An infrared small target detection algorithm based on high-speed local contrast method

Small-target detection in infrared imagery with a complex background is always an important task in remote sensing fields. It is important to improve the detection capabilities such as detection rate, false alarm rate, and speed. However, current algorithms usually improve one or two of the detection capabilities while sacrificing the other. In this letter, an Infrared (IR) small target detection algorithm with two layers inspired by Human Visual System (HVS) is proposed to balance those detection capabilities. The first layer uses high speed simplified local contrast method to select significant information. And the second layer uses machine learning classifier to separate targets from background clutters. Experimental results show the proposed algorithm pursue good performance in detection rate, false alarm rate and speed simultaneously.     

Highly flexible,transparent, conductive and antibacterial films made of spin-coated silver nanowires and a protective ZnO layer

We prepared highly flexible, transparent, conductive and antibacterial film by spin coating a silver nanowire suspension on a poly (ethylene terephthalate) (PET) substrate. The ZnO layer covered the conductive silver nanowire (AgNW) network to protect the metal nanowires from oxidization and enhance both wire-to-wire adhesion and wire-to-substrate adhesion. It is found that the number of AgNW coatings correlates with both the sheet resistance (R_s) and the transmittance of the AgNW/ZnO composite films. An excellent 92% optical transmittance in the visible range and a surface sheet resistance of only 9 Ω sq⁻¹ has been achieved, respectively. Even after bending 1000 times (5 mm bending radius), we found no significant change in the sheet resistance or optical transmittance. The real-time sheet resistance measured as a function of bending radius also remains stable even at the smallest measured bending radius (1 mm). The AgNW/ZnO composite films also show antibacterial effects which could be useful for the fabrication of wearable electronic devices.     

A scheme for a topological insulator field effect transistor

We propose a scheme for a topological insulator field effect transistor. The idea is based on the gate voltage control of the Dirac fermions in a ferromagnetic topological insulator channel with perpendicular magnetization connecting to two metallic topological insulator leads. Our theoretical analysis shows that the proposed device displays a switching effect with high on/off current ratio and a negative differential conductance with a good peak to valley ratio.     

3D α-Fe_2O_3/掺氮石墨烯/碳纳米管复合材料及其储锂性能

针对α-Fe2O3负极在充放电过程中存在的体积膨胀及首次库伦效率低等主要问题,本文采用简单的水热法制备出具有三维多孔结构的α-Fe2O3/掺氮石墨烯(N-GNS)/碳纳米管(CNTs)复合材料。XRD,SEM,TEM及XPS等测试结果表明碳纳米管成功插入到掺氮石墨烯片层间,暴露N-GNS表面的晶格缺陷,为α-Fe2O3晶体生长提供了大量成核位点。粒径大小为30~70 nm的α-Fe2O3颗粒均匀锚定于N-GNS/CNTs三维复合碳载体内进行高效储锂反应。电化学测试结果显示,这种三维复合结构有效改善了α-Fe2O3/GNS负极的电化学性能。     

双金属氮化物Co3W3N/CNTs纳米复合材料的制备及其室温常压氮还原性能

采用水热法并经氨气保护热处理制备了双过渡金属氮化物Co3W3N/CNTs复合材料,得到了价格低廉且拥有良好氮电化学还原性能(NRR)的催化剂。通过调节已经预氧化的CNTs与过渡金属氮化物前驱体CoWO4的比例以及氨气热处理温度,实现了Co3W3N在CNTs表面的均匀负载。扫描电子显微镜(SEM)及透射电子显微镜(TEM)测试结果显示该电化学活性纳米微粒均匀地分散于CNTs表面,表明经预氧化的CNTs由于表面富集了较多的活性基团,有利于双过渡金属氮化物的分散生长。热处理后CNTs表面的Co3W3N微粒尺寸约为20 nm,相较于无载体的Co3W3N尺寸(100 nm)有明显减小。室温条件下,在N2饱和的0.01 mol·L^-1 H2SO4溶液中测试了该纳米复合材料在不同过电位下的NRR,该材料在-0.3 V(vs RHE)时的产氨率及法拉第效率分别可达12.73μg·h^-1·cm-2和13.59%,对比同样条件下,纯相Co3W3N的产氨率及法拉第效率仅为1.08μg·h^-1·cm^-2和1.76%。结果表明,通过水热反应和氨气保护热处理的Co3W3N/CNTs纳米复合材料具有良好的NRR性能。     

基于神经网络的核电厂设备易损性分析

核电结构的易损性分析是核电厂地震安全评估中至关重要的一环, 但是由于核电结构的复杂性以及考虑土?结相互作用SSI时较大的计算规模, 使得计算核电厂设备易损性曲线十分耗时. 为发展高效的核电厂设备易损性分析方法, 本文采用核电结构土?结相互作用分析的分区计算方法, 并利用有限的SSI分析结果建立神经元模型ANN代替有限元模型, 分别基于对数正态假定的回归法和蒙特卡洛法进行了设备易损性分析. ANN数值模拟包括了以下内容: (1)基于半偏相关系数选择最相关的地震动参数作为ANN输入, 并通过交叉检验建立神经元模型; (2)量化研究ANN数值模拟的预测不确定性, 其中包含了由于简化地震动输入引起的随机不确定性和训练样本缺失引起的认知不确定性; (3)基于ANN模型预测结果分别采用蒙特卡洛法和基于对数正态假定的回归法进行设备的易损性分析. 本文探讨了不同的地震强度指标以及土层材料的不确定性对易损性曲线的影响, 同时验证了回归法中对数正态模型假定的基本合理性, 为核电厂设备易损性分析提供了一种可能方向.      

基于大偏差理论非高斯随机动力系统离出行为研究

本文介绍了大偏差理论的基本思想及其在非高斯随机动力系统的离出问题研究中的应用.依据不同的非高斯噪声类型,本文分别评述了随机混合系统、指数轻跳跃过程和α稳定Lévy噪声驱动的随机动力系统的离出问题的主要研究方法和近期研究进展.针对随机混合系统,本文介绍了利用随机微分方程对其进行近似的拟稳态扩散近似方法,计算拟势和最优离出路径的WKB近似方法与细致平衡条件的研究,以及求解随机混合系统的简化版本(即生灭过程)的离出问题的研究进展.对于指数轻跳跃过程驱动的随机动力系统,本文介绍了其大偏差原理和中度偏差原理的泛函极值问题的建立,拟势概念的定义和平均离出时间的估计.针对具有α稳定Lévy噪声的随机动力系统,本文介绍了计算平均首次离出时间和离出概率的理论和数值方法,计算最优离出路径的Onsager-Machlup理论、机器学习方法、最大似然法和数据驱动方法.最后,给出了非高斯随机动力系统的离出现象相关的一些开放性问题.