A New Economy Forecasting Method Based on Data Barycentre Forecasting Method

A new and useful method of technology economics, parameter estimation method, was presented in light of the stability of gravity center of object in this paper. This method could deal with the fitting and forecasting of economy volume and could greatly decrease the errors of the fitting and forecasting results. Moreover, the strict hypothetical conditions in least squares method were not necessary in the method presented in this paper, which overcame the shortcomings of least squares method and expanded the application of data barycentre method. Application to the steel consumption volume forecasting was presented in this paper. It was shown that the result of fitting and forecasting was satisfactory. From the comparison between data barycentre forecasting method and least squares method, we could conclude that the fitting and forecasting results using data barycentre method were more stable than those of using least squares regression forecasting method, and the computation of data barycentre forecasting method was simpler than that of least squares method. As a result, the data barycentre method was convenient to use in technical economy.

Phantom cosmologies from the simplest parameterization of the DE model using observational data in a BI type universe

To scrutinize the nature of dark energy,many equations of state have been proposed.In this context,we examine the simplest parameterization of the equation of state parameter of dark energy in an anisotropic Bianchi type I universe compared with theΛCDM model.Using different combinations of data samples,including Pantheon and Pantheon+H(z),alongside applying the minimization of theχ^(2)function of the distance modulus of data samples,we obtain the constrained values of cosmographic parameters in the parameterization of the dark energy scenario.One condition of the phantom barrier crossing is acquired.Several physical properties of the universe are discussed by considering the anisotropy effect and different observational data points.One should note that the deductions of the cosmological parameter verify recent observational data.

Software Metric Analysis of Open-Source Business Software

Over the past decade, open-source software use has grown. Today, many companies including Google, Microsoft, Meta, RedHat, MongoDB, and Apache are major participants of open-source contributions. With the increased use of open-source software or integration of open-source software into custom-developed software, the quality of this software component increases in importance. This study examined a sample of open-source applications from GitHub. Static software analytics were conducted, and each application was classified for its risk level. In the analyzed applications, it was found that 90% of the applications were classified as low risk or moderate low risk indicating a high level of quality for open-source applications.

Software Analytics of Open Source Business Software

This paper applies software analytics to open source code. Open-source software gives both individuals and businesses the flexibility to work with different parts of available code to modify it or incorporate it into their own project. The open source software market is growing. Major companies such as AWS, Facebook, Google, IBM, Microsoft, Netflix, SAP, Cisco, Intel, and Tesla have joined the open source software community. In this study, a sample of 40 open source applications was selected. Traditional McCabe software metrics including cyclomatic and essential complexities were examined. An analytical comparison of this set of metrics and derived metrics for high risk software was utilized as a basis for addressing risk management in the adoption and integration decisions of open source software. From this comparison, refinements were added, and contemporary concepts of design and data metrics derived from cyclomatic complexity were integrated into a classification scheme for software quality. It was found that 84% of the sample open source applications were classified as moderate low risk or low risk indicating that open source software exhibits low risk characteristics. The 40 open source applications were the base data for the model resulting in a technique which is applicable to any open source code regardless of functionality, language, or size.

Online Pattern Recognition and Data Correction of PMU Data Under GPS Spoofing Attack

Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from attacks.Compared with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical system.Therefore,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)deviation.Specifically,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp attack.Then,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line parameters.After obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD deviations.Finally,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.

Non-fragile switched H_∞ control for morphing aircraft with asynchronous switching

This paper deals with the problem of non-fragile linear parameter-varying（LPV） H_∞ control for morphing aircraft with asynchronous switching.The switched LPV model of morphing aircraft is established by Jacobian linearization approach according to the nonlinear model.The data missing is taken into account in the link from sensors to controllers and the link from controllers to actuators,which satisfies Bernoulli distribution.The non-fragile switched LPV controllers are constructed with consideration of the uncertainties of controllers and asynchronous switching phenomenon.The parameter-dependent Lyapunov functional method and mode-dependent average dwell time（MDADT） method are combined to guarantee the stability and prescribed performance of the system.The sufficient conditions on the solvability of the problem are derived in the form of linear matrix inequalities（LMI）.In order to achieve higher efficiency of the designing process,an algorithm is applied to divide the whole set into subsets automatically.Simulation results are provided to verify the effectiveness and superiority of the method in the paper.