基于ISO9000质量管理体系的高校多媒体管理及服务系统设计

本文把高校的多媒体管理系统与ISO9000质量管理体系相结合,探讨了基于ISO9000质量管理体系的高校多媒体管理及服务系统的设计,主要包括两方面,一是把质量管理体系应用到服务教学方面,二是把质量管理体系应用到内部管理方面,而内部管理同时又是为了更好地服务教学,通过ISO9000质量管理体系二者可达到空前的统一.     

基于Web的法律咨询系统的设计与实现

针对法律案例多样化,且法律条文中通常都含有大量专业性很强的法律专用语,使得法律按照条文来分析自身面临了很大难题,本文研究了基于Web的法律信息服务平台的设计与实现,将冗杂无序的网上法律信息进行统一搜集和分类,并提供了大量案例供用户阅读,为用户提供更多有价值的法律信息.系统主要功能有:商务实务查询,相关信息查询,用户权限管理.案例及其类别管理,法律法规及其类别管理,简易论坛,案例搜索,法律法规查询,相似案例查找等.本系统的核心功能是相似案例查找和关键字搜索功能,常要利用Lucene进行切词处理.相似案例查找功能逆向运用了KNN算法的思想,在切词处理后,形成空间向量,利用空间向量计算来分析两案例的相似度,从而实现了相似案例查找.为了实现关键字搜索功能,利用Lucene实现了对数据库中的案例的全文动态索引处理,从而提高了搜索速度和搜索精度.     

Cyclic moving average control approach to cylinder pressure and its experimental validation

Cyclic variability is a factor adversely affecting engine performance. In this paper a cyclic moving average regulation approach to cylinder pressure at top dead center （TDC） is proposed, where the ignition time is adopted as the control input. The dynamics from ignition time to the moving average index is described by ARMA model. With this model, a one-step ahead prediction-based minimum variance controller （MVC） is developed for regulation. The performance of the proposed controller is illustrated by experiments with a commercial car engine and experimental results show that the controller has a reliable effect on index regulation when the engine works under different fuel injection strategies, load changing and throttle opening disturbance.     

车道线检测的PSPNet改进算法

车道线检测已成为智能驾驶领域研究的一项重要课题,而实际应用时,常出现车道线分割不准确、实时检测能力不佳的问题。为此本文提出一种金字塔场景分析网络的改进算法。在编码结构的基础上搭建主体网络PSPNet,选用MobileNet v2轻量级网络作为编码器的主干网络,减少了整体网络的计算复杂度及参数量;网络中添加了空洞卷积,并在不同层间实现特征融合,扩充了模型感受野,同时丰富了局部特征;最后用自适应直线拟合算法对各类型车道线拟合。本文使用Caltech车道线数据集进行测试,实验结果显示,改进后的PSPNet算法对不同类型的车道线均有较好的分割结果,与PSPNet算法相比精度和交并比分别提升了3.91%、4.14%,且FPS达28帧/s,本文算法的分割精度和推理速度均优于其他对比算法。     

An Efficient One-Arrow-Two-Hawks Strategy Achieves High Efficiency and Stable Batch Variance for Benzodifuran-based Polymer Solar Cells

With the development of organic solar cells (OSCs), the high-performance and stable batch variance are becoming a new challenge for designing polymer donors. To obtain high photovoltaic performance, adopting polymers with high molecular weight as donors is an ordinary strategy. However, the high molecular weight need to subtly control the reaction time and state, inevitably caused batch-to-batch variations. Herein, a strategy of steric effect is applied to benzodifuran (BDF)-based polymer by introducing different positions of Cl atom, producing two polymers PBDFCl-1 and PBDFCl-2. The more twisted side chains conformation not only achieve the control of moderate molecular weight for PBDFCl-2, but also easily form molecular stacking through adopting BDF unit and maintain sufficient polymeric crystallinity. Due to the optimized stacking mode and good blend miscibility, PBDFCl-2-based device exhibitsa more elegant power conversion efficiency (PCE) of 17.00% compared to PBDFCl-1-based device. This is the highest efficiency record for BDF-based binary OSCs. Meanwhile, the PCE device variation of the different molecular weights for PBDFCl-2 is little, indicating the reduction of the batch variation. Therefore, smartly using steric effect of Cl atom in strong crystalline BDF unit can form efficient molecular stacking regulations and realize the coordination of high-performance and stable batch variance.     

Tough Transient Ionic Junctions Printed with Ionic Microgels

Emerging soft ionotronics better match the human body mechanically and electrically compared to conventional rigid electronics. They hold great potential for human-machine interfaces, wearable and implantable devices, and soft machines. Among various ionotronic devices, ionic junctions play critical roles in rectifying currents as electrical p–n junctions. Existing ionic junctions, however, are limited in electrical and mechanical performance, and are difficult to fabricate and degrade. Herein, the design, fabrication, and characterization of tough transient ionic junctions fabricated via 3D ionic microgel printing is reported. The 3D printing method demonstrates excellent printability and allows one to fabricate ionic junctions of various configurations with high fidelity. By combining ionic microgels, degradable networks, and highly charged biopolymers, the ionic junctions feature high stretchability (stretch limit 27), high fracture energy (>1000 Jm⁻²), excellent electrical performance (current rectification ratio >100), and transient stability (degrade in 1 week). A variety of ionotronic devices, including ionic diodes, ionic bipolar junction transistors, ionic full-wave rectifiers, and ionic touchpads are further demonstrated. This study merges ionotronics, 3D printing, and degradable hydrogels, and will motivate the future development of high-performance transient ionotronics.     

Understanding Boosted Selective CO2-to-CO Photoreduction with Pure Water Vapor over Hierarchical Biomass-Derived Carbon Matrix

Solar-driven CO₂ reduction reaction (CO₂RR) with water into carbon-neutral fuels is of great significance but remains challenging due to thermodynamic stability and kinetic inertness of CO₂. Biomass-derived nitrogen-doped carbon (N-C_b) have been considered as promising earth-abundant photocatalysts for CO₂RR, although their activities are not ideal and the reaction mechanism is still unclear. Herein, an efficient catalyst is developed for CO₂-to-CO conversion realized on diverse N-C_b materials with hierarchical pore structures. It is demonstrated that the CO₂-to-CO conversion preferentially takes place on positively charged carbon atoms next to pyridinic-N using two representatives treated pollens with the largest difference in pyridinic-N density and N content as model photocatalysts. Systematic experimental results indicate that surface local electric field originating from charge separation can be boosted by hierarchical pore structures, doped N, as well as pyridinic-N. Mechanistic studies reveal that positively charged carbon atoms next to pyridinic-N serve as active sites for CO₂RR, reduce the energy barrier on the formation of CO*, and facilitate the CO₂RR performance. All these benefits cooperatively contribute to treated chrysanthemum pollen catalyst exhibiting excellent CO formation rate of 203.2 µmol h⁻¹ g⁻¹ with 97.2% selectivity in pure water vapor. These results provide a new perspective into CO₂RR on N-C_b, which shall guide the design of nature-based photocatalysts for high-performance solar-fuel generation.     

面向人体健康防护的光纤生化传感技术

光纤生化传感器因具有不受电磁干扰、绝缘性好、安全防爆、损耗低和耐腐蚀等优点,在人体健康防护领 域表现出了良好的应用价值:及时且有效地监测污染物可为环境污染物的有效控制提供数据支撑,从源头上减少疾病的发生;准确且灵敏地检测疾病标志物可诊断人体疾病的情况,从而使得疾病的预防和早期治疗成为可能.对应用于人体健康防护中的光纤生化传感器进行全方位地概述:首先,介绍其使用的光纤传感原理;然后,总结并分析应用于气体和水质污染物监测的光纤生化传感技术;接着,总结并分析应用于人体呼出气体和生物体液检测的光纤生化传感技术;最后,讨论光纤生化传感器在人体健康防护领域实际应用的一些限制因素以及未来的发展方向.     

Stealthy switching attacks on sensors against state estimation in cyber-physical systems

This article focuses on designing sensor attacks to deteriorate the state estimation in cyber-physical systems. The scenario that the malicious attack signals can be injected into different but limited number of sensor communication channels is considered. The state estimation error variations and innovation variations are adopted to measure attack performance and attack stealthiness, respectively. A switching attack strategy is proposed, under which the estimation error variations are driven to the predesigned target value and the norm of innovation variations remains at a small level. The switching attack design problem is formulated as a discrete switched optimal control problem which can be solved by dynamic programming, while the computational burden is heavy. To overcome this difficulty, by using pruning technique to remove the redundant matrices generated in dynamic programming, the quadratic optimization problem becomes numerically tractable. In this way, the suboptimal attack signal sequence and switching sequence can be acquired. Finally, a simulation example is provided to illustrate the effectiveness of the proposed attack strategy.     

IoT设备程序同源性智能检测技术综述

IoT设备与各行业的深度融合方兴日盛,使得IoT程序快速开发的需求不断增长。开发者习惯于集成第三方库或常用代码。不幸的是,若这些代码中隐藏着潜在的漏洞,那他们也会被扩散到不同的程序中,为其大规模扩散创造了条件。这也是造成近年来IoT设备群体性安全事件频发的重要原因之一。为了降低危害,发现具备相似漏洞的程序并进行相关的处置是一个有效的方法。同源性分析作为挖掘程序间关联关系的重要手段之一,可高效地实现程序漏洞的智能溯源取证。结合机器学习和深度学习技术,它表现出解决大规模程序安全性检测的巨大潜力。然而,IoT设备的软硬件特点仍使得该技术的使用面临挑战。当前已有诸多方案在IoT设备程序的同源性智能检测方面取得了进展。因此,本文将系统性回顾近年来相关技术研究的成果,将他们分为相似性分析和创作者归属技术。首先,我们介绍了两种方式的数据来源。接着,检测过程中涉及的特征选择、特征表示以及相对应的检测方法也被依次介绍。进一步的,本文不仅比较和总结了方案的特点和局限性,还对他们在不同类型IoT设备程序的适配性进行了对比分析。最后,文章针对IoT程序分析提出了一些研究建议。作者希望本综述可为研究者阐明这些工作的核心技术点,并为他们在IoT设备上的进一步应用提供启发。