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This study aims to use frequency response analysis, a powerful tool to detect the location and types of transformer winding faults. Proposing an effective intelligent approach for interpreting the frequency responses is the most crucial problem of this method and has created many challenges.

Heat maps based on appropriate statistical indices have been supplied to depict the variations in the frequency responses associated with each fault type, fault location and fault extent along the windings. Also, after analyzing the results of artificial neural network (ANN) techniques, the generalized regression neural network method is introduced as the most effective solution for the classification of transformer winding faults.

Using a comparative approach, the performance of the used indices and ANN techniques are evaluated. The results showed the proper performance of Lin’s concordance coefficient (LCC) index and the amplitude (Amp) part of the frequency response. The proposed fitting percentage (FP) index can assist the intelligent classifiers in diagnosing the radial deformation (RD) fault with the highest accuracy considering all frequency response components in the classification procedure of winding faults.

Various ANN techniques are used to detect and determine the type of four important faults of transformer winding, i.e. axial displacement, RD, disc space variation and short circuit. Various statistical indices, such as cross-correlation factor, LCC, standard difference area, sum of errors, normalized root-mean-square deviation and FP, are used to extract the features of the frequency responses to consider as the ANN inputs. In addition, different components of the frequency response, such as Amp, argument, real and imaginary parts are examined in this paper. To implement the proposed procedure, step by step, various types of winding faults with different locations and extents are applied on the 20 kV winding of a 1.6 MVA distribution transformer.

Contributions have been made in identifying and diagnosing transformer winding defects through the use of appropriate algorithms for future research.

This study aims to examine the reuse of plastic and fly ash (FA) to improve the soil and achieve sustainable development goals.

Sand from the Anzali port was reinforced with Geopet (GP) and stabilized with FA plus 3% sodium hydroxide. The GP was placed in FA-stabilized soil and the California bearing ratio (CBR), and unconfined compressive strength (UCS) tests were performed on samples at the optimum moisture content.

The results showed that the improvement in the optimum CBR was 174.9%. The UCS increased 15.25% and 48.65% in soil reinforced with three layers of GP plus 15% FA over those containing 10% and 5% FA, respectively. Additionally, the current analysis used response surface methodology (RSM) to investigate the impact of FA percentage, GP layers and their interaction on CBR. The results highlight the efficacy of the used RSM model, as evidenced by the significantly low p-value (<0.0001).

This demonstrates the suitability and effectiveness of RSM for evaluating CBR in this scientific study.

In Iran the role of entrepreneurs in developing communities is considered to be a special issue by planners and policy‐makers; thus the aim of this paper is to explore and examine some of the main structural, behavioural and environmental barriers faced by entrepreneurs in Iranian public industrial corporations.

A survey (questionnaires and interviews), observation and available documentation formed the main methods (triangulation) for the generation of relevant data. Thirteen public organisations responsible for social affairs in the country's budget document were involved. Using an unlimited sampling formula and a categorised random sampling method 220 organisations were accessed, from which 169 questionnaires were received and analysed.

There is a direct relationship between managerial characteristics and organisational entrepreneurship. Also, there is a significant correlation between employees' characteristics and organisational entrepreneurship in public social cultural organisations. However, a host of constraints such as low income and a lack of research have caused a decrease in organisational entrepreneurship.

The survey is concerned with managers in public organisations. Future studies should include private‐sector organisations, which ought to provide a basis for comparative analysis.

There is a need for sustained structural and managerial reform. To achieve this, realistic human resource development policies should be formulated which lead to changes of attitude and behaviour in managers.

This is a first attempt to study managers and their entrepreneurial tendencies in public sector organisations. It has policy implications for future development of the sector.

The purpose of this paper is to propose a gauge for the convergence of the deterministic particle swarm optimization (PSO) algorithm to obtain an optimum upper bound for PSO algorithm and also developing a precise equation for predicting the rock fragmentation, as important aims in surface mines.

In this study, a database including 80 sets of data was collected from 80 blasting events in Shur river dam region, in Iran. The values of maximum charge per delay (W), burden (B), spacing (S), stemming (ST), powder factor (PF), rock mass rating (RMR) and D80, as a standard for evaluating the fragmentation, were measured. To check the performance of the proposed PSO models, artificial neural network was also developed. Accuracy of the developed models was evaluated using several statistical evaluation criteria, such as variance account for, R-square (R²) and root mean square error.

Finding the upper bounds for the difference between the position and the best position of particles in PSO algorithm and also developing a precise equation for predicting the rock fragmentation, as important aims in surface mines.

For the first time, the convergence of the deterministic PSO is studied in this study without using the stagnation or the weak chaotic assumption. The authors also studied application of PSO inpredicting rock fragmentation.

The appearance of social media in small and medium enterprise (SME) business operations seems to be increasing in recent years. SME owners have started to understand that digital marketing tools can benefit their businesses significantly. Hence, in this study, we explore further the relationship between organisations and customers, and how SMEs use social media as an opportunity to develop their enterprises. We report the results by relying on qualitative methods to explore the insights from a wider stakeholder perspective. The findings contribute to the existing literature in agreement with the latest theories that SMEs in Greece are aware of the hidden opportunities and try to apply branding with the combination of social media. This study explores further the role of electronic word of mouth (eWOM) in a business transition, customers' experience and competitive business advantage.

Due to the political, economic and infrastructure barriers and risks that international entrepreneurs (IEs) face when researching an emerging economy's agrifood sector, this research aims to identify the major barriers, analyse their relationships, quantify their importance, classify and rank them. Thus, the IEs will gain a better understanding and vision of their decision-making processes in this era.

To do this, the authors first created a list of barriers to entry for IEs into Iran's rising economy's agrifood industry. Following that, a multi-layer decision-making approach was developed and implemented to accomplish the research objectives. The first stage utilized a hybrid of interpretive structural modelling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) to depict the level-based conceptual model and classification of the IEs’ obstacles to entry into the agrifood sector. Following that, a hybrid decision-making trial and evaluation laboratory (DEMATEL), and analytic network process (ANP) called DANP was utilized to present a causal relationship between the barriers, identify their causes and effects, and also quantify the relevance of each barrier.

After employing the multi-layer decision-making approach, the results demonstrated that fundamental limitations, including infrastructure and technology limitations, are the most critical barriers alongside policy factors encompassing governmental support and access to global or regional economy/market. According to the results, innovation and economic sustainability of the agrifood supply chain also matter. All of these critical barriers are intertwined and should be planned and solved simultaneously. Furthermore, based on DANP results, the sustainability pillars (economy, environment, society), besides the low efficiency of the agrifood sector in Iran, should be investigated further for future policy makings.

A hybrid multi-layer decision-making approach has been used for analysing the barriers of investment in the agrifood sector of the emerging economy of Iran for the international entrepreneurs. Moreover, the authors provide implications and insights for IEs and officials for decision-making in the future.

This study investigates consumers' willingness to adopt genetically modified foods (GM) and the role of innovation and behavioral determinants.

A new integrated model that expands the Health Belief Model (HBM) into the Innovation Diffusion Theory (IDT) was developed and examined. A total of 241 consumers were selected from the capital of Iran, Tehran, through a multistage random sampling. The data were analyzed using SEM-PLS modeling.

The extended HBM model was able to predict about 84% of the variance changes in consumers' willingness to adopt GM foods. The effects of net benefit and perceived compatibility on the willingness were also significant. In addition, the mediating effect of compatibility on the relationship between net benefit/self-efficacy and willingness to adopt GM foods was also significant.

This study contributes to the literature by developing the HBM into the IDT to assess consumers' willingness to adopt GM foods.