse power. [Method/Process] Based on the trend of global standard digital transformation, this research is conducted from four aspects: new technologies, development policies, development patterns, and governance concepts. [Result/Conclusion] The research findings indicate that: (1) digital governance of standards needs to seize four opportunities: firstly, new technologies of standard digitization promote the development of the entire standard chain industry chain; secondly, standardization development policies encourage and guide the development of standard digitization; thirdly, the traditional standardization development pattern undergoes changes; fourthly, the concept of standard data governance undergoes changes; (2) The standard digital governance is facing three challenges. Firstly, the basic theory, key technologies, implementation paths, and application scenarios have not yet formed a complete system. Secondly, there are few mature products and excellent pilot cases. Thirdly, the institutional system and management mechanism need to be improved and perfected; (3) Four strategies need to be considered for standard digital governance: firstly, vigorously developing basic conceptual systems and key technologies with common characteristics; Secondly, strengthen relevant policy guarantees; Thirdly, promote the integration and innovative application of relevant theories with various business scenarios; The fourth is to plan ahead for the future international market.

  • Research on the Spatial Distribution of Scientific Research Output: Taking the Computer Software and Application Field as an Example

    Subjects: Library Science,Information Science >> Library Science submitted time 2023-07-26 Cooperative journals: 《图书情报工作》

    Abstract: [Purpose/significance] The extensive development of scientific research cooperation will inevitably lead to the imbalance of regional scientific research output. In order to explore its distribution, the paper analyzed the causes of differences, and studied the spatial distribution of regional scientific research output.[Method/process] Based on the bibliographic data of the computer field from 1997-2016, the geographical location information of the organization is extracted, and the observation point was used to visualize the distribution, and the Gini index and the centrality index are measured to study the distribution concentration. By measuring the global Moran index and local autocorrelation index, the spatial autocorrelation law was studied. By measuring the Pearson correlation coefficient, the correlation between the number of colleges and universities, the gross national product, the research and experimental input, and the population was studied.[Result/conclusion] The output of journals in the computer field showed an uneven geographical distribution, a clear concentration, and spatial autocorrelation. Meanwhile, it had a high correlation with the number of regional universities and regional research and experimental funding.

  • Evolutionary Analysis of Topic and Topic Clusters in Informal Communication from the Perspective of Conversation Analysis

    Subjects: Library Science,Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》

    Abstract: [Purpose/significance] Aiming at the limitations of current informal communication topic evolution research in both analysis level and measurement indicators, a universal evolution analysis method is proposed to explore the characteristics and patterns of topic evolution from micro and medium levels.[Method/process] Introducing the conversation analysis theory, taking Sina Microblog and Zhihu as examples, this paper revealed the evolutionary characteristics and patterns of informal information communication from the two dimensions of conversation content and discussion style through the analysis of running process of topics and topic clusters. Meanwhile, this paper designed the method of calculating and judging the continuity of a topic and explored measurement standard of the topic evolution.[Result/conclusion] The topic evolution analysis results show that the opinion group from Sina Microblog and Zhihu are obviously biased in topic content, and indicate the main perspectives of opinion group participating in the discussion of social focus event. The topic cluster evolution analysis find out that opinion group from Sina Microblog diversify and explore multiple topics in a certain range, while those from Zhihu always focus on the settled core topics. The difference in conversation content and discussion style between opinion groups in social media indicates the different role of Sina Microblog and Zhihu in informal information communication online.

  • 1982—2015 年科尔沁沙地植被时空变化及气候响应

    Subjects: Geosciences >> Geography submitted time 2021-04-23 Cooperative journals: 《干旱区研究》

    Abstract: 基于1982—2015年GIMMS NDVI3g.v1数据,结合站点气象数据,采用趋势分析、变异系数、Hurst指数及偏相关分析等方法,探讨了科尔沁沙地植被覆盖的时空特征、气候响应及未来趋势。结果表明:(1)科尔沁沙地34 a植被覆盖呈缓慢增加趋势,每10 a增速为0.23%。植被覆盖变化整体上可分为“三升”(1982—1999年、2000—2004年、2008—2012年)和“三降”(1999—2000年、2004—2007年、2012—2015年)的趋势,其中最大值出现在1999年,最小值出现在2009年。(2)科尔沁沙地植被覆盖格局呈“南北高,中间低”的分布特征。以“西拉木伦河—新开河”为界线,北部地区植被变化趋势以退化为主,南部地区以改善为主。(3)科尔沁沙地变异系数西高东低,地域性差异明显。低波动变化区域主要分布在北部海拔较高地区(占5.52%),其植被类型主要为针阔混交林。(4)科尔沁沙地植被变化的同向特征强于反向特征,持续退化和持续改善区域分别占61.48%和37.03%。降水是影响研究区植被变化的主要因素。

  • 基于ReliefF和改进乌鸦搜索优化的并行入侵检测方法

    Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》

    Abstract: The increase of network data leads to the increase of computation complexity and time cost, in order to further improve the detection accuracy and efficiency of network intrusion detection, a novel algorithm RICSA-KELM was proposed. Firstly, filter method ReliefF used to remove the irrelevant features and noises, and reduced the feature dimension. Secondly, wrapper method used to select optimal feature subset which based on improved crow search algorithm (ICSA) , and optimized parameters of kernel extreme learning machine (KELM) . Moreover, a linear-weighted multi-objective function designed to take into account the average accuracy rate, false alarm rate and the subset of feature selection, it helped to improve the accuracy of the algorithm. At last, RICSA-KELM implemented in parallel on multi-core processor by using OpenMP to speed up the search and optimization process. Experiment on KDD99 dataset and UNSW-NB15 dataset, by means of the experimental analysis and comparison with ELM, SVM and KNN, the proposed method not only improves the detection accuracy and detection efficiency, but also achieves lower false positive rate, it proves that the validity of the proposed method.

  • 基于FCBF特征选择和集成优化学习的基因表达数据分类算法

    Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-07-09 Cooperative journals: 《计算机应用研究》

    Abstract: In order to solve the problems of microarray gene expression data with the characteristic of high dimension and small sample, high爎edundancy燼nd燼 lot of爊oise, this article proposed a novel model FICS-EKELM, which was build based on the combination FCBF feature selection and ensemble optimized method, for gene expression data classification. In the proposed method, Fast Correlation-based Filter method(FCBF) firstly used to eliminate the irrelevant features and noise, and chose the discriminate feature subsets. Secondly, bootstrap technology produced many sample training subsets, by means of these subsets, the improved crow search algorithm(ICS) used to select optimal feature subsets and parameters for kernel extreme learning machine(KELM) synchronously. And then, ensemble classifiers were constructed for target gene data classification, which based on the basic classifiers. Moreover, the model implemented in parallel on multi-core processor, which used OpenMP to speed up the search and optimization process. Experiment on six public famous gene datasets, the proposed method not only achieves a higher classification performance with less characteristic genes, but also greatly improves the classification accuracy. It proves the effective and validity of the proposed method.