下一代图书馆系统平台的实践与思考

[目的/意义]大数据与人工智能等技术为图书馆智慧服务带来机遇与挑战，图书馆新系统平台建设刻不容缓。旨在探讨下一代图书馆系统平台发展现状及对策，为建设一流高校智慧图书馆提供实践案例与参考依据。[方法/过程]梳理图书馆系统平台发展脉络，在盘点现有的国内外下一代图书馆系统平台的研究与实践的基础上，以南京大学为例，探索图书馆新系统平台的建设方案。[结果/结论]智慧图书馆将通过建设一体化电子资源管理平台并打造NLSP，提升图书馆资源管控和知识服务水平，构建开放共享的智慧图书馆服务体系。     

学习团队协作信息搜索的共享心智模型研究

[目的/意义] 对协作信息搜索进行深入研究，为专业化协作信息搜索系统平台建设优化等提供启发和借鉴。[方法/过程] 聚焦于学习团队的信息搜索行为，以高校学生为研究样本，以共享心智模型为切入点，采用扎根理论研究方法，探讨协作信息搜索中团队共享心智模型建构过程。[结果/结论] 识别出四大核心环节——个体感知与探索、团队任务解析、团队信息收集和团队信息整合，并理清各环节的认知活动与共享心智模型内容要素。     

图书情报学领域学科交叉及其国家差异的动态分析

[目的/意义]领域知识的跨学科交叉研究能够打破学科间的壁垒,有助于发现重大科学问题的解决方案。[研究设计/方法]基于图书情报学领域文献题录信息构建轻量级领域知识图谱,从中提取学科信息、国家信息、时间信息及其关联,采用时间与空间相结合的多维度分析方法,对学科交叉的演化进程以及国家差异进行跟踪与分析。[结论/发现]图书情报学领域内学科交叉现象日渐显著,各国家的学科交叉程度与倾向存在差异,一些目前尚不突出的交叉学科方向值得关注。[创新/价值]采用多维度视角分析学科交叉现象,相关结论可以为国家科技战略制定及学科发展规划提供有益参考。     

Olfaction and emotion: The quest for olfactory restoration in two speech communities

ABSTRACT

Olfaction has been described as one of the least studied of the senses. This has certainly proven true in Communication. This project applies Ethnography of Communication and Cultural Discourse Analysis to examine the role that olfaction plays in the cultural meaning systems of two speech communities: residents surrounding the Gowanus Canal and bereaved parents. The cultural hub used to explore the cultural significance of olfaction in both speech communities is feeling. The analyses illustrate how emotions are tied to associated sensations and further become activated through radiants of dwelling, relating and acting. The analysis also shows how olfaction may serve to unify and separate members of a community. The significance of this research encourages stretching the boundaries of communication studies by examining the less studied physical senses and the boundaries of Cultural Discourse Analysis by providing distinctions that others can incorporate when examining feelings.     

Comparing cumulative index and factor analytic approaches to measuring maltreatment in the National Longitudinal Study of Adolescent to Adult Health

Child maltreatment is a complex and multifaceted construct in need of advanced statistical techniques to improve its measurement. The current study compared the predictive utility of a cumulative index to a factor analytic approach for constructing a measure of maltreatment. Data were from Waves III and IV of the National Longitudinal Study of Adolescent to Adult Health (Wave III: n = 14,800; Wave IV: n = 12,288). As adults, participants retrospectively reported on their childhood experiences of physical abuse, sexual abuse, emotional abuse, physical neglect, supervisory neglect, and social services investigations. Both the cumulative index and a two-factor solution showed evidence of convergent validity, predicting lifetime incidence of homelessness, being paid for sex, and various measures of running away or living apart from biological parents, and prospectively predicting depression, substance use, and criminal behavior. The latent variables, derived from a factor analytic approach, had greater explanatory power for many outcomes compared to the cumulative index, even when controlling for sociodemographic variables. Results suggest that factor analysis is a better methodology than a cumulative index for measuring maltreatment in large datasets when explanatory power for external outcomes is of greatest concern.     

Digital Module 16: Longitudinal Data Analysis

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

多旋翼无人机微多普勒特性分析与特征提取

针对多旋翼无人机目标的识别问题，提出一种基于伽柏（Gabor）变换的瞬时频率估计与快速傅里叶变换（FFT）相结合的微多普勒特征提取算法。首先建立多旋翼无人机旋翼回波模型，并通过仿真分析叶片数目、旋翼转速和初始相位等参数对微多普勒特征的影响，利用Gabor变换得到时频特征。在此基础上通过瞬时频率极大值法提取微多普勒频率，并对瞬时频率采用FFT提取旋翼数和转动频率，从而获得叶片长度估计值。实测数据验证了该算法较为准确地提取无人机的微多普勒参数。     

大数据时代个人信息保护研究综述

[目的/意义]通过梳理大数据时代个人信息保护的研究文献，为未来研究个人信息保护提供借鉴。[方法/过程]利用CNKI数据库，系统收集关于大数据时代个人信息保护的国内核心期刊论文，对文献的内容进行分析，归纳研究主题，并进行论述。[结果/结论]将现有的研究成果按主题分为5类：国内外实践经验研究、基本理论问题研究、个人信息保护机制探索、个人信息安全风险与应对、相关法律法规研究，评述现有研究的不足之处并对未来的研究方向提出展望。     

小学体育兴趣化游戏教学的多维性探索

随着新一轮教改工作在我国全国范围内的深入开展,体育已经成为各地小学素质教育工作中的重点内容。就目前来看,为进一步提高小学体育教学效率,兴趣化游戏教学已经逐步被引入实际教学工作中,该教学模式可以冲破传统教条主义教学思维的拘束,进一步提高学生对学习的兴趣,使被动学习转变为主动学习,从而更好地实现当今时代小学体育教学工作目标。