Robustness testing for safety-critical embedded software is still a challenge in its nascent stages. In this paper, we propose a practical methodology and implement an environment by employing model-based robustness t...Robustness testing for safety-critical embedded software is still a challenge in its nascent stages. In this paper, we propose a practical methodology and implement an environment by employing model-based robustness testing for embedded software systems. It is a system-level black-box testing approach in which the fault behaviors of embedded software is triggered with the aid of modelbased fault injection by the support of an executable model-driven hardware-in-loop （HIL） testing environment. The prototype implementation of the robustness testing environment based on the proposed approach is experimentally discussed and illustrated by industrial case studies based on several avionics-embedded software systems. The results show that our proposed and implemented robustness testing method and environment are effective to find more bugs, and reduce burdens of testing engineers to enhance efficiency of testing tasks, especially for testing complex embedded systems.展开更多
This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption,in which the predictive variable is persistent and its innovations are highly...This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption,in which the predictive variable is persistent and its innovations are highly correlated with returns.To this end,we propose a robust test which can capture empirical phenomena such as heavy tails,stationary,and local to unity.Moreover,we develop related asymptotic results without the second-moment assumption between the predictive variable and returns.To make the proposed test reasonable,we propose a generalized correlation and provide theoretical support.To illustrate the applicability of the test,we perform a simulation study for the impact of heavy-tailed innovations on predictability,as well as direct and/or indirect implementation of heavy-tailed innovations to predictability via the unit root phenomenon.Finally,we provide an empirical study for further illustration,to which the proposed test is applied to a U.S.equity data set.展开更多
The protocol testing technology used in the next generation Internet should satisfy some new challenges and requirements. This paper focuses on the test suite description and test implementation techniques. TTCN-3 is ...The protocol testing technology used in the next generation Internet should satisfy some new challenges and requirements. This paper focuses on the test suite description and test implementation techniques. TTCN-3 is chosen as the test suite description language and extended in both syntax and semantics to satisfy the requirements of protocol robustness testing. PITSv3, a protocol integrated testing system based on TTCN-3, is developed, and the extensions for robustness testing are implemented. Finally, two practical test applications are presented.展开更多
Covariate-adaptive randomisation has a long history of applications in clinical trials. Shao, Yu,and Zhong [(2010). A theory for testing hypotheses under covariate-adaptive randomization.Biometrika, 97, 347–360] and ...Covariate-adaptive randomisation has a long history of applications in clinical trials. Shao, Yu,and Zhong [(2010). A theory for testing hypotheses under covariate-adaptive randomization.Biometrika, 97, 347–360] and Shao and Yu [(2013). Validity of tests under covariate-adaptivebiased coin randomization and generalized linear models. Biometrics, 69, 960–969] showed thatthe simple t-test is conservative under covariate-adaptive biased coin (CABC) randomisation interms of type I error, and proposed a valid test using the bootstrap. Under a general additivemodel with CABC randomisation, we construct a calibrated t-test that shares the same propertyas the bootstrap method in Shao et al. (2010), but do not need large computation required by thebootstrap method. Some simulation results are presented to show the finite sample performanceof the calibrated t-test.展开更多
In this paper, we address an open problem raised by Levy(2009) regarding the design of a binary minimax test without the symmetry assumption on the nominal conditional probability densities of observations. In the bin...In this paper, we address an open problem raised by Levy(2009) regarding the design of a binary minimax test without the symmetry assumption on the nominal conditional probability densities of observations. In the binary minimax test, the nominal likelihood ratio is a monotonically increasing function and the probability densities of the observations are located in neighborhoods characterized by placing a bound on the relative entropy between the actual and nominal densities. The general minimax testing problem at hand is an infinite-dimensional optimization problem, which is quite difficult to solve. In this paper, we prove that the complicated minimax testing problem can be substantially reduced to solve a nonlinear system of two equations having only two unknown variables, which provides an efficient numerical solution.展开更多
In this paper,we propose a class of robust independence tests for two random vectors based on weighted integrals of empirical characteristic functions.By letting weight functions be probability density functions of a ...In this paper,we propose a class of robust independence tests for two random vectors based on weighted integrals of empirical characteristic functions.By letting weight functions be probability density functions of a class of special distributions,the proposed test statistics have simple closed forms and do not require moment conditions on the random vectors.Moreover,we derive the asymptotic distributions of the test statistics under the null hypothesis.The proposed testing method is computationally feasible and easy to implement.Based on a data-driven bandwidth selection method,Monte Carlo simulation studies indicate that our tests have a relatively good performance compared with the competitors.A real data example is also presented to illustrate the application of our tests.展开更多
This paper describes a brain-inspired simultaneous localization and mapping （SLAM） system using oriented features from accelerated segment test and rotated binary robust independent elementary （ORB） features of R...This paper describes a brain-inspired simultaneous localization and mapping （SLAM） system using oriented features from accelerated segment test and rotated binary robust independent elementary （ORB） features of RGB （red, green, blue） sensor for a mobile robot. The core SLAM system, dubbed RatSLAM, can construct a cognitive map using information of raw odometry and visual scenes in the path traveled. Different from existing RatSLAM system which only uses a simple vector to represent features of visual image, in this paper, we employ an efficient and very fast descriptor method, called ORB, to extract features from RCB images. Experiments show that these features are suitable to recognize the sequences of familiar visual scenes. Thus, while loop closure errors are detected, the descriptive features will help to modify the pose estimation by driving loop closure and localization in a map correction algorithm. Efficiency and robustness of our method are also demonstrated by comparing with different visual processing algorithms.展开更多
This paper aims to develop a new robust U-type test for high dimensional regression coefficients using the estimated U-statistic of order two and refitted cross-validation error variance estimation. It is proved that ...This paper aims to develop a new robust U-type test for high dimensional regression coefficients using the estimated U-statistic of order two and refitted cross-validation error variance estimation. It is proved that the limiting null distribution of the proposed new test is normal under two kinds of ordinary models.We further study the local power of the proposed test and compare with other competitive tests for high dimensional data. The idea of refitted cross-validation approach is utilized to reduce the bias of sample variance in the estimation of the test statistic. Our theoretical results indicate that the proposed test can have even more substantial power gain than the test by Zhong and Chen(2011) when testing a hypothesis with outlying observations and heavy tailed distributions. We assess the finite-sample performance of the proposed test by examining its size and power via Monte Carlo studies. We also illustrate the application of the proposed test by an empirical analysis of a real data example.展开更多
基金the Aeronautics Science Foundation of China(No.2011ZD51055)Science and Technology on Reliability&Environmental Engineering Laboratory(No.302367)the National Pre-Research Foundation of China(No.51319080201)
文摘Robustness testing for safety-critical embedded software is still a challenge in its nascent stages. In this paper, we propose a practical methodology and implement an environment by employing model-based robustness testing for embedded software systems. It is a system-level black-box testing approach in which the fault behaviors of embedded software is triggered with the aid of modelbased fault injection by the support of an executable model-driven hardware-in-loop （HIL） testing environment. The prototype implementation of the robustness testing environment based on the proposed approach is experimentally discussed and illustrated by industrial case studies based on several avionics-embedded software systems. The results show that our proposed and implemented robustness testing method and environment are effective to find more bugs, and reduce burdens of testing engineers to enhance efficiency of testing tasks, especially for testing complex embedded systems.
基金The research of WONG Hsin-Chieh is partially supported by the NSTC(111-2118-M-305-004-MY2)the research of PANG Tian-xiao is partially supported by the National Social Science Foundation of China(21BTJ067)。
文摘This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption,in which the predictive variable is persistent and its innovations are highly correlated with returns.To this end,we propose a robust test which can capture empirical phenomena such as heavy tails,stationary,and local to unity.Moreover,we develop related asymptotic results without the second-moment assumption between the predictive variable and returns.To make the proposed test reasonable,we propose a generalized correlation and provide theoretical support.To illustrate the applicability of the test,we perform a simulation study for the impact of heavy-tailed innovations on predictability,as well as direct and/or indirect implementation of heavy-tailed innovations to predictability via the unit root phenomenon.Finally,we provide an empirical study for further illustration,to which the proposed test is applied to a U.S.equity data set.
基金the National Basic Research Program of China (973 Program) (Grant No. 2003CB314801)the National Natural Science Foundation of China (Grant No. 60572082)
文摘The protocol testing technology used in the next generation Internet should satisfy some new challenges and requirements. This paper focuses on the test suite description and test implementation techniques. TTCN-3 is chosen as the test suite description language and extended in both syntax and semantics to satisfy the requirements of protocol robustness testing. PITSv3, a protocol integrated testing system based on TTCN-3, is developed, and the extensions for robustness testing are implemented. Finally, two practical test applications are presented.
文摘Covariate-adaptive randomisation has a long history of applications in clinical trials. Shao, Yu,and Zhong [(2010). A theory for testing hypotheses under covariate-adaptive randomization.Biometrika, 97, 347–360] and Shao and Yu [(2013). Validity of tests under covariate-adaptivebiased coin randomization and generalized linear models. Biometrics, 69, 960–969] showed thatthe simple t-test is conservative under covariate-adaptive biased coin (CABC) randomisation interms of type I error, and proposed a valid test using the bootstrap. Under a general additivemodel with CABC randomisation, we construct a calibrated t-test that shares the same propertyas the bootstrap method in Shao et al. (2010), but do not need large computation required by thebootstrap method. Some simulation results are presented to show the finite sample performanceof the calibrated t-test.
基金supported by National Natural Science Foundation of China(Grant Nos.61473197,61671411 and 61273074)Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT 16R53)Program for Thousand Talents(Grant Nos.2082204194120 and 0082204151008)
文摘In this paper, we address an open problem raised by Levy(2009) regarding the design of a binary minimax test without the symmetry assumption on the nominal conditional probability densities of observations. In the binary minimax test, the nominal likelihood ratio is a monotonically increasing function and the probability densities of the observations are located in neighborhoods characterized by placing a bound on the relative entropy between the actual and nominal densities. The general minimax testing problem at hand is an infinite-dimensional optimization problem, which is quite difficult to solve. In this paper, we prove that the complicated minimax testing problem can be substantially reduced to solve a nonlinear system of two equations having only two unknown variables, which provides an efficient numerical solution.
基金supported by National Natural Science Foundation of China(NNSFC)(Grant No.12201317)China Postdoctoral Science Foundation(Grant No.2022M721716),Changliang Zou’s research was supported by the National Key R&D Program of China(Grant Nos.2022YFA1003703,2022YFA1003800)+1 种基金the National Natural Science Foundation of China(Grant Nos.11925106,12231011,11931001,12226007,12326325)Cui’s research was supported by NNSFC(Grant Nos.12031016 and 11971324)。
文摘In this paper,we propose a class of robust independence tests for two random vectors based on weighted integrals of empirical characteristic functions.By letting weight functions be probability density functions of a class of special distributions,the proposed test statistics have simple closed forms and do not require moment conditions on the random vectors.Moreover,we derive the asymptotic distributions of the test statistics under the null hypothesis.The proposed testing method is computationally feasible and easy to implement.Based on a data-driven bandwidth selection method,Monte Carlo simulation studies indicate that our tests have a relatively good performance compared with the competitors.A real data example is also presented to illustrate the application of our tests.
基金supported by National Natural Science Foundation of China(No.61673283)
文摘This paper describes a brain-inspired simultaneous localization and mapping （SLAM） system using oriented features from accelerated segment test and rotated binary robust independent elementary （ORB） features of RGB （red, green, blue） sensor for a mobile robot. The core SLAM system, dubbed RatSLAM, can construct a cognitive map using information of raw odometry and visual scenes in the path traveled. Different from existing RatSLAM system which only uses a simple vector to represent features of visual image, in this paper, we employ an efficient and very fast descriptor method, called ORB, to extract features from RCB images. Experiments show that these features are suitable to recognize the sequences of familiar visual scenes. Thus, while loop closure errors are detected, the descriptive features will help to modify the pose estimation by driving loop closure and localization in a map correction algorithm. Efficiency and robustness of our method are also demonstrated by comparing with different visual processing algorithms.
基金supported by National Natural Science Foundation of China (Grant Nos. 11071022, 11231010 and 11471223)Beijing Center for Mathematics and Information Interdisciplinary ScienceKey Project of Beijing Municipal Educational Commission (Grant No. KZ201410028030)
文摘This paper aims to develop a new robust U-type test for high dimensional regression coefficients using the estimated U-statistic of order two and refitted cross-validation error variance estimation. It is proved that the limiting null distribution of the proposed new test is normal under two kinds of ordinary models.We further study the local power of the proposed test and compare with other competitive tests for high dimensional data. The idea of refitted cross-validation approach is utilized to reduce the bias of sample variance in the estimation of the test statistic. Our theoretical results indicate that the proposed test can have even more substantial power gain than the test by Zhong and Chen(2011) when testing a hypothesis with outlying observations and heavy tailed distributions. We assess the finite-sample performance of the proposed test by examining its size and power via Monte Carlo studies. We also illustrate the application of the proposed test by an empirical analysis of a real data example.
