A Fingerprint Minutiae Matching Method Based on Line Segment Vector

Minutiae-based fingerprint matching is the most commonly used in an automatic fingerprint identification system. In this paper, we propose a minutia matching method based on line segment vector. This method uses all the detected minutiae （the ridge ending and the ridge bifurcation） in a fingerprint image to create a set of new vectors （line segment vector）. Using these vectors, we can determine a truer reference point more efficiently. In addition, this new minutiae vector can also increase the accuracy of the minutiae matching. By experiment on the public domain collections of fingerprint images fvc2004 DID set A and DB4 set A, the result shows that our algorithm can obtain an improved verification performance.

Application of the sun line-of-sight vector in the optimal attitude estimation of deep-space probe

This paper proposed an optimal algorithm using the sun line-of-sight vector to improve the probe attitude estimation accuracy in deep-space mission.Firstly,the elaborate analysis of the attitude estimation error from vector observations was done to demonstrate that the geometric relation between the reference vectors is an important factor which influences the accuracy of attitude estimation.Then,with introduction of the sun line-of-sight vector,the attitude quaternion obtained from the star-sensor was converted into a pair of mutually perpendicular reference vectors perpendicular to the sun vector.The normalized weights were calculated according to the accuracy of the sensors.Furthermore,the optimal attitude estimation in the least squares sense was achieved with the quaternion estimation method.Finally,the results of simulation demonstrated the validity of the proposed optimal algorithm based on the practical data of the Deep Impact mission.

On-line Chatter Detection Using an Improved Support Vector Machine

On-line chatter detection can avoid unstable cutting through monitoring the machining process.In order to identify chatter in a timely manner,an improved Support Vector Machine(SVM)is developed in this paper,based on extracted features.In the SVM model,the penalty factor(e)and the core parameter(g)have important influence on the classification,more than from Kernel Functions(KFs).Hence,first the classification results are conducted using different KFs.Then two methods are presented for exploring the best parameters.The chatter identification results show that the Genetic Algorithm(GA)approach is more suitable for deciding the parameters than the Grid Explore(GE)approach.

On-line forecasting model for zinc output based on self-tuning support vector regression and its application

An on-line forecasting model based on self-tuning support vectors regression for zinc output was put forward to maximize zinc output by adjusting operational parameters in the process of imperial smelting furnace. In this model, the mathematical model of support vector regression was converted into the same format as support vector machine for classification. Then a simplified sequential minimal optimization for classification was applied to train the regression coefficient vector α- α* and threshold b. Sequentially penalty parameter C was tuned dynamically through forecasting result during the training process. Finally, an on-line forecasting algorithm for zinc output was proposed. The simulation result shows that in spite of a relatively small industrial data set, the effective error is less than 10% with a remarkable performance of real time. The model was applied to the optimization operation and fault diagnosis system for imperial smelting furnace.

Construction of a replication-competent hepatitis B virus vector carrying secreted luciferase transgene and establishment of new hepatitis B virus replication and expression cell lines

BACKGROUND Previously,we have successfully constructed replication-competent hepatitis B virus(HBV)vectors by uncoupling the P open reading frame(ORF)from the preC/C ORF to carefully design the transgene insertion site to overcome the compact organization of the HBV genome and maintain HBV replication competence.Consequently,the replication-competent HBV vectors carrying foreign genes,including pCH-BsdR,carrying blasticidin resistance gene(399 bp),and pCH-hrGFP,carrying humanized renilla green fluorescent protein gene(720 bp),were successfully obtained.However,the replication efficiency of the former is higher but it is tedious to use,while that of the latter is poor and cannot be quantified.Hence,we need to search for a new reporter gene that is convenient and quantifiable for further research.AIM To establish a helpful tool for intracellular HBV replication and anti-viral drugs screening studies.METHODS We utilized the replication-competent HBV viral vectors constructed by our laboratory,combined with the secreted luciferase reporter gene,to construct replication-competent HBV vectors expressing the reporter gene secretory Nanoluc Luciferase(SecNluc).HepG2.TA2-7 cells were transfected with this vector to obtain cell lines with stably secreted HBV particles carrying secNluc reporter gene.RESULTS The replication-competent HBV vector carrying the SecNluc reporter gene pCHsNLuc could produce all major viral RNAs and a full set of envelope proteins and achieve high-level secreted luciferase expression.HBV replication intermediates could be produced from this vector.Via transfection with pTRE-sNLuc and selection by hygromycin,we obtained isolated cell clones,named HBV-NLuc-35 cells,which could secrete secNLuc recombinant viruses,and were sensitive to existing anti-HBV drugs.Using differentiated HepaRG cells,it was verified that recombinant HBV possessed infectivity.CONCLUSION Our research demonstrated that a replication-competent HBV vector carrying a secreted luciferase transgene possesses replication and expression ability,and the established HBV replication and expression cell lines could stably secrete viral particles carrying secNluc reporter gene.More importantly,the cell line and the secreted recombinant viral particles could be used to trace HBV replication or infection.

基于GS-SVR的架空输电线路工程投资估算预测研究

传统的投资估算编制模式存在过度依赖定额的现象,随着大量工程造价数据的积累,利用其实现投资估算,以弥补传统定额计价模式的不足,能够对建设项目工程造价起到总体控制作用。文章以架空输电线路工程为例,基于支持向量回归机(Support Vector Regression,SVR)研究架空输电线路工程投资估算问题。结果表明:通过选取影响架空输电线路工程投资估算的主要指标,构建基于SVR的架空输电线路工程投资估算模型,并利用改进的网格搜索法(Grid Search,GS)优化模型参数,得到基于GS-SVR的投资估算预测模型;与传统的线性回归和SVR模型相比,GS-SVR模型表现出更为良好的性能。

基于单矢量水听器的水中目标高分辨线谱增强方法

微弱信号检测一直是被动声呐系统远程探测面临的技术挑战。为了解决水下微弱信号条件下,即低信噪比(SNR)情况下,目标线谱检测难点问题,本文基于单矢量水听器信号接收,提出一种水下目标声压振速频域解卷积联合(CPVD)处理方法,可以实现线谱增强以及提高频域分辨率。采用单矢量水听器接收,保证声呐系统体积小,同时利用其具有指向性这一特点,可以抑制噪声,提高信号增益。在此基础上,通过CPVD算法对水中微弱信号进行线谱增强,实现有效检测。本文提出的方法克服了一些增强算法以及功率谱分析算法需要一定的先验知识以及频域线谱分辨率较低的缺点,从仿真分析和海试数据处理结果可以看出:本文所提出的基于单矢量水听器的水下目标线谱增强算法在低SNR条件下提高频率分辨率方面具有优势,为被动声呐系统微弱信号下的线谱检测提供有效算法。

基于声压振速联合处理的稀疏协方差DOA估计

为充分利用矢量水听器中声压振速信息之间的关系来提高DOA估计精度,本文提出了基于声压振速联合处理的稀疏协方差DOA(Direction ofArrival)估计方法。该方法首先利用声压振速之间的相关性,构造阵列协方差矩阵;其次,将空间入射角度集合进行等角度划分,构造超完备冗余字典;然后,在过完备基上寻找阵列协方差矩阵的最稀疏系数,利用系数向量中的非零行所对应的行号得到DOA估计值。将该算法与CBF算法及L1-SVD算法进行对比仿真实验,结果表明,在信号源数分别为3,4,5的情形下,本文所提算法在低信噪比和小快拍数情形时,具有更低的均方根误差,DOA估计性能优势明显。

表达猪流行性腹泻病毒N蛋白Vero细胞系的构建及初步鉴定

【目的】构建表达猪流行性腹泻病毒(PEDV)N蛋白的Vero细胞系,将有助于PEDV的进一步深入研究。【方法】本研究将N基因克隆到慢病毒载体中,构建重组质粒pLenti-CMV-N,利用慢病毒载体包装系统转染293T细胞,包装表达N蛋白的慢病毒颗粒,将慢病毒颗粒转导至Vero细胞,用潮霉素B初步筛选阳性细胞,采用终点稀释法,筛选表达PEDV N蛋白的Vero细胞系,最后进行鉴定。【结果】RT-PCR结果表明构建的细胞系基因组中存在N基因序列,Western blot和IFA试验验证了N蛋白在细胞系中的表达。【结论】本研究成功构建了表达PEDV N蛋白的Vero细胞系。

基于改进U-Net网络的遥感影像农村道路矢量中心线提取及优化

遥感影像中农村道路矢量中心线的准确提取对乡村规划和地理信息数据库建设具有重要意义。针对现有深度学习方法未能充分利用上下文信息,且在下采样过程中易造成图像分辨率下降和局部特征丢失的问题,该文改进U-Net网络模型以提高提取结果的准确性。首先,网络结构设计两次下采样处理,并将上下文两处特征信息用跳跃层连接,使输出的道路细节清晰;其次,为避免样本不均衡导致训练效果不理想,采用交叉熵损失函数与广义骰子损失函数叠加的方式提升训练效果;最后,采用邻域质心投票算法和融合算法对提取的道路进行矢量化和中心线优化,得到高精度的农村道路矢量中心线。试验结果表明:改进方法在复杂场景的农村道路矢量中心线提取中准确率达95.03%,较4种对比算法(U-Net、DC-Net、PA-Net、SM-Net)具有明显优势。

基于ICEEMDAN-GWO-SVM的煤矿井下单相接地故障选线

为解决煤矿配电网发生单相接地故障时,难以对故障线路准确识别的问题,提出一种基于改进的自适应噪声完备集合经验模态分解(ICEEMDAN)的灰狼算法优化支持向量机(GWO-SVM)配电网单相接地故障选线方法。采用ICEEMDAN对不同工况下的每一条线路的零序电流进行分解,对各线路分解后的第一个模态分量IMF1求裕度因子、残差量相对能量系数和综合相关系数,然后将求解出的3种特征值组合形成特征向量,最后输入GWO-SVM中进行模式识别。通过Matlab/Simulink搭建包含4条馈线的10 kV配电网仿真模型进行验证。仿真结果表明,该方法不受故障位置、故障初始角、过渡电阻的影响,具有较高的选线准确率。

基于计算几何的多波束测线模型

多波束具有测点密度大、精度高、可视化等优点,被广泛应用于海洋测量。根据数学建模赛题给出的案例,在不同的海域条件下,借助计算几何和三角函数定理,建立并推导多波束测深过程中表征覆盖宽度和相邻条带重叠率关系的数学模型。同时,基于向量法提出了一种多波束测线设计优化方法,详细给出了MATLAB求解结果。模型的合理性通过模拟仿真进行检验说明。

基于改进灰度重心法的线结构光中心提取算法

针对传统算法无法准确提取线结构光条中曲率变化较大区域中心线的缺陷,提出了一种基于改进灰度重心法的线结构光中心线提取算法。基于阈值法提取感兴趣区域和开闭运算滤除图像中的噪声点,获取质量相对较高的待处理图像;利用灰度重心法提取光条中心点,得到初始坐标并设置一个矩形计算区域,根据最小二乘法计算每个初始点的方向向量和法向量;在设定的矩形区域内计算初始点在其法线方向上的偏移量,得到精确的中心点坐标。实验结果表明:提出的算法能在线结构光中心中曲率变化较大区域精确提取中心线,提取精度均值为0.096 pixels,精度比率为44.2%,平均提取速度为0.082 s。

顾及邻域几何特性的露天矿台阶线提取方法

台阶线数据是露天矿开采过程中的重要基础资料,也是确保露天矿高效、智能开采的重要前提。针对现有的基于点云的露天矿台阶线提取方法存在局部特征丢失、台阶线不连续等问题,将识别台阶线特征点转为识别几何特征面,从特征面轮廓中提取出台阶线特征点,由此提出了一种顾及邻域几何特性的露天矿台阶线自动提取方法。该方法首先对露天矿点云进行规则重采样,依据露天矿台阶平盘、坡面点云法向量与竖直平面夹角具有明显差异这一几何特性提取坡面的特征点云;在此基础上,采用区域生长算法分割坡面点云,通过凹包算法提取分割后的坡面点云轮廓边界获得台阶线特征点;最后利用三阶贝塞尔曲线拟合特征点以生成露天矿台阶线。为验证算法的提取精度,将台阶线与露天矿数字高程模型(Digital Elevation Model,DEM)叠加,并计算该方法提取的台阶线与实际台阶线的位置偏差。结果表明:该方法提取的台阶线完整且连续性好,与手工绘制的台阶线基本重合,能够满足比例尺为1∶2000的制图精度要求;运行效率高,对于面积为3 km2的露天矿,提取时间在4 min以内。证明所提方法能够准确、高效地提取露天矿台阶线,为实现露天矿山台阶线自动绘制提供重要的技术支持。

分离线扩张比对超音速分离线摆动喷管流场影响规律的数值与试验研究

为进一步优化超音速分离线摆动喷管性能,通过数值计算分析了分离线处扩张比(ε)对超音速分离线摆动喷管流场的影响规律,并进行了试验验证。结果表明:相同ε下,随着摆动角度(θ)的增加,轴向推力系数(C_(fx))逐渐减小;ε取不同值时,相同θ下C_(fx)区别较大,在ε=1.68时C_(fx)达到最大值。相同ε下,随着θ的增加,偏转放大系数(K)先增加后减小,θ为1°~2°时,K值达到最大(K=2.5);不同ε下K区别较大,当ε≥1.46、θ为1°~8°时,K>1,ε=1.21时偏转效益受θ影响较大,K最小值小于1。数值仿真喷管羽流状态与地面试验一致,验证了仿真方法的有效性;分离线处压强由于模型误差存在一定偏差,摆动力矩由于分离线处压强的非均匀分布存在计算偏差。

DIRECTIONAL DERIVATIVE OF VECTOR FIELD AND REGULAR CURVES ON TIME SCALES

The general idea in this paper is to study curves of the parametric equations where the parameter varies in a so-called time scale, which may be an arbitrary closed subset of the set of all real numbers. We introduce the directional derivative according to the vector fields.

Establishment of a Functional Cell Line Expressing both Subunits of H1a and H2c of Human Hepatocyte Surface Molecule ASGPR

To better understand the effect of a new split variant of human asialoglycoprotein receptor (ASGPR H1b) on ASGPR ligands’ binding ability, we established a functional cell line which expresses ASGPR.The full lengths of ASGPRH1a and H2c fragments from human liver were amplified by reverse transcript PCR (RT-PCR) and inserted into eukaryotic expression vector pIRES2EFP, pCDNA3.1 (Zeo+) respectively.The recombinants were cotransfected into HeLa cells.After selection by using Neocin and Zeocin, a stably transfected cell line was established, which was designated 4-1-6.The transcription and expression of ASGPRH1a and H2c in 4-1-6 were confirmed by RT-PCR, Western blotting and immunofluorescence.The endocytosis function of the artificial "ASGPR" on the surface of 4-1-6 was tested by FACS.It was found that the cell line 4-1-6 could bind ASGPR natural ligand molecular asialo-orosomucoid (ASOR).After the eukaryotic plasmid H1b/pCDNA3.1 (neo) was transfected into cell line 4-1-6, H1b did not down-regulate the ligand binding ability of ASGPR.The eukaryotic expression plasmid H1b/pcDNA3.1 (neo) and H2c/pcDNA3.1 (neo) were co-transfected transiently into Hela cell.Neither single H1b nor H1b and H2c could bind ASOR.In conclusion, a functional cell line of human asialoglycoprotein receptor (ASGPR) which expresses both H1a and H2c stably was established.The new split variant H1b has no effect on ASGPR binding to ASOR.ASGPRH1b alone can’t bind to ASOR, it yet can’t form functional complex with ASGPRH2c.

On-line Estimation in Fed-batch Fermentation Process Using State Space Model and Unscented Kalman Filter

On-line estimation of unmeasurable biological variables is important in fermentation processes,directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product.In this study,a novel strategy for state estimation of fed-batch fermentation process is proposed.By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model,a state space model is developed.An improved algorithm,swarm energy conservation particle swarm optimization(SECPSO) ,is presented for the parameter identification in the mechanistic model,and the support vector machines(SVM) method is adopted to establish the nonlinear measurement model.The unscented Kalman filter(UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process.The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process.