桓谭《新论》中狗怪故事的深层意蕴

桓谭《新论》中记载了两个狗怪故事：狗成为精怪,并以家中刚死去不久的人的身份和面貌出现,让世间人厌恶,最后被打死。狗具备灵性,曾充当很多部族的图腾,使人们相信狗会成精,以狗为图腾的部族与汉民族关系不错,使人们相信即使狗成精也不会伤害人类,因此故事中两只狗精没有给人带来多大灾难。但是汉代的谶纬迷信、人们的生存本能使人们对＂精怪＂的特殊本领有深层恐惧;汉代的生产力水平使得人们在面对自然界的猛兽时处于劣势,因此一直站在与＂魑魅魍魉＂等猛兽精怪对立的立场。人们的恐惧导致了狗怪被打死的厄运。     

新媒体时代对女性的“看”与“被看”——重新解读作为文本的“芙蓉姐姐”和“李宇春”

从芙蓉姐姐异化的形象中,男性畸形的女性审美观念暴露无遗;从李宇春的“中性”形象中,我们看到了新时代女性的继续突围,不断从正面打破男性主导的女性审美价值;从二者逐渐回归男性主导的女性审美价值来看,男性话语权力和大众传媒的规训实在是太强大了,揭示了女性在表达自己的过程中的困境和隐含的陷阱.     

SmartRolling: A human–machine interface for wheelchair control using EEG and smart sensing techniques

Smart wheelchairs based on brain–computer interface (BCI) have been widely utilized recently to address certain mobility problems for people with disability. In this paper, we present SmartRolling, an intuitive human–machine interaction approach for the direct control of robotic wheelchair that jointly leverages EEG signals and motion sensing techniques. Specifically, SmartRolling offers two wheelchair-actuation modes for users with different physical conditions: (1) head motion only — people who are severely disabled but able to do basic tasks using eyes and head, and (2) head and hands motion — in addition to type 1, people who can use functioning hands/arms for extra tasks. The system issues operation commands by recognizing different EEG patterns elicited by motor execution (ME) tasks including eye blink, jaw clench, and fist open/close, while at the same time estimates users’ steering intentions based on their facing direction by leveraging inertial measurements and computer vision techniques. The experiment results demonstrate that the proposed system is robust and effective to meets the individual’s needs and has great potential to promote better health.     

Positivity and quality of college life of business students: The mediating role of learning approaches

Drawing upon the causal agency theory, this study examined the direct and indirect (via learning approaches) links between positivity and quality of college life (QCL) of business students in a transitioning market, Vietnam. Two studies were conducted to test these relationships using structural equation modeling. Findings from study 1, based on a sample of 428 business students, showed that positivity was positively related to QCL. Further, deep learning approaches mediated the relationship between positivity and QCL. Findings from study 2, based on a sample of 416 business students, reconfirmed the role of positivity in QCL. However, the indirect relationship between positivity and QCL was not significant, demonstrating that surface learning approaches did not mediate the relationship between positivity and QCL. The findings contribute to the literature on positivity in higher education by confirming the overarching role that positivity plays, directly and indirectly (via deep learning approaches), in QCL.     

Understanding the overvaluation of facial trustworthiness in Airbnb host images

Renting a property via a peer-to-peer platform involves a variety of risks. Humans inherently, subconsciously use facial cues as important shortcuts in making assessments about other persons. On property sharing platforms, such as Airbnb, facial cues can be used in a similar fashion alongside reputational information. According to Dangerous Decisions Theory (DDT), intuitive evaluations of trustworthiness based on faces can bias subsequent assessment of an individual, requiring further information sources to make a more balanced assessment. In this study we apply DDT to demonstrate that evaluations based on perceived facial trustworthiness are overvalued; when combined with reputational measures, such as ‘super host’ status, such assessments are diminished. The study is based on deep learning to classify host faces for a large data set of online accommodation (n = 78,386). The research demonstrates that facial trust cues in online platforms should be treated with caution and must be combined with more objective measures of reputation in order to reduce the effects of overvaluation. The paper concludes with implications for practice and future research.     

深度学习及其对图书情报学的启示

深度学习是一种新颖的机器学习方法,它已经在图像识别、语音识别、信息检索等诸多领域广泛应用并取得了巨大成功。然而,笔者参阅了近年来国内主流的情报学文献,并未发现有关深度学习的研究成果。因此,本文旨在图书情报领域引入深度学习技术,重点探讨深度学习的基本理论、应用、下一步研究重点以及对情报学的启示等问题,以期为解决图书情报学研究面临的诸多问题提供重要参考。     

深阅读:概念构建与路径探索

深阅读是多学科讨论的热点概念,当前社会面临“深阅读危机”,促进深阅读已成为全民阅读推广的核心任务,但至今未见对深阅读的明确界定和具体阐释。现有研究对深阅读的理解主要有三个维度:与信息获取相关,与感受相关,与交流相关;而“参与性”是深阅读的基本属性。鉴于深阅读既是主体的参与行为,又是外部环境的作用结果,本文根据“生成认知”理论将深阅读定义为:读者这一具有心智能力的有机体与适合其条件的阅读对象相遇,在适宜的情境下产生积极的行为动力,进而发展而来的高参与度的阅读行为。文章剖析了深阅读对读者和社会的当代意义,认为数字时代深阅读的意义在于其具有“复合”价值,而新文本、新读者、新环境召唤着新型深阅读,应以创造相遇、丰富体验、回归对话为导向开展阅读推广工作。图1。参考文献 53。     

The effect of peer feedback for blogging on college students' reflective learning processes

Reflection is an important prerequisite to making meaning of new information, and to advance from surface to deep learning. Strategies such as journal writing and peer feedback have been found to promote reflection as well as deep thinking and learning. This study used an empirical design to investigate the interaction effects of peer feedback and blogging on college students' reflective thinking skills and their learning approaches. Forty-four first- and second-year undergraduate students participated in the study. Students kept blogs each week throughout a whole semester. Two journals were sampled at the beginning and end of the semester for each student. A repeated measure one-way ANOVA suggested that students' reflective thinking level increased significantly over time; however, peer feedback was found to negatively affect students' reflective thinking skills. The result of the study suggests more carefully designed uses in the future.     

比喻的结构模式及与其相关的几个问题

在比喻的深层有思维结构和信息结构,以此为基础,用演绎法可推导出表层有15类64种基本的结构模式;比喻的深层结构和表层结构形成了五个不同层次的比喻同义世界系统,其中有潜比喻和显比喻、零度比喻和偏离比喻。     

Research on evaluation model for interactive classroom enabled with mobile terminals

Information and Communication Technology (ICT) has improved education widely in China, transforming traditional teaching into an interactive one. It is important to build a new evaluation model to measure teaching efficiency in an “ICT-enabled classroom”. This study designed an evaluation model named “TPOCME Deep classroom” through ongoing five iterations. It includes six dimensions, which are higher-order Thinking, classroom Participation, Openness of educational system, Cooperative learning, Meaningful learning and Effectiveness of technology use (named TPOCME). This model helps educational researchers and teachers gain a comprehensive understanding of ICT in education.