Search results

In most applications the active power filters (APFs) are used to reduce harmonic distortion of a nonlinear load which is located near the APF installation point. This classic approach allows to reduce the distortion introduced to the power system but do not guarantee that the cost of the APFs installation is optimal. The purpose of this paper is to compare the classic approach to harmonic compensation with an optimization method of sizing and placement of the APFs in an existing distributed power network.

An exemplary real-life power system with distributed nonlinear loads was modeled using PCFLO power analysis software. Next, Matlab was used to implement the classic method and the optimization algorithm. Between Matlab and PCFLO a specially written Java middleware was used to provide a seamless workflow integration.

It was shown that the presented optimization method may lead to superior results in comparison with the classic approach. Simulation results clearly showed that the APFs installation cost can be significantly reduced when the optimization algorithm is used. Moreover, the proposed optimization method can overcome some problems connected with the nonlinearity and discontinuity of the APF's price/current function.

There are two main limitations of the presented method. First, the method needs much more computing power then the classic approach. Second, according to the authors’ knowledge, currently there are no commercially available APFs, which allow to directly apply the optimization method in industrial applications.

The presented results showed that the approach, which is the most popular in the industry, is far from being optimal from the cost perspective. As it has been shown in the investigated example, it might be possible to significantly reduce the total cost of APFs installed in the power system.

The optimization method presented in the paper as well as all simulation results are the original authors work. It was shown that the existing harmonic compensation strategies can be significantly upgraded and the proposed optimization method may be a basis and a reference point for future commercial solutions.

The purpose of this paper is to focus on the suitability of the multitrait-multimethod (MTMM) matrix approach for examining construct validity in human resource management (HRM) research. The authors also provide a number of suggestions on how to use MTMM more effectively in HRM research.

The authors start by presenting a basic introduction to MTMM approach. Next the authors briefly review the limitations of MTMM approach and suggested improvements. The authors elaborate on these limitations by providing HRM examples. To further illustrate these issues, the authors review employment interview research.

The construct validity analysis in HRM research suffers from three problematic assumptions of the classical MTMM approach: uncorrelated trait-method units, uncorrelated methods, and uncorrelated traits. The review of interview research shows that classical MTMM approach is by far the most popular approach given its relative simplicity and modest sample size requirements. This popularity stresses the significance of the review in highlighting these issues.

Several improvements to quantify the interpretations of MTMM analysis are available to researchers. This review closely examines how these limitations and proposed improvements influence HRM research, thereby making the methodological advances concerning the MTMM approach more accessible to HRM researchers and practitioners.

This paper aims to propose numerical-based and experiment-based identification processes, accounting for uncertainties to identify structural parameters, in a wave propagation framework.

A variant of the inhomogeneous wave correlation (IWC) method is proposed. It consists on identifying the propagation parameters, such as the wavenumber and the wave attenuation, from the frequency response functions. The latters can be computed numerically or experimentally. The identification process is thus called numerical-based or experiment-based, respectively. The proposed variant of the IWC method is then combined with the Latin hypercube sampling method for uncertainty propagation. Stochastic processes are consequently proposed allowing more realistic identification.

The proposed variant of the IWC method permits to identify accurately the propagation parameters of isotropic and composite beams, whatever the type of the identification process in which it is included: numerical-based or experiment-based. Its efficiency is proved with respect to an analytical model and the Mc Daniel method, considered as reference. The application of the stochastic identification processes shows good agreement between simulation and experiment-based results and that all identified parameters are affected by uncertainties, except damping.

The proposed variant of the IWC method is an accurate alternative for structural identification on wide frequency ranges. Numerical-based identification process can reduce experiments’ cost without significant loss of accuracy. Statistical investigations of the randomness of identified parameters illustrate the robustness of identification against uncertainties.

The purpose of this paper is to investigate the effect of managerial ability on tax avoidance in Tehran Stock Exchange (TSE) and OTC by classifying the income smoother and non-income smoother companies based on the theoretical approaches.

To measure the managerial ability the data envelopment analysis is applied based on the accounting data, company and industry characteristics. In this research, hypotheses are tested for the first time by three statistical methods, namely classical regression models, mixed effect multilevel models, and Bayesian multilevel models, which have never been addressed in Persian accounting research studies. The hypotheses are estimated during a 12-year period from 2004 to 2015 in TSE and OTC. In this research, according to Lucas’s critique, structural change test is used in order to control macroeconomic and political variables affecting the results of the study.

The results of hypothesis testing by employing three statistical methods suggest that only one hypothesis of this investigation is significant, which shows the significant association of type of market’s impact (exchange of OTC) on the relationship between managerial ability and tax avoidance.

Each company’s performance is affected by various factors. The study intends to mention that the performance of listed companies in the stock market depends heavily on its financial reports. And investors with perceived perception by the reports, can indirectly squeeze their stock indexes with their sudden sale of stocks, and question the company’s performance with losses to the company.

The purpose of this paper is to investigate the relationship between tax avoidance, firm value and managerial ability in Tehran Stock Exchange and Over the Counter (OTC), according to the related theoretical foundations.

To calculate the managerial ability in this study, DEA is used based on the accounting data, company profile and industry and the hypotheses are estimated in a period of 12 years during 2004 to 2015 in TSE and OTC. Within the previous studies, to test the hypotheses, only the classical regression method is usually used and most of the times the effect of macroeconomic variables is not considered. In this study, in a new act for testing the hypotheses, three statistical methods are used, that is, classical regression models, mixed effects multilevel models and Bayesian multilevel models. Also in this study, the test of structural change is used to control the effects of macroeconomic variables, like inflation and other economic and political influence, on the results.

The results of these three methods show that the effect of income smoothing and earnings quality on the relationship between tax avoidance and firm value are significant.

Although several studies are conducted so far on the subject of the study, the current study is the first project which combined Bayesian econometrics. Therefore, the results are quite noble.

In the present work, a novel dual time stepping approach is applied to a quasi-implicit (QI) fractional step method and its performance is assessed against the classical versions of the QI procedure for the solution of incompressible Navier-Stokes equations. The paper aims to discuss these issues.

In the proposed method, a local time stepping algorithm is utilised to accelerate the solution to steady state, while the transient solution is recovered through the use of a dual time step. It is demonstrated that, unlike the classical fractional step method, the temporal convergence rate of the proposed method depends solely upon the choice of the time discretisation.

While additional stabilisation is the prerequisite for obtaining higher order accuracy in the standard QI methods, the proposed dual time stepping approach completely eliminates this requirement. In addition, the dual time stepping approach proposed achieves the correct formal accuracy in time for both velocity and pressure. It is also demonstrated that a time accuracy beyond second order for both pressure and velocity is possible. In summary, the proposed dual time approach to QI methods simplifies the algorithm, accelerates solution and achieves a higher order time accuracy.

The dual time stepping removed first order pressure error.

The purpose of this paper is to reduce the waiting time on webcast for selective contents, by proposing a scheduling method called the “contents prefetched broadcasting considering user participation” (CPB‐CP) method.

The authors analyze and evaluate the performance of the proposed CPB‐CP method.

It is confirmed that the proposed method gives shorter average waiting time than the conventional methods.

A future direction of this study will involve making a scheduling method in the case where the playing time of each content item is different.

In selective contents delivery, users may wait for the next bit of content to start playing after watching the previous one. In quiz programs, users may wait to receive the content data for their selected answer after they select their answer.

In the CPB‐CP method, when a provider node pulls out of the network while delivering contents, waiting time is reduced effectively by reconstructing a delivery schedule that considers the available bandwidth of each provider node.

The purpose of this paper is to report upon research into developing a biologically inspired target‐tracking system (TTS) capable of acquiring quality images of a known target type for a robotic inspection application.

The approach used in the design of the TTS hearkens back to the work on adaptive learning by Oliver Selfridge and Chris J.C.H. Watkins and the work on the classification of objects by Zdzislaw Pawlak during the 1980s in an approximation space‐based form of feedback during learning. Also, during the 1980s, it was Ewa Orlowska who called attention to the importance of approximation spaces as a formal counterpart of perception. This insight by Orlowska has been important in working toward a new form of adaptive learning useful in controlling the behaviour of machines to accomplish system goals. The adaptive learning algorithms presented in this paper are strictly temporal difference methods, including Q‐learning, sarsa, and the actor‐critic method. Learning itself is considered episodic. During each episode, the equivalent of a Tinbergen‐like ethogram is constructed. Such an ethogram provides a basis for the construction of an approximation space at the end of each episode. The combination of episodic ethograms and approximation spaces provides an extremely effective means of feedback useful in guiding learning during the lifetime of a robotic system such as the TTS reported in this paper.

It was discovered that even though the adaptive learning methods were computationally more expensive than the classical algorithm implementations, they proved to be more effective in a number of cases, especially in noisy environments.

The novelty associated with this work is the introduction of an approach to adaptive adaptive learning carried out within the framework of ethology‐based approximation spaces to provide performance feedback during the learning process.

The purpose of this paper is to compare various linear opinion pooling models for aggregating probability judgments and to determine whether Cooke's performance weighting model can sift out better calibrated experts and produce better aggregated distribution.

The leave‐one‐out cross‐validation technique is adopted to perform an out‐of‐sample comparison of Cooke's classical model, the equal weight linear pooling method, and the best expert approach.

Both aggregation models significantly outperform the best expert approach, indicating the need for inputs from multiple experts. The performance score for Cooke's classical model drops considerably in out‐of‐sample analysis, indicating that Cooke's performance weight approach might have been slightly overrated before, and the performance weight aggregation method no longer dominantly outperforms the equal weight linear opinion pool.

The results show that using seed questions to sift out better calibrated experts may still be a feasible approach. However, because the superiority of Cooke's model as discussed in previous studies can no longer be claimed, whether the cost of extra efforts used in generating and evaluating seed questions is justifiable remains a question.

Understanding the performance of various models for aggregating experts' probability judgments is critical for decision and risk analysis. Furthermore, the leave‐one‐out cross‐validation technique used in this study achieves more objective evaluations than previous studies.

The purpose of this paper is to develop a combined control (CC) technique based on the direct torque control (DTC) strategy and vector control (VC) method, to improve the overall performance of a three-phase induction machine (TPIM) drives.

The proposed control scheme includes a table-based DTC strategy in connection with a proportional-integral-sliding mode controller and pulse width modulation switching strategy. The control system has merits of DTC technique such as simple structure, less dependent on machine parameters, fast dynamic response and merits of VC technique such as high accuracy and constant switching frequency.

To validate the effectiveness of the proposed control system, simulation and experimental studies are carried out for a 0.75 kW TPIM in different operating conditions. The achieved results show the superiority of the proposed method in terms of fast dynamics and simple structure compared to the VC strategy and low speed and torque ripples and constant switching frequency compared to the DTC method.

Compared to the conventional CC strategies, the control law of the proposed method is based on DTC theory and modulation is established based on VC. In other words, the variable switching frequency which is one of the main disadvantages of the conventional CC strategies is rectified using the proposed CC scheme.