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Cloud computing is qualified to present proper limitless storage and computation resources to users as services throughout the internet. Software as a service (SaaS) layer is the key paradigm perspective in the software layer of the cloud computing. SaaS is connected by business applications to access consumers on existing public, private and hybrid cloud models. This purpose of this paper is to present a discussion and analysis on the SaaS layer based on business applications in the cloud environment in form of a classical taxonomy to recognize the existing techniques, challenges and efforts.

Existing techniques, challenges and efforts are classified into four categories: platform-dependent, application-dependent, data-dependent and security-dependent mechanisms. The SaaS layer mechanisms are compared with each other according to the important factors such as the structural properties, quality of service metrics, applied algorithms and measurement tools.

The benefits and weaknesses of each research study are analyzed. In the comparison results, the authors observed that the application-based method, the non-heuristic algorithms, the business process method have the highest percentage of the usage in this literature.

The SaaS layer mechanisms based on business applications have some main features such as high accessibility, compatibility, reusability and collaboration to provide activated application and operation services for user with help of Web browsers. A comprehensive analysis was presented as originality on the SaaS layer mechanisms based on business applications for high level of the cloud environment that 46 peer-reviewed studies were considered.

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are used to dampen the electric field imposed on the insulator. The purpose of this study is to present a fast and intelligent surrogate model for determination of the electric field imposed on the surface of a 120 kV composite insulator, in presence of the Corona ring.

Usually, the structural design parameters of the Corona ring are selected through an optimization procedure combined with some numerical simulations such as finite element method (FEM). These methods are slow and computationally expensive and thus, extremely reducing the speed of optimization problems. In this paper, a novel surrogate model was proposed that could calculate the maximum electric field imposed on a ceramic insulator in a 120 kV line. The surrogate model was created based on the different scenarios of height, radius and inner radius of the Corona ring, as the inputs of the model, while the maximum electric field on the body of the insulator was considered as the output.

The proposed model was based on artificial intelligence techniques that have high accuracy and low computational time. Three methods were used here to develop the AI-based surrogate model, namely, Cascade forward neural network (CFNN), support vector regression and K-nearest neighbors regression. The results indicated that the CFNN has the highest accuracy among these methods with 99.81% R-squared and only 0.045468 root mean squared error while the testing time is less than 10 ms.

To the best of the authors’ knowledge, for the first time, a surrogate method is proposed for the prediction of the maximum electric field imposed on the high voltage insulators in the presence Corona ring which is faster than any conventional finite element method.

In this paper, the peak kinetic energy density (KED) of soil particles during earthquake excitation is used as an intensity measure for the evaluation of liquefaction potential under field conditions. The paper seeks to discuss this measure.

Using centrifuge tests data, it is shown that seismic pore water pressure buildup is proportional to cumulative KED at a particular soil depth. Linear relationships are found between cumulative kinetic energy and corresponding cumulative strain energy. To consider the effect of soil amplification, several equivalent linear ground response analyses are performed and the results are used to derive an equation for depth reduction factor of peak kinetic energy density. Two separate databases of liquefaction case histories are used in order to validate the proposed model. The performance of the proposed model is compared with a number of commonly used shear stress‐based liquefaction assessment methods. Finally, the logistic regression method is employed to obtain probabilistic boundary curves based on the present model. Parametric study of the proposed probabilistic model is carried out to verify its agreement with the previous methods.

It has been shown that the kinetic energy model works satisfactorily in classifying liquefied and non‐liquefied cases compared with the existing recommendations of shear stress‐based criterion. The results of the probabilistic kinetic energy model are in good agreement with those of previous studies and show a reasonable trend with respect to the variations of fines content and effective overburden pressure. The proposed model can be as used an alternative approach for assessment of liquefaction potential.

These findings make a sound basis for the development of a kinetic energy‐based method for assessment of liquefaction potential.

This study aims to present a basic mathematical model for investigating the structure of counter-flow non-premixed laminar flames propagating through uniformly-distributed organic fuel particles considering preheat, drying, vaporization, reaction and oxidizer zones.

Lycopodium particles and air are taken as biofuel and oxidizer, respectively. Dimensionalized and non-dimensionalized forms of mass and energy conservation equations are derived for each zone taking into account proper boundary and jump conditions. Subsequently, to solve the governing equations, an asymptotic method is used. For validation purpose, results achieved from the present analysis are compared with reliable data reported in the literature under certain conditions.

With regard to the comparisons, although different complex non-homogeneous differential equations are solved in this paper, acceptable agreements are observed. Finally, the impacts of significant parameters including fuel and oxidizer Lewis numbers, equivalence ratio, mass particle concentration, fuel and oxidizer mass fractions and lycopodium initial temperature on the flame temperature, flame front position and flow strain rate are elaborately explained.

An asymptotic method for mathematical modeling of counter-flow non-premixed multi-zone laminar flames propagating through lycopodium particles.

This study aims to explore the direct and indirect effects of organizational stakeholder’s relationship on performance through innovativeness and risk-taking among small and medium enterprises (SMEs).

This study used the cluster sampling method to select the study sample and the questionnaire survey approach to 580 SMEs established in Tehran. A total of 150 completed questionnaires were returned. Partial least squares-structural equation modeling was administered to analyze data via the SmartPLS 3.0 software.

The survey outcomes revealed that organization-stakeholder relationship had an indirect effect on performance through innovativeness and risk-taking. The results indicated positive links for organization-stakeholder relationship and innovativeness, as well as the organization-stakeholder relationship to risk-taking.

This research is beneficial for entrepreneurs who wish to learn about the specific resources significant for venture growth, to devise effective strategies to expand their relationship with stakeholders and to consider the significance of the correlations established, in this study, through innovativeness and risk-taking.

This research is one of the few attempts that have addressed the importance of innovativeness and risk-taking as the key mechanisms to transform the advantages of organization-stakeholder relationships to enhance performance.

This paper aims to design a neural controller based on radial basis function networks (RBFN) for electrically driven robots subjected to constrained inputs.

It is assumed that the electrical motors have limitations on the applied voltages from the controller. Due to the universal approximation property of RBFN, uncertainties including un-modeled dynamics and external disturbances are represented with this powerful neural network. Then, the lumped uncertainty including the nonlinearities imposed by actuator saturation is introduced and a mathematical model suitable for model-free control is presented. Based on the closed-loop equation, a Lyapunove function is defined and the stability analysis is performed. It is assumed that the electrical motors have limitations on the applied voltages from the controller.

A comparison with a similar controller shows the superiority of the proposed controller in reducing the tracking error. Experimental results on a SCARA manipulator actuated by permanent magnet DC motors have been presented to guarantee its successful practical implementation.

The novelty of this paper in comparison with previous related works is improving the stability analysis by involving the actuator saturation in the design procedure. It is assumed that the electrical motors have limitations on the applied voltages from the controller. Thus, a comprehensive approach is adopted to include the saturated and unsaturated areas, while in previous related works these areas are considered separately. Moreover, a performance evaluation has been carried out to verify satisfactory performance of transient response of the controller.

This paper aims to examine the integration of lateral transshipment and road vulnerability into the humanitarian relief chain in light of affected area priority to address equitable distribution and assess the impact of various parameters on the total average inflated distance traveled per relief item.

After identifying comprehensive critical criteria and subcriteria, a hybrid multi-criteria decision-making framework was applied to obtain the demand points’ weight and ranking in a real-life earthquake scenario. Direct shipment and lateral transshipment models were then presented and compared. The developed mathematical models are formulated as mixed-integer programming models, considering facility location, inventory prepositioning, road vulnerability and quantity of lateral transshipment.

The study found that the use of prioritization criteria and subcriteria, in conjunction with lateral transshipment and road vulnerability, resulted in a more equitable distribution of relief items by reducing the total average inflated distance traveled per relief item.

To the best of the authors’ knowledge, this study is one of the first research on equity in humanitarian response through prioritization of demand points. It also bridges the gap between two areas that are typically treated separately: multi-criteria decision-making and humanitarian logistics.

This is the first scholarly work in Shiraz focused on the equitable distribution system by prioritization of demand points and assigning relief items to them after the occurrence of a medium-scale earthquake scenario considering lateral transshipment in the upper echelon.

The paper clarifies how to prioritize demand points to promote equity in humanitarian logistics when the authors have faced multiple factors (i.e. location of relief distribution centers, inventory level, distance, lateral transshipment and road vulnerability) simultaneously.

In this study, two novel fluorescent dyes, based on naphthalimide derivatives have been synthesised from acenaphthene as a starting material. The ability of the dyes to graft to polymer chain was then demonstrated. The novel synthesised dyes and self-coloured polymers were characterised by a variety of techniques.

The novel dyes were prepared through by halogenation, oxidation, imidation and amination reactions. All steps of these processes were monitored by thin layer chromatography. The fluorescent dyes and their intermediates were characterised by differential scanning calorimeter, fourier transform infrared spectroscopy (FTIR), Proton Nuclear Magnetic Resonance (1H-NMR) and carbon-13 nuclear magnetic resonance (13-CNMR) spectroscopic techniques. The molar extinction coefficients and absorption maximum wavelength were obtained by examining the dyes and polymer solutions in Dimethylformamide (DMF) and toluene solvents. The fluorescency of novel dyes and self-coloured polymers was evaluated. Their quantum yields and Stokes shift values were determined as DMF and toluene solutions. The percentage of the covalently bounded dyes into the polymer chain was calculated.

The characterisation of the synthesised dyes and self-coloured polymers verified their structural correctness. The results of reaction dyes with resin demonstrated that the dyes were covalently bonded to the chain of an acrylic polymer (resin) containing carboxylic acid groups giving self-coloured polymers. The extent of fluorescence of the synthesised dyes and their polymers showed that compounds containing functional amino group in C-4 position of naphthalimide ring have high fluorescence properties.

This study is original. Self-coloured polymers based on acrylic were synthesised by novel naphthalimide dyes with acrylic resin for the first time, successfully. The novel dyes and their self-coloured polymers exhibit good and acceptable fluorescent activity.

As one of the dominant features in developing countries, gender inequality has driven individual development and the promotion of skills, behavioral and social competencies largely based on the male gender. The audit profession is considered one of the jobs where gender inequality exists, especially in developing countries. This has made educational programs more inclined toward enhancing masculine abilities, followed by less well-regarded feminine functions in the field. This study aims to present a triple-strength model of female auditors empowerment in Iran.

This is a goal-oriented, descriptive-applied developmental research and a mix of data types. In the qualitative section, the three-dimensional empowerment proposition of women working in the field of internal auditing (IA) were identified based on the Dacum model approach participated by 15 research experts, using cross-sectional and Delphi analyses. A total interpretive structural model analysis was performed with the participation of 20 women as internal auditors of companies listed on the Tehran Stock Exchange (TSE).

The purpose of this analysis was to prioritize the spectrum of the most influential indices of empowerment of female auditors in educational planning to the least effective ones in the form of the research model and to examine the relationships between them based on matrix comparisons. According to the results, 17 indices reached theoretical adequacy during the 2 rounds of Delphi analysis out of the initial 19 indices in the cross-mix analysis.

The results of the interpretive/structural analysis indicated that educational planning was selected to balance the other roles of women as internal auditors, and the most influential Dacum proposition was to enhance the capabilities of women in IA in listed companies in TSE.

The purpose of this study is simulation of of polymer electrolyte membrane fuel cell. Proton-exchange membrane fuel cells are promising power sources for use in power plants and vehicles. These fuel cells provide a high level of energy efficiency at low temperature without any pollution. The convection inside the cell plays a key role in the electrochemical reactions and the performance of the cell. Accordingly, the transport processes in these cells have been investigated thoroughly in previous studies that also carried out functional modeling.

A multi-phase model was used to study the limitations of the reactions and their impact on the performance of the cell. The governing equations (conservation of mass, momentum and particle transport) were solved by computational fluid dynamics (CFD) (ANSYS fluent) using appropriate source terms. The two-phase flow in the fuel cell was simulated three-dimensionally under steady-state conditions. The flow of water inside the cell was also simulated at high-current density.

The simulation results suggested that the porosity of the gas diffusion layer (GDL) is one of the most important design parameters with a significant impact on the current density limitation and, consequently, on the cell performance.

This study was mainly focused on the two-phase analysis of the steady flow in the fuel cell and on investigating the impacts of a two-phase flow on the performance of the cell and also on the flow in the GDL, the membrane and the catalyst layer using the CFD.