The effects of a “distinct window” screen design on computer-mediated group decision making

An experiment was performed to test a distinct-window conferencing screen design as an electronic cue of social status differences in computer-mediated group decision-making. The screen design included one distinct window to symbolize high-status, and two nondistinct windows to symbolize low-status. The results indicated that the distinct-window screen design did produce status affects in groups of peers making decisions on judgmental problems. Randomly assigned occupants of the distinct window had greater influence on group decisions and member's attitudes than occupants of nondistinct windows.The authors would like to thank Shyam Kamadolli and Phaderm Nangsue, the programmers who developed the software used in this experiment. We would also like to thank the editor and our three anonymous reviewers for exceedingly helpful comments on an earlier draft of this article.     

基于社团多特征融合嵌入表示的时序链路预测方法

时序动态网络在静态网络基础上综合了时间属性的概念,包含了网络结构的复杂性、动态性等内涵,是研究复杂网络链路预测问题的较优思维对象,因在现实世界中具有较高应用价值而备受关注。目前大部分传统方法研究对象仍局限于静态网络,存在对网络时域演化信息利用不充分、时间复杂度较高等问题。结合社会学理论,提出一种基于社团多特征融合嵌入表示的时序链路预测方法,该方法的核心思想是通过分析网络动态演化特性,在社团范围内学习节点的嵌入表示向量,融合多特征以衡量节点间连边的生成概率。利用网络集体影响力的方法对节点和连边的权值进行计算,基于集体影响的连边权值进行社团划分,将网络划分为若干个社团子图,得到基于集体影响的相似性指标。在社团范围内,利用有偏的随机游走,结合梯度优化的Skip-gram方法获取所有节点的嵌入表示向量,得到基于社团范围游走的相似性指标。融合节点的集体影响、社团范围节点的多个中心性特征和学习到的节点表示向量,得到多特征融合的相似性指标,3 种新指标都可以用于衡量节点之间形成连边的概率。对比基于移动平均、嵌入表示、图神经网络等经典时序链路预测方法,在 6 个真实数据集上的实验结果表明,所提基于社团多特征融合的方法在 AUC评价标准下取得更优的预测性能。     

考虑元件温-湿关联影响的氢燃料电池系统动态可靠性分析

为了研究元件关联作用对氢燃料电池系统可靠性的影响,以集流板、扩散层和催化层的性能状态与质子膜温度失效和湿度失效的关联关系为研究对象,利用马尔科夫方法建立元件多状态退化模型。通过转移系数描述元件状态转移率与关联特性的动态关系,构建新的状态转移矩阵;基于通用发生函数导出关联系统多态可靠性分析模型,并讨论了多元件关联情形的模型特点;结合Kolmogorov方程求得多态元件各状态下的概率,分别研究了单一关联组和多关联组温-湿复合影响两种情况下的系统可靠性趋势。结果表明: 质子膜的状态转移率会随着集流板、扩散层和催化层性能的退化而改变;当上述元件处于高性能状态时,质子膜的关联特性使系统的可靠度更高,而这些元件在低性能状态时,关联特性使系统的可靠度更低;冷却元件的状态对系统可靠性的影响比增湿元件状态的影响大。研究结果可为电池系统可靠性设计和寿命周期预测提供理论依据。     

Identification of Pivotal Causes and Spreaders in the Time‐Varying Fault Propagation Model to Improve the Decision Making under Abnormal Situation

Under abnormal conditions, timely and effective decisions of system recovery and protective measures are of great significance for safety‐critical systems. The knowledge of the roles that network nodes play in the spreading process is crucial for developing efficient maintenance decisions; for singling out and preferential control, the ‘pivotal spreaders’ may be a way to maximize the chances to timely hinder the fault pervasion. Inspired by the inhomogeneous topological nature of a complex fault propagation network, this study is devoted to exploring the spreading capabilities of nodes regarding both structural connectivity and causal influence strength, so as to provide decisions of preferential recovery actions under specific fault scenarios. Specifically, the dynamic betweenness centrality and nonsymmetrical entropy are incorporated to adaptively measure the system‐wide fault diffusion risk of a set of controllable fault events. In order to model the dynamics and uncertainties involved in the complex fault spreading process, we introduce the model of a dynamic uncertain causality graph, based on which solutions of time‐varying structure decomposition and causality reduction are adopted to improve the reasoning efficiency. Verification experiments consisting of simulated calculation cases and generator faults of a nuclear power plant show empirically the effectiveness and applicability of this method in large‐scale engineering practice. Copyright © 2014 John Wiley & Sons, Ltd.     

基于粗糙集的一体化保障技术属性约简问题研究

一体化保障技术是目前提高复杂武器系统测试和保障能力的研究重点,为解决一体化保障技术中存在的指标冗余问题,结合粗糙集相关理论,提出了基于属性重要性和属性间影响度的约简算法;通过在某型一体化保障设备的柴油发电机子模块中应用该算法,在精简测试指标的同时,保证了较高的测试准确性,缩短了测试时间,验证并说明该理论可以有效地解决一体化保障技术中的指标冗余问题。     

An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic of nodes by improving the K-shell method. Then, in the local scope, the calculation method of comprehensive degree is proposed to weigh the influence of nodes. Finally, the node with the highest comprehensive degree in each core layer is selected as the seed. However, the seed selection strategy of KT can easily lose some influential nodes. Thus, by optimizing the seed selection strategy, this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization (KTIM). According to the hierarchical distribution of cores, the algorithm adds nodes near the central core to the candidate seed set. It then searches for seeds in the candidate seed set according to the comprehensive degree. Experiments show that KTIM is close to the best performing improved method for influence maximization of temporal graph (IMIT) algorithm in terms of effectiveness, but runs at least an order of magnitude faster than it. Therefore, considering the effectiveness and efficiency simultaneously in temporal social networks, the KTIM algorithm works better than other baseline algorithms.     

影响图的扩展综述

影响图是单决策人基于不确定信息表示和求解复杂决策问题的图模型,已成为一种流行的标准建模工具。由于决策环境纷繁复杂,决策问题多种多样,没有任何一种建模工具能够普遍适用于各种决策问题。为了表示复杂决策问题,增强影响图的表达能力,研究者对影响图进行了多种扩展。从建模无限制决策问题、非对称决策问题、涉及连续变量的决策问题、涉及非精确变量的决策问题及多Agent决策问题等方面对影响图的扩展进行了较为全面的回顾与分析,指出了有关影响图的进一步研究方向。关键词:决策;影响图;无限制决策;非对称决策;多Agent决策     

基于拓扑势的网络拓扑建模方法

针对现有拓扑建模研究中层次型模型不满足幂率分布规律的问题,提出一种基于节点拓扑势与幂率特性的层次化网络拓扑建模方法,给出拓扑生成算法PPHM。通过计算拓扑势实现网络节点的分层,能准确发现网络中的重要连接。对平均最短路径长度等拓扑参数的比较结果证明了该方法的有效性。     

算法与数据结构学习兴趣影响因素分析

文章对算法与数据结构课程的学习兴趣调查结果进行了分析,提出采用自编学习兴趣量表测量学生的学习兴趣,总结学生的基础课程学习情况以及对课程教学的看法。分析结果显示:学生的学习兴趣受专业基础课程成绩和对课程学习重要性认识的影响,增加实践性教学和以案例为先导的理论课教学方式更有利于提高学生的学习兴趣。     

数字与造型——论数字绘画技术对传统插画的冲击与渗透

数字绘画作为一种新兴的艺术形式。在艺术创作过程中,从单纯地模仿走向利用电脑程序在电脑中创作或自动生成图像,达到了一定的艺术效果。同时,它也在不知不觉中或多或少地影响了传统的插画艺术。这两种绘画方式具有各自独特的个性及美感,我们把更多的目光投向了这两种技术手段的相通性。探讨在这两者间相互影响的过程中,在超越这些"感觉材料"之上、之外,是否存在着一个共同体,构成了不同的艺术手段之间的作品。