Designing Adaptive Multiple Dependent State Sampling Plan for Accelerated Life Tests

A novel adaptive multiple dependent state sampling plan(AMDSSP)was designed to inspect products from a continuous manufacturing process under the accelerated life test(ALT)using both double sampling plan(DSP)and multiple dependent state sampling plan(MDSSP)concepts.Under accelerated conditions,the lifetime of a product follows the Weibull distribution with a known shape parameter,while the scale parameter can be determined using the acceleration factor(AF).The Arrhenius model is used to estimate AF when the damaging process is temperature-sensitive.An economic design of the proposed sampling plan was also considered for the ALT.A genetic algorithm with nonlinear optimization was used to estimate optimal plan parameters to minimize the average sample number(ASN)and total cost of inspection(TC)under both producer’s and consumer’s risks.Numerical results are presented to support the AMDSSP for the ALT,while performance comparisons between the AMDSSP,the MDSSP and a single sampling plan(SSP)for the ALT are discussed.Results indicated that the AMDSSP was more flexible and efficient for ASN and TC than the MDSSP and SSP plans under accelerated conditions.The AMDSSP also had a higher operating characteristic(OC)curve than both the existing sampling plans.Two real datasets of electronic devices for the ALT at high temperatures demonstrated the practicality and usefulness of the proposed sampling plan.

A Novel Multiple Dependent State Sampling Plan Based on Time Truncated Life Tests Using Mean Lifetime

The design of a new adaptive version of the multiple dependent state(AMDS)sampling plan is presented based on the time truncated life test under the Weibull distribution.We achieved the proposed sampling plan by applying the concept of the double sampling plan and existing multiple dependent state sampling plans.A warning sign for acceptance number was proposed to increase the probability of current lot acceptance.The optimal plan parameters were determined simultaneously with nonlinear optimization problems under the producer’s risk and consumer’s risk.A simulation study was presented to support the proposed sampling plan.A comparison between the proposed and existing sampling plans,namely multiple dependent state(MDS)sampling plans and a modified multiple dependent state(MMDS)sampling plan,was considered under the average sampling number and operating characteristic curve values.In addition,the use of two real datasets demonstrated the practicality and usefulness of the proposed sampling plan.The results indicated that the proposed plan is more flexible and efficient in terms of the average sample number compared to the existing MDS and MMDS sampling plans.

基于SAM教学系统设计模型的钉钉医学检验实践教学分层培训系统构建

目的基于钉钉构建医学检验实践教学分层培训系统。方法2019年3月—2021年12月,课题组以SAM教学系统设计模型为理论框架,分析检验学员实践教学分层培训需求,基于钉钉系统对宜宾市第二人民医院检验科检验实践教学分层培训系统功能进行设计、开发。结果2019年完成钉钉医学检验实践教学分层培训系统的构建,对培训系统进行试运行,通过评价反馈进一步改进。至2021年12月该系统开设了104个规培、进修、实习学员分层课程,共162人参与网上学习,3216人次自主完成课程学习并通过在线考核,培训人员满意度达98.15%。结论基于SAM教学系统设计模型的钉钉医学检验实践教学分层培训软件可以用于医学检验实践教学,值得进一步推广应用。

Parker Test for Heteroskedasticity Based on Sample Fitted Values

To address the drawbacks of the traditional Parker test in multivariate linear models: the process is cumbersome and computationally intensive, we propose a new heteroscedasticity test. A new heteroskedasticity test is proposed using the fitted values of the samples as new explanatory variables, reconstructing the regression model, and giving a new heteroskedasticity test based on the significance test of the coefficients, it is also compared with the existing Parker test which is improved using the principal component idea. Numerical simulations and empirical analyses show that the improved Parker test with the fitted values of the samples proposed in this paper is superior.

MAPOD Analysis in Eddy Current Testing of Flaws Considering Multiple Response Signals and Multiple Flaw Parameters

The reliability of the eddy current testing (ECT) in flaw detection is quantitatively evaluated by theprobability of detection (POD). Precise and efficient modeling of POD gives direction for the implement of ECTon sites to avoid false or missing flaw detection. Traditional POD analysis focuses on single uncertain factor orsingle response signal with limited credibility in engineering. This paper considers multiple response signals andmultiple flaw parameters to perform POD. The flaw length, the flaw depth, the coil impedance, and the magneticflux density are comprehensively studied under various lift-off distances. A finite element model (FEM) of ECT isestablished and verified with experiments to obtain sufficient simulation data for discrete POD modeling. Thecontinuous POD function is then fitted based on the discrete values to show the superiority of integrating multiplefactors. A comparison with conventional POD analysis further demonstrates the higher reliability of ECT flawdetection considering multiple flaw parameters and multiple response signals, especially for small flaws.

Reliability Sensitivity Algorithm Based on Stratified Importance Sampling Method for Multiple Failure Modes Systems

Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.

A Likelihood-Based Multiple Change Point Algorithm for Count Data with Allowance for Over-Dispersion

Count data is almost always over-dispersed where the variance exceeds the mean. Several count data models have been proposed by researchers but the problem of over-dispersion still remains unresolved, more so in the context of change point analysis. This study develops a likelihood-based algorithm that detects and estimates multiple change points in a set of count data assumed to follow the Negative Binomial distribution. Discrete change point procedures discussed in literature work well for equi-dispersed data. The new algorithm produces reliable estimates of change points in cases of both equi-dispersed and over-dispersed count data;hence its advantage over other count data change point techniques. The Negative Binomial Multiple Change Point Algorithm was tested using simulated data for different sample sizes and varying positions of change. Changes in the distribution parameters were detected and estimated by conducting a likelihood ratio test on several partitions of data obtained through step-wise recursive binary segmentation. Critical values for the likelihood ratio test were developed and used to check for significance of the maximum likelihood estimates of the change points. The change point algorithm was found to work best for large datasets, though it also works well for small and medium-sized datasets with little to no error in the location of change points. The algorithm correctly detects changes when present and fails to detect changes when change is absent in actual sense. Power analysis of the likelihood ratio test for change was performed through Monte-Carlo simulation in the single change point setting. Sensitivity analysis of the test power showed that likelihood ratio test is the most powerful when the simulated change points are located mid-way through the sample data as opposed to when changes were located in the periphery. Further, the test is more powerful when the change was located three-quarter-way through the sample data compared to when the change point is closer (quarter-way) to the first observation.

A shock wave overpressure test system based on multiple triggers

Because single trigger system is unreliable for shock wave overpressure test, this paper presents a multi-trigger overpressure test system. The large memory capacity is divided into parts to achieve data acquisition and storage with multiple triggers. Compared with conventional single-shot storage test system, this system can prevent false trigger and improve reliability of the test. By using explosion time to extract valid signal segments, it improves the efficiency of data recovery. These characteristics of the system contribute to multi-point test. After the dynamic characteristics of the system are calibrated, the valid data can be obtained in explosion experiments. The results show that the multi-trigger test system has higher reliability than single trigger test system.

Influence of multiple structural parameters on interior ballistics based on orthogonal test methods

Influence of multiple structural parameters on the performance of a gun launch system driven by highpressure reactive gases is important for structural design and performance adjustment.A coupled lumped parameter model was utilized to predict the propellant combustion,and a dynamic finite element method was applied to approximate the mechanical interactions between the projectile and the barrel.The combustion and the mechanical interactions were coupled through a user subroutine interface in ABAQUS.The correctness and the capability of the finite element approximations in capturing small structural changes were validated by comparing predicted resistance with experiments.Based on the coupled model,the influence of structural parameters of a medium-caliber gun on the system performance was investigated.In order to reduce the research costs,orthogonal tests were designed to investigate the comprehensive effects of the parameters.According to statistical analysis,the important order of the structural parameters on the launching process was obtained.The results indicate that the influence of the width of the rotating band stands out among the studied parameters in the gun.The work provides a method to investigate the influence of multiple parameters on system performance and gives guidance for controlling the system performance.

Optimal Design of Multiple Stresses Accelerated Life Test Plan Based on Transforming the Multiple Stresses to Single Stress

For planning optimum multiple stresses accelerated life test plans, a commonly followed guiding principle is that all parameters of the life-stress relationship should be estimated, and the number of the stress level combinations must be no less than the number of parameters of the life-stress relationship. However, the general objective of an accelerated life test（ALT） is to assess thep-th quantile of the product life distribution under normal stress. For this objective,estimating all model parameters is not necessary, and this will increase the cost of test. Based on the theoretical conclusion that the stress level combinations of the optimum multiple stresses ALT plan locate on a straight line through the origin of coordinate, it is proposed that a design idea of planning the optimum multiple stresses ALT plan through transforming the problem of designing an optimum multiple stresses ALT plan to designing an optimum single stress ALT plan. Moreover, a method of planning the optimum multiple stresses ALT plan which can avoid estimating all model parameters is established. An example shows that, the proposed plan which only has two stress level combinations could achieve an accuracy no less than the traditional plan, and save the test time and cost on one stress level combination at least; when the actual product life is less than the design value, even the deviation of the model initial parameters value is up to 20%, the variance of the estimation of thep-th quantile of the proposed plan is still smaller than the traditional plans approximately 25%. A design method is provided for planning the optimum multiple stresses ALT which uses the statistical optimum degenerate test plan as the optimum multiple stresses accelerated life test plan.

MAXIMIN EFFICIENCY ROBUST TEST FOR MULTIPLE NUISANCE PARAMETERS AND ITS STATISTICAL PROPERTIES

We propose the maximin efficiency robust test（MERT） for multiple nuisance parameters based on theories about the maximin efficiency robust test for only one nuisance parameter and investigate some theoretical properties about this robust test.We explore some theoretical properties about the power of the MERT for multiple nuisance parameters in a specified scenario intuitively further more.We also propose a meaningful example from statistical genetic field to which the MERT for multiple nuisance parameters can be well applied.Extensive simulation studies are conducted to testify the robustness of the MERT for multiple nuisance parameters.

Genetic test in multiple endocrine neoplasia type 1 syndrome: An evolving story

Multiple endocrine neoplasia type 1(MEN1) is an autosomal dominant inherited tumour syndrome expressing various endocrine and non-endocrine lesions and tumours. Since the identification of the causative gene, the oncosuppressor gene MEN1, in 1997, genetic testing has revealed an important approach for the early and differential diagnosis of the disease. The finding of a MEN1 mutation in a patient has important clinical implications for relatives since it allows very early disease diagnosis and identification of carriers, even before biochemical and/or clinical manifestation, permitting their inclusion in a specific program of surveillance and subsequent praecox therapy. Currently, genetic testing for MEN1 consists principally of the sequencing of coding regions and intron-exon junctions of the MEN1 gene. However, the recent acquisition of novel high throughput technologies will allow the design of innovative, accurate, complete and rapid genetic diagnosis. These new tools are able to increase the strength of the analysis and almost completely eliminate the possibility of false negative results. This review aims to give an overview on genetic testing of MEN1 syndrome, reporting the positive aspects of performing the analysis and the future perspectives for improving the performance of the test, as well as its application in clinical practice.

Variable selection procedures from multiple testing

Variable selection has played an important role in statistical learning and scienti?c discoveries during the past ten years, and multiple testing is a fundamental problem in statistical inference and also has wide applications in many scienti?c ?elds. Signi?cant advances have been achieved in both areas. This study attempts to ?nd a connection between the adaptive LASSO(least absolute shrinkage and selection operator) and multiple testing procedures in linear regression models. We also propose procedures based on multiple testing methods to select variables and control the selection error rate, i.e., the false discovery rate. Simulation studies demonstrate that the proposed methods show good performance relative to controlling the selection error rate under a wide range of settings.

ON TESTING THE EQUALITY OF K MULTIPLE AND PARTIAL CORRELATION COEFFICIENTS

Coutsourides (1980) derives an ad hoc nuisance parameter removal test for testing the equality of two multiple correlation coefficients of two independent p variate normal populations, under the assumption that a sample of size n is available from each population. He also extends his ad hoc nuisance parameter removal test to the testing of the equality of two multiple correlation matrices. This paper presents likelihood ratio tests for testing the equality of k multiple correlation coefficients, and also k partial correlation coefficients.

Shaking table test and numerical simulation of an isolated cylindrical latticed shell under multiple-support excitations

In order to study the infl uence of the ground motion spatial eff ect on the seismic response of large span spatial structures with isolation bearings, a single-layer cylindrical latticed shell scale model with a similarity ratio of 1/10 was constructed. An earthquake simulation shaking table test on the response under multiple-support excitations was performed with the high-position seismic isolation method using high damping rubber (HDR) bearings. Small-amplitude sinusoidal waves and seismic wave records with various spectral characteristics were applied to the model. The dynamic characteristics of the model and the seismic isolation eff ect on it were analyzed at varying apparent wave velocities, namely infi nitely great, 1000 m/s, 500 m/s and 250 m/s. Besides, numerical simulations were carried out by Matlab software. According to the comparison results, the numerical results agreed well with the experimental data. Moreover, the results showed that the latticed shell roof exhibited a translational motion as a rigid body after the installation of the HDR bearings with a much lower natural frequency, higher damping ratio and only 1/2~1/8 of the acceleration response peak values. Meanwhile, the structural responses and the bearing deformations at the output end of the seismic waves were greatly increased under multiple-support excitations.

Multiple Objective Test Design for Accelerated Destructive Degradation Tests

Accelerated destructive degradation tests(ADDTs)are powerful to provide reliability information in the degradation processes with destructive measurements.In order to carry out an ADDT efficiently,both the estimation precision of parameters and the test cost should be considered.On the basis of the given degradation model and failure criterion,a multiple-objective optimization model for the design of ADDTs is proposed.Under constrains of the maximum measurement time,the total sample size and the number of stress levels,a comprehensive target function is suggested to reflect both the precision of lifetime estimation and total cost,and the optimal test plan is obtained,which is composed by optimal choices for samples size,measurement frequency,and the number of measurements at each stress level.A real example is illustrated to demonstrate the implementation of the proposed approach.

Multiple z-Score Based Method for Noninvasive Prenatal Test Using Cell-Free DNA in Maternal Plasma

Objective: To improve the detecting accuracy of chromosomal aneuploidy of fetus by non-invasive prenatal testing (NIPT) using next generation sequencing data of pregnant women’s cell-free DNA. Methods: We proposed the multi-Z method which uses 21 z-scores for each autosomal chromosome to detect aneuploidy of the chromosome, while the conventional NIPT method uses only one z-score. To do this, mapped read numbers of a certain chromosome were normalized by those of the other 21 chromosomes. Average and standard deviation (SD), which are used for calculating z-score of each sample, were obtained with normalized values between all autosomal chromosomes of control samples. In this way, multiple z-scores can be calculated for 21 autosomal chromosomes except oneself. Results: Multi-Z method showed 100% sensitivity and specificity for 187 samples sequenced to 3 M reads while the conventional NIPT method showed 95.1% specificity. Similarly, for 216 samples sequenced to 1 M reads, Multi-Z method showed 100% sensitivity and 95.6% specificity and the conventional NIPT method showed a result of 75.1% specificity. Conclusion: Multi-Z method showed higher accuracy and robust results than the conventional method even at low coverage reads.

On Dynamic Channel Emulation in Sector MPAC for Over-the-Air Testing of Beamformed Massive MIMO Devices

In this article,novel emulation strategies for the sectored multiple probe anechoic chamber(SMPAC)are proposed to enable the reliable evaluation of the massive multiple-input multiple-output(MIMO)device operating at beamforming mode,which requires a realistic non-stationary channel environment.For the dynamic propagation emulation,an efficient closed-form probe weighting strategy minimizing the power angular spectrum(PAS)emulation errors is derived,substantially reducing the associated computational complexity.On the other hand,a novel probe selection algorithm is proposed to reproduce a more accurate fading environment.Various standard channel models and setup configurations are comprehensively simulated to validate the capacity of the proposed methods.The simulation results show that more competent active probes are selected with the proposed method compared to the conventional algorithms.Furthermore,the derived closedform probe weighting strategy offers identical accuracy to that obtained with complicated numerical optimization.Moreover,a realistic dynamic channel measured in an indoor environment is reconstructed with the developed methodologies,and 95.6%PAS similarity can be achieved with 6 active probes.The satisfactory results demonstrate that the proposed algorithms are suitable for arbitrary channel emulation.

A Gene Score Test for Disease Association with Multiple Genes

The traditional method for creating a gene score to predict a given outcome is to use the most statistically significant single nucleotide polymorphisms (SNPs) from all SNPs which were tested. There are several disadvantages of this approach such as excluding SNPs that do not have strong single effects when tested on their own but do have strong joint effects when tested together with other SNPs. The interpretation of results from the traditional gene score may lack biological insight since the functional unit of interest is often the gene, not the single SNP. In this paper we present a new gene scoring method, which overcomes these problems as it generates a gene score for each gene, and the total gene score for all the genes available. First, we calculate a gene score for each gene and second, we test the association between this gene score and the outcome of interest (i.e. trait). Only the gene scores which are significantly associated with the outcome after multiple testing correction for the number of gene tests (not SNPs) are considered in the total gene score calculation. This method controls false positive results caused by multiple tests within genes and between genes separately, and has the advantage of identifying multi-locus genetic effects, compared with the Bonferroni correction, false discovery rate (FDR), and permutation tests for all SNPs. Another main feature of this method is that we select the SNPs, which have different effects within a gene by using adjustment in multiple regressions and then combine the information from the selected SNPs within a gene to create a gene score. A simulation study has been conducted to evaluate finite sample performance of the proposed method.

On Testing Equality of K Multiple Correlation Matrices

Coutsourides derived an ad hoc nuisance paratmeter removal test for testing equality of two multiple correlation matrices of two independent p variate normal populations under the assumption that a sample of size n is available from each population. This paper presents a likelihood ratio test criterion for testing equality of K multiple correlation matrices and extends the results to the testing of equality of K partial correlation matrices.