社保系统个人信息隐私保护算法

针对社会保障信息系统中公民的个人信息隐私保护越来越困难的现状,介绍了社保系统的隐私保护难题包括如何保护信息安全和如何界定隐私信息2个方面,分析了隐私信息保护的2个根源性问题在于个人信息的不当采集和不当使用,在此基础上提出了利用转换原始数据的方式保护隐私信息的算法,阻止了信息拥有者对隐私信息直接或间接的获取,为社保系统中个人信息隐私保护的实现提供了一定的研究思路。     

面向老年人的社会化网络服务平台研究

针对目前已有社会化网络服务对社会影响的研究更侧重于青少年,对老年人群体研究相对较少的情况,本文研究了面向老年人的社会化网络服务平台,介绍了平台的体系结构,阐述了社交系统、数据分析和信息服务。此平台利用面向老年人的社交网络服务系统获得用户行为数据,在数据集成、时空数据仓库存储的基础上,通过建立老年人社会网络行为的数学模型,运用统计学方法进行建模分析,分析结果可为多层次人员提供不同的信息服务。     

Oxytocin Signaling as a Target to Block Social Defeat-Induced Increases in Drug Abuse Reward

There is huge scientific interest in the neuropeptide oxytocin (OXT) due to its putative capacity to modulate a wide spectrum of physiological and cognitive processes including motivation, learning, emotion, and the stress response. The present review seeks to increase the understanding of the role of OXT in an individual’s vulnerability or resilience with regard to developing a substance use disorder. It places specific attention on the role of social stress as a risk factor of addiction, and explores the hypothesis that OXT constitutes a homeostatic response to stress that buffers against its negative impact. For this purpose, the review summarizes preclinical and clinical literature regarding the effects of OXT in different stages of the addiction cycle. The current literature affirms that a well-functioning oxytocinergic system has protective effects such as the modulation of the initial response to drugs of abuse, the attenuation of the development of dependence, the blunting of drug reinstatement and a general anti-stress effect. However, this system is dysregulated if there is continuous drug use or chronic exposure to stress. In this context, OXT is emerging as a promising pharmacotherapy to restore its natural beneficial effects in the organism and to help rebalance the functions of the addicted brain.     

融合节点状态信息的跨社交网络用户对齐

提出一种融合节点状态信息的跨社交网络用户对齐方法, 通过网络表示捕获节点的局部特征和节点状态信息得到每个账户的嵌入向量, 计算不同账户对应表示之间的相似性发现对齐用户。在2个真实数据集上的试验结果表明, 提出的方法相对于其他方法可以对齐更多的用户。在预测不同尺度的top-k时, 提出的方法在网络结构较稠密的Twitter-Foursquare数据集上能够在top-9时对齐准确率达到50%且在稀疏且大网络数据集DM-ML上相比其他方法对齐准确率提高12.06%~36.62%;在分析F1-score时, 提出的方法能够有效提高用户对齐的性能。     

论大学生社会责任感的培养

社会责任感的重要性在当今社会里凸显出来。可是，在多种因素的作用下，部分大学生的社会责任感却趋于淡化，这使大学生难以担负起历史的重任。对于部分大学生重才而轻德的现象，高等教育应该承担一定社会责任，这种社会责任就在于强化大学生的社会责任感。     

基于小波的实时烟雾检测*

传统的离子式、吸气式、光电式等烟雾检测器在大空间中检测烟雾时,会受到发射信号与接收信号之间的距离、平面角度、精确对准等限制,无法对整个空间的烟雾状况进行描述.新的方法通过监测区域的摄像机拍摄的视频图像序列,进行小波变换,分析图像帧在时域和空域的频率特性,来确定被监测区域是否有火灾烟雾的发生.实验证明该方法不受空间高度、热障、易爆、有毒等环境的限制,并且有灵敏度高、抗干扰力强、适用范围广等特点.     

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.