Reality-based interaction affecting mental workload in virtual reality mental arithmetic training

ABSTRACT

The concept of digital game-based learning (DGBL) evolves rapidly together with technological enhancements of virtual reality (VR) and smart phones. However, the mental workload (MWL) that VR-training applications demand and motivational qualities originating from user experience (UX) should be identified in order to create effective and enjoyable training/learning challenges that fit with individual users’ capabilities. This study examined the effects of reality-based interaction (RBI) and VR on measures of student motivation and MWL, in a mental arithmetic game for secondary school pupils. In a randomised controlled trial with sixty school children, a mental arithmetic game was tested with three different interaction and two different presentation methods – VR RBI, VR head-mounted-display tapping and tablet flick-gesture. Results found a significant effect of RBI on MWL but no differences in enjoyment of training were found between VR-experience and tablet training-experience. In fact, adding the gaming-context to the mental arithmetic task created an enjoyable, motivating experience regardless of presentation or interaction-style.     

Content adaptive video denoising based on human visual perception

In this paper, we propose content adaptive denoising in highly corrupted videos based on human visual perception. We introduce the human visual perception in video denoising to achieve good performance. In general, smooth regions corrupted by noise are much more annoying to human observers than complex regions. Moreover, human eyes are more interested in complex regions with image details and more sensitive to luminance than chrominance. Based on the human visual perception, we perform perceptual video denoising to effectively preserve image details and remove annoying noise. To successfully remove noise and recover the image details, we extend nonlocal mean filtering to the spatiotemporal domain. With the guidance of content adaptive segmentation and motion detection, we conduct content adaptive filtering in the YUV color space to consider context in images and obtain perceptually pleasant results. Extensive experiments on various video sequences demonstrate that the proposed method reconstructs natural-looking results even in highly corrupted images and achieves good performance in terms of both visual quality and quantitative measures.     

云杉八齿小蠹Ips typographus L.虚拟模型构建方法研究

本文以云杉八齿小蠹Ips typographus Linnaeus为例,经标本选取,观察虫体整体形态,绘制整体结构草图,电子显微镜观察局部、得到局部数字图像,分别建立虫体每一部分的高精度细节。把模型每部分拼装在一起组成整体模型,构建出了云杉八齿小蠹三维虚拟昆虫数字化模型。     

一款紧凑增强型可变阻抗电磁带隙结构

基于传统AI-EBG结构,提出了一种小尺寸的增强型电磁带隙结构,实现了从0.5~9.4 GHz的宽频带-40 dB噪声抑制深度,且下截止频率减少到数百MHz,可有效抑制多层PCB板间地弹噪声。文中同时研究了EBG结构在高速电路应用时的信号完整性问题,使用差分信号方案可改善信号完整性。     

Study of new flow field geometries to enhance water redistribution and pressure head losses reduction within PEM fuel cell

Efficiency of fuel cell is dependent on reactant distribution, products evacuation, pressure losses and many of these factors is dependent on the design of flow field plate. With an effective design, reactant distribution, pressure drop, and water and heat management can be further improved. In this work, two new designs, as multi-serpentine set-up with additional slots and hybrid geometry, on stainless steel bipolar plates, are presented. Electrical performance, and pressure head losses are analyzed by electrochemical methods such as polarization curve and use of electrochemical noise as a diagnostic tool to further understand the impact of water management on performance. On the one hand, multi-serpentine design shows the best electrical performance with an increase of 0.2 V (66%) at 0.9 A/cm² in comparison of traditional serpentine design. On the other hand, hybrid design reveals the lowest pressure head losses, with a decrease of 2 mbar (about 50%) in comparison of traditional serpentine design, and a higher stability with time that can be useful to downsize compressor and provide lower impact on fuel cell stack durability.     

基于信号增强的缓慢泄漏检测方法

目前管道泄漏检测方法可有效检测突发泄漏，对于缓慢泄漏则存在检测灵敏度低、定位不准确等问题。基于此，提出了一种基于信号增强的缓慢泄漏检测方法。通过信号压缩（抽取及移位）克服缓慢泄漏压力信号下降平缓的缺点；根据声波信号具有波形尖锐突出、对突发泄漏敏感的优点，通过建立以压力为输入、虚拟声波为输出的声波信号变送器模型，将压力信号转换为声波信号，克服了泄漏压力信号容易被淹没在管道压力波动及背景噪声中的缺点，实现了缓慢泄漏信号的增强；利用临近插值方法重构虚拟声波信号，基于延时互相关分析实现了缓慢泄漏的准确定位。实验结果表明，该方法具有显著的信号增强效果和定位精度，实现了缓慢泄漏的准确检测。     

A Hybrid Virtual Cloud Learning Model during the COVID-19 Pandemic

The COVID-19 pandemic has affected the educational systems worldwide, leading to the near-total closures of schools, universities, and colleges. Universities need to adapt to changes to face this crisis without negatively affecting students’ performance. Accordingly, the purpose of this study is to identify and help solve to critical challenges and factors that influence the e-learning system for Computer Maintenance courses during the COVID-19 pandemic. The paper examines the effect of a hybrid modeling approach that uses Cloud Computing Services (CCS) and Virtual Reality (VR) in a Virtual Cloud Learning Environment (VCLE) system. The VCLE system provides students with various utilities and educational services such as presentation slides/text, data sharing, assignments, quizzes/tests, and chatrooms. In addition, learning through VR enables the students to simulate physical presence, and they respond well to VR environments that are closer to reality as they feel that they are an integral part of the environment. Also, the research presents a rubric assessment that the students can use to reflect on the skills they used during the course. The research findings offer useful suggestions for enabling students to become acquainted with the proposed system’s usage, especially during the COVID-19 pandemic, and for improving student achievement more than the traditional methods of learning.     

基于HHT-RDT算法的高拱坝泄流结构工作模态识别方法

根据高拱坝泄流结构自身的工作特点,为准确辨识环境激励下的结构模态参数特征,提出了一种基于改进的HHT-RDT算法的高拱坝泄流结构工作模态识别方法。以某高拱坝原型振动响应测试资料为基础,利用改进的小波阈值-EMD算法对原始信号进行降噪预处理,滤除干扰噪声的同时保留有效特征信息;采用HHT-RDT算法识别高拱坝泄流结构的工作模态参数,运用带通滤波对振动响应信号的EMD过程进行控制得到结构的各阶模态分量,利用RDT法提取各阶模态分量的自由衰减信息,识别出高拱坝泄流结构系统的固有频率及阻尼比。工程实例表明,该方法避免了复杂系统定阶过程,有效提高结构振动响应工作模态识别精度,为辨识高拱坝泄流结构的工作模态参数提供捷径。     

沉浸式艺术审美体验的自我发现与再设计

探讨沉浸式艺术这一新概念，研究其审美体验是如何有助于自我发现并运用于艺术创作再设计中的。沉浸式艺术是一种能够启发感知联觉的审美体验方式，可使人们重新思考自己与“世界”(真实和虚拟)之间的关系。“感知”、“关系”和“转换”是三个相互交织并贯穿全文的主要问题，同时也是沉浸式艺术的研究基础。结合海德格尔“在世界上”(être-au-monde) 的观念来看，与其说“存在”，不如说人们沉浸并感知于这个世界中。然而，人们对周围环境的感知通常是无意识的，对于感知的认识也时常是冷漠和忽视的。沉浸式艺术使这些感觉得以被强调，它突出了个人的感知运动能力，同时也引起了人们对身体本身的重视。又如Bergson所提出的“投机性关注是建立在一种感知机制的基础上的，这种感知机制从根本上允许对世界进行一定行动而不是仅仅了解这个世界”。因此，对于一个完善的沉浸式审美体验过程来说，重要的是使观众自然地参与其中。当无意识的行为转换为肉眼可见的视觉效果时，审美体验将会更加深入人心。因此关于沉浸式艺术作品的创作，可以结合西方艺术家Marcel Duchamp的Ready-made的创作理念和中国道家的“无为”思想，研究怎样将被忽视的日常行为自然地转换为可见的，被重视的视觉效果，从而揭发主体与“世界”之间的多种潜在关系。