Moderators of nonverbal indicators of deception: A meta-analytic synthesis.

In many legal proceedings, fact finders scrutinize the demeanor of a defendant or witness, particularly his or her nonverbal behavior, for indicators of deception. This meta-analysis investigated directly observable nonverbal correlates of deception as a function of different moderator variables. Although lay people and professionals alike assume that many nonverbal behaviors are displayed more frequently while lying, of 11 different behaviors observable in the head and body area, only 3 were reliably associated with deception. Nodding, foot and leg movements, and hand movements were negatively related to deception in the overall analyses weighted by sample size. Most people assume that nonverbal behaviors increase while lying; however, these behaviors decreased, whereas others showed no change. There was no evidence that people avoid eye contact while lying, although around the world, gaze aversion is deemed the most important signal of deception. Most effect sizes were found to be heterogeneous. Analyses of moderator variables revealed that many of the observed relationships varied as a function of content, motivation, preparation, sanctioning of the lie, experimental design, and operationalization. Existing theories cannot readily account for the heterogeneity in findings. Thus, practitioners are cautioned against using these indicators in assessing the truthfulness of oral reports. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Speakers gaze at objects while preparing intentionally inaccurate labels for them.

When describing scenes, speakers gaze at objects while preparing their names (Z. M. Griffin & K. Bock, 2000). In this study, the authors investigated whether gazes to referents occurred in the absence of a correspondence between visual features and word meaning. Speakers gazed significantly longer at objects before intentionally labeling them inaccurately with the names of similar things (e.g., calling a horse a dog) than when labeling them accurately. This held for grammatical subjects and objects as well as agents and patients. Moreover, the time spent gazing at a referent before labeling it with a novel word or accurate name was similar and decreased as speakers gained experience using the novel word. These results suggest that visual attention in speaking may be directed toward referents in the absence of any association between their visual forms and the words used to talk about them. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

PD雷达欺骗干扰方法浅析

概要介绍了PD雷达的抗干扰性能及其特点．并主要对PD雷达的欺骗干扰方法进行了一定的讨论。     

运用模式分类的雷达抗转发式距离欺骗干扰方法

针对雷达转发式欺骗干扰中的距离欺骗，提出了一种基于模式分类来识别目标与干扰的方法。该方法基于干扰和目标能量和起伏特性差异确定提取特征因子，再利用RBF神经网络方法进行分类。仿真结果表明，该方法具有较好的抗距离欺骗干扰性能。     

网络化雷达协同抗欺骗式干扰技术研究进展

网络化雷达在战场上可以构成全方位、立体化、多层次的战斗体系,因 此对欺骗式干扰对抗具有很大的优越性。本文首先简要介绍了网络化雷达概念,并分析了其 抗干扰优势。根据网络化雷达融合结构不同,将现有协同抗干扰方法分为数据级融合抗欺骗 式干扰和信号级融合抗欺骗式干扰两大类,其中,数据级融合方法进一步分类为点迹关联和 航迹关联两类。本文对各类方法进行了详细介绍,在此基础上,比较分析了数据级融合和信 号级融合两类方法的抗干扰性能及算法复杂度,为抗干扰措施的选择提供依据。最后,针对 现有方法中存在的问题,对网络化雷达协同抗欺骗式干扰的发展趋势进行展望,指出下一步 的研究方向。     

计算机信息技术在互联网中的应用探析

探究了计算机信息技术在互联网中的应用。选取2010年1月至2014年1月间出版的有关"计算机信息技术在互联网中的应用"方面的文献资料10篇,进行参考研究。结合互联网技术的发展现状及计算机网络安全问题的发生,阐述了信息技术在互联网中的应用。计算机信息技术在互联网中的应用日益广泛,需依靠技术优势解决各类网络安全问题。     

基于网络消费者购买过程的网络营销策略分析

网络消费者是新的消费群体,与传统市场消费群体有着截然不同的特性。企业要想卓有成效地开展网络营销活动,获得来自虚拟世界的利益,就必须了解、分析和把握住网络消费者的消费过程,尽可能地为营销活动提供可靠的数据分析和营销依据。本文从网络消费者购买行为形成和实现的过程入手,对网络消费者购买过程的环节进行策略分析。     

网络空间安全实训设计

为保障网络空间安全,需要加强网络空间安全人才队伍建设,实训是把学生培养成为高素质复合型人才的重要手段。通过分析我国网络空间安全人才队伍建设现状,构建实训课程体系和实训平台,设计实训大纲和实训竞赛平台,形成了校企合作、教学与竞赛相结合的实训体系。实践证明,此网络空间安全实训设计能有效提高学生的网络空间安全技术能力,具有一定的推广价值,为高校培养应用型、复合型人才提供了新思路。     

Evolutionary digital twin: A new approach for intelligent industrial product development

To fulfill increasingly difficult and demanding tasks in the ever-changing complex world, intelligent industrial products are to be developed with higher flexibility and adaptability. Digital twin (DT) brings about a possible means, due to its ability to provide candidate behavior adjustments based on received “feedbacks” from its physical part. However, such candidate adjustments are deterministic, and thus lack of flexibility and adaptability. To address such problem, in this paper an extended concept – evolutionary digital twin (EDT) and an EDT-based new mode for intelligent industrial product development has been proposed. With our proposed EDT, a more precise approximated model of the physical world could be established through supervised learning, based on which the collaborative exploration for optimal policies via parallel simulation in multiple cyberspaces could be performed through reinforcement learning. Hence, more flexibility and adaptability could be brought to industrial products through machine learning (such as supervised learning and reinforcement learning) based self-evolution. As a primary verification of the effectiveness of our proposed approach, a case study has been carried out. The experimental results have well confirmed the effectiveness of our EDT based development mode.