درخت حوزه‌های تخصصی

In this paper, we discuss a new type of Mann iterative algorithm for finding a common fixed point of two nonexpansive mappings in real Hilbert spaces, and we establish the weak convergence of this fixed point approach by considering new circumstances. We can also show the algorithm’s strong convergence by taking into account an extra requirement. Our results extend the previous results given by Kanzow and Shehu as well as by Cho at et. al. Also in the last section, some applications of the main results are shown, and by some examples, we show the generality of our main results.

The aim of present study was to investigate the fundamental power strategy in the stock market with the role of arbitrage cost versus feelings in companies listed on the Tehran Stock Exchange. The spatial domain of this research was the compa-nies listed on the Tehran Stock Exchange and the temporal domain was the years between 2014 and 2019. The present research is among the applied studies and it is descriptive in terms of nature and correlational in term of method. In this study, a library method was used to collect data and information. Based on the systemat-ic elimination method, 139 companies were selected as a statistical sample. De-scriptive and inferential statistics were used to describe and summarize the collect-ed data. To analyze the data, first the variance heterogeneity test, F-Limmer test, Hausman test and Jarque-Bera test were used. Then, multivariate regression test was used to confirm and reject the research hypotheses (Eviews software). The results showed that the fundamental power strategy could predict future returns, and shareholder feeling and arbitrage cost strengthen the relationship between the fundamental power strategy and stock returns.

The spread of volatility between financial indices indicates the process of information transfer between markets. Despite the relationship between financial markets, the information created in one market can affect other markets as well. Therefore, the main purpose of this study is to investigate the volatility of energy and steel prices and the experimental test of inter-market volatility spillover. To do this, the monthly data of steel and energy price (oil and gas) during 2009 to 2019 were collected from valid databank using VECM and GARCH Family and VAR model and ICSS algorithm were analyzed by considering and without considering structural failure. Then, the causal relationship between them is examined through Granger causality test. The results show that there is volatility in the energy market (oil and gas) as well as the steel market during the studied time period. Results also show that the price of steel as well as its return and index are changed significantly by energy price effect. However, there is a causal link between energy prices and steel products and these results are consistent with the theoretical basics of the study and review of literature.

Many studies have been conducted in the field of bankruptcy prediction; But in most of them only financial ratios are used. However, in Iran, many non-financial factors affect bankruptcy. The main purpose of this study is to develop a mathematical model in which financial and non-financial indicators such as management and economics factors are used to predict bankruptcy. In this study, 44 variables that had the greatest impact on bankruptcy forecast were selected and with confirmatory factor analysis, a questionnaire was developed and sent to experts in the fields of management, accounting and economics to rank the impact of these variables. The statistical sample of the study includes 200 bankrupt and non-bankrupt companies listed in the period 2009-2018. After collecting the questionnaires using the OLS regression estimation method, the variables that had a factor load of less than 0.5 were eliminated and in the final model 9 main variables. The research model identified 95% of bankrupt companies and 93% of non-bankrupt companies with 95.4% confidence. Then, for verification, two hypotheses were developed and the model of this research was compared with two existing models. The ability to distinguish bankrupt companies from non-bankrupt ones by our proposed model was 6% more accurate than the Pourheidari et al. model, and 9.4% more accurate than Altman’s model.

This study was an attempt to evaluate the progress of capital market efficiency in Iran. Optimal resource allocation and micro and macro investments play a key role in the capital market. The capital market's main task is to circulate capital and allocate resources efficiently and optimally. The main task of this market is to flow capital and allocate resources efficiently and optimally. Is there a regular pattern for determining the stock price? Market efficiency gains significance as it is important to know what factor or factors are effective in determining the price of the stock in the stock market or whether there is a regular pattern for determining the price of a stock. Thus, this study examined the efficiency of the capital market in Iran. In this regard, the researchers used the daily data of the total index of the Tehran Stock Exchange for 2008-2017. Artificial neural network and time series training tests were used to perform the test. The test results showed weak efficiency in the Tehran Stock Exchange and this inefficiency did not change significantly compared to the first period. In other words, in the Tehran Stock Market, one can predict returns using artificial intelligence.

The aim of this study was to investigate the ranking of effective factors on how to implement timely management of goods and equipment and its evaluation criteria in the power distribution company of the whole country using Analytic Hierarchy (AHP). Five dimensions (production technical factors, managerial level management factors, factors related to IT processes and infrastructure, factors related to processes and factors related to training and manpower) were determined and the research hierarchical tree was drawn. Based on the opinions of experts in this tree, five Next, on how to implement timely management of goods and equipment in time and its criteria interact with each other. To determine their weight, the combined approach of fuzzy AHP and fuzzy DEMATEL was used. The influential and expressive dimensions of each other are the cause, and the dimensions of the factors related to IT processes and infrastructures are part of the influential or expressive dimensions of other effects.

The purpose of this study is to present and explain the paradigm model of the role of behavioral characteristics and financial literacy of real investors on the components of their financial management behavior in the Iranian capital market. For this purpose, a 77-item questionnaire derived from qualitative studies using grounded theory method was used. The chi-square value of the model is equal to 3946.370, the degree of freedom of the model is equal to 2174, the result of which is equal to 1.815, and the fit indices of the original model are all in an acceptable and appropriate level. Behavioral characteristics and financial literacy can predict financial management behavior and help real investors analyze stock market trends before making a decision, which leads to investment profitability, financial security and capital satisfaction.

This study was conducted to determine the stock portfolio with the best return and low-risk investments using momentum-contrarian strategies (MCSs). The momentum-Contrarian strategy is one of the well-known models to construct the portfolio which suggests buying the stocks with the best performance (the winner stocks) and selling the stocks with the worst performance (the loser stocks). The optimal values of the portfolio's objective function and the weight of all assets in the portfolio that are not necessarily the same are calculated by defining a nonlinear multivariate optimization model combined with momentum-contrarian strategies (MCSs). The return information of companies listed on the Tehran Stock Exchange from 2014 to 2019 was used to select the best optimal portfolio. The results confirmed the stability in the profitability of the contrarian optimal portfolio with minimum risk compared to other optimal portfolios. Furthermore, through MATLAB software the optimal weight of assets in the optimal portfolio is calculated based on statistical data.

This research, in line with the strategy of the World Customs Organization, order to provide a structural model for improving the ethics and administrative health of employees based on the use of information technology in customs affairs with a combined approach of fundamental theory and interpretive structural modeling to understand how information technology affects ethics and Administrative health and investigating the power of influence and the degree of dependence of the variables of ethics and administrative health of employees in the form of drawing a comprehensive structuring model. In the implementation of this research, a mixed method was used in the qualitative part of the foundation's data theory according to the research needs and structured interviews were used to collect data. To collect data in a qualitative method, with the help of Maxqda software, research findings through the opinions of 13 experts in three stages of open-centered and selective coding in the form of 6 categories affecting the ethics and administrative health of employees in the form of the Strauss paradigm model and Corbin and it was expressed theoretically. After building the theory, in the quantitative stage, interpretive structural modeling has been used in order to understand the relationship between the variables and the leveling of the promotion of ethics and administrative health of Iran Customs. The results of the research show that the variable "use of smart technologies" is the first level variable in the promotion of ethics and health, and the variables "Analysis of the situation of manpower and customs processes, ethical characteristics of employees and laws and management of information technology and human resources" » is the second level variable. And the variables of "conditions and structure of the organization and the requirements and infrastructure of information technology" are the variables of the third level.

Modern organizations’ strategy is reducing inventory, production cycle time, transportation cost, quality cost, while increasing competitiveness to maximize its benefits. Supply chain management, as part of an organization’s strategy, involves several stakeholders with different interests, each controlling part of the chain and pursuing different goals. This paper presents a comprehensive multi-level model of a supply chain consisting of several simultaneous stakeholders in a systematic way. The developed model first, consider the various transportation factors, such as distribution of goods for various members of the supply chain to achieves the lowest transportation cost at different levels, for both transporting parts and products. The model also provides lowest costs of purchase and production by considering the costs of maintenance, supply shortages and shortage, for all the involved parties. In addition, a competition in the context of a game to select the optimal situation between the stakeholders of the supply chain has been considered to make the best decision in terms of a participatory game by considering different scenarios. Through applying the principles of the game theory, various scenarios were developed to optimize the benefits of parties and to achieve the optimal design. The results of a numerical example showed that the answer provided by the game theory for the value of the objective function was less than the answers of the transport problem, despite the deficit penalty. Therefore, it can be concluded that game theory can achieve a better answer by considering the conditions of alliance between participants in a collaborative game.

In recent years, industrial clusters have received considerable attention from economists and industry analysts because they are seen as the main reason for certain economic regions' economic growth and success. For many Industrial States Organization, the selection of industrial clusters has become a critical strategic consideration due to the Budget allocation priority. In this paper, an extended qualitative flexible multiple (QUALIFLEX) methods is used to solve problems regarding the priority among this cluster using probability hesitant fuzzy information, which can lead to allocating the budget for industrial clusters more effectively. For more accuracy, we have applied a Hesitant fuzzy Topsis for prioritizing. Both rankings have been aggregated by the Copeland method. From our research results, the Larestan Muscat is of great importance, and Abade Inlaid Wood, Citrus packaging, Shiraz Marquetry, and Niriz stone have ranked respectively.

Organizational DNA expresses a method of investigation, thinking, reflection and thought about organizations, which examines the patterns of organizations, management practices, leadership style and other concepts related to the organization. Organizational DNA uses very diverse approaches to understand and recognize the organization, instead of organizational models and forms, by examining issues such as teamwork, decision-making, and development and improvement of human resources as separate or at least independent variables. In this research, by using the theoretical framework and using quantitative and qualitative methods, it has been done to identify the dominant DNA in Tocafulad Holding companies and determine the relationship model of hidden components using covariance analysis. The statistical population includes 435 employees of Isfahan Tokafulad companies and 6 company experts who used a mixed or mixed design to conduct the research. The technique of structural equations has been used to improve the model and evaluate the components and indicators to check and identify the model. In order to answer the research question, the steps are: 1) presentation of the conceptual model of the relationship between the corporate DNA and the investigated components, 2) quantitative evaluation of the components and indicators of the model, 3) determining the mutual influence of the hidden variables and the obvious variables of the model and 4) the relationship Between the apparent variables of the components with each other and the verification of the initial conceptual model has been carried out and then the model has been improved and finally the dominant DNA has been determined. The research showed that semantic DNA with a factor load of 0.93 is the dominant DNA in 4 out of 6 companies under investigation. It was also found that planning and payment system are the least important and change processes are the most important in line with the improvement model. In the improved model based on covariance analysis, the mutual effects of payment system and planning with mission, leadership style with teamwork, performance management with decision-making, interpersonal relations with change processes and change processes with work group should be considered.

There has not been presented any comprehensive index for Corporate Governance in spite of its crucial role in resolution and responsiveness. Although diverse methods have been sought for measuring the Corporate Governance in the previous studies, in this study, a comprehensive index is proposed for measuring Corporate Governance taking other indexes into account through mathematical equations. For testing the designed model’s functionality, a set of data related to 149 firms from 2014 to 2019 has been used jointly, too. To do so, a questionnaire, which asks the experts their idea about the weight and significance of the criteria of measuring the Corporate Governance of the firm, is made and distributed and the weight and significance of the criteria were determined through one method of multi-criteria decision model (Shannon Entropy). To measure the changeable hidden relationship which exists in this study of the Corporate Governance, provided with the measurement items, a confirmatory factorial analysis was taken, too; results show that the supposed model has been a proper index for Corporate Governance. This mixed index includes criteria such as the board of directors' size, independence, meetings, and its education, the CEO's permanence, the size, independence, financial specialty, financial experience, tenure and the meetings of the auditors hip committee, ownership concentration, organizational ownership, governmental ownership, deals with the dependent persons, the quality of the disclosure, proper information and weaknesses if the internal controls,

Nowadays, customer satisfaction is regarded as a strategic and influential factor for the success of various businesses. On the other hand, tourism, the world's largest and most diverse industry, is also a significant source of income and job creation for many countries. Therefore, the present study examines the effect of nostalgia, experiential marketing, and experiential values as relatively novel concepts on satisfaction in the tourism industry. In light of the COVID-19 outbreak, the research population includes all tourists who have previously visited the Kashan Rosewater Festival. Furthermore, since the population size is uncertain, it is assumed unlimited. A convenience sampling method was used to select sample members from the population. Methodologically, it is a descriptive survey study based on the subject matter under investigation. It is also a correlational study. A partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the questionnaire results. Based on our findings, nostalgia affects pull motivation, patronage behavior, and future travel intention. However, pull motivation does not influence travel intentions.

The purpose of this study was to present an optimal model Predicting Future Cash Flows optimized neural network with genetic (ANN+GA) and particle swarm algorithms (ANN+PSO). In this study, due to the nonlinear relationship among accounting information, we have tried to predict future cash flows by combining artificial intelligence algorithms. Variables of accruals components and operating cash flows were employed to investigate this prediction; therefore, the data of 137 companies listed in Tehran Stock Exchange during (2009-2017) were analysed. The results of this study showed that both neural network models optimized by genetic and particle swarm algorithms with all variables presented in this study (with 15 predictor variables) are able to provide an optimal model Predicting Future Cash Flows. The results of fitting models also showed that neural network optimized with particle swarm algorithm (ANN+PSO) has lower error coefficient (better efficiency and higher prediction accuracy) than neural network optimized with ge-netic algorithms (ANN+GA).

The application of machine learning technologies for cancer detection purposes are rising due to their ever-increasing accuracy. Melanoma is one of the most common types of skin cancer. Detection of melanoma in the early stages can significantly prevent illness and fetal death. The application of innovative machine learning technology is highly relevant and valuable due to medical practitioners' difficulty in early-stage diagnoses. This paper provides an open-source tutorial on the performance of an algorithm that helps to diagnose melanoma by extracting features from dermatoscopic images and their classification. First, we used a Dull-Razor preprocessing method to remove extra details such as hair. Next, histogram adjustments and lighting thresholds were used to increase the contrast and select lesion boundaries. After using a threshold, a binary-classified version of image was obtained, and the boundary of the lesion was determined. As a result, the features from skin tissue were extracted. Finally, a comparative study was conducted between three methods which are Artificial Neural Network (ANN), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The results show that ANN could achieve better accuracy (83.5%). In order to mitigate the biases in existing studies, the source code of this research is available at hadi-naghavipour.com/ml to serve aspiring researchers for improvement, correction and learning and provide a guideline for technology manager practitioners.