云计算在高校校园网资源管理中的应用

校园网以云计算为核心架构，可以实现基础设施与实际应用的分离，解决校园网面临的资源共享、设备更新、管理统一等问题，促进教师的教学和科研工作，丰富学生的学习和生活，并为资源的存储和安全提供的保障。     

高校思想政治教育网络教育手段的理性分析

网络技术运用于高校思想政治教育,不仅丰富了思想政治教育的途径和方式,而且也有效地拓展了思想政治教育的空间。但是由于思想观念、技术水平的差异性,网络为思想政治教育提供的手段并没有得到充分地开发利用。因此,大胆实施改革创新,不断完善网络教育手段和方式,是促使思想政治教育功能得以最大程度发挥的重要基础。     

高铁网络下的中国十大城市群旅游交通格局及其经济联系的比较研究

旅游交通是旅游经济发展中重要的内容之一,通过对中国十大城市群城市旅游交通可达性、铁路交通流分布情况与旅游经济联系、总量和隶属度进行计算,借助Arcgis10.2对中国十大城市群交通空间流分布情况和旅游经济联系进行空间可视化处理,并对计算结果进行综合比较分析。研究发现:高铁使得中国十大城市群城市旅游交通可达性水平得到大幅提升,且交通流分布均衡。中国十大城市群城市可达性的提升给城市旅游经济带来了一定的积极影响。高铁网络下中国十大城市群旅游经济联系分布不均衡。     

中小型企业网络的设备部署及配置研究

目前企业都在信息化,网络是企业必不可少的.而网络设备的部署则是一切的开端,只有将宽泛合理应用才能搭建一个良好的网络环境.目前网络设备部署大多采用多层交换网络.网络设备的选择必须根据实际做出适当的调整,以实际情况为最优先考虑,才能为企业设计出最合适的智能网络.     

On the reciprocity of connections in weighted and unweighted networks

Bivariate Bernoulli and bivariate geometric distributions are proposed to model reciprocity in weighted and unweighted networks. Sampling properties of commonly used reciprocity measures are studied, under both presence and absence of reciprocity. Extensions to situations where link parameters depend on outgoing and incoming nodes are investigated. Results are illustrated with a data set, on 50 anesthesia providers at a hospital, that describes the number of times an anesthesia provider starting an operation transfers his/her responsibilities to another anesthesia provider.     

党政机构微博在突发事件中传播效果的影响因素及策略

在分析铁路货运量预测方法的基础上，针对标准BP神经网络的不足，提出改进的BP神经网络预测模型。首先,利用动态陡度因子来改变激励函数的陡峭程度，以此来得到更好的激励函数响应特征以及更好的非线性表达能力；其次，利用附加动量因子，通过对以前经验的积累，既降低了神经网络对误差曲面的局部细节敏感特性，又较好的遏制了神经网络易于限于局部最小的缺陷；最后，采取改变学习率的方法，给定一个较大的学习率初始值，在学习的过程中学习率不断减小，网络最终趋于稳定。改进BP算法既可以得到更优的解，还能够缩短训练时间。利用全国铁路货运     

Social network and family business: Uncovering hybrid family firms

What does it mean for a private enterprise in China to be embedded in a family? Our purpose here is twofold: (1) use social network analysis to describe what it means for a firm to be embedded in a family, (2) reveal from the application a new kind of firm, not family, yet akin to family. Armed with data on a large probability sample of private enterprises — a third of which meet ownership and employment criteria of being family businesses — we uncover a category of “hybrid family firms” that look modern in the style of firms that exclude family, but operate socially in ways similar to family firms. Our conclusion from summary statistics on the sample is that there are no differences in average performance level or network advantage for the three categories of businesses: family firms, hybrid family firms, and family-excluded firms. The fact that CEOs of family firms and hybrid family firms more often turn to family as key business contacts is a fact about network composition that raises no question about network mechanisms. Whether the CEO turns to more or fewer family contacts, government help is more likely with stronger political connections, and business success and survival are more likely with a large, open network. That said, the look-modern, act-traditional hybrid family firms stand alone in prospering with a CEO embedded in a closed business network. Recognition of hybrid family firms adds to the literature’s illustrations of social network analysis used to distinguish types of businesses and business people, and extends the population of organizations within which governance and strategy are likely to be better understood when viewed through a family logic.     

基于消费者显著性偏好的双边平台转换成本和定价策略研究

针对消费者对转换成本和价格属性具有显著性偏好的实际情况，基于显著性理论对垄断双边平台企业的转换成本和定价策略问题进行了研究。研究发现：1)在显著性偏好非对称型市场上，对价格敏感的一方收取的价格最低，对高转换成本的一方收取的价格最高，而在显著性偏好对称型市场上，平台的最优价格位于非对称型市场之间，但是对价格敏感型市场收取的价格低于转换成本敏感型市场的价格。2)在高转换成本的市场，平台利润最低；低转换成本市场平台利润最高，而混合型情况的最优利润位于这两者之间。该研究结论说明平台企业应该采取措施来降低用户加入平台的转换成本，从而增加利润，这与现实的案例研究结论相吻合。     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.