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.

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.

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.

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)).

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 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）.

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.

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.

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.

考虑节点刚度随机性的焊接钢筋部品变形计算方法研究

为量化钢筋部品刚度,从受力机理角度出发,基于试验和理论分析,提出考虑刚度随机性的焊接钢筋部品变形计算方法。从受力机理的角度提出三向转动刚度独立力学求解模型,考虑钢筋直径的影响,设计了105组T形焊接钢筋试件及两类加载固定试验装置,开展分级加载试验;在此基础上,考虑焊接节点转动刚度随机性,提出基于蒙特卡洛随机抽样的焊接钢筋部品变形计算方法,并分别开展了6个焊接钢筋网片和6个钢筋块体试验进行验证。结果表明:钢筋焊接节点刚度与钢筋直径有关,当焊接条件相同时,钢筋直径越大,焊接节点刚度越大;同一钢筋直径组合的焊接节点转动刚度基本符合正态分布,3个方向的转动刚度R x>R z>R y;钢筋焊接节点刚度与焊接节点断面面积基本呈线性关系;竖筋和横筋连接节点刚度对钢筋部品变形影响显著,所采用的节点刚度取值方法计算的焊接钢筋部品变形偏差均在10%以内,与传统刚接和铰接方法相比,变形计算精度大幅提高,变形计算方法合理。

基于最小故障的充电桩检测策略构建方法研究

随机测试是发现和分析充电桩故障的重要手段,针对充电桩系统故障频繁发生,文中提出一种充电桩检测策略生成方法,利用测试过程的马尔可夫性将测试顺序建模为马氏链决定的随机变量。通过对转移顺序进行Gibbs随机采样建立马氏链以得到固有的最小故障,利用公共子串搜索方法来统计最小故障信息,并按照可疑程度将最小故障重新注入到测试策略中,以达到提高测试策略质量和降低测试策略数量的目的。以实测结果对基于最小故障的测试策略有效性进行了验证。所提方法有助于确定共性故障原因,对于减少充电桩故障带来的风险具有重要的指导意义。

空间管路结构振动控制技术研究

飞行器在服役过程中,管路结构会产生大量级振动响应,严重时会发生断裂失效。振动控制是延缓管路结构失效,提升可靠性的主要途径。本文通过边界简化及焊接部位建模,建立了复杂空间三维管路结构动力学模型,模态仿真结果与试验模态结果对比最大误差小于3%。在此基础上,使用金属减振器进行振动控制。通过计算,获得随机振动载荷下使用金属减振器前后空间管路结构的减振效率为8.46%;通过试验获得金属减振器实际的减振效率达到14.26%。本文计算和试验结果表明使用金属减振器能够显著降低复杂空间管路结构的振动响应。

连续振动载荷在线复现控制技术研究

提出一种主从分布式振动试验方法,建立了连续振动载荷在线复现控制技术,研制了系统样机。其中,提出一种信号分帧处理与重构技术,解决了长时连续振动载荷的在线波形复现难题;提出一种基于多量级样本库构建与加权平均的传递函数动态估计方法,抑制了系统非线性对控制精度的影响;采用谱误差反馈修正方法,改善了系统的频域控制精度。开展了“1主2从”联台试验,结果表明:时域和频域控制精度良好,整体延迟时间在亚秒量级,全程总均方根值误差在1%以内,为主从分布式振动试验提供了关键技术支撑。

基于载荷谱的电池包疲劳试验与计算方法

电池包作为电动汽车的核心部件之一,对电动汽车的整车性能有着关键性的影响。而在电动汽车的运行过程中,电池包会不断受到来自路面的持续性冲击力,造成电池包的疲劳损坏,对驾驶员和乘客的安全以及整车性能造成一定的影响。本文以电动汽车电池包为研究对象,建立了电池包随机振动试验方法与疲劳寿命的计算方法。先对振动台、工装夹具和电池包进行扫频分析,得到振动台台面、夹具空载端板、电池包与工装夹具连接端板处的加速度传感器的测量数值与输入扫频加速度值保持一致,验证振动信号的有效传递,确保输入的振动信号能够准确传递至电池包,然后开展电池包随机振动试验。并对电池包进行了电芯性能检测、气密性检查、绝缘电阻检查和共振频率检查,得出电池包的损伤部位。研究了电池包疲劳损伤计算方法,对电池箱、电池模组和电池包内各连接方式进行了精细化建模。基于精细化模型,进行了电池包频响特性的计算。基于计算得到的频响特性和实车路谱采集试验得到电池包随机振动载荷谱曲线,采用Goodman疲劳寿命估算方法和Miner线性累积损伤法则,并结合电池包材料S-N曲线,对电池包进行了随机振动疲劳损伤分析。试验得到的电池包结构损伤部位与分析得到的失效部位具有较好的一致性,证实了本文提出的疲劳损伤计算方法的准确性。

随机样本数据的概率表征方法

本文通过算例分析了参数概率表征方法的适用性和有效性.对于非参数概率密度估计,介绍了几种拟合变量概率密度函数的方法,通过算例对比了不同方法的拟合效果.

肌钙蛋白即时检验在急性冠状动脉综合征疑似患者院前急救中的应用

目的探讨疑似急性冠状动脉综合征(ACS)在院前急救车上应用即时检验(POCT)检测肌钙蛋白Ⅰ(cTnⅠ)的优势及可行性分析。方法将2019年5月—2020年5月北京急救中心院前接诊的60例疑似急性冠状动脉综合征(ACS)患者,通过现场抽签的方式随机分为试验组30例和对照组30例,对照组常规收集患者病史资料、进行体格检查和心电图测量,试验组在对照组基础上增加POCT检测cTnⅠ,比较两组患者急诊停留时间(EDLOS)、从首次医疗救治(FMC)到接受血运重建时间、出院45 d不良心血管事件发生率。结果试验组EDLOS较对照组更短(P<0.05),试验组从FMC到接受血运重建时间较对照组更短(P<0.05),试验组出院45 d不良心血管事件发生率较对照组更低(P<0.05)。结论院前应用POCT检测cTnⅠ能够缩短疑似ACS患者的EDLOS、缩短从FMC到接受血运重建时间、降低出院45 d不良心血管事件的发生率,对院前疑似ACS患者的早期诊断及预后具有一定的临床参考价值。

随机振动加速度响应谱及与冲击等效性分析

目的 获得随机振动的加速度响应谱,提升随机振动与冲击的等效性分析精度。方法 首先,基于维纳-辛钦定理,推导单自由度系统在随机振动基础激励作用下加速度响应均方值的通用表达式;其次,分别推导单自由度系统在理想白噪声和限带非均匀谱随机振动基础激励作用下的加速度响应均方值;再次,基于3σ准则,推导限带非均匀谱随机振动的3σ加速度响应谱;最后,基于加速度响应等效,通过将装备随机振动条件的3σ加速度响应谱与冲击条件的冲击响应谱进行等效性分析,对GJB 150.18A—2009中的冲击试验剪裁条件进行精细优化。结果 精细优化后,可有效改善冲击试验剪裁条件的工程实施精度。结论 获得了限带非均匀谱随机振动的3σ加速度响应谱,并基于此对GJB 150.18A—2009中的冲击试验剪裁条件进行了精细优化,对于装备合理剪裁冲击试验具有借鉴意义。