高等教育投资项目社会评价指标体系的分析与构建

我国高等教育的高速发展对高等教育投资主体和资金来源多元化提出了新的要求。如何对高等教育投资项目的经济和社会效益进行合理评价 ,这既是各投资主体关注的重点 ,也是高等院校如何加快高等教育建设步伐的核心问题。由于高等教育所具有的特殊性 ,目前 ,我国对高等教育投资项目的效益问题研究甚少 ,而高等教育投资项目的社会评价问题更是刚刚起步。本文在深入研究教育经济学及建设项目评价相关知识的基础上 ,总结了高等教育投资项目社会评价的基本特点 ,进而构建了高等教育投资项目社会评价指标体系。这对建立和完善高等教育投资项目评价理论 ,正确进行高等教育投资决策奠定了坚实的基础。     

Exploring album structure for face recognition in online social networks

In this paper, we propose an album-oriented face-recognition model that exploits the album structure for face recognition in online social networks. Albums, usually associated with pictures of a small group of people at a certain event or occasion, provide vital information that can be used to effectively reduce the possible list of candidate labels. We show how this intuition can be formalized into a model that expresses a prior on how albums tend to have many pictures of a small number of people. We also show how it can be extended to include other information available in a social network. Using two real-world datasets independently drawn from Facebook, we show that this model is broadly applicable and can significantly improve recognition rates.     

Guidelines for facilitating the development of learning communities in online courses

Online learning has grown exponentially in recent years; however, dropout problem remains challenging for some online programmes. The dropout problem can be attributed to a number of reasons, with a lack of interaction between learners and the instructor constituting one of the main reasons. The lack of interaction also leads to learners' feeling of isolation. Learning communities can provide learners with an environment conducive to increased interactions and alleviate their feeling of isolation. Unfortunately, there are no clear rules that instructors can follow to help learners create learning communities. In this paper, we propose guidelines for online instructors to facilitate the development of learning communities in online courses. We first review the definition of a learning community, importance of a learning community and factors affecting the development of a learning community. Afterwards, based on a review of the existing guidelines and other relevant literature, we propose guidelines for facilitating the development of learning communities in online courses.     

PRIVACY LEAKAGE IN HEALTH SOCIAL NETWORKS

Members of health social networks may be susceptible to privacy leaks by the amount of information they leave behind. The threat to privacy increases when members of these networks reuse their pseudonyms in other social networks. The risk of re‐identifying users from such networks requires quantitative estimates to evaluate its magnitude. The estimates will enable managers and members of health social communities to take corrective measures. We introduce a new re‐identification attack, the social network attack, that takes advantage of the fact that users reuse their pseudonyms. To demonstrate the attack, we establish links between MedHelp and Twitter (two popular social networks) based on matching pseudonyms. We used Bayesian networks to model the re‐identification risk and used stylometric techniques to identify the strength of the links. On the basis of our model 7‐11. 8% of the MedHelp members in the sample population who reused their pseudonyms in Twitter were re‐identifiable compared with 1% who did not. The risk estimates were measured at the 5% risk threshold. Our model was able to re‐identify users with a sensitivity of 41% and specificity of 96%. The potential for re‐identification increases as more data is accumulated from these profiles, which makes the threat of re‐identification more serious.     

华北平原地下水资源承载力评价

华北平原地下水严重超采,并带来一系列资源环境问题,地下水资源承载力的可持续性面临严重挑战。本研究定义了地下水资源承载力的概念,提出了一种定量评价地下水承载力的新方法,并对华北平原地下水承载力进行了评价。结果表明,华北平原地区地下水资源支撑的GDP从2003年的15 608.18亿元迅速提高到2011年的37 584.9亿元,33.3%的地市位于未超采未超载区;华北平原整体及57.2%的地市均位于超采未超载区,已发生地下水超采,但通过提高用水效率,未来社会经济规模仍有发展空间;9.5%的地市位于超采超载区。最后探讨地下水资源的承载力的提高途径,主要包括增加地下水资源可利用量和提高用水效率两方面,其中提高用水效率效果更显著。     

Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.     

环境保护与汽车涂装

叙述了与汽车涂装相关的国际环保法规及汽车涂装的公害,重点介绍了汽车用环保型涂料、5R活动和3C1B涂装技术等环保达标措施.     

Research on the measure method of complaint theme influence on online social network

Consumer complaints on online social network quickly become online groups complaints through many people’s aggregation and looking on, interaction and word-of-mouth communication. Therefore, assessing and managing online complain influence has become a new problem for enterprise to listen to and manage online group complaints. This paper analyzed the complaint information feature of consumer group on online social network, from three-dimensional perspective of complaint text’s quality, transmission timeliness and user interaction degree. We built the influence measure model of online complaint theme based on entropy weight model by monitoring and analyzing real-time the static and dynamic properties of complaint information, explored the measure method of complaint theme influence, employed empirical method to verify the validity and provided scientific decision-making tools and methods for enterprise listening to and managing online group complains.     

基于信息流动分析的动态社区发现方法

随着社交网络和微博等互联网应用的逐渐流行,其用户规模在迅速膨胀.在这些大规模网络中,社区发现可以为个性化服务推荐和产品推广提供重要依据.不同于传统的网络,这些新型网络的节点之间除了拓扑结构外,还进行频繁的信息交互.信息流动使得这些网络具有方向性和动态性等特征.传统的社区发现方法由于没有考虑到这些新的特征,并不适用于这些新型网络.在传染病动力学理论的基础上,从节点间信息流动的角度,提出一种动态社区发现方法.该方法通过对信息流动的分析来发现联系紧密、兴趣相近的节点集合,以实现动态的社区发现.在真实数据集上的实验结果表明：相对于传统的社区发现方法,所提出的方法能够更准确地发现社区,并且更能体现网络中社区的动态变化.     

基于多子群的社会群体优化算法

社会群体优化算法(social group optimization,SGO)是一种基于社会群体学习而提出的一种新型优化算法。针对社会群体优化算法易于陷入局部最优问题,提出了一种多群社会群体学习算法（MPSGO）。本算法采用多子群学习方法,对算法两个阶段的个体学习方法进行改进,在维持群体收敛性能的前提下提高群体多样性,同时对部分个体中引入量子学习,使个体学习的有用信息得以增强;此外,每隔一定代数对子群进行随机重组,既能保证各子群个体充分进化,又维持了子群多样性。在设计算法的基础上,分析了其收敛性和多样性;通过与其他四种算法进行对比实验,验证了改进后算法性能更优。