车联网环境下基于节点认知交互的路由算法

针对车联网（IoV）环境下消息传输效率低下、网络资源开销较大等诸多问题，提出一种适用于城市交通场景下基于车辆节点认知交互的路由算法。首先，依据信任理论提出节点认知交互度的概念，并在此基础上对车联网中的车辆节点进行分类，赋予它们不同的认知交互度初值；同时还引入车辆节点交互时间、交互频率、车辆节点物理间隔距离、间隔跳数以及消息生存时间等影响因子，进而构建了车辆节点认知交互评估模型。基于该模型计算并更新节点的认知交互度，并通过比较对应车辆节点间的认知交互度值来选取认知交互度相对较高的邻居节点作为中继节点进行消息转发。仿真实验结果表明，与Epidemic和Prophet路由算法相比，所提路由算法有效提高了消息投递率并降低了消息投递时延，同时显著降低了网络资源的开销，有助于提升车联网环境的消息传输质量。     

基于CNKI的X射线荧光光谱研究文献计量学分析

为客观掌握我国X射线荧光光谱(XRF)的研究进展,采用中国知网(CNKI)库内相关研究论文的年度分布、机构、基金、期刊来源等数据,结合Citespace的关键词分析方法,系统揭示了我国X射线荧光光谱的研究进展。结果表明:我国X射线荧光光谱研究处于快速发展阶段,每年论文发表数量呈指数增长;发表研究论文数量最多的是成都理工大学(69篇),总被引频次最高的机构是中国地质科学院国家地质实验测试中心(819次);目前X射线荧光光谱研究受到国家层面的基金支持力度不足;被引频次最高的论文第一作者是李国会(被引93次);发文量和论文被引率最高的期刊是《冶金分析》(300篇、占86.3%);总被引频次和篇均被引频次最高的期刊是《岩矿测试》(2541次、14.4次/篇);关键词分析结果表明,研究热点集中在样品制备、分析方法研究、检测应用;理论研究所占比例远远低于应用研究。所进行的研究对了解X射线荧光光谱的发展动态,推动相关研究工作的深化将产生重要的意义。     

物联网中基于Multi-Agent的物间动态关系发现

物联网中存在大量异构关系的实体，其信息间的交互造成了物联网的内在矛盾。针对这一问题，提出将物联网中实体抽象化为对应的Agent，并以个体人为中心，利用本体的语义匹配及改进的物间动态关系计算方法，计算出针对个体人的物间动态关系；将原本异构的实体关系转化为Agent间基于动态关系紧密度排序的网络关系。经实验验证，该方法构建的关系网络可明显改善异构实体间交互的矛盾，而且相比原有类似方法，该方法解决问题的准确率和误差率均有改善，说明了该方法的准确性和可行性。     

以“互联网+”促进学前教育信息化建设

云计算、大数据、人工智能等技术的快速发展，有力地促进了“互联网+教育”的普及和应用。学前教育作为“互联网+”的重要应用领域，可以充分地利用人工智能、物联网、大数据等技术，实现学前教育硬件设备的互联互通，利用大数据搜索与推荐学前教育资源，基于人工智能开发可视化、虚拟化的学前教育课程，培养儿童的学习积极性和主动性，让学生养成一种良好的学习习惯，具有重要作用和意义。     

A mobile crowd sensing ecosystem enabled by CUPUS: Cloud-based publish/subscribe middleware for the Internet of Things

Mobile crowd sensing (MCS) is a novel class of mobile Internet of Things (IoT) applications for community sensing where sensors and mobile devices jointly collect and share data of interest to observe phenomena over a large geographic area. The inherent device mobility and high sensing frequency has the capacity to produce dense and rich spatiotemporal information about our environment, but also creates new challenges due to device dynamicity and energy constraints, as well as large volumes of generated raw sensor data which need to be processed and analyzed to extract useful information for end users. The paper presents an ecosystem for mobile crowd sensing which relies on the CloUd-based PUblish/Subscribe middleware (CUPUS) to acquire sensor data from mobile devices in a flexible and energy-efficient manner and to perform near real-time processing of Big Data streams. CUPUS has unique features compared to other MCS platforms: It enables management of mobile sensor resources within the cloud, supports filtering and aggregation of sensor data on mobile devices prior to its transmission into the cloud based on global data requirements, and can push information of interest from the cloud to user devices in near real-time. We present our experience with implementation and deployment of an MCS application for air quality monitoring built on top of the CUPUS middleware. Our experimental evaluation shows that CUPUS offers scalable processing performance, both on mobile devices and within the cloud, while its data propagation delay is mainly affected by transmission delay on wireless links.     

A secure and quality-aware prototypical architecture for the Internet of Things

The increasing diffusion of services enabled by Internet of Things (IoT) technologies raises several risks associated to security and data quality. Together with the high number of heterogeneous interconnected devices, this creates scalability issues, thereby calling for a flexible middleware platform able to deal with both security threats and data quality issues in a dynamic IoT environment. In this paper a lightweight and cross-domain prototype of a distributed architecture for IoT is presented, providing minimum data caching functionality and in-memory data processing. A number of supporting algorithms for the assessment of data quality and security are presented and discussed. In the presented system, users can request services on the basis of a publish/subscribe mechanism, data from IoT devices being filtered according to users requirements in terms of security and quality. The prototype is validated in an experimental setting characterized by the usage of real-time open data feeds presenting different levels of reliability, quality and security.     

Does internet dependence affect young people's psycho-social status? Intrafamilial and social relations,impulse control,coping ability and body image

The purpose of this study was to investigate the relation between internet dependence in university students in late adolescence and self-image. The research group consisted of first year university students studying in various departments of the Karadeniz Technical University Fatih Faculty of Education. The study was performed with 623 students, 454 female and 169 male. The Internet Dependence Questionnaire, the Offer Self-Image Questionnaire and a Personal Data Form were used for data collection. Pearson product moment coefficient and multiple linear regression analysis results showed that students' internet dependence was significantly negatively correlated with the self-image subdimensions intrafamilial and social relations, impulse control, coping ability and body image. Multiple linear regression analysis showed that the self-image subdimensions of intrafamilial and social relations and impulse control subdimensions significantly predict internet dependence.     

The Social Media Disorder Scale

There is growing evidence that social media addiction is an evolving problem, particularly among adolescents. However, the absence of an instrument measuring social media addiction hinders further development of the research field. The present study, therefore, aimed to test the reliability and validity of a short and easy to administer Social Media Disorder (SMD) Scale that contains a clear diagnostic cut-off point to distinguish between disordered (i.e. addicted) and high-engaging non-disordered social media users.Three online surveys were conducted among a total of 2198 Dutch adolescents aged 10 to 17. The 9-item scale showed solid structural validity, appropriate internal consistency, good convergent and criterion validity, sufficient test-retest reliability, and satisfactory sensitivity and specificity. In sum, this study generated evidence that the short 9-item scale is a psychometrically sound and valid instruments to measure SMD.     

ePASS: An expressive attribute-based signature scheme with privacy and an unforgeability guarantee for the Internet of Things

The Internet of Things (IoT) provides anywhere, anything, anytime connections, for which user privacy is vulnerable and authentication methods that favor policy over attributes are essential. Thus, a signature scheme that considers user privacy and implements an attributes policy is required. Emerging attribute-based signature (ABS) schemes allow a requester of a resource to generate a signature with attributes satisfying the policy without leaking more information. However, few existing approaches simultaneously achieve an expressive policy and security under the standard Diffie–Hellman assumption. Here we describe ePASS, a novel ABS scheme that uses an attribute tree and expresses any policy consisting of AND, OR threshold gates under the computational Diffie–Hellman problem. Users cannot forge signatures with attributes they do not possess, and the signature provides assurance that only a user with appropriate attributes satisfying the policy can endorse the message, resulting in unforgeability. However, legitimate signers remain anonymous and are indistinguishable among all users whose attributes satisfy the policy, which provides attribute privacy for the signer. Compared to existing schemes, our approach delivers enhanced performance by reducing the computational cost and signature size.     

Does technology empower urban youth? The relationship of technology use to self-efficacy

Many propose technology as a tool for empowerment of lower SES urban students, but little research has investigated the relationship between technology and empowerment for this population. We investigate how different aspects of technology use and ownership could empower urban youth through increasing their self-efficacy. Instead of simply a general measure of self-efficacy, we focus on several important domains related to STEM (Science, Technology, Engineering, and Mathematics) subjects including technological, mathematics/science, academic, and general self-efficacy. Our investigation incorporates many aspects of technology use by considering first level digital divide characteristics, such as ownership and total amount of use, and second level digital divide characteristics, such as specific communication, multimedia, content creation, and social networking activities. We use a unique survey of fourth and fifth grade students who were given a laptop, thereby controlling for the typical disparity in computer ownership and access among lower SES students. We found that technology use influences each domain of efficacy in specific ways, indicating the importance of considering multiple domains of self-efficacy. Most notably, frequency of communication and especially frequency of email use related to all four domains of efficacy and frequency of playing games related to general, mathematics/science, and academic efficacy. However, social networking activities had a negative association with academic and general efficacy. We conclude by considering the importance of multiple domains in self-efficacy research and policy implications for students and their schools.