PIC simulation of plasma properties in the discharge channel of a pulsed plasma thruster with flared electrodes

Plasma in the discharge channel of a pulsed plasma thruster (PPT) with flared electrodes is simulated by a self-developed two-dimensional code. The fully particle-in-cell method with Monte Carlo collision is employed to model the particle movement and collisions and investigate the plasma properties and acceleration process. Temporal and spatial variations of the electron density distribution and the ion velocity between electrodes are calculated and analyzed in detail. The computational results of the electron number density, which is in the order of 10²³ m⁻³, show good agreements with experimental results of a PPT named ADD SIMP-LEX. The ion velocity distributions along the center line of the channel lead to a comprehensive understanding of ions accelerated by electromagnetic field. The electron distributions of PPT with discharge voltages varying from 1300 to 2000 V are compared. The diffusion of electrons presents strong dependency on discharge voltage and implies higher degree of ionization for higher voltage.     

一种用于故障隔离的参数区间包络线计算方法

基于参数区间的故障隔离方法的核心工具是区间判断阈值曲线,其计算一直是制约该方法发展的问题。参数区间动态轨迹包络线作为区间判断阈值曲线具有能够适用于多重参数故障隔离等优点,但包络线计算中的包裹效应问题在该领域内一直未能得到很好解决。介绍一种基于上、下函数的包络线计算方法,有别于区间算法计算的包络线随着迭代的进行而迅速变得肥大的可能性,采用该方法的仿真实验表明其计算的包络线的包裹效应得到很大程度上的减轻,可有效用于故障隔离的区间判断。     

Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language

Because of using traditional hand-sign segmentation and classification algorithm,many diversities of Bangla language including joint-letters,dependent vowels etc.and representing 51 Bangla written characters by using only 36 hand-signs,continuous hand-sign-spelled Bangla sign language(BdSL)recognition is challenging.This paper presents a Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language which consists of two phases.First phase is designed for hand-sign classification and the second phase is designed for Bangla language modeling algorithm(BLMA)for automatic recognition of hand-sign-spelled Bangla sign language.In first phase,we have proposed two step classifiers for hand-sign classification using normalized outer boundary vector(NOBV)and window-grid vector(WGV)by calculating maximum inter correlation coefficient(ICC)between test feature vector and pre-trained feature vectors.At first,the system classifies hand-signs using NOBV.If classification score does not satisfy specific threshold then another classifier based on WGV is used.The system is trained using 5,200 images and tested using another(5,200×6)images of 52 hand-signs from 10 signers in 6 different challenging environments achieving mean accuracy of 95.83%for classification with the computational cost of 39.972 milliseconds per frame.In the Second Phase,we have proposed Bangla language modeling algorithm(BLMA)which discovers all"hidden characters"based on"recognized characters"from 52 hand-signs of BdSL to make any Bangla words,composite numerals and sentences in BdSL with no training,only based on the result of first phase.To the best of our knowledge,the proposed system is the first system in BdSL designed on automatic recognition of hand-sign-spelled BdSL for large lexicon.The system is tested for BLMA using hand-sign-spelled 500 words,100 composite numerals and 80 sentences in BdSL achieving mean accuracy of 93.50%,95.50%and 90.50%respectively.     

Finite-time consensus protocols for multi-dimensional multi-agent systems

A finite-time consensus protocol is proposed for multi-dimensional multi-agent systems, using direction-preserving signum controls. Filippov solutions and nonsmooth analysis techniques are adopted to handle discontinuities. Sufficient and necessary conditions are provided to guarantee infinite-time convergence and boundedness of the solutions. It turns out that the number of agents which have continuous control law plays an essential role in finite-time convergence. In addition, it is shown that the unit balls introduced by ?p norms, where p∈[1,∞], are invariant for the closed loop.     

以金属氧化物为原料改进燃烧法合成γ-LiAlO_2（英文）

提出一种合成γ-LiAlO_2的替代解决方案—改进燃烧法直接合成γ-LiAlO_2,并将其用于相对简单的反应体系中,原料为非氧化性化合物如Al_2O_3和LiOH,燃料为尿素。采用1:1、1.5:1和2:1的非化学计量Li/Al摩尔比,在900和1000°C下反应5 min,制备LiAlO_2,并对其组织和结构进行表征。考察Li/Al摩尔比对材料形貌和高γ射线辐照下材料稳定性的影响。结果表明,所得粉体的晶体结构为?-LiAlO_2和?-LiAlO_2,其取决于Li/Al摩尔比。因此,用该方法可以成功合成微砖状、多面体状和层状?-LiAlO_2,而无需任何后续处理。γ辐照结果表明,所得到的?-LiAlO_2不分解,只形成少量的Li_2CO_3;由此可以确定,辐照会导致固结,不利于氚的有效提取;结果证明,用燃烧法生产高纯度?-LiAlO_2不需要硝酸盐前驱体。     

重振美国水电行业面临的挑战

对目前美国水电行业现状、近期计划开发项目以及相关机构立法情况进行了简述。指出重振美国水电行业面临的国有水利基建融资困难和项目审批程序冗长等问题,建议美国总统特朗普能与相关政府机构合作重振美国水电行业。     

空间的力量 新奥胡斯大学医院

正新奥胡斯大学医院是丹麦第一个超大型的医院案例,也是一个具有"康复医疗"概念的、超现代的国际先锋作品。医院的建筑设计通过系统运用"信息和循证"的工作方法,践行了"康复建筑"的综合理念。其"信息和循证"的方法是利用对现存建筑的研究和评估,以提供最有效的信息来创建最佳的康复建筑。从单人病房的设计、日光和光线的利用,以及景观和花园空间的设计,旨在尽量满足病人的需求,提升     

转子/密封系统失稳振动抑制的动力吸振方法研究

针对密封中流体引起转子/密封系统振动失稳的问题。提出采用动力吸振器(DVA)实现转子/密封系统失稳振动抑制。建立转子/密封-DVA系统非线性微分方程,采用数值方法求解并获得附加DVA前后转子/密封系统的非线性特性;根据Hurwitz判据获得系统的临界稳定条件;通过遗传算法优化DVA参数,获得附加优化DVA前后转子/密封系统稳定性。结果表明:附加DVA能够改变转子/密封系统失稳振动频率和失稳阈值;在一定的转速范围内失稳振动被完全抑制;在不完全抑制的转速范围内,附加DVA能降低失稳振动的振幅。     

基于深度网络迁移学习的致痫区脑电识别* .txt

摘要：致痫区脑电识别能够为癫痫外科手术提供重要的参考价值。提出了一种基于深度网络迁移学习的致痫区脑电识别算法。首先利用连续小波变换（CWT）对脑电信号进行时频分析，获得脑电信号时频图；然后迁移学习AlexNet网络模型，调整网络结构使之适应于致痫区脑电识别，将模型第7层全连接层输出作为脑电信号时频图的特征表示，最后利用支持向量机（SVM）、BP神经网络、长短期记忆网络（LSTM）、基于稀疏表达分类算法（SRC）、线性判别分析（LDA）等分类算法进行特征分类。基于开源脑电数据集采用十折交叉验证的方法对算法进行了验证,比较6种分类器的效果，得到SVM算法的平均特异性为8881%，灵敏度为8807%，准确率为8844%，证明了该方法识别致痫区脑电信号的有效性。 .txt