Affordances of social media in collective action: the case of Free Lunch for Children in China

This paper studies the socialised affordances of social media in the processes of collective action, exploring the role of technology in the under‐researched area of civil society. We examine the case of Free Lunch for Children (FL4C), a charitable programme in China based on the microblogging platform, Weibo. Adopting the perspective of affordances‐for‐practice, we draw upon the collective action model to better understand the sociomaterial practices and social processes involving social media, and seek to address the ‘when’ and ‘how’ questions of affordances. The study generates theoretical and practical implications for understanding the role of social media in social transformation.     

Internet messaging: An examination of the impact of attitudinal,normative, and control belief systems

While instant messaging (IM) has been very popular among teenagers and college students for social and recreation communication, its use in corporate settings has been limited. We examined the factors that influence the intention to use and actual use of IM. A research model was developed based on diffusion of innovation and Socio-psychological theories. The model examined the influence of seven variables in three belief structures (the attitudinal, normative, and control). The model was empirically validated using a field survey of 349 respondents. The results indicated that five of the seven variables explained about 41% of the variance in the intention to use IM. The five significant variables were: utilitarian beliefs, hedonic beliefs, subjective norms, critical mass, and ease of use. Affiliation motivation was not significant and social belief had a negative impact on intention. As expected, intention to use had a significant influence on actual usage.     

基于改进小波变换的农村集体土地测绘图像高分辨率自适应重建方法

为提高农村集体土地测绘图像的分辨率,改进在重建图像的过程中发生的灰度偏移的情况,研究了基于改进小波变换的农村集体土地测绘图像高分辨率自适应重建方法。采集农村集体土地测绘图像,对差值处理后的测绘图像进行Haar小波变换,高分辨率重建测绘图像,校正图像灰度化偏移的同时保证重建测绘图像的质量;采用基于贝叶斯估计的自适应小波去噪方法,去除重建测绘图像噪声,使重建的高分辨率测绘图像更清晰。实验结果表明：PSNR值接近30dm,SSIM值接近1;不同噪声方差下,PSNR值最高。提高了重建测绘图像的清晰度和分辨率,得到高分辨率的农村集体土地测绘图像。     

Errors in Seligman's "The effectiveness of psychotherapy: The Consumer Reports study."

Contends that there are 3 methodological errors and an inconsistency in M. E. P. Seligman's (see record 1996-13324-001) reanalysis of the 1995 Consumer Reports survey of the effectiveness of psychotherapy. These errors are directly relevant to the cost-effectiveness of psychotherapy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于机器人群的主动传感器网络自组织的运动规划

主动传感器网络的自组织通常要求移动节点群(机器人群)通过障碍物环境移动到指定地点后, 重新调整并按预定布局组网. 在网络的自组织过程中要保证每个移动节点(机器人)与整个网络之间的连通性. 在对移动机器人的保持连通性进行优化的基础上, 提出了单步位置预测与群体势场相结合的分布式运动规划方法进行主动传感器网络的部署和重置, 证明了机器人运动控制的稳定性和网络的连通性保持, 进行了有和无障碍物环境下超过40个机器人的仿真, 结果表明该方法适用于大规模的主动传感器网络重置, 并对不同规模的网络具有可扩展性.     

Enacting language games: the development of a sense of ‘we‐ness’ in online forums

A sense of ‘we‐ness’– enacted through collective identity and culture – is both crucial in online, remote contexts, and particularly difficult to develop in such settings. Using Wittgenstein's concept of language games, we examine how participants of two online forums construct collective identity and culture through their discursive practices. We suggest a strong performative interpretation of the notion of language games, i.e. members of a community produce a sense of we‐ness through their participation in the language game while also defining their expected behaviours and actions. We illustrate how the notion of language games offers an approach for researching and analysing the emergence of collective identity and culture in online forums.     

群集系统分群行为建模与控制研究进展

群集系统的分群行为表征为一个聚合的母群分裂成多个子群的现象, 探讨其产生机理和控制方法具有重要的理论意义和应用价值. 鉴于此, 从分群行为的理论建模和控制方法两个角度出发, 对近年来群集系统分群运动研究的主要成果进行综述, 回顾了目前分群运动理论建模研究的最新进展, 重点总结了分群运动的现有控制方法和结论, 并对分群控制研究中尚存在的问题进行了探讨, 最后就分群行为后续可能的研究方向进行了展望.

     

基于联合矩阵分解的话题发现与追踪模型

在文本流数据中,文本文档以流的形式源源不断地进入系统,数据量大和数据更新速度快给文本流话题发现与追踪提出了严峻的挑战。为了应对上述困难,本文提出了一种基于联合矩阵分解的话题发现与追踪模型。为了有效地处理海量数据,将流数据按照时间戳划分为数据块;为了能在数据的快速变化中追踪到话题的演化,将当前时刻的话题分布表示为前一时刻话题分布的线性演化。本文采用联合矩阵分解技术将当前的数据块分别表示为当前的话题分布和前一时刻的话题分布两种形式,通过同时分解两个矩阵得到当前的话题分布。在优化求解过程中,通过Karush-Kuhn-Tucker条件分析得到参数的更新策略,并给出相应的求解算法。Yahoo数据集对比实验表明,本文提出的话题发现算法能更好的发现文本流中蕴含的话题分布情况,并且可以随着时间的推移对话题的演化进行追踪。