跨语言文献检索系统研究

[目的/意义]旨在探讨解决原英日文献检索分析中存在的不足,实现以中文为检索语言的中、英、日文献资源的统一检索。[方法/过程]介绍了一种通过机器翻译技术实现以中文为检索语言的中日英文献资源的统一检索系统。[结果/结论]该系统基于MASH-UP技术将检索结果整合进行统一的内容分析,帮助用户跨越语言的障碍,方便地查询和使用外文文献。     

循证决策视角下的患者健康咨询主题分析

[目的/意义]为了将大数据更好地用于循证决策,文章构建了循证决策视角下的患者健康主题分析模型。[方法/过程]首先使用LDA主题模型对高血压问答数据进行主题探测,并结合文献提炼出高血压八大主题;再次使用问卷调查法和层次分析法对主题探测结果进行评估;最后对得到的证据进行实践讨论。[结果/结论]文章对大数据和循证决策的结合做了尝试性探索,结果表明循证决策视角下的患者健康主题分析模型,具有一定的实用性和创新性。     

Towards sentiment and Temporal Aided Stance Detection of climate change tweets

Climate change has become one of the most significant crises of our time. Public opinion on climate change is influenced by social media platforms such as Twitter, often divided into believers and deniers. In this paper, we propose a framework to classify a tweet’s stance on climate change (denier/believer). Existing approaches to stance detection and classification of climate change tweets either have paid little attention to the characteristics of deniers’ tweets or often lack an appropriate architecture. However, the relevant literature reveals that the sentimental aspects and time perspective of climate change conversations on Twitter have a major impact on public attitudes and environmental orientation. Therefore, in our study, we focus on exploring the role of temporal orientation and sentiment analysis (auxiliary tasks) in detecting the attitude of tweets on climate change (main task). Our proposed framework STASY integrates word- and sentence-based feature encoders with the intra-task and shared-private attention frameworks to better encode the interactions between task-specific and shared features. We conducted our experiments on our novel curated climate change CLiCS dataset (2465 denier and 7235 believer tweets), two publicly available climate change datasets (ClimateICWSM-2022 and ClimateStance-2022), and two benchmark stance detection datasets (SemEval-2016 and COVID-19-Stance). Experiments show that our proposed approach improves stance detection performance (with an average improvement of 12.14% on our climate change dataset, 15.18% on ClimateICWSM-2022, 12.94% on ClimateStance-2022, 19.38% on SemEval-2016, and 35.01% on COVID-19-Stance in terms of average F1 scores) by benefiting from the auxiliary tasks compared to the baseline methods.     

基于因子分析与交叉DEA的国家自主创新效率评价——以山东半岛国家自主创新示范区为例

从科技创新投入与产出效率入手,构建国家自主创新示范区创新能力评价指标体系,将各指标按照投入和产出的性质进行分类,并用因子分析方法对其进行处理,最后利用交叉DEA模型评价山东半岛国家自主创新示范区中的6个高新技术开发区的科技创新效率,研究得出山东半岛国家自主创新效率是DEA有效,但其交叉效率水平仍处于中等水平,创新效率需进一步提高。     

新时期我国软科学研究前沿热点研究——基于软科学文献的知识图谱分析(2008—2018)

运用科学计量方法对软科学领域的六大核心期刊(2008—2018年)现状和研究热点进行分析。研究发现,目前我国软科学以国家创新驱动发展战略为主要研究方向,围绕区域创新体系及创新链的热点焦点问题和关键环节开展研究,同时,发现各个参与研究者之间合作紧密。研究运用描述性分析的方法,管窥我国软科学领域研究现状,并对未来发展做出展望,为我国软科学繁荣发展提供参考。     

我国5种医药大学学报在国内外数据库中高被引论文的对比分析

【目的】 对比国内高被引论文在国外的被引情况与国外高被引论文在国内的被引情况,探讨二者的相关性,以了解国内外高被引论文的差异。【方法】 选择2017年《中国科技期刊引证报告(核心版)》医药大学学报类综合评价总分排名前5位的期刊,选取2008—2017年各期刊在CNKI中的高被引论文共512篇及WoS中高被引论文共486篇,统计分析所选文献的被引频次等相关指标。【结果】 5种期刊的CNKI高被引论文的被引频次差异较小,而WoS高被引论文的被引频次差异较大;CNKI高被引论文的被引频次远高于WoS高被引论文的被引频次;除《南方医科大学学报》外,CNKI/WoS高被引论文的被引频次与其在WoS/CNKI中的被引频次的差异不具有统计学意义(P>0.05)。【结论】 我国5种国内学术影响力较高的医药大学学报的国际影响力均较低,这些期刊国内/外高被引论文的被引频次与其在国外/内的被引频次之间的相关性均不明显,国内外对5种期刊的引用存在差异。     

基于熵值-主成分分析法的天津市低碳经济发展水平评价

针对低碳经济发展水平评价中存在的问题,将主成分分析法与熵值法结合,建立低碳经济评价模型,分析天津市2000—2015年低碳经济的发展状况。实证结果表明,低碳环境水平、低碳产业水平和居民生活水平是天津市低碳经济发展水平的主要影响因素。依据实证分析结果,从优化低碳市场环境、调整产业结构、倡导低碳生活、鼓励低碳出行四方面提出有利于天津市发展低碳经济的对策和建议。     

Intermittent control strategy for synchronization of fractional-order neural networks via piecewise Lyapunov function method

In this paper, the synchronization problem of fractional-order neural networks (FNNs) with chaotic dynamics is investigated via the intermittent control strategy. Two types of intermittent control methods, the aperiodic one and the periodic one, are applied to achieve the synchronization of the considered systems. Based on the dynamic characteristics of the intermittent control systems, the piecewise Lyapunov function method is employed to derive the synchronization criteria with less conservatism. The results under the aperiodically intermittent control show more generality than the ones via the periodically intermittent control. For each of the aperiodic and periodic cases, a simple controller design process is presented to show how to design the corresponding intermittent controller. Finally, two numerical examples are provided to demonstrate the effectiveness of the obtained theoretical results.     

Linear output-feedback-based semi-global stabilization for switched nonlinear time-delay systems

This paper focuses on the problem of semi-global output-feedback stabilization for a class of switched nonlinear time-delay systems in strict-feedback form. A switched state observer is first constructed, then switched linear output-feedback controllers for individual subsystems are designed. By skillfully constructing multiple Lyapunov–Krasovskii functionals and successfully solving several troublesome obstacles, such as time-varying delay and switching signals and nonlinearity in the design procedure, the switched linear output-feedback controllers designed can render the resulting closed-loop switched system semi-globally stabilizable under a class of switching signals with average dwell time. Furthermore, under some milder conditions on nonlinearities, the semi-global output-feedback stabilization problem for switched nonlinear time-delay systems is also studied. Simulation studies on two examples, which include a continuous stirred tank reactor, are carried out to demonstrate the effectiveness of the proposed approach.     

Mean square consensus of double-integrator multi-agent systems under intermittent control: A stochastic time scale approach

We consider the leader–follower consensus problem for a multi-agent system where information is exchanged only on a non-uniform discrete stochastic time domain. For a second-order multi-agent system subject to intermittent information exchange, we model the tracking error dynamics as a $\mu ?$varying linear system on a discrete stochastic time scale, where μ is the graininess operator. Based on a Lyapunov operator and a positive perturbation operator on the space of symmetric matrices, we derive necessary and sufficient conditions to design a decentralized consensus protocol. This protocol allows us to cast the mean-square exponential consensus problem within the framework of dynamic equations on stochastic time scales. We establish some theoretical results which allow for the computation of the control gain matrix which guarantees the mean-square exponential stability with a given decay rate for the error dynamics. To show the effectiveness of the theoretical results, some simulation and experimental results on multi-robot systems have been performed.