Distributed Coordination and Workflow on the World Wide Web

This paper describes WebFlow, an environment thatsupports distributed coordination services on theWorld Wide Web. WebFlow leverages the HTTP Webtransport protocol and consists of a number of toolsfor the development of applications that require thecoordination of multiple, distributed servers.Typical applications of WebFlow include distributeddocument workspaces, inter/intra-enterprise workflow,and electronic commerce. In this paper we describe thegeneral WebFlow architecture for distributedcoordination, and then focus on the environment fordistributed workflow.     

Automatic coding of dialogue acts in collaboration protocols

Although protocol analysis can be an important tool for researchers to investigate the process of collaboration and communication, the use of this method of analysis can be time consuming. Hence, an automatic coding procedure for coding dialogue acts was developed. This procedure helps to determine the communicative function of messages in online discussions by recognizing discourse markers and cue phrases in the utterances. Five main communicative functions are distinguished: argumentative, responsive, informative, elicitative, and imperative. A total of 29 different dialogue acts are specified and recognized automatically in collaboration protocols. The reliability of the automatic coding procedure was determined by comparing automatically coded dialogue acts to hand-coded dialogue acts by a human rater. The validity of the automatic coding procedure was examined using three different types of analyses. First, an examination of group differences was used (dialogue acts used by female versus male students). Ideally, the coding procedure should be able to distinguish between groups who are likely to communicate differently. Second, to examine the validity of the automatic coding procedure through examination of experimental intervention, the results of the automatic coding procedure of students, with access to a tool that visualizes the degree of participation of each student, were compared to students who did not have access to this tool. Finally, the validity of the automatic coding procedure of dialogue acts was examined using correlation analyses. Results of the automatic coding procedure of dialogue acts of utterances (form) were related to results of a manual coding procedure of the collaborative activities to which the utterances refer (content). The analyses presented in this paper indicate promising results concerning the reliability and validity of the automatic coding procedure for dialogue acts. However, limitations of the procedure were also found and discussed.     

Evaluating Community Safety Programmes and Community Engagement: The Role of Qualitative Methods and Collaborative Approaches to Policy Research

This article explores the role of qualitative and collaborative methods when undertaking evaluation research into local community safety partnerships and neighbourhood strategies. It draws on recent examples of research and evaluation studies of regeneration and community safety programmes in a number of cities and towns in England. The discussion is set against the background of the major changes in policy relating to crime and community safety, particularly the introduction of Crime and Disorder Partnerships and their engagement with local communities. The value of qualitative methods in exploring some key questions is discussed, particularly within a collaborative approach to policy research.     

基于多学科协同的某锁机构系统故障仿真

为解决机电液耦合的复杂运动机构系统的故障仿真问题,提出一种基于多学科软件协同的故障仿真分析方法.通过软件接口建立机构系统基于多学科协同的仿真模型.将相关故障模式影响因素注入机构系统仿真模型,仿真分析其对系统参数的影响.某锁机构系统的上锁故障仿真分析表明,该方法对工程实际复杂运动机构系统有效可行.该故障仿真方法有助于提高机械产品可靠性,也可为复杂机械系统的故障机理分析、故障诊断和维修等提供数据支持。     

Mine,ours, and yours: Whose engagement and prior knowledge affects individual achievement from online collaborative learning?

In computer-supported collaborative learning research, studies examining the combined effects of individual level, group level and within-group differences level measures on individual achievement are scarce. The current study addressed this by examining whether individual, group and within-group differences regarding engagement and prior knowledge predict individual achievement. Engagement was operationalised as group members' exhibited activities in the task space (i.e., discussing domain-content) and social space (i.e., regulating ideas, actions and socioemotional processes). Prior knowledge and achievement were operationalised as group members' performance on a domain-related pre-test and post-test, respectively. Data was collected for 95 triads of secondary education students collaborating on a complex business-economics problem. Subsequently, three different multilevel models were tested to examine the combined effect. First a model with the individual level measures (model 1) was tested and in subsequent models the group level measures (model 2) and within-group levels measures (model 3) were added. Findings indicate model 2 showed the best fit; group members' individual engagement in the social space activities as well as the groups' average prior knowledge positively predicts individual achievement. No effects were found for either group members' or groups' engagement in the task space and for the within-group differences.     

众筹项目推荐:面向隐式反馈的深度学习协同过滤

目前,在推荐系统研究中,用户的隐式反馈,以及极度稀疏的数据,已成为影响协同过滤推荐效果的主要问题.针对这一现象,本文提出了深度学习协同过滤算法,先利用卷积神经网络,对用户-项目矩阵的隐层特征进行学习,再结合协同过滤,对用户-项目的交互信息进行建模,并将两种特征融合预测推荐列表.以众筹平台的数据为实验对象,比较模型中各参数对推荐效果的影响,并设计与基线方法的对比实验.实验结果表明:均匀采集负反馈,并在一定卷积层数的网络中,数据稀疏度越高,效果越好;对比基线方法,本文提出的算法在公开数据集(Yahoo!Movie)上取得了最好的推荐结果.本文提出的算法有助于提高众筹平台的融资成功率,同时也丰富了推荐系统的研究体系.     

Graph-Based Dimensionality Reduction for Hyperspectral Imagery: A Review

Hyperspectral image(HSI) contains a wealth of spectral information, which makes fine classification of ground objects possible. In the meanwhile, overly redundant information in HSI brings many challenges. Specifically, the lack of training samples and the high computational cost are the inevitable obstacles in the design of classifier. In order to solve these problems, dimensionality reduction is usually adopted. Recently, graph-based dimensionality reduction has become a hot topic. In this paper, the graph-based methods for HSI dimensionality reduction are summarized from the following aspects. 1) The traditional graph-based methods employ Euclidean distance to explore the local information of samples in spectral feature space. 2) The dimensionality-reduction methods based on sparse or collaborative representation regard the sparse or collaborative coefficients as graph weights to effectively reduce reconstruction errors and represent most important information of HSI in the dictionary. 3) Improved methods based on sparse or collaborative graph have made great progress by considering global low-rank information, local intra-class information and spatial information. In order to compare typical techniques, three real HSI datasets were used to carry out relevant experiments, and then the experimental results were analysed and discussed.Finally, the future development of this research field is prospected.     

基于BC聚类的差分隐私保护推荐算法

为提高差分隐私保护下推荐算法的准确性,提出了一种考虑差分隐私保护的基于Bhattacharyya系数（BC）的聚类推荐算法.以BC作为项目相似性度量的标准,根据BC相似性对项目进行K-medoids聚类,并在聚类簇中进行私有项目邻居选择.最后,根据最近邻居集信息,对用户的评分进行预测和Top-n推荐.提出的方案有效地克服了已有方法中存在的相似性度量依赖于共同评分的问题,提高了相似性度量的准确性,有效避免了因隐私保护而造成的最近邻居集质量下降的问题.理论分析和实验测试的结果表明,该方法在实现隐私保护的同时还能有效保证推荐的高质量,较好地实现了隐私保护和数据效用之间的平衡,具有良好的应用潜力.