فهرست مطالب علیرضا ایرجپور

In response to the Covid-19 pandemic, governments around the world have imposed severe traffic restrictions and presented different scenarios to reduce emissions from traffic sources. By applying the traffic restrictions caused by the Covid-19 epidemic, it was expected to see changes in the concentrations of air pollutants. Therefore, it was decided that the changes of air pollutants as one of the subsets of the environmental index of sustainable urban development during the covid-19 epidemic will be investigated. For this purpose, the aforementioned data are first collected in the four metropolitan cities: Tehran, Karaj, Ahvaz and Tabriz, and then processed and cleaned. After that, a proposed algorithm based on machine learning methods is presented. Machine learning methods decision tree, random forest, support vector machine, Bayesian network and perceptron neural network are applied to the selected features. Investigations showed that the prediction model using decision tree and random forest had the best performance for both recall and accuracy criteria. The research results showed that the effect of restrictions on the concentration of pollutants in different cities is different. Also, the results show that, in general, the application of traffic restrictions during the epidemic period did not have a significant and noticeable effect in reducing the concentration of air pollutants. Also, the studies showed that the application of traffic restrictions and consequently the possible reduction of some air pollutants are not related to the deaths caused by Covid-19.

Given the potential impact of blockchain technology on the banking industry, it is crucial to explore how this technology influences business models within the sector. This understanding can provide valuable insights into how value is created, delivered, and captured in banking. The main objective of this article is to present a blockchain technology framework as applied to fintech in the financial and banking sectors. This study employs metacomposition to identify key factors, the fuzzy Delphi method to evaluate, refine, and localize the model, and the Dimetal technique to analyze relationships and effects. The research involved a systematic review of 849 articles (ranging from 1395 to 1402 in the Iranian calendar for domestic articles, and from 2016 to 2023 for international articles), from which 73 articles were selected and analyzed using content analysis. Subsequently, 7 dimensions, 23 components, and 102 indicators were validated and localized with the assistance of 17 experts. In the final stage, these dimensions and components were prioritized with expert input, leading to the extraction of the final framework. The results indicate that fintech-driven blockchain technology enhances value creation in the dimensions of innovation and technology, transparency, security, quality, speed, business models, and collaboration, providing strategic capabilities to financial and banking businesses.

Considering the importance and role of tax in the economic cycle of the country, in this research we are looking for the design of the tax ecosystem model. The purpose of this research is to provide a model of antecedent and consequential factors of the value added tax ecosystem model, which causes the agility of the supply chain. This research is qualitative and basic in terms of its purpose. Also, according to the method of data collection, it is considered a type of field research. The statistical population of the research is university professors, employees of tax audit offices and senior managers of tax administration in the country. The data collection tool in this study was a semi-structured interview. In this research, theoretical sampling was used and the sample size was 10 people according to theoretical saturation. For the validation of the model, the fuzzy Delphi method was used, and in this section, 16 people were considered as a sample, and according to the results, the indicators identified in the qualitative section were confirmed. According to the results of the research, there are two categories of themes. The main themes were discovered. The first group includes the main themes that have been identified as antecedent or influencing factors on the creation of the VAT ecosystem, and the second group includes the main themes that have been identified as consequential or influencing factors. According to the results of the antecedent and consequent model of the tax ecosystem, factors such as the reduction of tax costs, the tax culture of self-disclosure and the reduction of tax evasion can be important consequences of planning the tax ecosystem.

In response to the Covid-19 pandemic, governments around the world have imposed severe traffic restrictions and presented different scenarios to reduce emissions from traffic sources. By applying the traffic restrictions caused by the Covid-19 epidemic, it was expected to see changes in the concentrations of air pollutants. Therefore, it was decided that the changes of air pollutants as one of the subsets of the environmental index of sustainable urban development during the covid-19 epidemic will be investigated. For this purpose, the aforementioned data are first collected in the four metropolitan cities: Tehran, Karaj, Ahvaz and Tabriz, and then processed and cleaned. After that, a proposed algorithm based on machine learning methods is presented. Machine learning methods decision tree, random forest, support vector machine, Bayesian network and perceptron neural network are applied to the selected features. Investigations showed that the prediction model using decision tree and random forest had the best performance for both recall and accuracy criteria. The research results showed that the effect of restrictions on the concentration of pollutants in different cities is different. Also, the results show that, in general, the application of traffic restrictions during the epidemic period did not have a significant and noticeable effect in reducing the concentration of air pollutants. Also, by comparing the change in air quality index with the death rate during the epidemic period, it was found that there is no relationship between them.

By applying the restrictions caused by the Covid-19 pandemic, it seems that changes in the concentrations of pollutants CO, O3, NO, NO2, SO2, PM2.5, PM10 and AQI can be seen in the periods before and after the epidemic. Therefore, the changes of air pollutants and traffic restrictions are investigated as one of the sub-categories of environmental indicators of sustainable urban development in the period of 2018/01/21 to 2022/03/20 in the stations under the supervision of Tehran city. First, the data is collected, processed and cleaned. Machine learning methods including decision tree, random forest, support vector machine, Bayesian network and perceptron neural network are applied to select the effective features using the particle swarm optimization method. Investigations showed that the prediction model using decision tree and random forest had the best performance for both precision and recall criteria. The results of the research showed that the concentration of pollutants in the period of Covid-19 compared to before, is increased in some stations and decreased in others, and also the application of traffic restrictions during the epidemic did not have a significant and noticeable effect in reducing the concentration of air pollutants. Also, by examining the trend of deaths during the epidemic period, it was found that the decrease or increase of pollutants has no significant relationship with the trend of deaths caused by Covid-19.

The timely production of orders and their delivery to the customer is a competitive advantage that makes production systems and becomes customer satisfaction. Balancing the load of orders on work stations, reducing the time of the production period and minimizing the cost of human skills and access to machines can be components in the cases of balance of production lines. In this article, by addressing the above components of the mathematical model, several objectives for checking the online load balance are presented. Solving the mathematical model is done by introducing the combined meta-heuristic algorithm of multi-objective genetics and ant milk, this solution method selects the fittest parents based on the fitness of the initial population by using the feature of selecting the initial population and having the search memory to find quality answers at the right time. produces. The results obtained compared to the previous online load balancing methods show that the production time and load balance on the workstations have been improved.

This research has been carried out to identify the effective factors in the formation of the technology-based entrepreneurship ecosystem in the technical faculties of the University of Tehran.

First, by reviewing the extant literature, the effective factors in the formation of the technology-based academic entrepreneurship ecosystem were identified. Then, the collected items were completed by conducting in-depth and exploratory interviews with 17 specialists and experts in the research community. Using an open and axial coding method, nine main factors affecting the formation of the technology-based university entrepreneurship ecosystem were obtained. By distributing paired questionnaires among experts and with the help of the structural-interpretive modeling method, the components of the model were configured in six levels.

A six-level model was developed. The first level included the infrastructure components of entrepreneurship ecosystem development, policy and management of financial resources, intensity and level of design preparation, development and commercialization, creation and development of supporting institutions, and business development in the region. The second level included the university policy and rules component.  The market component stood in the third level. The fourth level embraced the economic factors and the business environment. The fifth level included the governance factors and the last level included the cultural component of the academic technological entrepreneurship ecosystem. It was also shown that the cultural component is the most influential factor and the infrastructure components of entrepreneurship ecosystem development, policy, and financial resource management, intensity and level of preparation for design, development, and commercialization, creation and development of supporting institutions, and business development in the region were the most effective factors in the formation of the technology-based academic entrepreneurship ecosystem in the University of Tehran.

The development of entrepreneurial culture and spirit is the base of the formation of the university entrepreneurship ecosystem. Relying on technology, it can be implemented by applying correct policies and competent management at both micro and macro levels.

The current research was conducted with the aim of providing a fuzzy model for the evaluation of business plans focused on the development of new products. This research can be used in the industrial cluster of chemical production and systematically examines and analyzes the development of new products. It is an exploratory-modeling research method in terms of practical purpose and in terms of implementation. . In this research, the present research community consists of 12 experts from chemical industry companies. In order to analyze the data, fuzzy Delphi technique has been used. The results show that 6 exogenous variables were selected as key variables in the selection and development of a new product in the organization. In order to determine the importance of exogenous variables that experts doubt in specifying their importance, the method of fuzzy fuzzy analysis technique was used. (0.239), new product development strategy (0.209), level of passing standards and requirements (0.136), absorption of product development research funding (0.077) and absorption of applied research funding (0.061). The dynamic product development model, which is based on the cause and effect relationship, needs to be designed and tested in future studies to simulate the current and future decision-making performance.

Various researches have been done on the development of new products based on innovation. There is also a significant increase in studies in which there is a concept of "systemic approach". However, according to previous researches, decision-making in hesitant atmosphere to select exogenous variables of business development model based on new product development was not observed. The main issue in this research is to investigate and find the factors affecting the feasibility of new product development plans and finally to obtain a method for evaluating new product development plans in industry. In evaluating economic plans, the parameters are usually considered definite, but the study of uncertainty is important considerably. The results show that 6 exogenous variables were selected as key variables in the selection and development of a new product in the organization. The weighted importance of variables is the share of new product acceptance in the market (0.275), new product development investment confidence (0.239), new product development strategy (0.209), level of passing standards and requirements (0.136), attracting development research funding Product (0.077) and Applied Research Fundraising (0.061). The dynamic product development model is designed based on the cause-and-effect relationship and in future studies needs to test the simulation performance of present and future decision making .

The development of a technology-based entrepreneurship ecosystem in universities leads to great economic changes in society. This paper aims to identify the influencing factors for the design of the technology-based entrepreneurship ecosystem model in the College of Engineering of Tehran University. Based on grounded theory as a qualitative method, 17 interviews were conducted with experts and after coding, 51 sub-categories were obtained in the form of 9 main categories. To validate the components, a questionnaire was distributed among the academics and researchers of the College of Engineering of Tehran University, and it was analyzed by the partial least squares method, and all the components were confirmed. Finally, with the help of the structural-interpretive modeling method, by distributing 23 paired questionnaires among the experts, the components of the model were configured in six levels. The findings showed that the category of "culture" is the most influential factor and the components of "Entrepreneurial ecosystem development infrastructures", "Policy and management of financial resources", "Intensity and level of preparation for design, development and commercialization", "Creation and development of supporting institutions and business development in the region" are the most influential factors in the formation of the technology-based entrepreneurship ecosystem in the university.

In today's competitive and dynamic environment, organizations desperately need to increase their entrepreneurial capabilities to maintain growth and profitability in corporate entrepreneurship, and this is only possible through the exchange of innovative ideas and the opening of organizational boundaries; Therefore, the aim of this study is to provide a model of corporate entrepreneurship in the banking of the Islamic Republic of Iran, to identify the conditions and factors that should be considered in corporate entrepreneurship. The statistical population included experimental and theoretical experts in this field. The data collection method was in-depth interviews with 18 experts active in the field of banking and sampling was done in a targeted manner. Data analysis was performed using Maxqda software in three stages of open, axial and selective coding. After open coding, categories and concepts are extracted. 65 open source, 19 concepts and 6 categories were extracted from the collected information based on the data theory process of the foundation. The results showed that in the phased coding stages of corporate entrepreneurship as the main category and causal conditions (corporate entrepreneurship capabilities, strategic innovation capabilities, and strategic entrepreneurship capabilities), underlying factors (structural, environmental, behavioral), intervention factors, strategies (innovation, coalition, networking, growth strategy) and outcomes (market, customers, economy, technology) are designed. In general, the corporate entrepreneurship model in banking is presented in the form of a paradigm model based on grounded theory.

Several  studies show that apprenticeship in the field have not been able to improve the professional ability and competence of students to the desired level. Therefore, this study was conducted to Compare the effect of two methods of internship and apprenticeship in the field on clinical competence of nursing students.

This is a quasi-experimental study in which two methods of internship and apprenticeship in the field were performed for 89 final year nursing students in two groups for two semesters. Data were collected using demographic information and clinical competency questionnaire that its validity and reliability was confirmed by content validity and chronbach`s alpha( 0.93) respectively. Data were analyzed by descriptive statistics,paired t-test and chi-square test with  statistical significance( p<0.05)  through SPSS.

Paired t-test showed that the mean score of total clinical competencies and dimension of care management, its individual management in the apprenticeship group of two times did not differ significantly (P> 0.05) and in other dimensions in the apprenticeship group was significantly higherat the end of the semester than before the beginning of the semester (P <0.05). Also, the mean score of total clinical competencies and all its dimensions in the internship group after the end of the semester was significantly higher than before the beginning of the semester and in the internship group this increase was greater. (P <0.05).

Using the internship plan for final year nursing students improve their clinical competence, which will definitely improve the quality of care of patients and reduce  clinical care errors . Therefore, the use of internship plan for clinical education of nursing students is recommended.

In general, social and economic systems can be defined in terms of common sets of common expectations for each behavior. Therefore, accountability can be considered as a factor that connects the research and development system to industry. In this regard, after examining different models in the field of learning and innovation in society and research and development and accountability, a comprehensive new model that introduces important approaches in research and technology and organizational accountability including: managerial accountability, bureaucratic accountability Political and social accountability, market accountability and professional accountability have been extracted. Then, for each approach (dimension), ten components with different metrics (fifty metrics in total) are considered. In this research, acceptance of research and technology has been used as a new paradigm to make organizations more responsive to internal customers or employees. In this regard, after confirming the appropriateness and efficiency of the model by academic and gas industry experts (managers and experts), the main and secondary hypotheses in a field study using the gas industry data were tested and the results show that It is that the review of bureaucratic, economic, managerial criteria, market index, customer orientation and political, social approach and after reviewing through t-test, the coefficient of effectiveness of each of the indicators was measured and ranked. The basis of ranking, management index with a coefficient of 0.412 and bureaucracy with a coefficient of 0.571 in the acceptance status indicate that the research and development accountability model is successful and can be considered in policy and planning.

In today's world, corporate entrepreneurship plays an important role in the development and survival of organizations in the face of turbulent environments and sudden changes. The purpose of this study is to provide a corporate entrepreneurship framework in Iranian banking using the Meta-synthesis method. This applied research in terms of the objective was a descriptive study, as far as its nature was concerned; and, the effort had been made in the research for previous studies to be reviewed systemically and for output achievements to be analyzed. Accordingly, and through a selection of 37 types of research from among 365 recalled kinds of research; codes of the framework had been counted. The provided framework has 3 categories and 18 concepts obtained through a review of thematic literature and views provided by experts dominating the field. Kappa coefficient being 0/752confirms quality of the framework provided. The final framework includes 3 main codes of corporate entrepreneurship capabilities, strategic entrepreneurship, and strategic innovation along with related indicators in this field. Also, the proposed framework was able to address banking challenges and create the right environment to formulate entrepreneurial policies, improve service quality and achieve effective innovative goals.

Recently, recruitment of clinical nursing faculty members with the aim of reducing the theory-practice gap and improving the quality of clinical education is being implemented in some nursing and midwifery schools in Iran. However, the dimensions of this approach have not been studied. The aim of this study was to identify the factors affecting the implementation of clinical nursing faculty regulations.

The study was performed by descriptive qualitative method. By purposeful sampling method, 24 participants of clinical nursing faculty members and PhD nursing students in the participated in the study. Data were collected by individual interviews, focus group discussions and receiving electronic descriptive answers and analyzed by conventional content analysis method.

Effective factors were described in 2 categories: "Barriers to implementation of clinical nursing faculty" and"Facilitators of implementation of clinical nursing faculty" and 4 subcategories include; Psychological challenges, structural problems, organizational transparency, and organizational justice.

Psychological challenges and structural problems are among the executive barriers of clinical nursing faculty. Organizational transparency and organizational justice can facilitate the process of implementation of clinical nursing faculty.

The purpose of this study is to design a multi-objective model of fuzzy closed-loop supply chain network in the automotive industry with an urban management approach. Automobile manufacturing is a complex and energetic process that consumes significant amounts of raw materials and water. To continue the competition, major automotive equipment manufacturers must strive for better product quality by continuously improving their production process and directing low-carbon emissions and increasing sustainability. In this regard, reverse supply chain networks and closed loop chains have special features that are very useful in the industry under study.

In the present study, in order to achieve the research objectives, a quantitative research method will be used and based on the purpose, it is defined in a practical way. In this study, we use the MOPSO method to facilitate its implementation and its ability to provide good convergence, as well as to maintain a proper balance between exploitation and exploration, as well as the NSGA II genetic algorithm.

In the study of the findings of the proposed algorithms, it found that the average error resulting from these algorithms is less than 0.04. The results also show that the proposed algorithms have the necessary efficiency in solving these problems.

The notable results of our model are as follows: (1) an efficient closed-loop network that demonstrates the economic benefits of considering the value of time over the recycling of a worn product. (2) It has the ability to show the capacity to achieve maximum benefits in terms of cost value as well as the environmental perspective of what capacity it should maintain.

The Ministry of Defense is responsible for planning, coordinating, supporting, and expanding defense capabilities.it is the ministry's task to equip the defense forces to deal with potential threats.it is imperative for the defense industry to follow the constraints that preclude their inherent missions from seeking a procedural change. According to the findings of this study, this will be done by agency representatives using agency theory.Modeling this research, considering the concepts of supply chain and dealership theory simultaneously, it intends to apply the capabilities and capabilities beyond the organization's boundaries and to organize the network of industrial agents to supply the required and widely used components in the final product. Design stakeholders.In this approach, we aim not only to reduce costs but also to increase the utility of the parties in the relationship between agent, owner and customer.The proposed model is one of several types of decision making models.The fuzzy multi-objective decision making method is used to solve the model.Solving the model using the parameters present in the current situation in the relevant organization showed that the model with optimal resource allocation has been able to generate more overall utility for the system. According to the average results, the utility of the organization in the current situation equals 19% of the various sectors. By optimizing the allocation of resources by the model, the utility can reach 60%.

According to previous research, most studies on the evaluation of sustainable supply chain capabilities are limited to statistical variables and mathematical modeling. The purpose of this study is to propose multiple capacity evaluation models in the sustainable supply chain. The spatial scope of this research includes a survey of 16 companies active in the ceramic & tile industry in Iran. According to fuzzy expert system modeling, four capabilities, including competitiveness, operational, technology, and resilience as input variables and three levels for sustainable supply chain capabilities as output variables were determined. Simulink was used to simulate and integrate the designed fuzzy systems. The evaluation results show that most of the companies studied fall into the level 2 capability. It is recommended that the ceramic tile manufacturing companies evaluate the level of capability and determine the sustainable capabilities of their supply chain capabilities to exploit these variables. Resiliency capabilities have an impact on upgrading the evaluation of multiple capabilities in the sustainable supply chain. Therefore, companies are advised to incorporate flexibility and adaptability into developing domestic and foreign markets and market orientation and not to define future projects as environmental changes.

Traumatic brain injury management focuses on the prevention and treatment of secondary brain injuries. The aim of this study was to adapt a clinical guideline (CG) for nursing care of secondary brain injuries in adults.

This study was carried out through a multi-stage evolutionary study at Isfahan University of Medical Sciences in 2017. Based on the opinions of experts using AGREE tool, the quality of 8 out of 13 CGs for the treatment and care of head injuries was assessed as optimal. These were used in drafting the adaptive CG. In addition, 12 CGs, 13 articles and 5 books were used to complete the recommendations of the mentioned guideline. The CG draft was evaluated using the Delphi method and the panel of experts. Finally, it was presented as an adaptive CG.

The adaptive CG for nursing care of secondary brain injuries was developed in 158 recommendations and five sections; nursing care to prevent and manage the increased intracranial pressure, nursing care to maintain and increase cerebral blood pressure, nursing care to prevent and control seizures, nursing care to prevent and control brain infections, and nursing care to prevent and control secondary extracranial injuries.

The nursing staff of emergency and neurological wards and intensive care units can apply the recommendations of this clinical guideline to address some of the care needs of the injured patients and improve their health conditions.

Balanced production line in terms of timing and load distribution on machines can improve the important indicators of timely delivery and production, which creates customer satisfaction and competitive advantage for production.Production line balance reduces lost capacity costs and unbalanced lines.Robin Hood algorithm is one of the production balance methods, the most important advantage of which is online production planning and proportional distribution of load on machines, but when the number of work orders is large, this method is not responsive.This paper focuses on optimizing and developing the mathematical model of Robin Hood algorithm so that this model can plan a large number of work orders.Development of the model with two objectives minimizing the maximum load on the production system and minimizing the order completion time Takes place on machines.The problem of production balance is one of the NP-hard problems, and since no Iuick and feasible solution to such problems has been found in a reasonable time, the NSGA algorithm can be found to find close to optimal solutions to the proposed multi-objective mathematical model.-II has been used.The results of the development of the mathematical model in Robin Hood algorithm show that the balance of the production line in the large number of orders and momentary changes in the production plan, using this method can improve production planning.

Today, green supply chain managers in leading companies strive to offer green logistics and improve their environmental performance throughout the supply chain as a strategic weapon to gain a sustainable competitive advantage by creating profitability and satisfaction across the supply chain. Therefore, considering the purpose of the research, which is to design a multi-objective model of closed-loop supply chain networks in the automotive industry according to energy efficiency and time efficiency plans, we try to model the closed-loop supply chain in the automotive industry.

In this study, we use the MOPSO method to facilitate its implementation and its ability to provide good convergence, as well as to maintain a proper balance between exploitation and exploration, as well as the NSGA II genetic algorithm.

In the study of the findings of the proposed algorithms, it found that the average error resulting from these algorithms is less than 0.04. The results also show that the proposed algorithms have the necessary efficiency in solving these problems.

We note the significant findings of our model as follows: (1) An efficient closed-loop network that shows the economic benefits of considering the value of time due to the recycling of worn-out products. (2) Has the ability to demonstrate the capacity to achieve maximum benefits in terms of cost value as well as environmental prospects.

One of the most important problems at the tactical level is the mass production of different orders, each of which has different priorities according to the production conditions and the importance of customers. The production line consists of several workstations and machines, each in production frequency. They are interconnected and the input is one output. In this case, each machine and process that must produce the product is faced with process and technology limitations in terms of time, volume and weight of each work and physical health of machines, manpower efficiency. This article aims to take into account all the factors affecting the balancing of the production line, which is of particular importance in workshop production planning, and by analyzing the history of solving the problems of the production line and using experts, the component Identify the ones that are effective in planning and scheduling the production line, and using the combined method of Swara and Copras, these effective components add to the balancing algorithm in time in production systems. The results of this study show that the update made in the balancing algorithm during the production line compared to the previous methods has operational capability and quality in results