A novel design for humidifying an open-cathode proton exchange membrane fuel cell using anode purge

The low performance of open-cathode proton-exchange-membrane fuel cells (OCPEMFCs) is attributed to the low-humidity ambient air supplied to the cathode using electric fans. To improve the OCPEMFC performance, this paper proposes a novel humidification method by collecting water purged from the anode and supplying it to the open cathode. The OCPEMFC performance is evaluated at various humidifier distances from the cathode inlet, and it is compared with that where no humidifier is used when the OCPEMFC operates under three different current levels of 1, 5, and 8 A. The results show that the novel design improves the stack power, and optimal performance is achieved at a humidifier distance of 2 cm. The energy efficiency achieves an improvement between 1.4% and 1.8% when a humidifier is used.     

Patterns in environmental priorities revealed through government open data portals

The ways in which environmental priorities are framed are varied and influenced by political forces. One technological advance--the proliferation of government open data portals (ODPs)--has the potential to improve governance through facilitating access to data. Yet it is also known that the data hosted on ODPs may simply reflect the goals and interests of multiple levels of political power. In this article, I use traditional statistical correlation and regression techniques along with newer natural language processing and machine learning algorithms to analyze the corpus of datasets hosted on government ODPs (total: 49,066) to extract patterns that relate scales of governance and political liberalism/conservatism to the priorities and meaning attached to environmental issues. I find that state-level and municipal-level ODPs host different categories of environmental datasets, with municipal-level ODPs generally hosting more datasets pertaining to services and amenities and state-level ODPs hosting more datasets pertaining to resource protection and extraction. Stronger trends were observed for the influences of political conservatism/liberalism among state-level ODPs than for municipal-level ODPs.     

直角坐标在软件开发中的应用研究

为简化不同软件开发技术处理界面中组件关系的算法,增强使用数学模型解决软件开发中算法设计的能力,全面分析和总结直角坐标系在界面设计中的应用十分必要。通过对不同开发技术处理界面设计的分析,界面中组件位置关系实质上都可以转化为坐标关系的计算。本文列举了直角坐标系在Python编程、Android编程、Java编程和Unity编程中的应用,以期给相应的算法设计提供借鉴思路。     

基于残差决策的自动飞行控制系统远程实时故障诊断

针对自动飞行控制系统结构复杂、关联部件众多,发生故障时诊断时间长,从而影响飞机运行效率的问题,提出一种基于飞机通信寻址报告系统(ACARS)的远程实时故障诊断方案。首先,分析自动飞行控制系统的故障特点,设计搭建检测滤波器;然后,利用ACARS数据链实时发送的自动飞行控制系统的关键信息进行相关部件的残差计算,并根据残差决策算法进行故障诊断及定位;最后,针对不同故障部件残差间的差异大、决策门限无法统一的缺点,提出基于二次差值的残差决策改进算法,减缓了检测对象的整体变化趋势,降低了随机噪声和干扰的影响,避免了将瞬态故障诊断为系统故障的情况。实验仿真结果表明,基于二次差值的改进残差决策算法避免了多决策门限的复杂性,在采样时间为0.1 s的情况下,故障检测所需时间大约为2 s,故障检测时间大幅降低,有效故障检测率大于90%。     

Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

铜浮选专家控制系统设计与应用

针对国内某选矿厂铜浮选工艺泡沫速率不稳定,精矿品位波动大,回收率不理想等特点,设计了一套浮选专家控制系统,该系统结合泡沫影像分析技术,在线品位分析技术,PID控制与模糊逻辑控制技术。系统架构简明合理,逻辑层次清晰有效,投入运行一段时间后,在不同原矿品位前提下,都能实现稳定泡沫速率,减少精矿品位波动,提高回收率等指标优化,同时药剂添加量也有明显减少。这表明该系统运行效果良好,值得应用推广。     

一种北斗联合低轨星座的导航增强方法研究

单纯依靠北斗导航系统提供定位导航授时服务,存在卫星信号落地功率低、易受遮蔽和阻断的不足。针对此问题,研究了一种北斗联合低轨星座实现导航增强的系统架构;提出了一种新的适应严重遮蔽或干扰条件下,基于到达时间(TOA)和到达频率(FOA)联合观测的定位解算算法;对高中低轨混合星座条件下的覆盖特性和精度衰减因子进行了仿真分析。分析结果表明,用户可见星数平均增加了64.2%,位置精度衰减因子(PDOP)平均改善了28.7%。研究结果可为下一代北斗的论证设计与研制建设提供参考借鉴。     

快递分拣机器人控制系统的设计

为提高快递分拣效率,设计了一种基于OpenMV机器视觉模块的快递分拣机器人控制系统。在这一控制系统中,通过机器视觉技术实现快递件的轮廓识别、定位、扫码及分类,将STM32单片机作为运动控制核心,外接传感器感知机器人的状态,基于串口与机器视觉模块双向通信,实现对放置在地面的快递件进行自动分拣。通过制作样机验证了设计的合理性与可行性。     

矿用无人卡车国内外研究现状及关键技术

分析了国内外露天矿山用卡车无人驾驶技术发展现状,详细介绍了露天矿山卡车无人驾驶关键技术;通过分析对比前装线控和后装线控两种技术路线的优缺点以及超声波雷达、毫米波雷达、激光雷达、4D光场智能感知系统、红外传感器、视觉传感器等环境感知技术的优缺点;提出多传感器高度融合将是露天矿山卡车实现全天候环境感知的发展方向。通过分析对比惯性导航系统、GNSS差分定位技术、车联网定位技术、电子地图定位技术、视觉传感器等定位导航技术的差异,指出多定位技术融合是露天矿山无人驾驶卡车定位方式的必然选择。结合露天煤矿的生产实际,提出将现有的无人驾驶各种技术算法与露天矿山标准作业流程有机融合是实现卡车无人驾驶的必由之路。最后指出无人驾驶卡车应用5G技术是露天矿山安全生产的关键和核心,是无人驾驶的必备技术。