Affective computing vs. affective placebo: Study of a biofeedback-controlled game for relaxation training

Relaxation training is an application of affective computing with important implications for health and wellness. After detecting user׳s affective state through physiological sensors, a relaxation training application can provide the user with explicit feedback about his/her detected affective state. This process (biofeedback) can enable an individual to learn over time how to change his/her physiological activity for the purposes of improving health and performance. In this paper, we provide three contributions to the field of affective computing for health and wellness. First, we propose a novel application for relaxation training that combines ideas from affective computing and games. The game detects user׳s level of stress and uses it to influence the affective state and the behavior of a 3D virtual character as a form of embodied feedback. Second, we compare two algorithms for stress detection which follow two different approaches in the affective computing literature: a more practical and less costly approach that uses a single physiological sensor (skin conductance), and a potentially more accurate approach that uses four sensors (skin conductance, heart rate, muscle activity of corrugator supercilii and zygomaticus major). Third, as the central motivation of our research, we aim to improve the traditional methodology employed for comparisons in affective computing studies. To do so, we add to the study a placebo condition in which user׳s stress level, unbeknown to him/her, is determined pseudo-randomly instead of taking into account his/her physiological sensor readings. The obtained results show that only the feedback presented by the single-sensor algorithm was perceived as significantly more accurate than the placebo. If the placebo condition was not included in the study, the effectiveness of the two algorithms would have instead appeared similar. This outcome highlights the importance of using more thorough methodologies in future affective computing studies.     

Public Displays of Play: Studying Online Games in Physical Settings

As research on virtual worlds gains increasing attention in educational, commercial, and military domains, a consideration of how player populations are ‘reassembled’ through social scientific data is a timely matter for communication scholars. This paper describes a large‐scale study of virtual worlds in which participants were recruited at public gaming events, as opposed to through online means, and explores the dynamic relationships between players and contexts of play that this approach makes visible. Challenging conventional approaches to quantitatively driven virtual worlds research, which categorizes players based on their involvement in an online game at a particular point in time, this account demonstrates how players' networked gaming activities are contingent on who they are playing with, where, and when.     

Reputation mechanism for e-commerce in virtual reality environments

The interest in 3D technology and virtual reality (VR) is growing both from academia and industry, promoting the quick development of virtual marketplaces (VMs) (i.e. e-commerce systems in VR environments). VMs have inherited trust problems, e.g. sellers may advertise a perfect deal but doesn’t deliver the promised service or product at the end. In view of this, we propose a five-sense feedback oriented reputation mechanism (supported by 3D technology and VR) particularly for VMs. The user study confirms that users prefer VMs with our reputation mechanism over those with traditional ones. In our reputation mechanism, five-sense feedback is objective and buyers can use it directly in their reputation evaluation of target sellers. However, for the scenarios where buyers only provide subjective ratings, we apply the approach of subjectivity alignment for reputation computation (SARC), where ratings provided by one buyer can then be aligned (converted) for another buyer according to the two buyers’ subjectivity. Evaluation results indicate that SARC can more accurately model sellers’ reputation than the state-of-the-art approaches.     

利用虚拟机技术提高独立学院实验教学质量和科研水平

现阶段,在实验教学硬件设备要求较高而实验教学改革注重综合能力培养的指导下,很多依靠计算机硬件设备开展的实验课程遇到了较大的挑战.本文根据独立学院的具体情况结合虚拟机技术的特点,具体的分析了虚拟机技术在计算机实践教学中能起到的巨大作用和广阔的应用前景.并倡导全国独立院校要善于通过模拟真实的环境,去探索和研究科学的东西,提高自己的实践教学和科研水平.     

虚拟机在计算机实践教学中的应用

针对目前计算机实践教学中存在的问题,提出了一种虚拟机技术的解决方法。该方法不仅充分有效地利用现有设备,而且对硬件及系统具有很好的安全性,并能够增加学生的实践动手机会。教学上更加灵活、方便地设计实践项目,从而提高实践教学的质量。     

基于Creator的战场地形仿真研究

如何解决地形模型精细度、逼真度与仿真速度之间的矛盾是军事仿真的难点问题。本文研究了三维地形生成的关键技术,并详细阐述了利用MultiGen Creator建模工具,采用DEM数据和卫星遥感影像数据构建和优化大面积战场地形的原理和方法,最后结合实例生成战场地形。仿真结果表明,该方法生成的模型达到了精细度高、真实感强、实时性好等仿真要求。     

VR技术对地下步行商业街心理环境辅助设计初探

文章力图以VR（虚拟现实）技术手段应用于城市地下步行商业街规划设计,来解决当前传统规划手段地下步行商业街规划中普遍存在的对其心理环境构筑的忽视和考虑不完善的诟病,以期最大限度消除规划设计中消极空间的产生,并对其关键技术进行了研究和探讨     

实验动物在血液制品中的应用

目的：阐述实验动物在血液制品生产质量控制过程中应用的重要性。方法：按《中华人民共和国药典》2005年版三部要求及相关项目的技术规范进行血液制品质量控制。结果：血浆数量150吨,可同时生产以下品种的产品,人血白蛋白共30批次,总瓶数约40万瓶（折10g）;免疫球蛋白类：共30批次,总瓶数约30万瓶（折2.5g）;人纤维蛋白原：共30批次,总瓶数约15万瓶（折0.5g）;人凝血酶原复合物：共30批次,总瓶数约12万瓶（折300IU）;人凝血因子Ⅷ：共30批次,总瓶数约10万瓶（折200IU）。需使用家兔870只、豚鼠300只小鼠750只。结论：实验动物应用于血液制品生产质量控制发挥了非常重要的作用。     

基于可操作度的虚拟人手部避障运动控制算法

研究复杂作业环境中虚拟人手部避障运动的高精度控制问题,问题的关键是解决虚拟人手的设计.为了灵活操作能在操作的末端临时变换姿态,给控制过程中手臂转动路线,速度,加速度等参数的控制带来较大困难.传统的控制方法通过增加控制自由度来解决这个问题,但是一旦自由度增加,会带来冗余控制影响,弊端较为明显.提出一种采用可操作度矩阵的逆向运动学控制算法,引入可操作度模型进行肢体末端效应器运动路径的生成,与HAL链IK分析求解方法相结合,实现了真实感较强的肢体实时运动控制.通过仿真和动作捕获实验验证了算法的有效性,可应用于人机工程仿真中的避障控制和干涉检查.     

轮轨式扒渣机防滑夹轨装置研究

轮轨式扒渣机在驻机作业的过程中,工作装置受到渣石阻力的影响,使整机产生水平方向的作用力,导致设备产生滑动,影响工作稳定性及安全性.针对此类情况,通过对机器作业过程中整体受力情况进行分析,提出了通过安装一套水平缸式夹轨装置提高机器与轨道间摩擦阻力的方案来解决此类问题.通过对夹轨装置的运动轨迹分析以及整机的虚拟样机仿真分析,验证了安装该类型夹轨装置防滑方案的可行性.