RMPC-Based Visual Servoing for Trajectory Tracking of Quadrotor UAVs With Visibility Constraints

Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.

High-visibility ghost imaging with phase-controlled discrete classical light sources

We take phase modulation to create discrete phase-controlled sources and realize the super-bunching effect by a phasecorrelated method. From theoretical and numerical simulations, we find the space translation invariance of the bunching effect is a key point for the ghost imaging realization. Experimentally, we create the orderly phase-correlated discrete sources which can realize high-visibility second-order ghost imaging than the result with chaotic sources. Moreover, some factors affecting the visibility of ghost image are discussed in detail.

Detection of EEG signals in normal and epileptic seizures with multiscale multifractal analysis approach via weighted horizontal visibility graph

Electroencephalogram(EEG) signals contain important information about the regulation of brain system. Thus, automatic detection of epilepsy by analyzing the characteristics obtained from EEG signals has important research implications in the field of clinical medicine. In this paper, the horizontal visibility graph(HVG) algorithm is used to map multifractal EEG signals into complex networks. Then, we study the structure of the networks and explore the nonlinear dynamics properties of the EEG signals inherited from these networks. In order to better describe complex brain behaviors, we use the angle between two connected nodes as the edge weight of the network and construct the weighted horizontal visibility graph(WHVG). In our studies, fractality and multifractality of WHVG are innovatively used to analyze the structure of related networks. However, these methods only analyze the reconstructed dynamical system in general characterizations,they are not sufficient to describe the complex behavior and cannot provide a comprehensive picture of the system. To this effect, we propose an improved multiscale multifractal analysis(MMA) for network, which extends the description of the network dynamics features by focusing on the relationship between the multifractality and the measured scale-free intervals.Furthermore, neural networks are applied to train the above-mentioned parameters for the classification and identification of three kinds of EEG signals, i.e., health, interictal phase, and ictal phase. By evaluating our experimental results, the classification accuracy is 99.0%, reflecting the effectiveness of the WHVG algorithm in extracting the potential dynamic characteristics of EEG signals.

Two-dimensional horizontal visibility graph analysis of human brain aging on gray matter

Characterizing the trajectory of the healthy aging brain and exploring age-related structural changes in the brain can help deepen our understanding of the mechanism of brain aging.Currently,most structural magnetic resonance imaging literature explores brain aging merely from the perspective of morphological features,which cannot fully utilize the grayscale values containing important intrinsic information about brain structure.In this study,we propose the construction of two-dimensional horizontal visibility graphs based on the pixel intensity values of the gray matter slices directly.Normalized network structure entropy(NNSE)is then introduced to quantify the overall heterogeneities of these graphs.The results demonstrate a decrease in the NNSEs of gray matter with age.Compared with the middle-aged and the elderly,the larger values of the NNSE in the younger group may indicate more homogeneous network structures,smaller differences in importance between nodes and thus a more powerful ability to tolerate intrusion.In addition,the hub nodes of different adult age groups are primarily located in the precuneus,cingulate gyrus,superior temporal gyrus,inferior temporal gyrus,parahippocampal gyrus,insula,precentral gyrus and postcentral gyrus.Our study can provide a new perspective for understanding and exploring the structural mechanism of brain aging.

Visibility graph approach to extreme event series

An extreme event may lead to serious disaster to a complex system.In an extreme event series there exist generally non-trivial patterns covering different time scales.Investigations on extreme events are currently based upon statistics,where the patterns are merged into averages.In this paper from extreme event series we constructed extreme value series and extreme interval series.And the visibility graph is then adopted to display the patterns formed by the increases/decreases of extreme value or interval faster/slower than the linear ones.For the fractional Brownian motions,the properties for the constructed networks are the persistence,threshold,and event-type-independent,e.g.,the degree distributions decay exponentially with almost identical speeds,the nodes cluster into modular structures with large and similar modularity degrees,and each specific network has a perfect hierarchical structure.For the volatilities of four stock markets(NSDQ,SZI,FTSE100,and HSI),the properties for the former three's networks are threshold-and market-independent.Comparing with the factional Brownian motions,their degree distributions decay exponentially but with slower speeds,their modularity behaviors are significant but with smaller modularity degrees.The fourth market behaves similar qualitatively but different quantitatively with the three markets.Interestingly,all the transition frequency networks share an identical backbone composed of nine edges and the linked graphlets.The universal behaviors give us a framework to describe extreme events from the viewpoint of network.

Analysis of the Causes of a Low Cloud and Low Visibility Weather at Cangyuan Washan Airport

At 11:00 am on August 5, 2017, Cangyuan Washan Airport experienced low cloud and low visibility weather, accompanied by aircraft turbulence, which affected the normal operation of flights, which was closely related to the meteorological conditions at that time. Using the hourly reanalysis data of the European Centre for Medium-range Weather Forecast (ECMWF) Reanalysis 5 (ERA5), including Geopotential height, temperature, precipitation, wind field, specific humidity, vorticity and other elements, with a spatial resolution of 0.25° × 0.25°, this paper focuses on the horizontal distribution and vertical configuration of various physical quantities before and after the occurrence of low cloud and low visibility weather at the airport. The results indicate that the main influencing system of this low cloud and low visibility weather is the westward tropical depression. Before the occurrence of low cloud and low visibility weather, low-level water vapor converges and is accompanied by precipitation. The temperature decreases with precipitation, the near-surface wind direction changes, and the wind speed decreases.

N-CDs@Nb_(2)O_(5)-AMMC纳米材料的制备及其可见光催化性能研究

通过工艺简单的水热法成功制备出N-CDs和不同含量N-CDs修饰的N-CDs-X@Nb_(2)O_(5)-AMMC纳米材料。对N-CDs-X@Nb_(2)O_(5)-AMMC进行XRD、SEM、TEM、FT-IR、XPS和UV-vis DRS等表征分析。结果表明,经过N-CDs改性之后Nb_(2)O_(5)-AMMC的带隙变窄,样品的吸收边红移和光吸收范围变宽,从而有利于提高光催化性能。另外,N-CDs减少了电子传输的阻力,有利于光生电子向N-CDs结构的转移,同时光生载流子的迁移及分离效率提高,有利于光催化反应的进行。与纯Nb_(2)O_(5)-AMMC相比,N-CDs-X@Nb_(2)O_(5)-AMMC在可见光下光催化降解TC-HCl的性能均有提高,其中样品N-CDs-1@Nb_(2)O_(5)-AMMC的降解效率最高,1 h内对TC-HCl的降解率能达到63.2%,是纯Nb_(2)O_(5)-AMMC的1.59倍。

基于深度学习的玉米包衣种子品种识别

为实现玉米包衣种子品种低成本、高效便捷识别,基于智能手机采集的18个品种4种颜色的23100张玉米包衣种子双面图像构建数据集,采用轻量级卷积神经网络模型ShuffleNetV2、MobileNetV3、MobileViT、MobileOne、RepGhostNet和基于上述模型的集成模型分别进行玉米包衣种子品种识别。结果表明,5种单一模型均具有较高的识别准确率和综合性能,识别准确率分别为98.48%、98.23%、98.44%、98.23%和98.01%,模型大小分别为1.55、4.96、4.42、6.97、4.19 MB,推理速度分别为106、94、84、212、94 f/s。集成模型相比单一模型具有更高的识别准确率,其中,ShuffleNetV2和MobileViT组成的集成模型识别准确率达到99.22%。分析发现,品种误识别仅发生在相同颜色包衣种子品种之间,并且随着相同颜色包衣种子品种数量增多,模型对该颜色包衣种子的识别准确率有下降的趋势。

紫外可见波长溶液标准物质的研制

以紫外可见区无吸收的高氯酸溶液作为空白基体,利用稀土元素钬和钕在紫外可见光区丰富的光谱特征吸收,研制一种可以覆盖200~900nm的紫外可见区的波长溶液标准物质。采用对峰值点附近进行3次样条插值进行数据处理,并以插值后的峰值数据作为峰值波长,分辨力可到小数点后两位。经过均匀性和稳定性检验,由9家实验室采用高精度紫外可见分光光度计对该标准物质进行协同定值,并进行不确定度评定。结果表明,该标准物质均匀性良好,在25℃下保存稳定性在1年以上。该标准物质可应用于光谱光度测量仪器的波长校准和期间核查等。

可见光减反射膜薄层控制误差的分析与性能优化

为提升光学镜头的成像质量,消除杂散光的影响,以K9玻璃为基底设计可见光波段平均反射率小于0.1%的减反射膜。采用电子束离子辅助沉积的制备方式,针对薄层敏感度高、光谱变化大等问题,通过建立稳定控制膜层厚度的数学模型来减小膜厚误差,提高制备精度和成膜稳定性。对减反射膜进行环测实验,优化调整工艺参数,侧重提高减反射膜的硬度和耐水煮能力。实验结果表明,最终制备出的减反射膜在420~680 nm波段内的平均反射率约为0.044%,最高反射率为0.0712%,克服了以MgF2为外层的减反射膜机械性能和化学稳定性较差的问题,满足工程应用低损耗、稳定可靠、高强度、可重复性制备的要求。

GQDs/TiO_(2)可见光催化降解抗抑郁药阿米替林的研究

阿米替林是一种被广泛使用的抗抑郁药,阿米替林及其代谢产物对水生生物和人体健康产生危害。阿米替林作为一种新兴污染物,其去除方法的研究受到广泛关注。研究采用水热法制备石墨烯量子点/二氧化钛(GQDs/TiO_(2))复合催化剂,通过X射线粉末衍射(XRD)、扫描电镜(SEM)和比表面测试(BET)表征了复合物的结构和形貌。催化剂可见光催化降解阿米替林性能表明,当GQDs的负载量为4%,溶液pH为11,催化剂投加量为0.08 g,阿米替林的初始浓度为5μmol/L时,GQDs/TiO_(2)对阿米替林的降解性能达到最优,为93.1%。GQDs的引入促进了光生电子空穴对的有效分离和转移,超氧阴离子自由基(·O_(2)^(-))是光催化过程中最主要的活性物种,其次是电子(e^(-))和羟基自由基(·OH)。

我国6个典型城市大气能见度及其影响因素研究

采用线性相关性分析、分类变量分析等统计学方法,分析了巴彦淖尔、石家庄、廊坊、郑州、武汉、广州六市2019—2020年的PM_(2.5)与气象观测数据,研究了PM_(2.5)浓度与大气相对湿度对大气能见度的影响。结果表明:六市大气能见度年变化规律虽存在较大差异,但最低值均出现于每年12月—次年2月,且年变化规律基本一致;气象条件、相对湿度、PM_(2.5)浓度对能见度的影响明显,其中相对湿度通过改变PM_(2.5)物化性质间接影响能见度,与能见度相关程度相对较弱。PM_(2.5)浓度与能见度的线性相关性良好,以幂函数为主;整体上,相对湿度与PM_(2.5)浓度对大气能见度影响呈协同作用,相对湿度越大的城市对PM_(2.5)的控制要求越高。此外,PM_(2.5)浓度高于平台点时,大气能见度基本不随PM_(2.5)浓度增加而继续降低,只有PM_(2.5)浓度低于突变点时,大气能见度才会随PM_(2.5)浓度降低而显著提升,各市能见度突变点与平台期点所对应PM_(2.5)浓度差异较大。

机场能见度临近预测方法

能见度是保障机场航班安全、正常运行的重要标准之一。为精准预测能见度,使用2020年天津机场气象和常规空气质量监测数据,构建基于方差膨胀因子(Variance Inflation Factor,VIF)、主成分分析(Principal Components Analysis,PCA)和Informer的能见度预测模型,并将均方根误差、平均绝对误差、平均绝对百分比误差作为评价指标进行误差分析。结果显示,VIF PCA Informer模型比单一的Informer和简单组合模型效果更优,能更好地捕捉长时间序列特征的关系。相比于单一的Informer、长短期记忆神经网络和门控循环单元模型,VIF PCA Informer模型均方根误差下降了0.2141~0.3486,平均绝对误差下降了0.1842~0.2753,平均绝对百分比误差下降了0.3224~0.5270;VIF PCA Informer模型对能见度的临近预测(1 h)更为精准。使用高效的机场能见度预测模型可在保障航班安全高效运行方面发挥较大支撑作用。

可见光室内定位技术研究进展

可见光赋能的定位技术具有无电磁辐射、成本低、精度高、安全性高、不易受电磁干扰等优势,故近年来可见光室内定位技术(Visible Light Indoor Positioning,VLIP)受到了学界和业界的广泛关注。为了展示VLIP的研究进展和发展全貌,阐述了VLIP的系统架构及相关通信技术,对VLIP基础定位方法及其相关辅助定位技术进行了详细地梳理、分类和对比分析,针对VLIP当前面临的挑战分析了潜在的解决方案,展望了VLIP未来研究方向。

基于SSK的室内VLPC系统设计及性能分析

本文设计了一个多输入单输出(Multiple-Input Single-Output,MISO)的三维室内可见光定位通信一体化(Visible Light Position and Communication,VLPC)系统,该系统在接收端基于接收信号强度(Received Signal Strength,RSS)的三维可见光定位(Visible Light Position,VLP)算法获得定位数据,同时估计信道状态信息(Channel State Information,CSI)并上传给发射端进行定向通信.该系统的发射端基于空移键控(Space Shift Keying,SSK)的室内可见光通信(Visible Light Communication,VLC)技术实现系统的通信功能.另外,本方案可以完全避免通信与定位子系统之间的干扰.同时,通过推导定位误差的克拉美罗下界(Cramér-Rao Lower Bound,CRLB)和SSK-VLC的通信可达速率来评估本文提出的VLPC系统的性能.仿真结果验证了本文所提方案的有效性.

兽用中化药注射剂可见异物现状分析及对策探讨

本文旨在探讨兽用中化药注射剂中可见异物的原因及对策。通过总结近5年兽药质量监督抽检中可见异物的检测情况,从人员、设备、原辅料质量、生产工艺、环境等方面对导致注射剂可见异物的主要原因进行了分析。基于产品全过程质量控制理念,有针对性的提出了系列控制对策和措施,希望有助于帮助兽药生产企业降低可见异物的发生概率,保障兽药质量安全和动物养殖健康。

铁磷共掺杂氮化碳光催化剂的制备及催化性能

以双氰胺单体、硝酸铁和磷酸氢二铵为前驱体,制备了铁磷共掺杂氮化碳(P/Fe-CN)。采用X射线衍射(XRD)、扫描电镜(SEM)、透射电镜(TEM)、X光电子能谱(XPS)和BET比表面积分析等方法研究了P/Fe-CN的晶相、结构和元素组成。结果表明:Fe和P共掺杂的协同作用打开了原始氮化碳紧密的片层堆积结构和团聚状态,有效降低了原始g-C_(3)N_(4)的禁带宽度,增加了活性物质,提高了光催化性能。其中,P掺杂量为5%的双掺杂样品(5%P/Fe-CN)在可见光下对甲基橙(MO)表现出最优的光催化活性。其光催化降解MO的速率常数为0.03863min-1,是g-C 3N 4光催化效率的4.7倍。紫外-可见光(UV-Vis)结果表明,5%P/Fe-CN的带隙宽度为2.248eV,较原始g-C 3N 4减小了0.331eV。

建筑空间可视性分析的量化研究综述

文章通过对空间可视性分析方法相关文献的检索和梳理,对通视性分析、可视域分析和可视图分析法进行了介绍。这些方法为空间量化研究提供了理论基础与技术工具,通过运用不同的分析方法,可以解释不同领域的空间环境问题。具体而言,文章从城市规划与景观设计、建筑空间认知与行为预测、消防安全、战术规划和军事应用、自然景观等五个领域的应用进行了概括和总结,希望能够为后续的环境空间研究提供一定的启示和借鉴。

三维多级结构α-FeOOH的制备及其光催化性能

以硝酸铁、尿素及表面活性剂为原料,过滤沉淀得饱和溶液,在70℃的条件下通过尿素的缓慢水解低温水热合成了形貌均一的花状或海胆状三维多级结构α-FeOOH,用XRD、SEM、TEM、FTIR等进行了表征。讨论了反应物浓度和反应时间对产物形貌的影响,对该物质的形成机理进行了推理。250℃煅烧α-Fe00H可以得到形貌不变的α-Fe_(2)O_(3)。以卤钨灯为可见光源,α-Fe0OH为催化剂,在Fe_(2)O_(3)存在下,可见光催化降解亚甲基蓝效果最好。

通过包络面重构的大规模粒子并行绘制算法

针对大规模粒子高表现可视化需求,提出基于包络面重构的大规模粒子并行绘制算法。该算法以连续曲面的形式表示,绘制大规模粒子的团簇表面及其物理量分布。对算法进行了分布式并行化,从而可以通过大规模并行来处理亿以上规模的粒子数据。在算法实现上,还解决了并行计算时的块间裂缝问题,并提出了快速查找邻域粒子的方法,同时,基于可见性对粒子数据进行剔除,提高了绘制效率。由此,可以通过带光照效果的光滑曲面来高表现展示大规模粒子数据中的团簇结构及其物理量分布。实验结果表明,该算法在512核上可在5 s内完成上亿粒子的绘制,并行效率可达60%。该算法已成功应用到大规模并行非平衡分子动力学模拟等实际模拟应用中。