Modified DS np Chart Using Generalized Multiple Dependent State Sampling under Time Truncated Life Test

This study presents the design of a modified attributed control chart based on a double sampling(DS)np chart applied in combination with generalized multiple dependent state(GMDS)sampling to monitor the mean life of the product based on the time truncated life test employing theWeibull distribution.The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing.Three control limit levels are used:the warning control limit,inner control limit,and outer control limit.Together,they enhance the capability for variation detection.A genetic algorithm can be used for optimization during the in-control process,whereby the optimal parameters can be established for the proposed control chart.The control chart performance is assessed using the average run length,while the influence of the model parameters upon the control chart solution is assessed via sensitivity analysis based on an orthogonal experimental design withmultiple linear regression.A comparative study was conducted based on the out-of-control average run length,in which the developed control chart offered greater sensitivity in the detection of process shifts while making use of smaller samples on average than is the case for existing control charts.Finally,to exhibit the utility of the developed control chart,this paper presents its application using simulated data with parameters drawn from the real set of data.

Research on aiming methods for small sample size shooting tests of two-dimensional trajectory correction fuse

The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator.The impact point easily deviates from the target,and thus the correction result cannot be readily evaluated.However,the cost of shooting tests is considerably high to conduct many tests for data collection.To address this issue,this study proposes an aiming method for shooting tests based on small sample size.The proposed method uses the Bootstrap method to expand the test data;repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method;and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback-Leibler divergence,which to some extent avoids the real data being"submerged"by the simulation data and achieves the fusion Bayesian estimation of the dispersion center.The experimental results show that when the simulation accuracy is sufficiently high,the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods,which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.;in addition,this study provides a knowledge base for further comprehensive studies in the future.

Cautionary Remarks When Testing Agreement between Two Raters for Continuous Scale Measurements: A Tutorial in Clinical Epidemiology with Implementation Using R

Background: When continuous scale measurements are available, agreements between two measuring devices are assessed both graphically and analytically. In clinical investigations, Bland and Altman proposed plotting subject-wise differences between raters against subject-wise averages. In order to scientifically assess agreement, Bartko recommended combining the graphical approach with the statistical analytic procedure suggested by Bradley and Blackwood. The advantage of using this approach is that it enables significance testing and sample size estimation. We noted that the direct use of the results of the regression is misleading and we provide a correction in this regard. Methods: Graphical and linear models are used to assess agreements for continuous scale measurements. We demonstrate that software linear regression results should not be readily used and we provided correct analytic procedures. The degrees of freedom of the F-statistics are incorrectly reported, and we propose methods to overcome this problem by introducing the correct analytic form of the F statistic. Methods for sample size estimation using R-functions are also given. Results: We believe that the tutorial and the R-codes are useful tools for testing and estimating agreement between two rating protocols for continuous scale measurements. The interested reader may use the codes and apply them to their available data when the issue of agreement between two raters is the subject of interest.

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.

Calculation of Two-Tailed Exact Probability in the Wald-Wolfowitz One-Sample Runs Test

The objectives of this paper are to demonstrate the algorithms employed by three statistical software programs (R, Real Statistics using Excel, and SPSS) for calculating the exact two-tailed probability of the Wald-Wolfowitz one-sample runs test for randomness, to present a novel approach for computing this probability, and to compare the four procedures by generating samples of 10 and 11 data points, varying the parameters n0 (number of zeros) and n1 (number of ones), as well as the number of runs. Fifty-nine samples are created to replicate the behavior of the distribution of the number of runs with 10 and 11 data points. The exact two-tailed probabilities for the four procedures were compared using Friedman’s test. Given the significant difference in central tendency, post-hoc comparisons were conducted using Conover’s test with Benjamini-Yekutielli correction. It is concluded that the procedures of Real Statistics using Excel and R exhibit some inadequacies in the calculation of the exact two-tailed probability, whereas the new proposal and the SPSS procedure are deemed more suitable. The proposed robust algorithm has a more transparent rationale than the SPSS one, albeit being somewhat more conservative. We recommend its implementation for this test and its application to others, such as the binomial and sign test.

Modular zonal fluid sampling and pressure testing technology for production well

To accurately obtain development dynamic data such as zonal pressure and fluid parameters of each oil layer in the late development stage of a high water-cut old oilfield, a modular zonal sampling and testing technology with the characteristics of modularization, full electronic control and rapidity was proposed and developed. Lab testing and on-site testing was carried out. The modular zonal sampling and testing system is composed of 10 functional modules, namely ground control system, downhole power supply module, drainage pump, electronically controlled anchor, electronically controlled packer, electronically controlled sampler, magnetic positioning sub, terminal sub, adapter cable, and quick connector. Indoor tests have confirmed that the performance parameters of each module meet the design requirements. The downhole function modules of the system can withstand pressures up to 35 MPa and temperatures up to 85 ℃. The rubber cylinder of the electronically controlled packer can withstand a pressure difference of more than 10 MPa. The electronically controlled anchor has an anchoring force of greater than 6.9 t, and can be forcibly detached in the event of an accident. The discharge pump has a displacement of 0.8 m;/d and a head of 500 m. The electronically controlled sampler can meet the requirement of taking 500 mL of sample in each of the 3 chambers. Field tests in Jilin Oilfield show that the system can realize rapid isolation and self-check of isolation of a certain production interval downhole, as well as layer-by layer pressure build-up test. The drainage pump can be used to discharge the mixed liquid between the upper and lower packers and near the wellbore to obtain real fluid samples of the tested formation interval. The data obtained give us better understanding on the pay zones in old oilfields, and provide important basis for development plan adjustment, reservoir stimulation, and EOR measures.

Adaptive sampling strategy for characterizing spatial distribution of soil liquefaction potential using cone penetration test

Characterizing spatial distribution of soil liquefaction potential is critical for assessing liquefactionrelated hazards(e.g.building damages caused by liquefaction-induced differential settlement).However,in engineering practice,soil liquefaction potential is usually measured at limited locations in a specific site using in situ tests,e.g.cone penetration tests(CPTs),due to the restrictions of time,cost and access to subsurface space.In these cases,liquefaction potential of soil at untested locations requires to be interpreted from limited measured data points using proper interpolation method,leading to remarkable statistical uncertainty in liquefaction assessment.This underlines an important question of how to optimize the locations of CPT soundings and determine the minimum number of CPTs for achieving a target reliability level of liquefaction assessment.To tackle this issue,this study proposes a smart sampling strategy for determining the minimum number of CPTs and their optimal locations in a selfadaptive and data-driven manner.The proposed sampling strategy leverages on information entropy and Bayesian compressive sampling(BCS).Both simulated and real CPT data are used to demonstrate the proposed method.Illustrative examples indicate that the proposed method can adaptively and sequentially select the required number and optimal locations of CPTs.

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.

Acceptance Sampling Plans with Truncated Life Tests for the Length-Biased Weighted Lomax Distribution

In this paper,we considered the Length-biased weighted Lomax distribution and constructed new acceptance sampling plans(ASPs)where the life test is assumed to be truncated at a pre-assigned time.For the new suggested ASPs,the tables of the minimum samples sizes needed to assert a specific mean life of the test units are obtained.In addition,the values of the corresponding operating characteristic function and the associated producer’s risks are calculated.Analyses of two real data sets are presented to investigate the applicability of the proposed acceptance sampling plans;one data set contains the first failure of 20 small electric carts,and the other data set contains the failure times of the air conditioning system of an airplane.Comparisons are made between the proposed acceptance sampling plans and some existing acceptance sampling plans considered in this study based on the minimum sample sizes.It is observed that the samples sizes based on the proposed acceptance sampling plans are less than their competitors considered in this study.The suggested acceptance sampling plans are recommended for practitioners in the field.

Sample Size Determination and Statistical Hypothesis Testing for Core Centration in Press Coated Tablets

A novel statistical approach to evaluate the manufacturing quality of press coated tablets in terms of the centering of their core is presented. We also provide a formula to determine the necessary sample size. This approach is applied to real data.

A Cross-cultural Examination of the Noise-sensitivity Scale-short Form:Measurement Invariance Testing between the US and Chinese Samples

Unwanted sound that is unpleasant or disruptive to hear, often interpreted as noise, is a widespread environmental pollutant. Similar to other environmental pollutants, this noise incurs a variety of costs to society. Numerous negative health impacts are linked to increases in noise exposure,such as increased cardiovascular risk;and sleep

Testing and estimation of spatial econometric model in the case of limited samples

In econometric models, the error term is usually assumed to be normally distributed for ease of calculation. However, in the real socio-economic world, the distribution of error terms is usually unknown or does not satisfy the classical assumption of normal distribution. The random sampling method provides an effective way to solve the econometric model study of the unknown or non-normal distribution of error terms. The Monte Carlo method and Bootstrap method are often used to solve related problems in the case of limited samples.

Selection of Test Samples for Monitoring Veterinary Drug Residue in Bred Animals

[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue in bred animals. [Method]Total three different concentrations of cimaterol were administered to pigs, and the residue amounts of cimaterol in pig hair, urine and flesh were monitored at different raising stage. [Result] During the administration period, the residue amount of cimaterol was highest in urine, so urine is the suitable sample for rapid detection of cimaterol in manufacturing enterprises. Cimaterol could be accumulated in pig hair,where cimaterol was metabolized slowly. Thus, pig hair can be used as the test sample for tracing illegal use of veterinary drugs and for vivo detection. Flesh can be used as test sample for direct judgment whether cimaterol residue exceeds the relevant standard. [Conclusion] This study will provide certain theoretical basis for drug monitor in animal husbandry.

Novel technique for cost reduction in mutation testing

Aimed at the problem of expensive costs in mutation testing which has hampered its wide use,a technique of introducing a test case selection into the process of mutation testing is proposed.For each mutant,a fixed number of test cases are selected to constrain the maximum allowable executions so as to reduce useless work.Test case selection largely depends on the degree of mutation.The mutation distance is an index describing the semantic difference between the original program and the mutated program.It represents the percentage of effective test cases in a test set,so it can be used to guide the selection of test cases.The bigger the mutation distance is,the easier it is that the mutant will be killed,so the corresponding number of effective test cases for this mutant is greater.Experimental results suggest that the technique can remarkably reduce execution costs without a significant loss of test effectiveness.

Sample preference for colorectal cancer screening tests: Blood or stool?

Objective: Despite the high prevalence of CRC and the proven benefits of faecal sampling tests, participation rates in CRC screening are suboptimal. Literature has identified a number of barriers to participation, including faecal aversion. Emerging test technologies suggest blood-based molecular markers might provide an alternative, more acceptable option, for CRC screening tests. We aim to determine preference for blood compared to faeces as the sample for the screening test. Methods: A survey was mailed to 956 South Australians aged 50 to 74 years. Data were collected on sample preference, demographic variables, and ratings of screening test convenience and comfort. Results: The survey yielded a 43% response rate. The majority of participants preferred to provide a blood sample (78% v 22%, p < 0.001). Women were more likely to prefer blood than men (82% vs 74%, p = 0.05). Sample experience influenced preferences, with a significantly higher preference for faeces among participants with experience in faecal sampling (27% vs 17% with no experience, p < 0.05). Participants who preferred to provide a faecal sample rated it significantly more convenient (p < 0.001), more comfortable (p < 0.001), and more acceptable (p < 0.001) than those who preferred blood sampling. Conclusions: Survey participants overwhelmingly indicate a preference for the idea of a blood sample over a faecal sample for CRC screening. Preference was influenced by gender, experience with sampling method and the individual’s perception of sampling convenience, sampling comfort and sample acceptability. Our results suggest population participation rates are likely to improve with blood-based screening tests.

Numerical analysis of the effects of downhole dynamic conditions on formation testing while drilling

Formation testing while drilling is an innovative technique that is replacing conventional pressure testing in which the fluid sampling is conducted in a relatively short time following the drilling. At this time, mud invasion has just started, mudcake has not formed entirely and the formation pressure is not stable. Therefore, it is important to study the influence of the downhole dynamic environment on pressure testing and fluid sampling. This paper applies an oil-water two phase finite element model to study the influence of mudcake quality and mud filtrate invasion on supercharge pressure, pretest and sampling in the reservoirs of different permeability. However, the study is only for the cases with water based mud in the wellbore. The results illustrate that the mudcake quality has a significant influence on the supercharge pressure and fluid sampling, while the level of mud filtrate invasion has a strong impact on pressure testing and sampling. In addition, in-situ formation pressure testing is more difficult in low permeability reservoirs as the mud filtrate invasion is deeper and therefore degrades the quality of fluid sampling. Finally, a field example from an oil field on the Alaskan North Slope is presented to validate the numerical studies of the effects of downhole dynamic conditions on formation testing while drilling.

A New Maximum Test via the Dependent Samples t-Test and the Wilcoxon Signed-Ranks Test

A maximum test in lieu of forcing a choice between the two dependent samples t-test and Wilcoxon signed-ranks test is proposed. The maximum test, which requires a new table of critical values, maintains nominal α while guaranteeing the maximum power of the two constituent tests. Critical values, obtained via Monte Carlo methods, are uniformly smaller than the Bonferroni-Dunn adjustment, giving it power superiority when testing for treatment alternatives of shift in location parameter when data are sampled from non-normal distributions.

Reliability testing and reliability analysis of the over-load protective relay

The over-load protective relay is widely used directly affects the safe running of a motor. The reliability for motor protection. The reliability of the over-load protective relay testing and reliability analysis of the over-load protective relay is an important way to improve the reliability of products. In this paper, the reliability test method of the over-load protective relay is studied, and the reliability tests of the typical products are carried out on a reliability tester developed by authors. In terms of the testing results, the reliability analysis is finished. The failure reasons are found and the measures are put forward to improve the reliability of the products.

Life prediction and test period optimization research based on small sample reliability test of hydraulic pumps

Hydraulic pumps belong to reliable long-life hydraulic components. The reliability evaluation includes characters such as long test period,high cost,and high power loss and so on. Based on the principle of energy-saving and power recovery,a small sample hydraulic pump reliability test rig is built,and the service life of hydraulic pump is predicted,and then the sampling period of reliability test is optimized. On the basis of considering the performance degradation mechanism of hydraulic pump,the feature information of degradation distribution of hydraulic pump volumetric efficiency during the test is collected,so an optimal degradation path model of feature information is selected from the aspect of fitting accuracy,and pseudo life data are obtained. Then a small sample reliability test of period constrained optimization search strategy for hydraulic pump is constructed to solve the optimization problem of the test sampling period and tightening end threshold,and it is verified that the accuracy of the minimum sampling period by the non-parametric hypothes is tested. Simulation result shows it could possess instructional significance and referenced value for hydraulic pump reliability life evaluation and the test's research and design.

Study on Complete Analysis of LRE Test Samples Based on PCA

Incomplete data samples have a serious impact on the effectiveness of data mining.Aiming at the LRE historical test samples,based on correlation analysis of condition parameter,this paper introduced principle component analysis(PCA)and proposed a complete analysis method based on PCA for incomplete samples.At first,the covariance matrix of complete data set was calculated;Then,according to corresponding eigenvalues which were in descending,a principle matrix composed of eigen-vectors of covariance matrix was made;Finally,the vacant data was estimated based on the principle matrix and the known data.Compared with traditional method validated the method proposed in this paper has a better effect on complete test samples.An application example shows that the method suggested in this paper can update the value in use of historical test data.