非权力因素在校长治校中的地位和作用

校长在办学治校中,依靠的不仅是法定权力和工作阅历,更重要的是在学校管理工作中如何充分发挥校长的非权力影响力.     

Stability of switching linear systems with switching signals driven by stochastic processes

This paper presents conditions to assure the exponential stability in probability for autonomous switching linear systems. The switching signal acting on the autonomous system produces intervals that follow independent, identically distributed stochastic processes—the stability then follows by verifying simple-to-check linear matrix inequalities.     

知识网络方法在城市产业技术选择中的应用——以北京建设科技创新中心产业技术选择为例

产业技术选择是城市发展中一项重要的决策内容。传统产业技术选择方法,诸如德尔菲法、层次分析法等,面临着技术分属领域跨度大,颗粒度大小难界定,以及专家主观判断依赖性大的问题。本研究旨在利用知识网络理论,结合文献计量的量化方法,打破传统产业技术选择的局限,帮助城市识别所需的产业技术。本研究以北京的产业技术选择为例,从梳理国家研究机构发布的技术预测结果为起点,筛选与北京城市发展相关度高的产业技术,并结合知识网络理论,量化产业技术在知识网络中的特征参数,并探讨整体网络参数对产业技术选择与政策设计的影响,由此作为城市发展规划中产业选择以及后续产业政策制定的重要参考依据。研究认为,基于知识网络基础的量化方法,在一定程度上解决了现有决策方法偏重定性分析的问题,为城市产业技术选择提供了一种具有科学依据、能够量化评价的分类方法。     

基于C-OWA算子的业主驱动下BIM应用效益灰色聚类评价

随着BIM的推广普及和深化应用,构建一套科学可行的BIM效益评价体系对推动BIM落地和效益发挥具有非常重要的现实意义。本文在文献综述的基础上,从BIM应用现状和业主方项目管理目标的视角出发,从七个维度建立了业主方驱动下的BIM效益评价指标,运用C-OWA算子赋权法和灰色系统理论进行评价,提出了业主方BIM应用效益评价指标体系,为BIM应用的前期决策和后期评价提供参考,促进BIM效益的真正发挥。     

关于我国科技决策智库人才队伍建设研究

科技决策智库发展水平与人才队伍素质关系日益密切,加强人才队伍建设是推动科技决策智库发展的必经之路。分析科技决策智库人才相关前期研究基础及国内外智库人才相关评价指标,搭建科技决策智库人才队伍结构,分析不同类型人才素质要求,梳理国外科技决策智库在引人、育人、用人、留人等方面经验做法,研究我国科技决策智库人才队伍建设总体情况及存在问题,最终提出启示建议。     

Information retrieval in the workplace: A comparison of professional search practices

Legal researchers, recruitment professionals, healthcare information professionals, and patent analysts all undertake work tasks where search forms a core part of their duties. In these instances, the search task is often complex and time-consuming and requires specialist expertise to identify relevant documents and insights within large domain-specific repositories and collections. Several studies have been made investigating the search practices of professionals such as these, but few have attempted to directly compare their professional practices and so it remains unclear to what extent insights and approaches from one domain can be applied to another. In this paper we describe the results of a survey of a purposive sample of 108 legal researchers, 64 recruitment professionals and 107 healthcare information professionals. Their responses are compared with results from a previous survey of 81 patent analysts. The survey investigated their search practices and preferences, the types of functionality they value, and their requirements for future information retrieval systems. The results reveal that these professions share many fundamental needs and face similar challenges. In particular a continuing preference to formulate queries as Boolean expressions, the need to manage, organise and re-use search strategies and results and an ambivalence toward the use of relevance ranking. The results stress the importance of recall and coverage for the healthcare and patent professionals, while precision and recency were more important to the legal and recruitment professionals. The results also highlight the need to ensure that search systems give confidence to the professional searcher and so trust, explainability and accountability remains a significant challenge when developing such systems. The findings suggest that translational research between the different areas could benefit professionals across domains.     

Creating value from Social Big Data: Implications for Smart Tourism Destinations

This paper aims to demonstrate how the huge amount of Social Big Data available from tourists can nurture the value creation process for a Smart Tourism Destination. Applying a multiple-case study analysis, the paper explores a set of regional tourist experiences related to a Southern European region and destination, to derive patterns and opportunities of value creation generated by Big Data in tourism. Findings present and discuss evidence in terms of improving decision-making, creating marketing strategies with more personalized offerings, transparency and trust in dialogue with customers and stakeholders, and emergence of new business models. Finally, implications are presented for researchers and practitioners interested in the managerial exploitation of Big Data in the context of information-intensive industries and mainly in Tourism.     

高校新闻教学改革新探

培养懂理论、强业务、视野开阔、具有跨国沟通和协调能力的新闻人才的要求对高校新闻教学提出了新的挑战,高校必须改革新闻教学的理念及方法,精心选择和利用好教学案例,切实构建科学的教学体系,推动新闻教育的发展.     

Meta-Circuit machine: Inferencing human collaborative relationships in heterogeneous information networks

Human collaborative relationship inference is a meaningful task for online social networks and is called link prediction in network science. Real-world networks contain multiple types of interacting components and can be modeled naturally as heterogeneous information networks (HINs). The current link prediction algorithms in HINs fail to effectively extract training samples from snapshots of HINs; moreover, they underutilise the differences between nodes and between meta-paths. Therefore, we propose a meta-circuit machine (MCM) that can learn and fuse node and meta-path features efficiently, and we use these features to inference the collaborative relationships in question-and-answer and bibliographic networks. We first utilise meta-circuit random walks to obtain training samples in which the basic idea is to perform biased meta-path random walks on the input and target network successively and then connect them. Then, a meta-circuit recurrent neural network (mcRNN) is designed for link prediction, which represents each node and meta-path by a dense vector and leverages an RNN to fuse the features of node sequences. Experiments on two real-world networks demonstrate the effectiveness of our framework. This study promotes the investigation of potential evolutionary mechanisms for collaborative relationships and offers practical guidance for designing more effective recommendation systems for online social networks.