Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction

This paper deals with the problem of adaptive output feedback neural network controller design for a SISO non-affine nonlinear system. Since in practice all system states are not available in output measurement, an observer is designed to estimate these states. In comparison with the existing approaches, the current method does not require any information about the sign of control gain. In order to handle the unknown sign of the control direction, the Nussbaum-type function is utilized. In order to approximate the unknown nonlinear function, neural network is firstly exploited, and then to compensate the approximation error and external disturbance a robustifying term is employed. The proposed controller is designed based on strict-positive-real (SPR) Lyapunov stability theory to ensure the asymptotic stability of the closed-loop system. Finally, two simulation studies are presented to demonstrate the effectiveness of the developed scheme.     

Managing research and innovation networks: Evidence from a government sponsored cross-industry program

Important innovations are increasingly produced based on research engagement and fertilization across industries. However, we know little about the challenges associated with managing innovation networks in specific contexts that involves researchers in cross-industry collaboration. Against this backdrop, we draw on theory on design and orchestration of innovation networks to analyze a large-scale government sponsored program, “ProcessIT Innovations” that was designed to increase competitiveness and accelerate economic growth in Northern Sweden. The program was initiated and led by firms from the traditionally strong local process industry and engaged local researchers and firms from the emerging IT industry. Based on our analyses, we offer two contributions. First, we provide a detailed analysis of the challenges related to configuration of the network, orchestration of partnerships between participants, and facilitation of innovation in dedicated development projects. Second, we propose a model of managing research and innovation networks through fertilization across industries and between firms and research institutions.     

网络环境下基层科技信息机构的信息服务

本文论述了网络环境下科技信息机构要结成联盟，注重网络信息资源开发和科技网站建设，提高信息服务人员的素质。     

四种搜索引擎的比较研究

本文对目前常用的4种中文搜索引擎：Google、百度、天网、Openfind的索引数据库收录范围、检索功能、检索结果显示格式、用户界面等方面进行了比较分析，并指出它们各自的优势与不足。     

基于共轭分析的网络对抗效能评估

本文为了探讨影响网络对抗效能评估的众多因素,利用可拓学中的共轭分析进行研究。介绍了共轭分析原理中的虚实、软硬、潜显和负正这四对概念,并利用这四对概念分别从网络对抗系统的物质性、系统性、动态性和对立性这四个方面分析影响其效能的各种因素,为网络对抗效能评估提供了新的思路。     

图书馆信息资源建设宏观与微观的把握

从阐述图书馆信息资源建设入手,提出了搞好图书馆信息资源建设的宏观举措,并指出要在微观上切实促进馆藏文献资源的开发利用。参考文献9。     

网络环境下如何做好纸本科技期刊阅读服务

本文主要论述了网络环境下,纸本科技期刊生存状态受到冲击,并从三个方面提出了改进期刊的服务措施。     

高校网络思政教育与传统思政教育互动模式研究

文章首先概括了网络思想政治教育与传统思想政治教育互动模式,然后阐述了高校网络思政教育和传统思政教育的优势,最后提出了几点优化策略,主要包括加强高校思政网站建设、加强高校互动机制的构建、延伸传统思政教育内容、强化思政教育的辅助性作用等,从而实现高校网络思政教育与传统思政教育的互动整合目标。     

Core–periphery structures in national higher education systems. A cross-country analysis using interlinking data

This paper presents a comparative analysis of the structure of national higher education networks in six European countries using interlinking data. We show that national HE systems display a common core–periphery structure, which we explain by the lasting reputational differences in science, as well as the process of expansion and integration of HE systems. Furthermore, we demonstrate that centrality in national networks (coreness) is associated with organizational characteristics, reflecting that interlinking is motivated by access to resources and the status of the organizations concerned, and that national policies impact network structures by influencing the level of inequality in the distribution of resources and status. Finally, we show that, as an outcome of the core–periphery structure, the strength of ties between two HEIs is largely determined by their individual coreness, while the impact of distance is too small-scale to alter the network structure generated by organizational attributes.     

Mathematical properties of Q-measures

Q-measures are network indicators that gauge a node's brokerage role between different groups in the network. Previous studies have focused on their definition for different network types and their practical application. Little attention has, however, been paid to their theoretical and mathematical characterization. In this article we contribute to a better understanding of Q-measures by studying some of their mathematical properties in the context of unweighted, undirected networks. An external Q-measure complementing the previously defined local and global Q-measure is introduced. We prove a number of relations between the values of the global, the local and the external Q-measure and betweenness centrality, and show how the global Q-measure can be rewritten as a convex decomposition of the local and external Q-measures. Furthermore, we formally characterize when Q-measures obtain their maximal value. It turns out that this is only possible in a limited number of very specific circumstances.