A quick identification model for assessing human anxiety and thermal comfort based on physiological signals in a hot and humid working environment

We propose a simple and quick method for quantifying workers' anxiety and thermal comfort levels using physiological signals. Nine subjects enrolled in a series of controlled laboratory experiments involving varying temperature, relative humidity, and labor intensities. A total of 40 experiments were conducted, and 1592 groups of anxiety data and 1624 groups of thermal comfort data were obtained, respectively. During 2-h-working trials, Electroencephalogram (EEG), photoplethysmography (PPG), and pupil diameter of each subject were collected synchronously, and the State-Trait Anxiety Inventory (STAI) and thermal comfort vote (TCV) were completed in stages. Random Forest was adopted to screen out the appropriate sensitivity feature indicators of anxiety levels and thermal comfort levels from the 70 features of the 10 EEG channels. Finally, Random Forest, Gradient Boosting Decision Tree, K-nearest Neighbor Algorithm, and Support Vector Machine were used to determine relevant physiological data combinations and modeling algorithms. The Precision of the anxiety level and thermal comfort level quick identification model based on Random Forest Algorithm can reach 81.04% and 84.79%, respectively. This suggests that the proposed quick identification method for assessing workers' anxiety and thermal comfort levels holds promise. Physiological data need to be obtained by monitoring only PPG, pupil diameter, and 5 EEG channels. By processing these data, the workers' anxiety and thermal comfort level could be judged realistically to ensure their safety. It is suggested that PPG, pupil diameter, and EEG should be considered all together in the future study of anxiety and thermal comfort.     

UAV imagery based potential safety hazard evaluation for high-speed railroad using Real-time instance segmentation

Potential safety hazards (PSHs) along the track needs to be inspected and evaluated regularly to ensure a safe environment for high-speed railroad operations. Other than track inspection, evaluating potential safety hazards in the nearby areas often requires inspectors to patrol along the track and visually identify potential threads to the train operation. The current visual inspection approach is very time-consuming and may raise safety concerns for the inspectors, especially in remote areas. Using the unmanned aerial vehicle (UAV) has great potential to complement the visual inspection by providing a better view from the top and ease the safety concerns in many cases. This study develops an automatic PSH detection framework named YOLARC (You Only Look at Railroad Coefficients) using UAV imagery for high-speed railroad monitoring. First, YOLARC is equipped with a new backbone having multiple available receptive fields to strengthen the multi-scale representation capability at a granular level and enrich the semantic information in the feature space. Then, the system integrates the abundant semantic features at different high-level layers by a light weighted feature pyramid network (FPN) with multi-scale pyramidal architecture and a Protonet with residual structure to precisely predict the track areas and PSHs. A hazard level evaluation (HLE) method, which calculates the distance between identified PSH and the track, is also developed and integrated for quantifying the hazard level. Experiments conducted on the UAV imagery of high-speed railroad dataset show the proposed system can quickly and effectively turn UAV images into useful information with a high detection rate and processing speed.     

基于改进YOLOX-s的安全帽检测

在施工现场中, 发生过许多高空坠落事故, 因此在施工现场佩戴安全帽是十分有必要的. 针对安全帽佩戴状况检测中遇到的小目标样本缺检、漏检的情况, 提出一种基于YOLOX-s的改进算法. 首先, 在Neck层引入主干特征提取网络中的160×160特征层进行特征融合, 并且增加了一个针对小目标的检测头; 其次, 采用SIoU损失函数计算损失值, 使得网络在训练过程中考虑的损失项更加全面; 并且采用varifocal loss函数来计算置信度损失值, 进一步改善训练过程中存在的正样本与困难样本不均衡的问题, 最后, 采用CA (coordinate attention)注意力机制来增强模型的特征表达能力. 实验结果表明, 通过对Neck层与检测层、损失函数的优化以及引入CA注意力机制, 使得网络在训练过程中收敛与回归性能更佳. 改进后的算法的mAP值为95.57%, 相较于YOLOv3及原YOLOX-s算法在mAP值上分别提高了17.11%、3.59%. 改进后的算法检测速度为54.73帧/s, 符合实时检测速度要求.     

RISC-V架构硬件辅助用户态内存安全防御方案概览

传统的用户态内存安全防御机制基于x86架构和纯软件方式实现,实现内存安全保护的运行时开销很高,难以部署在生产环境中.近年来,随着主流商业处理器开始提供硬件安全扩展,以及RISC-V等开源处理器架构的兴起,内存安全保护方案开始面向x86-64、ARM、RISC-V等多种体系架构和硬件辅助实现方式.我们对RISC-V架构上实现的内存安全防御方案进行了讨论,并对x86-64、ARM、RISC-V等处理器架构在安全方案设计上的特点进行了比较.得益于开放的指令集架构生态, RISC-V架构的内存安全防御方案相较于其他架构有一些优势.一些低成本的安全防御技术有望在RISC-V架构上实现.     

Adaptive prescribed time control for quadrotor formation with stochastic links failure

The formation control for multiple quadrotors subject to maintaining the formation configuration and collision avoidance in the situation of stochastic links failure is investigated in this paper. First, the distributed formation controller is designed, the position controller is developed to manage the desired formation of position, and the attitude controller is developed to control the translation and rotation movements of the quadrotor. Then, in order to avoid the collisions between multiple quadrotors and the obstacles, a potential energy function method is introduced into the quadrotor formation control combined with the nest adaptive control. Inspired by the design of event trigger controller, a communication compensation controller is designed to ensure the stability of quadrotor formation under the condition of random communication interruption and recovery. Moreover, a prescribed time function is designed, which means the convergence time of the formation system can be set in advance. The prescribed time stability of the formation control system is proved by Lyapunov theory. Finally, the simulation results verify the effectiveness and superiority of this method.     

统一门户工作下门户网站安全防护研究

门户网站是对外信息发布和网上业务办理的窗口,是与外界进行网络沟通的桥梁,它的正常工作与否不仅直接关系到我们提供的服务质量,而且关系到广西移动的公众形象和客户资料的安全与否.为了提高“统一门户”整合工作后门户网站的安全性,在实现集团“统一门户”工作要求的同时,保证门户网站的安全性,需要提高门户网站安全防控能力.     

煤矿电气安全关键技术研究

分析了2005—2009年全国重特大瓦斯爆炸事故的火源,得出了由电气火源引爆瓦斯事故最多且达48.1%的结论,并分析了矿用电气设备的安全性能,提出了矿用电气设备的使用场所及安全要求:(1)煤矿监控、通信、控制、信号等弱电系统和设备应优选本质安全型电气设备,设备之间传输的信号必须是本质安全型信号;(2)大功率电气设备应优选隔爆型电气设备,隔爆型电气设备宜将接线腔与主腔分腔布置;(3)当瓦斯浓度达到爆炸浓度时严禁开关特殊型矿灯;(4)低瓦斯矿井井底车场等非爆炸性环境宜选用矿用防爆型电气设备;(5)煤与瓦斯突出矿井严禁使用架线电机车和矿用一般型电气设备;(6)井下电气设备的欠压保护和失压保护应有延时措施,减少局部通风机停电次数;(7)井下排水设备宜选用大功率潜水泵;(8)开关等电气设备应设置在全风压进风处,若不能满足,必须设置甲烷传感器,并具备甲烷超限断电闭锁功能。文章对提高煤矿电气安全性、避免或减少瓦斯爆炸和淹井等事故发生具有指导作用。     

矿井作业区域环境安全评价系统的设计与实现

分析了现有煤矿安全监控系统的状况,在安全监测的基础上建立了作业区域危险程度分级判定的评价模型,设计了一个矿井作业区域环境安全评价系统,详细介绍了该系统的设计思想、系统结构原理及主要功能。该系统可对煤矿井下主要作业区域生产安全的环境参数的变化进行动态分析和综合评价,并以不同的颜色给出该作业区域的危险等级,为保证井下作业人员的环境安全提供参考依据。该评价系统可独立运行,也可作为安全监控系统的功能组件运行。     

一种拼接式大型矿用LED阵列显示屏的设计

针对地面应用的大型LED电子显示屏存在功耗大、不能应用到煤矿井下的问题,提出了一种拼接式矿用LED阵列显示屏的设计方案;给出了该显示屏的结构,详细介绍了该显示屏的硬件及软件设计。该显示屏可单独使用,也可与煤矿信息指引系统联合使用。调试与测试结果表明,该显示屏能够实时接收、显示上位机的图形、文字信息,达到了预期目标。     

白云鄂博铁矿东矿边坡稳定性研究

针对白云鄂博铁矿东矿C区边坡产生的3处不稳定滑体,结合现场工程地质勘察和岩石力学试验,采用理正岩土分析软件5.5版及加拿大岩质边坡稳定性分析计算软件SLIDE5.0对削坡、锚索加固、注浆的二次加固措施进行了分析计算,通过计算得到的安全系数来综合判断该二次加固措施的有效性。分析计算结果表明,通过削坡、锚索加固、注浆的加固措施,可以使白云鄂博铁矿东矿C区边坡最危险滑面的安全系数达到1.186,符合设计边坡稳定安全系数要求。文章最后提出了实施这些措施时的注意事项。