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This study aims to obtained the failure probability distributions of subsystems for industrial robot and filtrate its fault data considering the complicated influencing factors of failure rate for industrial robot and numerous epistemic uncertainties.

A fault data screening method and failure rate prediction framework are proposed to investigate industrial robot. First, the failure rate model of the industrial robot with different subsystems is established and then the surrogate model is used to fit bathtub curve of the original industrial robot to obtain the early fault time point. Furthermore, the distribution parameters of the original industrial robot are solved by maximum-likelihood function. Second, the influencing factors of the new industrial robot are quantified, and the epistemic uncertainties are refined using interval analytic hierarchy process method to obtain the correction coefficient of the failure rate.

The failure rate and mean time between failure (MTBF) of predicted new industrial robot are obtained, and the MTBF of predicted new industrial robot is improved compared with that of the original industrial robot.

Failure data of industrial robots is the basis of this prediction method, but it cannot be used for new or similar products, which is the limitation of this method. At the same time, based on the series characteristics of the industrial robot, it is not suitable for parallel or series-parallel systems.

This investigation has important guiding significance to maintenance strategy and spare parts quantity of industrial robot. In addition, this study is of great help to engineers and of great significance to increase the service life and reliability of industrial robots.

This investigation can improve MTBF and extend the service life of industrial robots; furthermore, this method can be applied to predict other mechanical products.

This method can complete the process of fitting, screening and refitting the fault data of the industrial robot, which provides a theoretic basis for reliability growth of the predicted new industrial robot. This investigation has significance to maintenance strategy and spare parts quantity of the industrial robot. Moreover, this method can also be applied to the prediction of other mechanical products.

The hydro-viscous drive (HVD) has been widely used in fan transmission in vehicles, fans, and scraper conveyors for step-less speed regulating and soft starting. It is an efficient method to save energy and reduce consumption. This study aims to analyze the influencing factors of oil film shear torque accurately.

The shear torque calculation model of double arc oil groove friction pairs was established. The influence of groove structure parameters on shear torque was analyzed. The interaction between viscosity temperature and shear torque was considered. Meanwhile, the equivalent radius was calculated when the rupture of oil film appeared. Finally, the test rig of torque characteristics was set up. The variance of shear torque with the input rotation speed under different oil film thickness, different oil temperature, and different flow rate was seen.

The results show that the shear torque increases with the growth of rotation speed. However, the increase of torque is quite gradual because of the effect of the change of viscosity, which is caused by the rise of temperature. The shear torque increases with the decrease of thickness, the increase of inlet flow rate, and the decrease of inlet oil temperature. Meanwhile, when the feeding flow rate is less than the theoretical, the oil film gets ruptured and the shear torque decreases sharply.

The influence on shear torque during full film shear stage in HVD can be achieved much more accurately through both experimental research and theoretical modeling in which groove parameters, influence of temperature, and oil film rupture are considered. Therefore, the shear torque of HVD can be predicted by theoretical model and experimental research in full film shear stage.

This paper aims to investigate whether close auditor-client relationships affect audit quality over the tenure of the audit partner and the potential role of partner rotation in mitigating this effect.

Using the Chinese mandatory audit partner rotation setting, the authors identify the existence of a close auditor-client relationship if the audit partner tenure with a client is larger than the audit firm tenure with that client. The sample period (1998–2009) is divided into voluntary and mandatory rotation periods when examining the effects of audit partner tenure on audit quality for the normal and close auditor-client relationship subsamples, respectively. The authors also conduct a propensity score matching analysis to address a selection issue.

The paper finds that under the voluntary partner rotation regime, audit quality decreases with audit partner tenure for the subsample with close auditor-client relationships, whereas this effect is not shown in the normal relationship subsample. However, audit quality no longer declines with audit partner tenure under the mandatory partner rotation regime.

This is the first study that directly examines the effect of audit partner tenure on audit quality associated with close auditor-client relationships under the voluntary and mandatory partner rotation regimes.

China’s swift economic rise, as symbolized by the first Chinese Olympics and by surpassing Japan to become the world’s second largest economy despite the recent global financial meltdown, has been accompanied by a transformation of Chinese foreign policy behavior. After spending the last decade emphasizing China’s “peaceful rise” or “peaceful development,” Beijing has begun to expound its policy preferences and territorial claims more forthrightly, even assertively. The purpose of this chapter will be to consider the origins, consequences, and likely future of the new Chinese foreign policy in the wake of the leadership transition at the 18th Party Congress in 2012 and the 12th National People’s Congress in 2013.

This paper aims to extract the comment targets in Chinese online shopping platform.

The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment.

The extracting comment target method the authors proposed in this paper is effective.

First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information.

Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients.

The extracting comment target method the authors proposed in this paper is effective.

This paper is focused at studying the current state of research involving the four dimensions of defect management strategy, i.e. software defect analysis, software quality, software reliability and software development cost/effort.

The methodology developed by Kitchenham (2007) is followed in planning, conducting and reporting of the systematic review. Out of 625 research papers, nearly 100 primary studies related to our research domain are considered. The study attempted to find the various techniques, metrics, data sets and performance validation measures used by researchers.

The study revealed the need for integrating the four dimensions of defect management and studying its effect on software performance. This integrated approach can lead to optimal use of resources in software development process.

There are many dimensions in defect management studies. The authors have considered only vital few based on the practical experiences of software engineers. Most of the research work cited in this review used public data repositories to validate their methodology and there is a need to apply these research methods on real datasets from industry to realize the actual potential of these techniques.

The authors believe that this paper provides a comprehensive insight into the various aspects of state-of-the-art research in software defect management. The authors feel that this is the only research article that delves into the four facets namely software defect analysis, software quality, software reliability and software development cost/effort.