基于文献计量学的国际基础数学领域作者合作网络分析

系统地统计了基础数学领域10本国际顶级期刊在1981-2011年间发表的所有论文的作者情况,做出了作者合作网络图。并应用社会网络分析方法对最大连通子网络的属性进行了具体分析,对网路的小世界效应、无标度特点、集聚系数等分别进行了计算分析,得到了一些有意义的结论。     

浅谈我馆图书索书号取法

随着科学技术的发展,各高校图书馆都在探究适合自身的图书取号方法,并在实际的工作中不断摸索改进,基本上都确立了各自的取号方法。本文首先对索书号的构成进行了叙述,重点对华侨大学厦门工学院图书馆图书索书号的取法进行了阐述,针对一般图书、不同版本图书、多卷书、连续出版物、配套书以及套书种次号的取法进行论述,全面讲述了一个让图书馆的藏书排架更科学合理、便于利用的图书取号法。     

Library Instruction in Medical Libraries

No abstract available for this article.     

科技文稿的审稿结果应予反馈

科技期刊的稿件处理结果是否实行反馈进行了长期的探索和研究，分析了实现反馈的可能性，指出了稿件处理意见实行反馈的积极意义，得出了在目前科技高速发展的情况下，科技期刊的稿件处理该实行反馈的结论。最后简要介绍了实施反馈的一些做法。     

《吉林农业大学学报》2002-2005年载文作者统计与分析

采用文献计量学方法,对《吉林农业大学学报》2002-2005年载文作者的性别、年龄、职称等进行了统计分析,并根据普赖斯定律确定了核心作者和杰出作者人数,最后对稳定作者队伍及如何进一步办好《吉林农业大学学报》提出了相应的建议。     

Relevance-based entity selection for ad hoc retrieval

Recent developments have shown that entity-based models that rely on information from the knowledge graph can improve document retrieval performance. However, given the non-transitive nature of relatedness between entities on the knowledge graph, the use of semantic relatedness measures can lead to topic drift. To address this issue, we propose a relevance-based model for entity selection based on pseudo-relevance feedback, which is then used to systematically expand the input query leading to improved retrieval performance. We perform our experiments on the widely used TREC Web corpora and empirically show that our proposed approach to entity selection significantly improves ad hoc document retrieval compared to strong baselines. More concretely, the contributions of this work are as follows: (1) We introduce a graphical probability model that captures dependencies between entities within the query and documents. (2) We propose an unsupervised entity selection method based on the graphical model for query entity expansion and then for ad hoc retrieval. (3) We thoroughly evaluate our method and compare it with the state-of-the-art keyword and entity based retrieval methods. We demonstrate that the proposed retrieval model shows improved performance over all the other baselines on ClueWeb09B and ClueWeb12B, two widely used Web corpora, on the [email protected], and [email protected] metrics. We also show that the proposed method is most effective on the difficult queries. In addition, We compare our proposed entity selection with a state-of-the-art entity selection technique within the context of ad hoc retrieval using a basic query expansion method and illustrate that it provides more effective retrieval for all expansion weights and different number of expansion entities.     

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.     

Design of a fast real-time LPV model predictive control system for semi-active suspension control of a full vehicle

This article is concerned with the control of a Semi-Active suspension system of a 7DOF Full Vehicle model, equipped with four Electro Rheological (ER) dampers, taking into account their incipient dissipativity constraints. Herein, a real-time, fast, advanced control structure is presented within the Model Predictive Control framework for Linear Parameter Varying (LPV) systems. The control algorithm is developed to provide a suitable trade-off between comfort and handling performances of the vehicle in a very limited sampling period ($T_s=5\text{ms}$), in view of a possible realtime implementation on a real vehicle. The control structure is tested and compared to other standard fast control approaches. Full nonlinear realistic simulation results illustrate the overall good operation and behaviour of the proposed control approach.