Bayesian sequential testing for exponential life system with reliability growth

A Bayesian sequential testing method is proposed to evaluate system reliability index with reliability growth during development.The method develops a reliability growth model of repairable systems for failure censored test,and figures out the approach to determine the prior distribution of the system failure rate by applying the reliability growth model to incorporate the multistage test data collected from system development.Furthermore,the procedure for the Bayesian sequential testing is derived for the failure rate of the exponential life system,which enables the decision to terminate or continue development test.Finally,a numerical example is given to illustrate the efficiency of the proposed model and procedure.

Optimization of dynamic sequential test strategy for equipment health management

Testing is the premise and foundation of realizing equipment health management （EHM）. To address the problem that the static periodic test strategy may cause deficient test or excessive test, a dynamic sequential test strategy （DSTS） for EHM is presented. Considering the situation that equipment health state is not completely observable in reality, a DSTS optimization method based on partially observable semi-Markov decision pro- cess （POSMDP） is proposed. Firstly, an equipment health state degradation model is constructed by Markov process, and the control limit maintenance policy is also introduced. Secondly, POSMDP is formulated in great detail. And then, POSMDP is converted to completely observable belief semi-Markov decision process （BSMDP） through belief state. The optimal equation and the corresponding optimal DSTS, which minimize the long-run ex- pected average cost per unit time, are obtained with BSMDP. The results of application in complex equipment show that the proposed DSTS is feasible and effective.

A SEQUENTIAL TESTING PROGRAM FOR PREDICTING AND IDENTIFICATING CARCINOGENS AND ITS APPLICATION

In this paper our studies about the sequential testing program for predicting and identificating carcinogens, sequential discriminant method and cost- effectiveness analysis are summarized. The analysis of our database of carcinogeniclty and genotoxicity of chemicals demonstrates the uncertainty . of short- term tests ( STTs ) to predict carcinogens and the results of most routine STTs are statistically dependent. We recommend the sequential testing program combining STTs and carclnogenicity assay, the optimal STT batteries, the rules of the sequential discrimination and the preferal choices of STTs tor specific chemical class. For illustrative pmposes the carclnogenicity prediction of several sample chamicals is presented. The results of cost-effectiveness analysis suggest that this program has vast social-economic effectiveness.

Sequential experimental observation on the curative effect of Yingbupu decoction of Zhuang medicine on stage I and II acute kidney injury

Objective:To observe the clinical efficacy of the Zhuang medicine Yingbupu decoction on stage I and II acute kidney injury through sequential test.Methods:The open one-way qualitative response sequential design of experiments was adopted,and the patients with AKI in phase I and II who met the inclusion criteria were divided into the treatment group and the control group according to the order of hospitalization by random number table.On the basis of basic treatment,the treatment group was treated with Zhuang medicine Yingbupu decoction,and the control group was treated with Jinshuibao tablet.The clinical efficacy,TCM syndrome score,24 h urine volume,serum creatinine(Scr),microalbumin in urine(mAlb),neutrophil Gelatinase related lipid delivery albumin(NGAL)of the two groups were compared,and the adverse reactions and complications of the two groups were observed.Results:After 14 d of treatment,when the treatment group reached the 10th case,the experimental line contacted the upper bound U-line and reached the experimental standard to terminate the experiment.The effective hypothesis was accepted,and it was believed that the Zhuang medicine Yingbupu decoction had a therapeutic effect on stage I and II AKI.The conclusion was drawn that the treatment group received the Zhuang medicine Yingbupu.The clinical effective rate and improvement days were similar between the two groups,and there was no significant difference(P>0.05).However,the integral value of traditional Chinese medicine syndrome in the treatment group was lower than that in the control group(P<0.05),After treatment,the Scr,mAlb,and NGAL levels of patients in both groups were lower than before treatment(P<0.05).After treatment,the Scr,mAlb,and NGAL values in the treatment group were significantly lower than those in the control group(P<0.05).After treatment,the 24-hour urine volume in both groups was higher than that before treatment,and the values in the treatment group were significantly higher than those in the control group(P<0.05).During the treatment period,there were no significant adverse reactions or complications in either group.Conclusion:The Zhuang medicine Yingbupu decoction is effective in treating stage I and II AKI,and the Zhuang medicine Yingbupu can significantly improve the symptoms and quality of life of patients with stage I and II AKI.Its improvement of renal function is better than that of Jinshuibao tablets,and its safety is good.

Incorporating Uncertain Costs within a Series of Sequential Probability Ratio Tests

We consider an extension to Sequential Probability Ratio Tests for when we have uncertain costs, but also opportunity to learn about these in an adaptive manner. In doing so we demonstrate the effects that allowing uncertainty has on observation cost, and the costs associated with Type I and Type II error. The value of information relating to modelled uncertainties is derived and the case of statistical dependence between the parameter affecting decision outcome and the parameter affecting unknown cost is also examined. Numerical examples of the derived theory are provided, along with a simulation comparing this adaptive learning framework to the classical one.

Fast nuclide identification based on a sequential Bayesian method

The rapid identification of radioactive substances in public areas is crucial.However,traditional nuclide identification methods only consider information regarding the full energy peaks of the gamma-ray spectrum and require long recording times,which lead to long response times.In this paper,a novel identification method using the event mode sequence(EMS)information of target radionuclides is proposed.The EMS of a target radionuclide and natural background radiation were established as two different probabilistic models and a decision function based on Bayesian inference and sequential testing was constructed.The proposed detection scheme individually processes each photon.When a photon is detected and accepted,the corresponding posterior probability distribution parameters are estimated using Bayesian inference and the decision function is updated.Then,value of the decision function is compared to preset detection thresholds to obtain a detection result.Experiments on different target radionuclides(137Cs and 60Co)were performed.The count rates of the regions of interest(ROI)in the backgrounds between[651,671],[1154,1186],and[1310,1350]keV were 2.35,5.14,and 0.57 CPS,respectively.The experimental results demonstrate that the average detection time was 6.0 s for 60Co(with an activity of 80400 Bq)at a distance of 60 cm from the detector.The average detection time was 7 s for 137Cs(with an activity of 131000 Bq)at a distance of 90 cm from the detector.The results demonstrate that the proposed method can detect radioactive substances with low activity.

Sequential Detection of Digital Watermarking

The paper analyzed a new watermarking detection paradigm including double detection thresholds based on sequential hypothesis testing. A joint design of watermarking encoding and detection was proposed. The paradigm had good immunity to noisy signal attacks and high detection probability. Many experiments proved that the above algorithm can detect watermarks about 66% faster than popular detectors, which could have significant impact on many applications such as video watermarking detection and watermark-searching in a large database of digital contents.

Study on fault locating technology for satellite power system

It is currently prevalent to locate faults for a satellite power system based on an expert system, not utilizing all the available information provided by tests. The casual network model for a satellite power system is presented. Considerations for failure probability of each component of the power system, the cost of applying each test, the influence of a precedent test result on the next test selection, and an optimal sequential testing algorithm for fault location is presented. This program is applied to locate the failure component of the power system of a satellite. The results show this program is very effective and it is very fast to generate an optimal diagnosis tree.

Multiple hypothesis tracking based on the Shiryayev sequential probability ratio test

To date, Wald sequential probability ratio test(WSPRT) has been widely applied to track management of multiple hypothesis tracking(MHT). But in a real situation, if the false alarm spatial density is much larger than the new target spatial density, the original track score will be very close to the deletion threshold of the WSPRT. Consequently, all tracks, including target tracks, may easily be deleted, which means that the tracking performance is sensitive to the tracking environment. Meanwhile, if a target exists for a long time, its track will have a high score, which will make the track survive for a long time even after the target has disappeared. In this paper, to consider the relationship between the hypotheses of the test, we adopt the Shiryayev SPRT(SSPRT) for track management in MHT. By introducing a hypothesis transition probability, the original track score can increase faster, which solves the first problem. In addition, by setting an independent SSPRT for track deletion, the track score can decrease faster, which solves the second problem. The simulation results show that the proposed SSPRT-based MHT can achieve better tracking performance than MHT based on the WSPRT under a high false alarm spatial density.

IEC 62059 Standards' Application in Reliability Prediction and Verification of Smart Meters

This article introduces the current situation of the smart then describes the relationship of meter reliability characteristics meter＇s reliability and the failure mechanisms at first, and combined with its Bathtub Curve. It also introduces both the feasible failure tree model for meter lifecycle prediction based on actual experiences and meter reliability prediction methodology by SN 29500 norms based on this model. This article also brings forward that it is necessary that the ＂Learning Factor＂ shall be adopted in meter reliability prediction for new materials, new process, and customized parts by referring to GJB/Z299C. Thereafter, this article also tries to apply IEC 62059 and JB/T 50070 to introduce the feasible method for the lifecycle prediction result verification by accelerated lifecycle test. Furthermore, the article also explores ways to increase the firmware reliability in smart meter.

Self-adapting RF Stealth Signal Design Method in RATR

Combining the mutual information theory and the sequential hypothesis testing(SHT)method,a selfadapting radio frequency(RF)stealth signal design method is proposed. The channel information is gained through the radar echo and feeds back to the radar system,and then the radar system adaptively designs the transmission waveform. So the close-loop system is formed. The correlations between these transmission waveforms are decreased because of the adaptive change of these transmission waveforms,and the number of illuminations is reduced for adopting the SHT,which lowers the transmission power of the radar system. The radar system using the new method possesses the RF stealth performance. Aiming at the application of radar automatic target recognition(RATR),experimental simulations show the effectiveness and feasibility of the proposed method.

Test sequencing problem arising at the design stage for reducing life cycle cost

Previous test sequencing algorithms only consider the execution cost of a test at the application stage. Due to the fact that the placement cost of some tests at the design stage is considerably high compared with the execution cost, the sequential diagnosis strategy obtained by previous methods is actually not optimal from the view of life cycle. In this paper, the test sequencing problem based on life cycle cost is presented. It is formulated as an optimization problem, which is non-deterministic polynomial-time hard （NP-hard）. An algorithm and a strategy to improve its computational efficiency are proposed. The formulation and algorithms are tested on various simulated systems and comparisons are made with the extant test sequencing methods. Application on a pump rotational speed control （PRSC） system of a spacecraft is studied in detail. Both the simulation results and the real-world case application results suggest that the solution proposed in this paper can significantly reduce the life cycle cost of a sequential fault diagnosis strategy.

CHAITIN COMPLEXITY,SHANNON INFORMATION CONTENT OF A SINGLE EVENT AND INFINITE RANDOM SEQUENCES(Ⅰ)

<正> Based on program-size complexity, a logical basis for information theory and probabilitytheory has been proposed by A. N. Kolmogorov. The aim of this paper is to furtherstrengthen this logical basis and make it more perfect. First, for the general case of com-putable probability distributions. sufficient and necessary conditions are given for an infinitesequence x∈A~∞ to be a Martin-lof (M. L.) infinite random sequence of a computable proba-bility distribution. These sufficient and necessary conditions give a complexity-baseddefinition of an infinite random sequence which is equivalent to P. Martin-lof’s statisticaldefinition of the concept of randomness. Consequently, a common complexity-based theoryof finite and infinite random sequences is established. Finally, inequalities between Chaitincomplexity and Shannon information content of a single event are given, and asymptoticallyequivalent relationships between them are also presented.

Application of Analytic Redundancy-based Fault Diagnosis of Sensors to Onboard Maintenance System

Analytic redundancy-based fault diagnosis technique （ARFDT） is applied to onboard maintenance system （OMS）. The principle of the proposed ARFDT scheme is to design a redundancy configuration using ARFDT to enhance the functions of redundancy management and built in test equipment （BITE） monitor. Redundancy configuration for dual-redundancy and analytic redundancy is proposed, in which, the fault diagnosis includes detection and isolation. In order to keep the balance between rapid diagnosis and binary hypothesis, a filter together with an elapsed time limit is designed for sequential probability ratio test （SPRT） in the process of isolation. Diagnosis results would be submitted to central maintenance computer （CMC） together with BITE information. Moreover, by adopting reconstruction, the designed method not only provides analytic redundancy to help redundancy management, but also compensates the output when both of the sensors of the same type are faulty. Our scheme is applied to an aircraft’s sensors in a simulation experiment, and the results show that the proposed filter SPRT （FSPRT） saves at least 50% of isolation time than Wald SPRT （WSPRT）. Also, effectiveness, practicability and rapidity of the proposed scheme can be successfully achieved in OMS.

Utilizing Probabilistic Linear Equations in Cube Attacks

Cube attacks, proposed by Dinur and Shamir at EUROCRYPT 2009, have shown huge power against stream ciphers. In the original cube attacks, a linear system of secret key bits is exploited for key recovery attacks. However, we find a number of equations claimed linear in previous literature actually nonlinear and not fit into the theoretical framework of cube attacks. Moreover, cube attacks are hard to apply if linear equations are rare. Therefore, it is of significance to make use of probabilistic linear equations, namely nonlinear superpolys that can be approximated by linear expressions effectively. In this paper, we suggest a way to test out and utilize these probabilistic linear equations, thus extending cube attacks to a wider scope. Concretely, we employ the standard parameter estimation approach and the sequential probability ratio test （SPRT） for linearity test in the preprocessing phase, and use maximum likelihood decoding （MLD） for solving the probabilistic linear equations in the online phase. As an application, we exhibit our new attack against 672 rounds of Trivium and reduce the number of key bits to search by 7.