Online evolution reconstruction from a single measurement record with random time intervals for quantum communication

Online reconstruction of a time-variant quantum state from the encoding/decoding results of quantum communication is addressed by developing a method of evolution reconstruction from a single measurement record with random time intervals. A time-variant two-dimensional state is reconstructed on the basis of recovering its expectation value functions of three nonorthogonal projectors from a random single measurement record, which is composed from the discarded qubits of the six-state protocol. The simulated results prove that our method is robust to typical metro quantum channels. Our work extends the Fourier-based method of evolution reconstruction from the version for a regular single measurement record with equal time intervals to a unified one, which can be applied to arbitrary single measurement records. The proposed protocol of evolution reconstruction runs concurrently with the one of quantum communication, which can facilitate the online quantum tomography.     

A combined shape control procedure of cable mesh reflector antennas with optimality criterion and integrated structural electromagnetic concept

A combined shape control procedure with optimality criterion and integrated structural electromagnetic concept for cable mesh reflector antennas is presented in this study. Using the optimality criterion, the shape control algorithm drives the distorted surface towards the ideal shape. The optimality criterion is implemented by pseudo inverse of sensitivity matrix of surface nodal displacements with respect to cable member dimensions to accelerate the iterative convergence. The following integrated structural electromagnetic design is performed to make good electromagnetic performance by a sequential quadratic programming optimization model. A distorted offset cable mesh reflector antenna is employed to show its effectiveness.     

基于自适应背景的目标跟踪算法研究

随着现在的社会发展以及经济进步,我国的科学技术方面发展迅速,特别是在技术监控方面更是突飞猛进。为了更好的对目标遮挡影响进行降低,我国在这方面主要依据自适应的技术发展背景下提出目标跟踪计算法,用来完善我国的监督控制技术。这种计算方式第一是根据对观察目标的基本外观形态进行的鉴定与跟踪,将其自身的运动量进行平均计算;其次是根据时空的运行方向与特征进行跟踪目标的计算,建立比较完善整体的运行模型,再根据这个运动模型以及整体的状态对监督目标进行检测与控制,这期间就会形成一种遮挡掩膜。对于掩膜是一种将程序数据等绘制成光刻板,在程序使用期间非常可靠,并且制造成本比较低,使用方便;最后是在不同的使用情况下将不同参数进行收集,自动的适应运动模型的运行。针对这种计算方式的实验主要是利用两种在国际上经常使用的CAVIAR、York数据进行测试,并且根据这两种数据对测试的精准度与多重目标跟踪等进行评定,检测跟踪的整体性能。通过多方面的研究表明这种方式的跟踪的性能非常好,并且还能很好的将跟踪目标的鲁棒性进行遮挡。     

基于STM32大气动态雾霾检测系统的设计

大气的质量直接关系到人们的生存环境,衡量大气污染的程度和对身体健康造成的伤害,都离不开对大气的检测;如何进行检测,用什么方法来评判,文章提出一种方法来实时检测大气雾霾的状况,尤其是PM2.5(空气动力学当量直径小于等于2.5微米的颗粒物)被认为是造成雾霾天气的“元凶”;大气雾霾监测系统利用雾霾检测器和GPRS传导,将所在地雾霾情况实时监测传输给手机APP终端,手机接收之后将数据整合显示给使用者,达到雾霾监测和提前应对恶劣天气的作用。     

分类错误指导的分层B-CNN模型用于细粒度分类

目的 细粒度分类近年来受到了越来越多研究者的广泛关注,其难点是分类目标间的差异非常小。为此提出一种分类错误指导的分层双线性卷积神经网络模型。方法 该模型的核心思想是将双线性卷积神经网络算法（B-CNN）容易分错、混淆的类再分别进行重新训练和分类。首先,为得到易错类,提出分类错误指导的聚类算法。该算法基于受限拉普拉斯秩（CLR）聚类模型,其核心“关联矩阵”由“分类错误矩阵”构造。其次,以聚类结果为基础,构建了新的分层B-CNN模型。结果 用分类错误指导的分层B-CNN模型在CUB-200-2011、 FGVC-Aircraft-2013b和Stanford-cars 3个标准数据集上进行了实验,相比于单层的B-CNN模型,分类准确率分别由84.35%,83.56%,89.45%提高到了84.67%,84.11%,89.78%,验证了本文算法的有效性。结论 本文提出了用分类错误矩阵指导聚类从而进行重分类的方法,相对于基于特征相似度而构造的关联矩阵,分类错误矩阵直接针对分类问题,可以有效提高易混淆类的分类准确率。本文方法针对比较相近的目标,尤其是有非常相近的目标的情况,通过将容易分错、混淆的目标分组并进行再训练和重分类,使得分类效果更好,适用于细粒度分类问题。     

结合MSCRs与MSERs的自然场景文本检测

目的 目前,基于MSERs(maximally stable extremal regions)的文本检测方法是自然场景图像文本检测的主流方法。但是自然场景图像中部分文本的背景复杂多变,MSERs算法无法将其准确提取出来,降低了该类方法的鲁棒性。本文针对自然场景图像文本背景复杂多变的特点,将MSCRs(maximally stable color regions)算法用于自然场景文本检测,提出一种结合MSCRs与MSERs的自然场景文本检测方法。方法 首先采用MSCRs算法与MSERs算法提取候选字符区域;然后利用候选字符区域的纹理特征训练随机森林字符分类器,对候选字符区域进行分类,从而得到字符区域;最后,依据字符区域的彩色一致性和几何邻接关系对字符进行合并,得到最终文本检测结果。结果 本文方法在ICDAR 2013上的召回率、准确率和F值分别为71.9%、84.1%和77.5%,相对于其他方法的召回率和F值均有所提高。结论 本文方法对自然场景图像文本检测具有较强的鲁棒性,实验结果验证了本文方法的有效性。     

自动气象站Z文件传输质量分析及异常处理

国家级自动气象站正点观测资料是自动气象站采集数据文件的重要部分,出现因设备、软硬件故障、网络、通信或误操作等原因,造成数据资料不能及时传输等。通过分析宁夏地区2012年4月-2013年6月,国家级自动气象站资料传输质量,查找分析逾限报、缺报的原因,给出了自动站观测资料出现异常的处理方法,以确保自动站观测资料的传输及时率和准确性,来满足现代气象业务的需求,为提高自动气象站资料传输质量提供参考。     

高职Linux项目化课程教学评价体系的研究

高职院校培养一专多能的复合型应用型人才成为当前高职教育的首要任务。因此对高职Linux教学评价体系改革进行了实证研究,提出高职Linux教学评价应该结合高职培养目标的特点,依据真实性评价的理念,构建基于能力本位的高职Linux教学评价体系,从而促进高职学生Linux综合应用能力和综合素质的提高。     

New receipt-free voting scheme using double-trapdoor commitment

It is considered to be the most suitable solution for large scale elections to design an electronic voting scheme using blind signatures and anonymous channels. Based on this framework, Okamoto first proposed a receipt-free voting scheme [30] for large scale elections. However, in the following paper, Okamoto [31] proved that the scheme [30] was not receipt-free and presented two improved schemes. One scheme requires the help of the parameter registration committee and the other needs a stronger physical assumption of the voting booth. In this paper, we utilize the double-trapdoor commitment to propose a new receipt-free voting scheme based on blind signatures for large scale elections. Neither the parameter registration committee nor the voting booth is required in our scheme. We also present a more efficient zero-knowledge proof for secret permutation. Therefore, our scheme is much more efficient than Okamoto’s schemes [30] and [31] with the weaker physical assumptions. Moreover, we prove that our scheme can achieve the desired security properties.