Penalized total least squares method for dealing with systematic errors in partial EIV model and its precision estimation

When the total least squares(TLS)solution is used to solve the parameters in the errors-in-variables(EIV)model,the obtained parameter estimations will be unreliable in the observations containing systematic errors.To solve this problem,we propose to add the nonparametric part(systematic errors)to the partial EIV model,and build the partial EIV model to weaken the influence of systematic errors.Then,having rewritten the model as a nonlinear model,we derive the formula of parameter estimations based on the penalized total least squares criterion.Furthermore,based on the second-order approximation method of precision estimation,we derive the second-order bias and covariance of parameter estimations and calculate the mean square error(MSE).Aiming at the selection of the smoothing factor,we propose to use the U curve method.The experiments show that the proposed method can mitigate the influence of systematic errors to a certain extent compared with the traditional method and get more reliable parameter estimations and its precision information,which validates the feasibility and effectiveness of the proposed method.

Use of Total Precipitable Water Classification of A Priori Error and Quality Control in Atmospheric Temperature and Water Vapor Sounding Retrieval

This study investigates the use of dynamic a priori error information according to atmospheric moistness and the use of quality controls in temperature and water vapor profile retrievals from hyperspectral infrared （IR） sounders. Temperature and water vapor profiles are retrieved from Atmospheric InfraRed Sounder （AIRS） radiance measurements by applying a physical iterative method using regression retrieval as the first guess. Based on the dependency of first-guess errors on the degree of atmospheric moistness, the a priori first-guess errors classified by total precipitable water （TPW） are applied in the AIRS physical retrieval procedure. Compared to the retrieval results from a fixed a priori error, boundary layer moisture retrievals appear to be improved via TPW classification of a priori first-guess errors. Six quality control （QC） tests, which check non-converged or bad retrievals, large residuals, high terrain and desert areas, and large temperature and moisture deviations from the first guess regression retrieval, are also applied in the AIRS physical retrievals. Significantly large errors are found for the retrievals rejected by these six QCs, and the retrieval errors are substantially reduced via QC over land, which suggest the usefulness and high impact of the QCs, especially over land. In conclusion, the use of dynamic a priori error information according to atmospheric moistness, and the use of appropriate QCs dealing with the geographical information and the deviation from the first-guess as well as the conventional inverse performance are suggested to improve temperature and moisture retrievals and their applications.

Application of Total Error Strategy in Validation of Affordable and Accessible UV-Visible Spectrophotometric Methods for Quality Control of Poor Medicines

In the framework of fighting against the poor quality medicines sold in developing countries using classical analytical methods easily accessible in those countries, four UV-Visible spectrophotometric methods for one antimalarial (quinine) and two antibiotics (amoxicillin and metronidazole) have been developed and validated according to the total error strategy using the accuracy profiles as a decision tool. The dosing range was 2 - 10 μg/mL (for quinine sulfate in tablet), 4 - 12 μg/mL (for quinine bichlorhydrate in oral drop-metronidazole benzaote in oral suspension) and 15 - 35 μg/mL (for amoxicillin trihydrate in capsule). The validated methods were then applied in determining the content of some analogous medicines sold in the Democratic Republic of Congo. Thus, the proposed UV-Visible spectrophotometric methods are simple and suitable to quantify quinine, amoxicillin and metronidazole in different pharmaceutical forms.

Total Sensitivity Index Calculation of Tool Requirement Model via Error Propagation Equation

A new and convenient method is presented to calculate the total sensitivity indices defined by variance-based sensitivity analysis. By decomposing the output variance using error propagation equations, this method can transform the ＂double-loop＂ sampling procedure into ＂single-loop＂ one and obviously reduce the computation cost of analysis. In contrast with Sobors and Fourier amplitude sensitivity test （FAST） method, which is limited in non-correlated variables, the new approach is suitable for correlated input variables. An application in semiconductor assembling and test manufacturing （ATM） factory indicates that this approach has a good performance in additive model and simple non-additive model.

Error model identification of inertial navigation platform based on errors-in-variables model

Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression model and the least squares （LS） method will result in bias. Based on the models of inertial navigation platform error and observation error, the errors-in-variables （EV） model and the total least squares （TLS） method axe proposed to identify the error model of the inertial navigation platform. The estimation precision is improved and the result is better than the conventional regression model based LS method. The simulation results illustrate the effectiveness of the proposed method.

Error Model of Curves in GIS and Digitization Experiment

A stochastic error process of curves is proposed as the error model to describe the errors of curves in GIS. In terms of the stochastic process, four characteristics concerning the local error of curves, namely, mean error function, standard error function, absolute error function, and the correlation function of errors , are put forward. The total error of a curve is expressed by a mean square integral of the stochastic error process. The probabilistic meanings and geometric meanings of the characteristics mentioned above are also discussed. A scan digitization experiment is designed to check the efficiency of the model. In the experiment, a piece of contour line is digitized for more than 100 times and lots of sample functions are derived from the experiment. Finally, all the error characteristics are estimated on the basis of sample functions. The experiment results show that the systematic error in digitized map data is not negligible, and the errors of points on curves are chiefly dependent on the curvature and the concavity of the curves.

Attribute-Based Authentication Scheme from Partial Encryption for Lattice with Short Key

Wireless network is the basis of the Internet of things and theintelligent vehicle Internet. Due to the complexity of the Internet of things andintelligent vehicle Internet environment, the nodes of the Internet of thingsand the intelligent vehicle Internet are more vulnerable to malicious destructionand attacks. Most of the proposed authentication and key agreementprotocols for wireless networks are based on traditional cryptosystems such aslarge integer decomposition and elliptic curves. With the rapid developmentof quantum computing, these authentication protocols based on traditionalcryptography will be more and more threatened, so it is necessary to designsome authentication and key agreement protocols that can resist quantumattacks. In this paper, an anti-quantum authentication scheme for wirelessnetworks based on lattice cryptosystem is constructed. In the attribute-basedauthentication scheme, the length of the authenticated public-private keypair depends on the maximum order and complexity of the formula in thealgorithm. In the attribute-based authentication scheme, there is a certaincorrelation between the authenticated data and the attribute value of theuser in the scheme. We show that the attribute-based authentication schemegives an attribute-based with smaller public-private key pairs. The securityof the attribute-based authentication scheme is based on the sub-exponentialhard problem of the LWE (Learning With Errors). The Q-poly made bythe adversary in the scheme, and our attribute-based authentication schemeguarantees that private data about user attributes and ciphertext cannot beobtained by malicious attackers.

全入射角叠前密度反演在白云岩优质储层预测中的应用

川西坳陷三叠系雷口坡组雷四上亚段发育潮坪相低渗致密白云岩储层,该套储层埋藏深(5600~5900 m)、厚度薄(相对地震分辨率)、纵向多层叠置、横向储层厚度和物性变化快、储层与围岩波阻抗差异小,白云岩优质储层预测难度大。研究区测井数据的岩石物理分析结果表明,密度对该区优质储层最敏感。首先基于目的层储盖层的测井数据开展了Zoeppritz近似线性方程误差分析、AVO道集正演和全入射角道集叠前密度反演的可行性研究,并与基于部分叠加的叠前密度反演方法即叠前同时反演方法进行了对比。在对实际叠前偏移道集优化处理的基础上,采用适用于研究区的Zoeppritz近似线性方程,并优选参数(包括v_(P)/v_(S)、道集切除参数和入射角参数)开展全入射角叠前密度反演,得到高质量的密度数据体,并与部分叠加的叠前密度反演得到的密度数据体进行了对比。将全入射角叠前密度反演得到的密度反射率数据应用于后续的密度高分辨率反演,该反演结果得到了雷四上亚段两套优质储层预测结果的证实,11口后钻井揭示的储层厚度和物性的符合率均超过85%。

广义频分复用系统峰均功率比抑制算法

为了降低广义频分复用系统存在着多载波系统中固有的高峰均功率比问题,本文提出了一种适用于广义频分复用系统的子载波抑制高峰均功率比算法。该算法以限幅法为基础,降低了系统的高峰均功率比,但与限幅法不同的是,该算法几乎不会对带外性能及误码率性能造成影响。由于子载波抑制高峰均功率比算法的峰均功率比抑制性能略差于限幅法,因此本文进一步提出将部分序列传输与子载波抑制高峰均功率比结合来进一步抑制系统高峰均功率比的算法。仿真表明:本文提出的算法的高峰均功率比抑制性能与限幅法相同,且不会对系统的带外与误码率性能造成影响。

自适应分数阶偏微分方程修正模型的能量泛函及Euler-Lagrange方程研究

首先对分数阶微分方程进行构建,结合全变分项,提出了修正的自适应分数阶偏微分方程模型。研究首先确定出分数阶偏分去噪模型的最优分数阶数,当分数阶次为1.8时,峰值信噪比和结构相似度达到33.12和0.874,均方根误差降低至5.62。然后将研究提出的模型与全变分模型、分数阶偏分去噪模型等在图像上进行对比实验,研究提出的模型在峰值信噪比、结构相似度上达到最高,分别为29.045与0.839,均方根误差为9.427,表明模型能够抑制阶梯效应,具有优越的去噪性能。

Partial EIV模型的解法

提出了一种求解partial errors-in-variables(partial EIV)模型的思路。通过对partial EIV模型的部分元素进行移项,重组成新形式下的平差函数模型,两次运用间接平差原理分别求解平差参数与系数矩阵中的随机元素,把总体最小二乘平差问题转化为最小二乘平差问题,并通过适当变换提高了新解法的收敛速度。最后分别采用实测数据和模拟数据进行验证,求解了本文算法与已有算法的估值结果。算例结果表明,本文算法能取得与已有算法相同的结果,是切实可行的。

平均轨迹误差、血清内毒素与CR假体全膝关节置换术后早期疗效的关系

目的分析平均轨迹误差、血清内毒素与后交叉韧带保留型(CR)假体全膝关节置换术(TKA)后早期疗效的关系。方法收集2021年8月至2023年6月于邯郸市第一医院拟行TKA的膝骨关节炎(KOA)患者为研究对象,术后3个月时采用美国膝关节协会(AKS)评分和膝关节功能评分表(HSS)评分评估患者TKA后的早期疗效,同时收集患者基线资料,术后1、2、3个月时测定患者本体感觉(平均轨迹误差)、血清内毒素水平。分析平均轨迹误差、血清内毒素与患者CR假体TKA后早期疗效的关系。结果术后3个月时,100例患者中AKS评分<70分23例(23.00%),HSS评分<70分26例(26.00%)。重复测量方差分析显示,不同AKS评分患者及不同HSS评分患者血清内毒素水平、平均轨迹误差均存在组间效应、时间效应和交互效应(P<0.05),故进一步单独效应分析。两组术后2、3个月时血清内毒素水平、平均轨迹误差均低于术后1个月时(P<0.05)。多变量方差分析显示,AKS评分<70分者术后1、2、3个月时的血清内毒素水平、平均轨迹误差均高于AKS评分≥70分者(P<0.05),HSS评分<70分者术后1、2、3个月时的血清内毒素水平、平均轨迹误差均高于HSS评分≥70分者(P<0.05)。Pearson相关分析显示,平均轨迹误差、血清内毒素水平与AKS评分、HSS评分均呈负相关(r=-0.285~-0.206,P<0.05)。多因素Logistic回归分析显示,平均轨迹误差、血清内毒素是CR假体TKA后早期AKS评分≥70分或HSS评分≥70分的影响因素(P<0.05)。结论CR假体TKA后患者早期疗效与平均轨迹误差、血清内毒素存在一定关系。

超声全聚焦成像的裂纹类缺陷定量误差分析

虽然超声全聚焦成像(total focusing method,TFM)具有直观显示裂纹特征的明显优势,但通过TFM图像进行裂纹定量时不可避免地出现测量误差。该文采用模拟与实验对比的方式,分析TFM技术的裂纹定量误差。从超声波波长对缺陷深度的影响规律入手,分析和研究裂纹长度和取向的全聚焦图像测量误差原因。最后,通过模拟实验对比的方式验证裂纹定量误差。研究结果表明,裂纹上、下尖端的测量深度比实际深度均有所下沉,但两者下沉的深度基本相同,相差在0.6 mm以内,裂纹长度的测量误差范围为0~1 mm,带取向裂纹的取向测量误差基本保持在3°以内。因此,上、下尖端在深度上的测量误差对裂纹长度和取向的影响极小。经实验验证,裂纹深度、长度及取向误差的结论与模拟的结论一致。

一种相关观测的Partial EIV模型求解方法

Partial errors-in-variables(Partial-EIV)模型作为EIV模型的扩展形式,其构造方式更有规律,解算方法更为简便,能有效应用于实际情况。针对已有Partial EIV模型方法未考虑观测向量和系数矩阵存在相关性这一情况,通过提取观测向量和系数矩阵组成的增广矩阵中非重复出现的随机元素,构建更具一般适用性的Partial EIV模型,在该模型的基础上,将特殊假定条件扩展到不限定观测数据相关性的一般情况,详细推导了观测向量和系数矩阵元素相关且不等精度情况下的加权总体最小二乘方法,通过算例试验,并与目前已有的解决EIV模型相关观测情况下的方法进行了比较分析,研究表明本文方法可以提高计算效率,更具一般性,特别是对于观测向量和系数矩阵中存在常数元素和重复元素的情况。

临床实验室基于EQA和IQC数据设定生物化学检验常规项目分析性能规范

目的基于室间质量评估(external quality assessment,EQA)和室内质量控制(internal quality control,IQC)数据,设定生物化学检验常规项目分析性能规范(analytical performance specifications,APS)。方法收集成都市郫都区中医医院检验科2021~2023年参加国家卫生健康委员会临床检验中心生物化学检验常规项目EQA和IQC数据,将EQA数据的百分差值与IQC在控不精密度[以变异系数(coefficient of variation,CV)表示]与基于生物学变异(biological variation,BV)导出的三个标准进行比较,计算EQA数据百分差值通过率和在控CV通过率,以达到80%及以上为该水平质控品的APS设定为实验室常规生化检验项目的质量目标。对于未达到BV导出三个标准APS或达到标准而不适用的检验项目,采用WS/T 403-2012行业标准或基于当前技术水平设定APS。结果生物化学检验常规项目推荐的TEa/允许CV分别为:钾(K)2.4%/1.9%,钠(Na)4.0%/0.9%,氯(Cl)4.0%/0.9%,钙(Ca)3.4%/1.8%,磷(P)9.6%/1.9%,镁(Mg)3.8%/2.0%,血糖(Glu)6.1%/2.3%,肌酐(Crea)3.9%/2.2%,尿素(Urea)8.6%/3.3%,总蛋白(TP)4.9%/2.0%,清蛋白(Alb)3.3%/1.9%,总胆红素(TBil)6.3%/2.4%,丙氨酸氨基转移酶(ALT)9.3%/2.9%,天门冬氨酸氨基转移酶(AST)6.2%/2.1%,γ-谷氨酰基转移酶(GGT)9.2%/2.1%,乳酸脱氢酶(LDH)6.8%/2.2%,碱性磷酸酶(ALP)7.2%/3.3%,总胆固醇(TC)8.3%/2.6%,三酰甘油(TG)12.9%/4.9%,淀粉酶(AMY)5.9%/1.6%,肌酸激酶(CK)4.3%/1.6%和尿酸(UA)2.9%/1.0%。结论基于BV或当前技术水平设定的APS可作为实验室生物化学检验常规项目的质量目标,实验室根据实际情况选择适合自己的APS。

基于ACPI的磁浮球系统控制方法

针对传统控制算法在解决磁浮球系统中存在高度非线性特性、参数摄动以及外部扰动的技术局限性问题,提出一种基于自耦PID(Auto-coupling PID, ACPID)控制理论的磁浮球系统控制方法。首先根据电磁力在平衡点附近进行1阶Taylor展开,结合电磁线圈的动态模型,形成以电压为控制输入的磁浮球位置动态系统。在磁浮球动力学模型的基础上,再将不确定高阶项、电磁线圈的未知电流动态以及外部未知有界扰动定义为总扰动,从而可将一个非线性不确定磁浮球系统映射为一个2阶线性扰动系统。其次,基于ACPID控制量纲匹配构造的误差函数,可将2阶线性扰动系统映射为1阶线性系统,进而构建一个在总扰动反相激励下的闭环受控误差系统,据此设计了基于速度因子的磁浮球位置通道控制器,建立磁浮球位置控制系统并进行鲁棒稳定性分析,理论证明了ACPI方法的有效性。最后与国外现有较为先进的控制方法进行对比仿真,分别进行了方波跟踪实验、正弦跟踪实验、抗扰动实验以及鲁棒性实验。与NTSMC+GPIO方法相比,在方波跟踪实验中ACPI控制系统的响应速度提升了50%,ITAE值降低了82%,RMSE值降低了22.4%,其他仿真实验下的控制性能也有明显的提升。研究结果表明,ACPI控制策略不仅可以实现在超调量较小的情况下具备较快的响应速度、较高的控制精度、较强的抗扰动能力以及较好的鲁棒性,而且控制器结构简单、计算量小,在磁浮球控制系统领域具有一定的应用前景。

基于Partial-EIV模型的TLS姿态估计方法

推导了基于乘性姿态角误差的观测方程,顾及其系数矩阵也含有误差的特点提出一种利用整体最小二乘原理估计姿态参数的新思路。该问题的系数矩阵中同时存在随机元素和固定元素且存在结构性特征,故引入Partial-EIV模型,设计了一种符合其系数矩阵结构特点的新模型。最后通过两组仿真实验将其与已有姿态估计方法进行对比,得出结论:基于Partial-EIV模型的整体最小二乘解法解算精度高于常规最小二乘法;其解算效果与基于乘性姿态角误差的最小二乘法基本一致。表明本文提出的方法正确有效。

水准测量中尺度比参数的附加系统参数的Partial EIV模型解法

针对目前水准测量中尺度比参数的附加系统参数的平差模型,本文对模型进行重构,提出尺度比参数的附加系统参数的partial errors-in-variables(Partial EIV)模型,给出总体最小二乘准则下的解算公式及迭代算法。实际算例和模拟数据结果表明,本文方法与传统方法在处理尺度比参数为附加系统参数时的效果基本一致,并给出相关的理论依据。

在线社交网络中基于多态信任融合的信任估计

为提高大型在线社交网络中信任计算方法的准确性和鲁棒性,采用共被引和转置信任传播操作,提出一种基于多态信任融合的信任估计方法估计连续信任/不信任值。结合信任者、被信任者的相邻用户的信息以及被信任者对信任者的信任,平均估计出两个用户信任或被其它用户信任的差异,以及一个用户信任另一个用户和被该用户信任的差异;利用这些差异,计算4种部分信任估计值,将这些部分估计值加权平均,得到信任者对被信任者的最终信任估计值。仿真结果表明,所提方法比其它最新的现有信任计算算法更准确和鲁棒,对应用于大型网络更高效。

部分线性变系数模型的贝叶斯分位数回归

针对部分线性变系数模型的参数估计问题,采用B样条方法逼近非参数部分的未知光滑函数,进而利用非对称拉普拉斯分布实现贝叶斯分位数回归,并基于Gibbs抽样推导出所有未知参数的后验分布,通过数值模拟比较分析了贝叶斯分位数回归与分位数回归参数估计的优劣,结果表明,在均方误差准则下,贝叶斯分位数回归的估计效果更优。最后,通过实例分析说明了所提方法的有效性。