Non-destructive testing and pre-warning analysis on the quality of bolt support in deep roadways of mining districts

The bolt support quality of coal roadways is one of the important factors for the efficiency and security of coal production. By means of a self-developed technique and equipment of random non-destructive testing, non-destructive detection and pre-warning analysis on the quality of bolt support in deep roadways of mining districts were performed in a number of mining areas. The measured data were obtained in the detection instances of abnormal in-situ stress and support invalidation etc. The corresponding relation between axial bolt load variation and roadway surrounding rock deformation and stability was summarized in different mining service stages. Pre-warning technology of roadway surrounding rock stability is proposed based on the detection of axial bolt load. Meanwhile, pre-warning indicators of axial bolt load in different mining service stages are offered and some successful pre-warning cases are also illustrated.The research results show that the change rules of axial bolt load in different mining service stages are quite similar in different mining areas. The change of axial bolt load is in accord with the adjustment of surrounding rock stress, which can consequently reflect the deformation and stability state of roadway surrounding rock. Through the detection of axial bolt load in different sections of roadways, the status of real-time bolt support quality can be reflected; meanwhile, the rationality of bolt support design can be evaluated which provides reference for bolting parameters optimization.

Random testing for system-level functional verification of system-on-chip

In order to deal with the limitations during the register transfer level verification, a new functional verification method based on the random testing for the system-level of system-on-chip is proposed.The validity of this method is proven theoretically.Specifically, testcases are generated according to many approaches of randomization.Moreover, the testbench for the system-level verification according to the proposed method is designed by using advanced modeling language.Therefore, under the circumstances that the testbench generates testcases quickly, the hardware/software co-simulation and co-verification can be implemented and the hardware/software partitioning planning can be evaluated easily.The comparison method is put to use in the evaluation approach of the testing validity.The evaluation result indicates that the efficiency of the partition testing is better than that of the random testing only when one or more subdomains are covered over with the area of errors, although the efficiency of the random testing is generally better than that of the partition testing.The experimental result indicates that this method has a good performance in the functional coverage and the cost of testing and can discover the functional errors as soon as possible.

Random-Like Testing of Very Large Scale Integration Circuit

A new approach to improve the test efficiency of random testing is presented in this paper. In conventional random testing, each test pattern is selected randomly regardless of the tests previously generated. This paper introduces the concept of random like testing. The method provided appears to have the same concepts as used in random testing,but actually takes an opposite way to it in order to improve the efficiency of random testing.In a random like testing sequence, the total distance among all test patterns is chosen to be maximal so that the fault sets detected by one test pattern are as different as possible from that detected by the tests previously applied. The procedure to construct a random like testing sequence (RLTS) is described in detail. Theorems to justify the effectiveness and usefulness of the procedure presented are developed. Experimental results on benchmark circuits as well as on other circuit are also given to evaluate the performance of the new approach.

TESTING FOR VARYING DISPERSION OF LONGITUDINAL BINOMIAL DATA IN NONLINEAR LOGISTIC MODELS WITH RANDOM EFFECTS

In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)).

TESTING OF CORRELATION AND HETEROSCEDASTICITY IN NONLINEAR REGRESSION MODELS WITH DBL(p,q,1) RANDOM ERRORS

Chaos theory has taught us that a system which has both nonlinearity and random input will most likely produce irregular data. If random errors are irregular data, then random error process will raise nonlinearity （Kantz and Schreiber （1997））. Tsai （1986） introduced a composite test for autocorrelation and heteroscedasticity in linear models with AR（1） errors. Liu （2003） introduced a composite test for correlation and heteroscedasticity in nonlinear models with DBL（p, 0, 1） errors. Therefore, the important problems in regression model axe detections of bilinearity, correlation and heteroscedasticity. In this article, the authors discuss more general case of nonlinear models with DBL（p, q, 1） random errors by score test. Several statistics for the test of bilinearity, correlation, and heteroscedasticity are obtained, and expressed in simple matrix formulas. The results of regression models with linear errors are extended to those with bilinear errors. The simulation study is carried out to investigate the powers of the test statistics. All results of this article extend and develop results of Tsai （1986）, Wei, et al （1995）, and Liu, et al （2003）.

Robustness self-testing of states and measurements in the prepare-and-measure scenario with 3 → 1 random access code

Recently, Tavakoli et al.proposed a self-testing scheme in the prepare-and-measure scenario, showing that self-testing is not necessarily based on entanglement and violation of a Bell inequality [Phys.Rev.A 98 062307(2018)].They realized the self-testing of preparations and measurements in an N → 1(N ≥ 2) random access code(RAC), and provided robustness bounds in a 2 → 1 RAC.Since all N → 1 RACs with shared randomness are combinations of 2 → 1 and 3 → 1 RACs, the3 → 1 RAC is just as important as the 2 → 1 RAC.In this paper, we find a set of preparations and measurements in the3 → 1 RAC, and use them to complete the robustness self-testing analysis in the prepare-and-measure scenario.The method is robust to small but inevitable experimental errors.

External validation of the Prostate Cancer Prevention Trial and the European Randomized Study of Screening for Prostate Cancer risk calculators in a Chinese cohort

Several prediction models have been developed to estimate the outcomes of prostate biopsies. Most of these tools were designed for use with Western populations and have not been validated across different ethnic groups. Therefore, we evaluated the predictive value of the Prostate Cancer Prevention Trial （PCPT） and the European Randomized Study of Screening for Prostate Cancer （ERSPC） risk calculators in a Chinese cohort. Clinicopathological information was obtained from 495 Chinese men who had undergone extended prostate biopsies between January 2009 and March 2011. The estimated probabilities of prostate cancer and high-grade disease （Gleason 〉6） were calculated using the PCPT and ERSPC risk calculators. Overall measures, discrimination, calibration and clinical usefulness were assessed for the model evaluation. Of these patients, 28.7% were diagnosed with prostate cancer and 19.4% had high-grade disease. Compared to the PCPT model and the prostate-specific antigen （PSA） threshold of 4 ng m1-1, the ERSPC risk calculator exhibited better discriminative ability for predicting positive biopsies and high-grade disease （the area under the curve was 0.831 and 0.852, respectively, P〈O.01 for both）. Decision curve analysis also suggested the favourable clinical utility of the ERSPC calculator in the validation dataset. Both prediction models demonstrated miscalibration： the risk of prostate cancer and high-grade disease was overestimated by approximately 20% for a wide range of predicted probabilities. In conclusion, the ERSPC risk calculator outperformed both the PCPT model and the PSA threshold of 4 ng ml- z in predicting prostate cancer and high-grade disease in Chinese patients. However, the prediction tools derived from Western men significantly overestimated the probability of prostate cancer and high-grade disease compared to the outcomes of biopsies in a Chinese cohort.

EMPIRICAL BAYES TEST PROBLEMS OF VARIANCE COMPONENTS IN RANDOM EFFECTS MODEL

Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.

Generation of 3D random meso-structure of soil-rock mixture and its meso-structural mechanics based on numerical tests

The mesoscopic failure mechanism and the macro-mechanical characteristics of soil-rock mixture(S-RM) under external load are largely controlled by S-RM's meso-structural features. The objective of this work is to improve the three-dimensional technology for the generation of the random meso-structural models of S-RM, for randomly generating irregular rock blocks in S-RM with different shapes, sizes, and distributions according to the characteristics of the rock blocks' size distribution. Based on the new improved technology, a software system named as R-SRM3 D for generation and visualization of S-RM is developed. Using R-SRM3 D, a three-dimensional meso-structural model of S-RM is generated and used to study the meso-mechanical behavior through a series of true-triaxial numerical tests. From the numerical tests, the following conclusions are obtained. The meso-stress field of S-RM is influenced by the distribution of the internal rock blocks, and the macro-mechanical characteristics of S-RM are anisotropic in 3D; the intermediate principal stress and the soil-rock interface properties have significant influence on the macro strength of S-RM.

OUTLIER TEST IN RANDOMIZED LINEAR MODEL

In this papert we give an approach for detecting one or more outliers inrandomized linear model.The likelihood ratio test statistic and its distributions underthe null hypothesis and the alternative hypothesis are given. Furthermore,the robustnessof the test statistic in a certain sense is proved. Finally,the optimality properties of thetest are derived.

TESTING FOR VARYING DISPERSION IN DISCRETE EXPONENTIAL FAMILY NONLINEAR MODELS

It is necessary to test for varying dispersion in generalized nonlinear models.Wei,et al(1998) developed a likelihood ratio test,a score test and their adjustments to test for varying dispersion in continuous exponential family nonlinear models.This type of problem in the framework of general discrete exponential family nonlinear models is discussed.Two types of varying dispersion,which are random coefficients model and random effects model,are proposed,and corresponding score test statistics are constructed and expressed in simple,easy to use,matrix formulas.

MLSI-RT: memorize LOS range measurements identified residual test location algorithm and performance analysis

The dominant error source of mobile terminal location in wireless sensor networks （WSNs） is the non-line-of-sight （NLOS） propagation error. Among the algorithms proposed to mitigate the influence of NLOS propagation error, residual test （RT） is an efficient one, however with high computational complexity （CC）. An improved algorithm that memorizes the light of sight （LOS） range measurements （RMs） identified memorize LOS range measurements identified residual test （MLSI-RT） is presented in this paper to address this problem. The MLSI-RT is based on the assumption that when all RMs are from LOS propagations, the normalized residual follows the central Chi-Square distribution while for NLOS cases it is non-central. This study can reduce the CC by more than 90%.

基于Test RT的嵌入式系统自动化测试

自动化测试在Agile开发过程中非常重要。但是在嵌入式系统中,自动化测试一直没有找到一种行之有效的方法,从而严重影响了软件质量和开发效率。本文提出了一种基于Test RT的自动化测试方案,描述了实施的技术细节并比较了与其他方案的优势,为Agile的广泛应用铺平了道路。

A recoverable stress testing algorithm for compression and encryption cards

This study proposes a recoverable stress testing algorithm （RSTA） for such special devices as compression/decompression card and encryption/deeryption card. It uses a chaos function to generate a random sequence, and then, according to the random sequence, generates an effective command sequence. The dispatch of command obeys a special schedule strategy we designed for such devices, i.e., the commands are sent according to the command sequence, and the complete commands are put in a buffer for further result check. RSTA is used to test the HIFN compression acceleration card SAICHI-1000. Test results show that RSTA can make the card work continuously and adequately.

Randomized trial estimating effects of hypnosis versus progressive muscle relaxation on medical students’test anxiety and attentional bias

BACKGROUND Test anxiety is prevalent among medical students and leads to impaired academic performance.Test-related attentional bias has been identified as an important maintaining factor in test-anxious individuals.AIM To evaluate whether hypnosis and progressive muscle relaxation(PMR)could modify medical college students’test anxiety and attentional bias.METHODS A total of 598 medical students were screened.The participants were divided into higher and lower test anxiety groups according to their scores on the test anxiety scale(TAS).Ninety medical college students with high TAS score were randomly assigned to a hypnosis or PMR group.Another 45 students with low TAS score were included,forming a baseline control group.The intervention was conducted weekly for 6 wk,and each session lasted approximately 30 min.The total intervention time and the number of intervention sessions for the hypnosis and PMR groups were equal.Data were collected at the pretest,posttest,and 2-mo follow-up.RESULTS Hypnosis group participants had a significantly lower TAS score at posttest(t=-21.827,P<0.001)and at follow-up(t=-14.824,P<0.001),compared to that at pretest.PMR group participants also had a significantly lower TAS score at posttest(t=-10.777,P<0.001)and at follow-up(t=-7.444,P<0.001),compared to that at pretest.At the posttest level,the hypnosis group had a significantly lower TAS score than the PMR group(t=-3.664,P<0.001).At the follow-up level,the hypnosis group also had a significantly lower TAS score than the PMR group(t=-2.943,P=0.004).Clinically significant improvement was found in both the hypnosis and PMR groups(hypnosis=64.0%;PMR=62.22%).Hypnosis was more effective than PMR in reducing test anxiety among medical college students.Hypnosis could modify attentional bias toward threatening stimuli,but PMR could not.CONCLUSION These results suggest that attentional bias plays an important role in test anxiety treatment.

Research on the Computer Network Protocol Test Model based on Genetic and Random Walk Algorithm

In this paper, we conduct research on the computer network protocol test model based on genetic and random walk algorithm.Network protocol is the abstract concept, is important in the process of the development of network system. Fully understand and grasp of thenetwork protocols for managers is there is a big diffi cult. Network covert channel is the evaluation of intrusion detection system and fi rewallsecurity performance of an important means, the paper will start from the angle of the attacker, the fl aws of the research, and use this kind ofdefect to realize network covert channel, the random walk algorithm will be feasible for dealing with this issue. For achieving this, we integratethe genetic and random walk algorithm for systematic optimization.

Use of Random Regression Test-Day Model to Estimate Genetic Parameters of Milk Yield in Holstein Cows

(Co) variance components and genetic parameters were estimated for milk yield of Iranian Holstein cows. A total number of 68,945 milk test-day records of first, second and third lactations of 8515 animals from 100 sires and 7743 dams originated from 34 herds collected during 2007 to 2009 by Iranian animal breeding center were used. The ASReml computer program was used to analyze the milk test-day records using the random regression procedure. Herd test date (HTD), milking times per day (milking frequency), number of lactations, year of birth, year of calving, age of animal at calving and days in milk (DIM) considered as fixed effects and additive genetic effects and animal permanent environmental effects were considered as the random effects. Additive genetic variance, animal permanent environment variance, residual variance, phenotypic variance, heritability and repeatability were estimated during different months of lactation between 5.7 - 19.6, 15.3 - 27.1, 31.4 - 17.2, 45.8 - 64.83, 0.1 - 0.32 and 0.4 - 0.6, respectively. Genetic correlation and phenotypic correlation were also estimated between months of lactation in range of -0.35 - 0.98 and 0.03 - 0.67, respectively. Genetic correlation and phenotypic correlation both showed the same changing pattern and they decreased as the interval between months of lactation increased.

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.

基于ART优化选择策略的遗传算法生成测试数据方法

测试数据自动生成方法是软件测试领域研究的热点。基于遗传算法的启发式搜索算法是一种路径覆盖生成测试数据的方法。文中提出了一种基于自适应随机测试(Adaptive Random Testing,ART)算法更新种群的方法,将ART融入遗传算法,优化选择操作,动态更新种群,从而增加种群进化过程中的个体多样性,提高了收敛速度,有效地减少了陷入局部最优。实验结果显示,与传统遗传算法生成测试数据的方法相比,改进的算法明显提高了路径覆盖率,减少了种群平均进化代数。

实时荧光定量RT-PCR在麻疹和风疹病毒检测中的应用

目的探讨实时荧光定量RT-PCR在麻疹和风疹病毒检测中的应用效果。方法选取2021年12月—2022年12月盘锦市疾病预防控制中心接收的麻疹与风疹患者76例为研究对象,入院后所有研究对象均接受酶联免疫吸附试验法和实时荧光定量RT-PCR法检测,以检测患者恢复期血免疫球蛋白G(IgG)抗体水平(相对急性期是否4倍升高)为麻疹诊断金标准,对比两种检测方法的检测准确率、不同检测时间的阳性检出率。结果实时荧光定量RT-PCR法总诊断准确率为97.37%;酶联免疫吸附试验法中总诊断准确率为88.16%,比较两种方法的诊断准确率差异有统计学意义(P<0.05)。第1d,实时荧光定量RT-PCR法阳性检出率高于酶联免疫吸附试验法,差异有统计学意义(P<0.05)。第5d,实时荧光定量RT-PCR法阳性检出率低于酶联免疫吸附试验法,差异有统计学意义(P<0.05)。第2d、第3d、第4d实时荧光定量RT-PCR法和酶联免疫吸附试验法阳性检出率对比差异无统计学意义(P>0.05)。结论实时荧光定量RT-PCR对麻疹、风疹检测有一定诊断作用,可以有效提高检测准确率,同时操作简单,灵敏性较高,值得在麻疹与风疹病毒检测中推广。