GPS测量系统误差分析

本文引出了GPS姿态测量,介绍了GPS测量原理,根据GPS测量系统的特点分析了测量过程中的各种误差,并提出了相应的误差消除措施。     

微量Mg元素添加对Cu-Cr合金析出行为及性能的影响

通过熔炼铸造工艺制备了Cu-Cr和Cu-Cr-Mg合金,评价了Mg元素对Cu-Cr合金硬度、导电和抗软化性能的影响,研究了Mg元素对Cu-Cr合金析出相的细化作用,探讨了Mg元素的迁移行为。结果表明,相比于Cu-Cr二元合金,时效态Cu-Cr-Mg合金具有更高的硬度和软化温度,且保持较高的导电性能。两种合金的主要时效强化相均为纳米Cr析出相,Mg元素的加入抑制了纳米沉淀相的长大和结构转变,峰时效态Cu-Cr-Mg合金的析出相与基体可能仍保持共格界面关系,过时效态合金中出现与Heulser相结构相同的析出相,且峰时效态Cu-Cr-Mg合金经过高温保温处理后,其强化相的尺寸明显小于Cu-Cr合金析出相。EDS的结果表明,在时效初期Mg和Cr共存于析出相内部,而在时效后期析出相内部只有Cr元素存在,Mg元素发生迁移,同时理论估算结果显示,Mg元素可明显降低Cu(fcc)/Cr(bcc)之间的界面能,导致其偏聚于基体/析出相界面处,这可能是Mg元素能够细化析出相和提高合金性能的主要原因。     

Heterogeneous Fenton-like discoloration of methyl orange using Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>/MWCNTs as catalyst: combination mechanism and affecting parameters

Multi-walled carbon nanotubes (MWCNTs) can act not only as a support for Fe₃O₄ nanoparticles (NPs) but also as a coworker with synergistic effect, accordingly improving the heterogeneous Fenton-like efficiency of Fe₃O₄ NPs. In this study, Fe₃O₄ NPs were in situ anchored onto MWCNTs by a moderate co-precipitation method and the as-prepared Fe₃O₄/MWCNTs nanocomposites were employed as the highly efficient Fenton-like catalysts. The analyses of XRD, FTIR, Raman, FESEM, TEM and HRTEM results indicated the formation of Fe₃O₄ crystals in Fe₃O₄/MWCNTs nanocomposites prepared at different conditions and the interaction between Fe₃O₄ NPs and MWCNTs. Over a wide pH range, the surface of modified MWCNTs possessed negative charges. Based on these results, the possible combination mechanism between Fe₃O₄ NPs and MWCNTs was discussed and proposed. Moreover, the effects of preparation and catalytic conditions on the Fenton-like catalytic efficiency were investigated in order to gain further insight into the heterogeneous Fenton-like reaction catalyzed by Fe₃O₄/MWCNTs nanocomposites.     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

Microsecond pulsed glow discharge as an analytical spectroscopic source

A pulsed glow discharge, operating in the microsecond regime, has been found to be advantageous for the examination of solid samples. We have studied the spectroscopic response by atomic emission, absorption, fluorescence, and mass spectrometries. Results to date show enhanced efficiency for analytical response of the sputtered sample atoms. This type of discharge also permits acquisition of useful diagnostic information concerning glow discharge processes.     

基于正交试验设计的克隆选择函数优化

将正交试验设计引入到克隆选择操作中,设计出基于正交试验的克隆选择操作(clonal selection operation based on orthogonal experiment design,简称CSO-OED),并将其加入到典型的克隆选择算法中,设计出并联式的CSO+CSO-OED(I)算法和串联式的CSO+CSO-OED(II)算法.将新设计的算法用于9个经典的测试函数和6个复杂的测试函数进行对比测试,实验结果表明,CSO-OED能够有效地保持种群的多样性,避免算法不成熟收敛.CSO+CSO-OED(I)和CSO+CSO-OED(II)将全局搜索和局部搜索分开进行优化,对比实验表明,这种搜索策略不但能够保证算法的收敛性,还能有效地提高搜索解的精度,增强算法的鲁棒性.     

BASE: A bacteria foraging algorithm for cell formation with sequence data

A cellular manufacturing system (CMS) is considered an efficient production strategy for batch type production. A CMS relies on the principle of grouping machines into machine cells and grouping parts into part families on the basis of pertinent similarity measures. The bacteria foraging algorithm (BFA) is a newly developed computation technique extracted from the social foraging behavior of Escherichia coli (E. coli) bacteria. Ever since Kevin M. Passino invented the BFA, one of the main challenges has been employment of the algorithm to problem areas other than those for which the algorithm was proposed. This research work studies the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem considering the operation sequence. In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. In this paper, an attempt is made to solve the CF problem, while taking into consideration the number of voids in the cells and the number of inter-cell travels based on operational sequences of the parts visited by the machines. The BFA is suggested to create machine cells and part families. The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. The results show better performance of the proposed algorithm.     

嵌入式操作系统进程监测器的设计与实现

为避免嵌入式操作系统的进程受到恶意软件的修改破坏,提出一种适合于嵌入式操作系统的进程监测器。监测器周期性地对系统进程控制块进行检测恢复,通过设置进程检查点为系统提供恢复操作进程,并在Linux上进行实现,给出主要的数据结构和实现过程。实验结果表明,监测器的运行对系统性能影响小,能对系统进程进行有效的检测恢复。     

多传感器数据融合在轮式机器人朝向角控制中的应用

针对轮式全向移动机器人运动时容易产生朝向角偏差这一问题,分析了轮式全向移动机器人的运动模型,对当前普遍采用的仅依靠编码器反馈的朝向角控制方法进行改进,将MEMS陀螺仪和数字罗盘应用到机器人系统中,提出了基于多传感器数据融合的朝向角控制方法,提高了朝向角的控制精度.通过实验数据和在机器人足球比赛中的实际表现,证明了该方法...     

基于遗传算法的高考志愿填报排序问题的研究

针对高考志愿填报录取最优化、最佳匹配问题,提出了基于遗传算法搜索最优解的解决方案。该方案模拟物种自然选择和遗传进化过程,将不同考生的高考志愿按录取结果利益最大化进行排序。在可选择院校数量相同的情况下,对不同考生考试成绩的数据通过程序不断进行智能优化和迭代,志愿排序结果趋于稳定,且达到最佳匹配。其不但满足考生的实际需求,而且达到志愿填报利益最大化的目的。该方法采用涵盖985、211、普通院校的10所高校的实际数据进行测试,结果表明,遗传算法可以用来求解最优高考志愿填报排序问题,且具有很高的准确率和适应度。