映射之难——人文社科学科评价中跨库数据的学科归属问题

合理判别数据的学科归属是高校图书馆学科评价服务中亟待解决的重要问题,它直接影响评价数据的准确性和评价结果的合理性。文章聚焦人文社科学科评价中跨库数据的学科归属问题,应用案例研究法,考察南开大学图书馆在开展人文社科学科评价中,根据数据库特点及映射理论,在辨析学科分类体系的基础上,通过制定多维学科映射方案对来自CNKI、CSSCI和Web of Science等数据源的评价数据实现判别学科归属的实践过程。基于案例实践,剖析学科评价中跨库数据学科归属问题的本质、根本原因、解决途径及制约性因素,提出从理论探究到实践方法的应对策略。

关系型数据库向图数据库的转换方法

由于关系型数据库和图数据库存储模式的天然差别,将关系型数据库中的数据转存到图数据库的过程中,需解决对于关系的定义、节点唯一性以及保留原数据库约束信息的主要问题。针对上述问题,提出了一种关系型数据库向图数据库转换的方法。首先通过自定义或使用已有主键,并结合数据库表名的唯一性,解决了节点唯一性的问题;通过不同的配置方案,最大化保留了原关系型数据库的约束信息;然后提出了基于配置与中间表的边定义方法(Edge Definition Method based on Configuration and Intermediate Table,EDCIT),针对多种类型的数据库提供不同关系的映射方案,解决了转换过程中对于关系的定义。最终,通过对多个数据集进行实验,并使用Gremlin语句对转换后的数据进行测试,验证了转换后的数据具有完整性和可靠性。

Auditory attention model based on Chirplet for cross-corpus speech emotion recognition

To solve the problem of mismatching features in an experimental database, which is a key technique in the field of cross-corpus speech emotion recognition, an auditory attention model based on Chirplet is proposed for feature extraction.First, in order to extract the spectra features, the auditory attention model is employed for variational emotion features detection. Then, the selective attention mechanism model is proposed to extract the salient gist features which showtheir relation to the expected performance in cross-corpus testing.Furthermore, the Chirplet time-frequency atoms are introduced to the model. By forming a complete atom database, the Chirplet can improve the spectrum feature extraction including the amount of information. Samples from multiple databases have the characteristics of multiple components. Hereby, the Chirplet expands the scale of the feature vector in the timefrequency domain. Experimental results show that, compared to the traditional feature model, the proposed feature extraction approach with the prototypical classifier has significant improvement in cross-corpus speech recognition. In addition, the proposed method has better robustness to the inconsistent sources of the training set and the testing set.

一种信息资源整合优化模型及其性能分析

基于搜索引擎和跨库检索技术,从信息资源整合的性能角度出发,提出信息资源动态重组系统模型,详细介绍新模型的基本思路和主要步骤,通过性能分析比较可知新模型的有效性,最后简要指出其实现过程中需要注意的问题。

Research development of digital maintenance and management system for long-span cable-stayed bridges

Digital cable-stayed bridge maintenance and management system （DCBMS） was developed for the need of maintenance and management of long-span cable-stayed bridges. In this paper, the major functions and theoretical application of eight modules were systematically stated with the background of Harbin Songhua River cable-stayed bridge, which include data management module, inspection and measurement module, assessment module, finite dement analysis module, disease diagnosis and prediction module, maintenance module, query module and help module. By analyzing and calculating the data from manual inspection database, basic database and health monitoring subsystem, DCBMS can accomplish the functions like life prediction, disease diagnosis, comprehensive assessment, maintenance and management of bridges. Therefore, the maintenance and management of long-span cable-stayed bridges can be made digital, professional and scientific. By running this system, a real-time and specific technical guidance can be provided for the maintainers and managers of long- span cable-stayed bridges.