一种分布式可持续集成自动化测试平台

软件开发过程中,随着逻辑复杂度的不断增加,专门的测试可以有效地减少软件的bug,提高软件的质量,然而传统的人工测试已经不能满足当前软件开发的需求。为此,提出一种分布式可持续集成的自动化测试平台,基于Jenkins平台实现分布式可持续集成,选用Git作为版本管理工具,使用Katalon作为自动化测试工具。平台实现对Web软件每日自动更新并持续集成自动化测试,该平台在Web软件测试中大大地减少了测试人员重复回归测试的工作量。     

Comparison of multivariate statistical methods for dynamic systems modeling

In this paper two multivariate statistical methodologies are compared in order to estimate a multi‐input multi‐output transfer function model in an industrial polymerization process. In these contexts, process variables are usually autocorrelated (i.e. there is time‐dependence between observations), posing some problems to classical linear regression models. The two methodologies to be compared are both related to the analyses of multivariate time series: Box‐Jenkins methodology and partial least squares time series. Both methodologies are compared keeping in mind different issues, such as the simplicity of the process modeling (i.e. the steps of the identification, estimation and validation of the model), the usefulness of the graphical tools, the goodness of fit, and the parsimony of the estimated models. Real data from a polymerization process are used to illustrate the performance of the methodologies under study. Copyright © 2010 John Wiley & Sons, Ltd.     

Dynamic analysis of a rigid rotor supported by three-pad hydrostatic squeeze film damper lubricated with ferrofluid

This work describes an analytical study on the dynamic behaviour of a three-pad hydrostatic journal bearing lubricated with ferrofluids. Each pad is fed with an external pressure through a capillary restrictor-type hydraulic resistance. Ferrofluid or magnetic fluid is a colloidal dispersion of magnetic nano-particles in a carrier liquid. In this study, a non-linear method was performed using Jenkins model in order to investigate the effect of ferrofluids lubrication on the vibrations amplitude and the transmitted forces of hydrostatic squeeze film dampers. The results presented in this paper showed that the ferrofluid lubrication is useful in controlling the bearing vibrations and transmitted forces. The results illustrated in this work are expected to be quite useful to the bearing designers.     

Forecasting Electricity Demand on Short, Medium and Long Time Scales Using Neural Networks

This paper examines the application of artificial neural networks (ANNs) to the modelling and forecasting of electricity demand experienced by an electricity supplier. The data used in the application examples relates to the national electricity demand in the Republic of Ireland, generously supplied by the Electricity Supply Board (ESB). The paper focusses on three different time scales of interest to power boards: yearly (up to fifteen years in advance), weekly (up to three years in advance) and hourly (up to 24 h ahead). Electricity demand exhibits considerably different characteristics on these different time scales, both in terms of the underlying autoregressive processes and the causal inputs appropriate to each time scale. Where possible, the ANN-based models draw on the applications experience gained with linear modelling techniques and in one particular case, manual forecasting methods.     

基于Jenkins的持续集成测试环境插件开发

现代软件规模已经极具膨胀,软件测试所占用的时间的比例也越来越大,如何提供高效,快速,自动化,可定制的继承测试环境已经成为软件行业亟待解决的问题.DevOps和持续集成是一种软件开发实践,对于提高软件开发效率并保障软件开发质量提供了理论基础.Jenkins是一个开源软件项目,提供了一个开放易用的软件平台,使持续集成和自动化测试成为可能.     

Identification of errors‐in‐variables systems: An asymptotic approach

This work studies the identification of errors‐in‐variables (EIV) systems. An asymptotic method (ASYM) is developed for the EIV system. Firstly, an auto regressive with exogeneous (ARX) model estimation method is proposed, which is consistent for EIV systems. Then the asymptotic variance expression of the estimated high‐order ARX model is derived, which forms the basis of the ASYM method. In parameter estimation, the ASYM starts with a high‐order ARX model estimation followed by a frequency domain weighted model reduction. The obtained model is consistent, and its efficiency needs to be investigated. Besides parameter estimation, a criterion for model order selection is proposed, which is based on frequency domain considerations, and the frequency domain error bound is established that can be used for model validation. Simulations and comparisons with other methods are used to illustrate the performance of the method.     

Recursive least squares parameter identification algorithms for systems with colored noise using the filtering technique and the auxilary model

This paper focuses on the parameter estimation problems of output error autoregressive systems and output error autoregressive moving average systems (i.e., the Box–Jenkins systems). Two recursive least squares parameter estimation algorithms are proposed by using the data filtering technique and the auxiliary model identification idea. The key is to use a linear filter to filter the input–output data. The proposed algorithms can identify the parameters of the system models and the noise models interactively and can generate more accurate parameter estimates than the auxiliary model based recursive least squares algorithms. Two examples are given to test the proposed algorithms.     

观测数据分析中几种方法的探讨(一) 回归-时间序列模型和贝叶斯预测模型

首先，叙述用回归分析与随机时间序列技术的组合方法来处理大坝的监测数据。通常，回归分析后的残差序列并不满足白噪声假设，这个理论缺陷在一定程度上降低了监测的可靠性和预测的正确性。为此，采用鲍克斯—詹金斯方法对残差序列进行再处理。按照上述组合方法求得的计算数据能更好地吻合实测数据，最终的误差序列能符合白噪声特性，并使拟合和预测的正确程度有了较大改善。然后，利用贝叶斯动态模型分析监测资料。采用贝叶斯模型时，由于状态参数(相当于回归系数)能及时调整跟踪，故所得的结果比常规回归分析的结果有更高的精度，计算曲线与实测曲线吻合得更好。     

Ferrofluids lubrication: a status report

Ferrofluids (FFs) are stable colloidal suspensions composed of single‐domain magnetic nanoparticles dispersed in a carrier liquid. And it is an intelligent material, exhibiting normal liquid behaviour coupled with superparamagnetic properties. Since the properties and the location of these fluids can easily be influenced by a magnetic field, FFs have recently attracted many scientific, industrial and commercial applications. Lubrication is one of the most important applications for FFs, and the advantage of FFs as lubricant, over the conventional ones, is that the former can be retained at the desired location with moderate magnetic fields. The main focus of this paper is to present a comprehensive review on FFs lubrication theories based on the three flow models of Neuringer–Rosensweig, Shliomis and Jenkins. Besides, a few experimental studies on FFs lubrication are discussed briefly. Copyright © 2015 John Wiley & Sons, Ltd.