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The purpose of this paper is to design an inference engine to measure the level of readiness of each bank before starting the corporate sustainability auditing process. Based on the output of the designed inference engine, the audition team can decide about the audition resources and the auditing process.

In this paper, the hybrid rough and grey set theory are used to design and create a rule model system to measure the sustainability level of banks. First, 16 rule models are extracted using rough set theory (RST), and the cross-validation of each model is done. Then, the grey clustering is used to combine the same condition attributes and improve the validity of the final model. A total of 16 new rule models are extracted based on the decreased condition attributes, and the best model is selected based on the cross-validation results.

By comparing the accuracy of rough-gray’s rule models and as a result of decreasing the condition attributes, a proper increase in the accuracy of all models is obtained. Finally, the Naive/Genetic/object-related reducts model with 95.6% accuracy is selected as an inference engine to measure new banks’ readiness level.

Sustainability measurement of banks based on RST is a new approach in the field of corporate sustainability. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

Risk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology in all fields and the high failure rate of software development projects, it is essential to predict the risk level of each project effectively before starting. Therefore, the main purpose of this paper is proposing an expert system to infer about the risk of new banking software development project.

In this research, the risk of software developing projects is considered from four dimensions including risk of cost deviation, time deviation, quality deviation and scope deviation, which is examined by rough set theory (RST). The most important variables affecting the cost, time, quality and scope of projects are identified as condition attributes and four initial decision systems are constructed. Grey system theory is used to cluster the condition attributes and after data discretizing, eight rule models for each dimension of risk as a decision attribute are extracted using RST. The most validated model for each decision attribute is selected as an inference engine of the expert system, and finally a simple user interface is designed in order to predict the risk level of any new project by inserting the data of project attributes

In this paper, a high accuracy expert system is designed based on the combination of the grey clustering method and rough set modeling to predict the risks of each project before starting. Cross-validation of different rule models shows that the best model for determining cost deviation is Manual/Jonson/ORR model, and the most validated models for predicting the risk of time, quality and scope of projects are Entropy/Genetic/ORR, Manual/Genetic/FOR and Entropy/Genetic/ORR models; all of which are more than 90% accurate

It is essential to gather data of previous cases to design a validated expert system. Since data documentation in the field of software development projects is not complete enough, grey set theory (GST) and RST are combined to improve the validity of the rule model. The proposed expert system can be used for risk assessment of new banking software projects

The risk assessment of software developing projects based on RST is a new approach in the field of risk management. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

This study aimed to provide a model for evaluating organizational agility in the banking industry in Isfahan using the data envelopment analysis (DEA) approach.

This research’s population consists of selected first-class branches of Saderat, Melli, Shahr, Maskan, Keshavarzi, Refah and Tejarat banks. Five branches of each bank and Bank Shahr as a newly established bank with two branches were included in the study. First, a suitable DEA model was selected and then agility inputs and outputs for designing the model were extracted from the literature. The selected model is an output-oriented returns to scale model. Inputs were agility enablers extracted from the A.T. Kearney model, whereas agility results were considered as the output.

The results showed that of the 32 selected branches, 4 were efficient and 28 were inefficient. In the end, the efficient branches were ranked using the Anderson–Peterson ranking model.

This study tries to provide a model for evaluating the efficiency of bank branches in terms of agility (relative agility) through the DEA technique, considering inputs and outputs of the organizational agility system. Accordingly, the managers can identify the efficiency of bank branches and also they can improve the inefficiency of bank branches.

The purpose is to develop and apply a systematic simulation approach for dynamic analysis in order to study a two combustion chambers liquid propellant engine.

The logic of the simulation method and the software is based on following the liquids. The implicit nonlinear algebraic equations are solved using a number of nested Newton‐Raphson loops, and the nonlinear and time varying differential equations are solved using a first‐order Euler technique.

It is found that the developed simulation code predicts the steady‐state values with errors under 5 percent, and this code has the capability to be used in studying the effect of various elements and subsystems parameters on the forecasting the performance and operation of the engine system.

At present, the research is limited to a specific liquid propellant engine. Development of a general purpose software package for simulation of liquid propellant engines, based on the developed simulation algorithm, is subject of future research.

The major outcome of this research is that verifies liquid engine simulation code may be used as a suitable tool to optimize the engine.

This is the first paper in the area of a two combustion chambers engine simulation and dynamic analysis that is based on the application of an existing simulation algorithm.

This paper aims to evaluate the financial performance of companies listed on Tehran Stock Exchange by using negative data envelopment analysis (DEA) approach.

First, the financial metrics for performance evaluation were extracted and then filtered based on the experts’ opinions. Upon choosing the appropriate financial measures, the financial information of 72 companies selected from four automotive, pharmaceutical, petrochemical and cement industries were collected, and the criteria values were also measured. The financial performance of selected companies was assessed using negative data bounded adjusted measure in the DEA, and efficient and inefficient companies were identified. Finally, the efficient companies were ranked using Andersen and Petersen model.

The required analysis was conducted, and the financial performance of selected companies listed on Tehran Stock Exchange was evaluated. There were 58 efficient companies with a performance value of 1; 14 companies became inefficient because the efficiency size was less than 1; therefore, reference units were also introduced to the managers for efficiency of inefficient companies.

The aim of this study was to identify the required financial criteria and to determine an appropriate model for performance evaluation based on negative DEA. The findings can help shareholders to identify efficient companies and make the optimal portfolio accordingly; the managers of inefficient companies can also take the proper reforming actions to improve efficiency.

Development and application of a new systematic approach for design of a control system in order to control the mixture ratio of liquid propellant engines.

The design approach is based on a full nonlinear dynamic model of the engine, and the controller design method is based on describing function models of the engine coupled with the factorization theory. The presented systematic design procedure is comprised of five primary steps. The developed software for the design approach is in the MATLAB environment.

It is found that the presented design approach may successfully be used to control the mixture ratio of a class of liquid propellant engines whose control loops are decoupled. The performance and robustness of the designed controller is found to be satisfactory.

At present, the research is limited to liquid propellant engines whose control loops are decoupled.

The major outcome of this research is that complicated hydromechanical control valves that are used to control the mixture ratio may be replaced by simple microprocessor based servomechanisms that drive simple valves. This will allow for the engine to accept various set point values for mixture ratio as is required in multi‐regime engines.

This is the first paper in the area of mixture ratio control of a liquid propellant engine that is based on the application of describing function approach coupled with the factorization theory.

This study aims to examine the potential determinants of entrepreneurial intentions (EIs) among business students. To that end, the study investigates the role of entrepreneurship education (EE) and entrepreneurial passion (EP) (inventing and founding), as well as the mediating role of attitude towards entrepreneurship (ATE) and the moderating role of university support.

A close-ended questionnaire measured on a seven-point Likert scale was used to collect data from business students at nine universities in Punjab, Pakistan. The sample size comprises 377 participants who were selected using a stratified random sampling technique. Partial least square structural equation modeling (PLS-SEM) was then applied to assess the study’s model and the postulated hypothesis.

The findings indicated that (a) every independent variable (IV) directly impacts EI [dependent variable (DV)] except EP for founding (EPF), (b) ATE significantly mediates the relationship between IV and DV (c) perceived university support positively moderates the relationship between ATE and EI.

As an implication to policy, the Government must ensure that students are exposed to business environments and find university support through different paths. Specifically, Pakistan’s Minister of Education and the Higher Education Commission (HEC) may consider designing university programs that lead to more influential EE. The empirical findings may help policymakers develop effective policies for promoting entrepreneurship.

The purpose of this paper is to apply a new systematic simulation approach to an existing liquid propellant engine.

The simulation approach is based on following the liquids (oxidizer and fuel) in their respective paths. The nonlinear dynamic model of the engine is composed of implicit nonlinear algebraic equations coupled with a set of differential equations. The model is solved by placing the implicit nonlinear algebraic equations in a set of nested Newton‐Raphson loops followed by numerical integration of the differential equations using a first‐order Euler technique.

It is found that the simulation algorithm may successfully be applied to an operating point model to predict the steady‐state values with errors under 10 percent. These results indicate that such engine models may be used to design reiable robust engine control systems because a robust control system design would allow for about 20 percent discrepancy between the model and the actual case.

At present, the research is limited to liquid propellant engines that are modeled by a set of implicit nonlinear algebraic equations coupled with a set of differential equations; engine models that are entirely modeled by differential equations are subject of future research.

The major outcome of this research is that verifies liquid engines may be simulated by the novel idea of following the engine liquids in their respective paths.

This is the first paper that adapts an existing simulation algorithm for simulation of the specific liquid engine under study with experimental verification.

Considering the direct impact of retailers' performance on the economy, this paper aimed to propose a comprehensive framework to evaluate the performance of different branches of a retailer.

Through a case study, the weights of indicators were calculated by the best-worst method (BWM) and the branches' performance was appraised using data envelopment analysis (DEA).

The branches were ranked in terms of performance, and sensitivity analysis and statistical tests were conducted to realize the weaknesses and strengths of the branches. Then, some strategies were proposed using strengths, weaknesses, opportunities and threats (SWOT) analysis to improve the performance of the weak branches.

This paper contributes to previous studies on the evaluation of retailers' performance by proposing a triple framework based on resilience, sustainability and sales-marketing indicators. This paper focused on branches' operations and branches' optimization by improving performance in terms of these three indicators. This paper also offers a qualitative and quantitative analysis of retailers' performance, which has received less attention in previous studies.

The purpose of this paper is to present an assessment of the ability of combined finite and slab element method (FSEM) for analyzing the wire flat rolling process.

Using the FSEM, the effective strain field of flat rolled wire is predicted for different reductions in height and frictional conditions. The validity of the method is assessed by performing the Vickers microhardness measurements on the flattened wire cross section. Also, the creation of macroscopic shear bands in cross section of the flat rolled wire is investigated and confirmed by microhardness and metallographic examinations. Moreover, the lateral spread and width of contact area are predicted by the FSEM for different reductions in height and frictional conditions.

The FSEM and microhardness results show the minimum and the maximum effective strains at the round edge and center of the flattened wire, respectively. Also, the results show the bands of maximum effective strain at cross section of the flattened wire, i.e. macroscopic shear bands.

This paper can be useful in rolling industries to produce electronic parts, various springs, trolley cables, piston rings, and guide rails.

The paper shows the applicability of the FSEM for calculating the effective strain field and geometry of wire after wire flat rolling process.