International Journal Of Nonlinear Analysis And Applications
Volume:15 Issue: 4, Apr 2024

In the Hyers-Ulam-Rassias stability depending on the type of the function whose stability we want to verify a suitable functional equation is used. The authors in [6] want to investigate the Hyers-Ulam-Rassias stability of $n$-Jordan $C^*$-homomorphisms on $C^*$-algebras, but they used a quadratic functional equation while we know that the homomorphisms are linear on $C^*$-algebras. In this paper, we correct the main results of  [6]  by removing the quadratic functional equation and replacing the linear one and removing some extra conditions. We also show that by using some other multi-variable linear functional equations, the estimation becomes better and more accurate.

In the current paper, we numerically investigate the approximation of a timewise-dependent heat transfer coefficient (HTC) along with the temperature in the one-dimensional heat equation with the third-type boundary conditions and an integral measurement. We utilize the integral overdetermination condition to reformulate the third-type boundary conditions and seek the solution to the converted problem in the form of the linear combination of the method of fundamental solutions and the heat polynomials. By applying the collocation method, the problem is reduced to the solution of a linear system of algebraic equations. The method takes advantage of the combination of the natural cubic spline technique and the Tikhonov regularization method to provide a stable approximation of the derivative of the perturbed boundary data. We provide several numerical tests to show the effectiveness of the proposed method.

Artificial intelligence plays an important role in the field of personal computers. Right now personal computers are part of our lives, so AI should be used in all everyday tasks. Humans are great thinkers, but machines can be more effective at counting than humans. The machine cannot fully explain different conditions, but it can create a different type of connection between different salient points and features. Either way, there can be many benefits to establishing machine learning computing in our daily lives. Machine learning or machine learning is one of the subsets of artificial intelligence that enables systems to learn and improve automatically without explicit programming, and controlling the credit risk of real bank customers is one of these benefits that can help the monetary and banking system to improve conditions and reduce risk. Therefore, the use of machine learning to create an algorithm to manage credit risks is a topic addressed in this research.

Luxury brands in various industries are one of the most attractive and profitable segments of the market, which, in addition to economic advantage, helps to develop the quality level of those products in the world by creating competition among luxury brands. Meanwhile, marketers and brand owners are constantly creating loyalty programs for their fanatical consumers. The purpose of this research is to identify the mental pattern of fanatical consumers towards luxury brands. The current research is of mixed exploratory type and was done using the Q method. The statistical population of this research is the customers of luxury watch brands. A sufficient number of statistical samples were asked based on theoretical saturation in a purposeful and accessible manner, six experts familiar with the subject were interviewed, and in a small part, 38 fanatical customers were interviewed to sort sample expressions into They were selected purposefully. The mental model of obsessive consumers included four types: devoted, deceitful, pleasure-seeking, and dysfunctional, which explained about 79\% of the variance of the views. Fanatic and dedicated consumers were the dominant model of this research. Finally, implementation suggestions were presented for each of the mental patterns of fanatical consumers for the use of luxury brand owners.

Profitability is an intrinsic factor to keep the bank strong because profitability shows that a bank is operating efficiently. Considering the strong relationship between a strong banking system and economic growth, research on the determinants of bank profitability has been widely conducted. However, according to the extent of the studies, there is no proper and consistent attitude regarding the factors that determine the bank's profitability. Accordingly, the purpose of this research was meta-analysis of factors affecting the profitability of the banking industry. This research was based on the purpose of applied-developmental research. In order to achieve the purpose of the study, first, articles were searched with the keywords of banking profitability and banking performance, and finally, 51 studies were selected for meta-analysis based on the inclusion and exclusion indicators of the articles. In order to analyze the data in this research, the overall effect size index and Z value were used to check its significance. Also, in the diffusion detection section, along with the use of funnel and precision charts, Duvall and Toid indices have been used to show point estimates and obtain error-free Q and N values. The results of the research show that there are 14 effective factors for the profitability of the banking industry, the most important of which are inflation, deposits and operational efficiency.

Many studies have addressed supply chain that shows the importance of the subject and the competition in the supply chain consisting of several companies. The previous studies address the issue of reducing the Bullwhip Effect in the supply chain, which is possible by predicting the correct amount of customer demand. This paper improves the accuracy of the model prediction and reduces the existing error in the previous models to attain an accurate and very close-to-reality forecast and also to reduce the Bullwhip Effect in the supply chain. Literature shows the absence of research on the presentation of a metaheuristic algorithm consisting of a neural network and bat algorithm to forecast supply chain demand in manufacturing companies; therefore, this article is innovative. On the other hand, no researchers have addressed Bullwhip Effect reduction using mixed metaheuristic algorithms. Therefore, this article improves the previous models, reduces the number of errors in demand forecasting, and reduces the Bullwhip Effect. For this purpose, the scalable gradient algorithm method is used for better network training. The results indicate the optimal performance of neural network training with a comparable gradient and bat algorithm on reducing the Bullwhip Effect.

The aim of the current research is to design a model to develop the market share based on the strategies for entering the international market of the National Iranian Drilling Company. A quantitative and qualitative mixed method was used to achieve this goal. In the qualitative phase, the data were collected through interviews with 12 experts using the snowball sampling method and analyzed with the help of the Foundation's data theory in three stages of open, central and selective coding. The findings of this phase showed that 39 concepts can be identified, which can be classified into 17 categories by examining the conceptual similarity, which can be classified as components of the paradigm model, which can be based on the main criterion of causal conditions (government support, factors related to the country of origin and factors related to the target market), the central phenomenon (maintaining the market share and increasing the market size), the dominant base (communication and functional infrastructures, specialized infrastructures, appropriate policy-making and planning), intervening conditions (political and economic factors, cultural factors and social), strategies (customer orientation, empowerment and promotion of international capabilities, participation in investment and non-participation in investment) and consequences (improvement of technology, growth and survival, and credibility and reputation of the company). In the second phase, using the opinion of experts and using the AHP hierarchical analysis method, the determined criteria were identified and prioritized. The results of this stage showed that the criterion of the leaders with the highest weight of 0.278 and the criterion of the ruling platforms with the lowest weight of 0.081 can play a role in the development of the market share of this company.

Architectural models serve as a bridge between the idea and its realization. Moreover, it is considered one of the main means by which the architect invents and develops his design. The “Architectural Models” course in many architectural schools introduces the basics of implementing architectural models. Students learn how to think of and build architectural models using different materials. While many of these courses overlook how to think about architectural concepts using physical models. The aim of this research is to state and examine strategies for generating architectural ideas using physical models. This paper discusses various strategies for generating architectural ideas using physical models. Furthermore, it illustrates an experiment conducted in the “Architectural Models” course in the Department of Architecture and Environmental Design at the Arab Academy for Science and Technology, Egypt, which was offered in 2021. The experiment was followed by a small questionnaire. The experiment aims to stimulate the creation of innovative architectural forms using physical models. The role of architectural models goes beyond presenting projects.  Therefore, the intended learning outcomes of the “Architectural Models” courses in architecture departments should be developed. Strategies for generating ideas using architectural models were adopted and applied. This is the first paper in which such strategies are examined. The final students' products were very good, and their feedback was very encouraging.

This research was carried out with the aim of providing an optimal integrated model of the chicken supply chain based on the human resource management system among the group of well-raised poultry farms in the whole country. In terms of the purpose of this research, it is the type of applied and exploratory research; And from the point of view of the method of collecting information, it is descriptive and survey type (due to the use of a questionnaire). The statistical population of the research was all the employees of Behparvor Group's poultry farms in the whole country, based on the table of Karjesi and Morgan, 337 people were selected as a sample, and the same number of questionnaires were distributed and collected. A research questionnaire based on interviews with the company's experts in the form of four dimensions of the challenges of the chicken production supply chain with an emphasis on the human resource management approach, the success factors of the chicken production supply chain with an emphasis on the human resource management approach, the limitations of the chicken production supply chain with an emphasis on the resource management approach humane and optimal supply chain of chicken production was designed. The information collected by questionnaires was analyzed by SPSS and Smart PLS software using structural equation modeling. The analysis of the research hypotheses using structural equation modeling at the 95% confidence level showed that the challenges of the supply chain of chicken production with an emphasis on the human resource management approach have a negative and significant effect on the optimal supply chain of chicken production. The success factors of the chicken production supply chain with emphasis on the human resources management approach have a positive and significant effect on the optimal supply chain of chicken production. The limitations of the supply chain of chicken production with emphasis on the human resource management approach have a negative and significant effect on the optimal supply chain of chicken production.

This paper is concerned with developing an adaptive method on the basis of a nonlinear disturbance observer (NDO) in order to control a switched nonlinear system in the presence of unknown functions and external disturbances, and under arbitrary switching signals. The proposed approach employs an adaptive backstepping technique, NDO, a fuzzy logic system (FLS), and the particle swarm optimization (PSO) algorithm. Based on a common Lyapunov function (CLF), the adaptive backstepping technique is used to design a nonlinear state-feedback controller. Also, NDO and FLS are stated to estimate the disturbances and the unknown nonlinear functions, respectively. In addition, to improve the performance of the closed-loop system, the PSO algorithm is used to optimize the controller parameters. Finally, simulation examples are taken into account to demonstrate the effectiveness of the proposed strategy.

In recent years, companies have used various competitive tools to sell products to customers due to increased competition, the proximity of products, and saturated markets. Supporting various activities and cause marketing is one of these methods that has attracted the attention of companies today. Therefore, this study aimed to design and explain the cause marketing model in the dairy food industry in 2021. This applied, the qualitative-quantitative study was conducted using a mixed method on 12 academic experts and managers of Pegah Dairy, Solico (Kale) Kalber Dairy, Sabah, and Mihan food companies. The sampling was performed through a targeted process and the snowball method and continued until reaching theoretical saturation. The statistical population of the quantitative part was the buyers of dairy products from branches of Refah and Shahrvand chain stores in Tehran, who were selected using the cluster sampling method of at least 384 samples. The data were coded and analyzed to reach the cause marketing model in the dairy food industry. First, basic concepts were produced, and in the first stage, 111 concepts were extracted from interviews with experts, then integrated and categorized into 74 basic concepts. These concepts were coded for greater coherence and better interpretation in 16 more abstract concepts, including resources and capabilities, campaign implementation, the views of company managers and stakeholders, people's beliefs, attitudes, values, demographic factors, social stimuli, and experience and awareness. The 16 concepts were categorized into four major dimensions related to the campaign, customers, company, and charity marketing results with MAXQDA software in the next step. A consensus was reached among the experts in the Delphi process. The next step was carried out with the confirmatory factor analysis method in structural equation modeling and SmartPLS software. The results indicated the appropriate fit of the final model. Based on the results, managers of dairy companies can use the identified concepts and categories in their future marketing plans to achieve a suitable position in customers’ minds and carry out their charitable activities under social responsibilities.

In order to attract customers choosing a digital marketing approach in business has become an inevitable issue. Through the persuasion principles of Cialdini psychology, many companies are trying to persuade visitors to choose and use their products or services. Despite the frequent use of customer persuasion psychology principles in this marketing approach, little information is found in the academic literature about the effectiveness of these principles on consumer response in digital marketing. The purpose of this study is to investigate whether the use of Cialdini's six principles of persuasion is effective on consumers' reactions to furniture digital marketing. The results indicate the significant effect of these principles in convincing customers of digital marketing in the furniture industry. Therefore, one of the effective ways to attract customers in digital marketing is to pay attention and apply these principles in the production and presentation of content in this marketing method. Persuading people to choose a product in the furniture industry by using persuasion principles requires observing the aspects of caution because the inappropriate and false use of these principles can have a negative and harmful consequence, especially the principle of scarcity, although it is the most effective, but in some cases suspicion It is going to have a negative impact on decision making. However, this effect was only observed for this group of participants. Therefore, to measure the effectiveness of persuasion principles in digital marketing based on Cialdini principles in different fields and to categorize more products, wider research is needed.

Gold has always been considered as a strategic commodity in crises. When markets are down, gold acts as a safe haven. Because the price of gold usually does not move with the market prices. The purpose of this research is to investigate the gold market bubble and the possibility of its contagion to the stock exchange. For this purpose, in order to check the existence of a price bubble in the gold market, using (RADF), (SADF) and (GSADF) tests, the price bubble of the gold market was tested and the date of their creation and collapse was determined. To investigate the contagion of the gold market bubble to the stock exchange, a time variable regression model was used. The results indicate the existence of 4 periods of explosive behavior and the existence of multiple price bubbles in the price of gold. Based on this, the bubble periods in the Iranian gold market are related to the periods 1395:07:13-1395:04:13, 1397:09:25-1396:10:17, 1398:06:04-1397:10 09:09 and 1399:12:30–1398:09:19 and the contagion of the price bubble from the gold market to the stock market has also occurred.

This study aims to provide an open innovation model for hi-tech startups in the unit of industries related to information technology (IT). The research method of the present study is mixed and it is done with two types of qualitative and quantitative (mixed) approaches. In the qualitative part of the research, in order to collect data, interview questions were developed. In the following, the ISM questionnaire and the researcher-made questionnaire with a 5-point Likert scale were used. The statistical population in the qualitative and ISM sections consisted of 10 qualified experts who were selected using the purposeful and non-probability sampling method and in-depth and semi-structured interviews were conducted with them. The first step of the current study is to identify the main and sub-categories of the research by using the method of qualitative analysis of the theme (the approach of editing interviews, summarizing them and interpreting concepts and words). MAXQDA software was used for qualitative analysis. Then, in the second and quantitative part of the research, the structural-interpretive modeling method and MICMAC software were used to identify the causal relationships between the main categories of the research. In total, the pattern obtained consists of 10 main themes. The results showed that the strategic management of open innovation, investment and financing, and information technology infrastructure affect technology development in services and products and innovative leadership. Innovative leadership and technology development have an effect on knowledge management and human resource empowerment and lead to the participation of startups in open innovation and improving competence of startups. Through improving the competence and participation of hi-tech startups, it is finally possible to achieve open innovation.

In the present paper, the relatively new method of Radial Basis Function-Generated Finite Difference (RBF-FD) is used to solve a class of Partial Differential Equations (PDEs) with Dirichlet and Robin boundary conditions. For this approximation, Polyharmonic Splines (PHS) are used alongside Polynomials. This combination has many benefits. On the other hand, Polyharmonic Splines have no shape parameter and therefore relieve us of the hassle of calculating the optimal shape parameter. As the first problem, a two-dimensional Poisson equation with the Dirichlet boundary condition is investigated in various domains. Then, an elliptic PDE with the Robin boundary condition is solved by the proposed method. The results of numerical studies indicate the excellent efficiency, accuracy and high speed of the method, while for these studies, very fluctuating and special test functions have been used.

In developed countries, most of the economic activities of these countries are carried out through small and medium-sized companies, and SMEs act as the backbone of the dynamic economy of these countries. The purpose of this study is to design and validate the internationalization model of small and medium industries with marketing innovation, emphasizing the mediating role of market orientation in the direction of the prosperity of the leather industry market, centered on the East Azerbaijan region. The statistical population in the quantitative part included 1620 active units in East Azarbaijan province, and the statistical sample included 310 people based on the Morgan-Karjesi table, who were selected by a simple random sampling method. To do sampling, cluster sampling and available people were used for sampling. A Likert scale questionnaire was used to collect data. Structural equation modeling method and smart-pls software were used for data analysis. The findings of this study showed that marketing innovation has an effect on the performance of innovation and internationalization with mediating variables of market orientation, process innovation, innovation capability, and product innovation.

The aim of the current research is to explain and investigate the pattern of using experiential marketing in building tourism dreams. In terms of purpose, this research is applied, in terms of data collection, it is descriptive-survey and quantitative research. The research community was formed by tourists visiting Khuzestan province during the years 2020-2021 (the last 10 years), whose number is unlimited and uncertain. The sample size based on Cochran's formula was 384 people who were selected by simple random method. Data collection was done through a closed questionnaire, and its reliability and validity were confirmed through the conducted tests. The mentioned questionnaire was prepared based on the results of data analysis related to the data obtained from interviews with experts in the design stage of the model. To test the model of using experiential marketing in the construction of tourism dreams, the structural equation model test was used, which was done through PLS software. The results showed that there is a significant relationship between the model variables. In such a way that the causal conditions have a positive effect on the central phenomenon; The central phenomenon, background conditions, and intervention conditions have a positive, positive, and negative effect on strategies, respectively; And finally, the strategies had a positive and significant effect on the results.

The current research has been conducted to design a model to create a suitable platform for the preservation and maintenance of human capital and increase the productivity of the organization in the central building of Iran Oil Company. The statistical population of this research consists of two groups, the first group includes experts who are familiar with the theories of human capital preservation and organizational productivity, whose number is unknown and are scattered throughout the country, and their selection was selective and in This research has been used in the design part of the model according to them, the second group included all the employees of the central building of Iran Oil Company (582 people), according to Cochran's formula, 232 of them were selected as a sample. To collect data, questionnaires on human capital maintenance and organization productivity were used. The results indicate that there is a significant relationship between the maintenance of human capital and the productivity of the organization in the central building of Iran Oil Company. There is a significant relationship between individual factors, organizational factors, managerial factors, and job factors with organizational productivity in the central building of Iran Oil Company.

Lack of human resources auditing is associated with problems such as unhealthy performance of human resources, the uncertainty of effectiveness and efficiency, and non-compliance of human resources performance with rules, goals and macro policies in the organization. The present study was conducted using a qualitative method. To analyze the data, it used the cognitive mapping method. The study's statistical population included audit and human resources elites and 10 of them were selected using a purposeful (non-probabilistic) sampling method. During the research and survey of experts, 106 indicators for the implementation of functional and macro-level strategies were identified and were placed in the form of 15 concepts. The CVI of the questionnaire was confirmed with a value larger than 0.79. The developed questionnaire was submitted to 10 human resources experts. The data in the final cross-matrix questionnaire were used as input data for the Ucinet and NetDraw systems to design the pattern. The links were weighted towards management and individual skills. Management skills as a focal node called ego with nodes connected to it directly called Alter, including thinking skills, mental abilities, organization, monitoring, scientific abilities, psychological abilities, professional abilities, allocation, strategic, cognitive, individual, interpersonal, and interaction formed an ego network. The results of the present study can be used by managers in the area of human resource auditing model with the approach of functional and macro level strategies of the hospital to adapt human resource performance to the rules, goals and macro policies of related organizations.

For the solution of a variety of problems which concern molecular structures, it is often necessary to calculate the Cartesian coordinates of the atoms from a set of geometric parameters. In order to fully utilize symmetry operations in the calculation of Cartesian coordinates, it is necessary to construct the molecule within a primary coordinate system. This is accomplished by introducing a set of four dummy atoms, by which unit vectors are specified. One atom is placed at the origin and the others at unit distances along each of the three Cartesian axes. in this framework according to the attachment procedures described below. The atoms of a molecule are positioned through the use of a secondary coordinate system. A base coordinate system is defined by the positions of three atoms, numbered 1, 2, and 3. The origin is taken at Atom 1, the negative x-axis passes through Atom 2, and Atom 3 lies in the first or second quadrant of the xy plane. In order to define the angles, the following conventions are adopted: for a general atom j, the atom to which it was attached is called $j^{\prime}$, and the atom to which $j^{\prime}$ was attached is called $j^{\prime \prime}$, and the atom to which $j^{\prime \prime}$ was attached is called $j^{\prime \prime \prime}$. Two special cases where these definitions do not suffice are atoms attached to Atom 1 and to Atom 2. Where j is attached to Atom 2, Atom 1 is taken as $j^{\prime \prime}$ and Atom 3 as $j^{\prime \prime \prime}$. Where j is attached to Atom 1, Atom 2 is taken as $j^{\prime \prime}$ and Atom 3 as $j^{\prime \prime \prime}$. The program described is being used extensively for specifying molecular structures for electron diffraction investigations. Other current uses are in programs for x-ray diffraction of polymers, for estimating magnitudes of energy via postulated force field functions, and in molecular orbital calculations.

This research is aimed to explain the tax avoidance measurement model in private companies, the effective factors and the relationships between them based on interpretive structural modeling. In terms of the purpose, the current research is in the category of fundamental research, and in terms of nature and method, it is descriptive and a case study in private companies. The statistical population of this research is experts familiar with the subject matter of the research, which includes professors and experts related to the field of taxation. A sample of 20 experts answered the questions through purposeful judgmental sampling. In order to present the model, interpretive structural modeling has been used. The results of interpretive structural modeling showed that internal organizational factors in the process of tax avoidance include financial leverage, company size, quality of internal information, ownership structure and corporate governance. Also, external organizational factors include financial constraints, customer focus, product market competition, corporate social responsibility, and social trust. Finally, based on the mentioned factors, the research model was presented. Also, the results of the Meek Meek matrix analysis showed that the ten factors related to the explanation of the pattern of influence on the tax avoidance process in private companies are divided into three categories of permeating, dependent and linked factors from the dimension of permeability and dependence. The factors of customer focus and social trust have low influence and high dependence, so they are dependent factors. The factors of corporate social responsibility, ownership structure, corporate governance and quality of internal information are influential factors or main drivers because they have high influence power and low dependence power. Also, the factors of financial leverage, company size, competition in the product market, and financial limitations are strategic variables of the research and are classified as linked variables.

The success and growth of organizations are due to their timely actions against challenges and problems and having dynamic capabilities, responsiveness and competitiveness. The purpose of this research is to design and validate a dynamic, responsive and competitive structure model for the Railways of the Islamic Republic of Iran. The research method was qualitative and the statistical population in the qualitative department included senior and middle managers of the Railways of the Islamic Republic of Iran, professors of railway engineering, transportation engineering and public administration in higher education centers and specialists related to the subject and written documents related to the research. In the validation section, the statistical population included faculty members of public administration in higher education centers and senior intermediate managers of the Railways of the Islamic Republic of Iran. In the qualitative section, 15 experts and 6 documents (texts) were selected using the snowball and purposive sampling methods for experts and documents, respectively.  20 experts were selected in the validation section using the purposive sampling method. For data analysis, in the qualitative section, the grounded method with open, axial and selective coding in One Note software was used while in the validation section, the Delphi method in SPSS software was used. In order to determine the validity and reliability of the resulting data, necessary reviews including acceptability (expert review) and verifiability (expert review) were used. According to the results of the qualitative section, the paradigmatic model has 10 dimensions (categories) and 23 components (concepts) as follows: the causal conditions (upstream policies, control and supervision, laws and regulations, commercialization of the company and changes in the organizational structure), contextual conditions (organizational agility, intelligent marketing, human capital, upstream support and non-human resources), intervening conditions (private sector investment, top and middle managers, organizational values, supply chain and re-engineering and new technologies), strategies (motivation and innovation, being knowledge-oriented, optimality, discarding old strategies and national and international interactions) and consequences (company profitability, improving non-financial performance and service quality). The results of the validation section indicated the confirmation of the components identified in the qualitative section.

Currently, cloud computing provides the necessary infrastructure and software services to provide the requested services needed by users on the Internet. Due to the spectacular growth of cloud computing, the number of users and the number of demands are increasing rapidly, which creates a high workload on servers and computing resources. In this situation, for the optimal use of resources, the need for an efficient and effective management approach is fully felt. For this purpose, game theory has been used. The game structure is designed in such a way that the leader (leader) owns a large number of resources and plans the allocation of resources based on the request received from mobile users. The goal from the leader's point of view is to minimize the cost of using the resources located in the fog nodes, on the other hand, the goal considered from the mobile users' point of view is to minimize the cost of responding and transmitting the message to the desired fog node. For this purpose, the entire region is divided into regions and a fog node is considered for each region. The main goal of this research is to reduce the average delay in the provision of services related to Internet of Things applications in cloud computing platforms. For this purpose, an attempt is made to provide a new method for allocating multiple tasks in mobile collective monitoring based on fog computing in the Internet of Things using the inverse Stackelberg game theory with the help of fuzzy logic and deep reinforcement learning algorithm.

Return and risk are significant parameters in selecting an optimal portfolio, depending on the portfolio return distribution. In a stochastic process, the Markov property causes the future distribution of a random process to be measurable according to the state-transition matrix and the initial process state. According to the main idea of the present study in the optimal portfolio selection, portfolio weights are chosen in a way that the Markov property is established for the portfolio return series and the distribution of future portfolio returns is close to the distribution of investor's expected returns; hence, K-L divergence (Kullback–Leibler divergence) is utilized as a criterion of closeness. Using this idea, an optimal portfolio selection model was designed and implemented in the present study. This optimal portfolio was optimized using a Markov approach and according to historical data of 10 indices on the Tehran Stock Exchange from 2009 to 2022 in a six-member state. The optimal portfolio performance evaluation using the Sharpe ratio and value at risk criteria indicated that the research model had a higher performance than the mean-variance and weight parity models.

Skin detection is a useful and popular method to identify and recognize human body parts, faces, naked people, and skin diseases and retrieve people in multimedia databases. Therefore, finding a suitable method to divide the pixels of an image into different skin groups can be very important. One of the most common methods is based on convolutional neural networks (CNN). However, the process of training a CNN is a challenging issue. Various optimization strategies have recently been used to optimize CNN biases and weights, such as the firefly algorithm (FA) and ant colony optimization (ACO). In this study, we use a well-known nature-inspired technique called Chimp optimization algorithm (ChOA) to train a classical LeNet-5 CNN structure for skin detection. The proposed skin classification algorithms operate directly on the RGB and HVS color space. The results clearly show that the proposed algorithm significantly improves the performance of a convolutional neural network.

The present study was conducted with the aim of investigating the factors of the business boom and jump in the commercial banking system of Iran, emphasizing the role of moderating factors. The research method is mixed (quantitative-qualitative) and all the data and information needed for the research have been prepared in both quantitative and qualitative parts. The statistical population of the current research includes all participants from among banking experts and academic experts in the fields of accounting, finance, management, banking, and economics in the field of commercial banks in Iran. To test the hypotheses of the research from theoretical bases and field survey (distribution of 384 questionnaires), Used. In order to analyze the data, descriptive and inferential statistical techniques such as Cronbach's alpha tests, Kolmogorov-Smirnov tests, and structural equation modeling have been used. In the qualitative part, by selecting the key criteria of the research with the fuzzy Delphi method, factors of business boom and jump and moderating factors were identified. Then, by conducting factorial and structural analysis, the research results showed that the boom and jump of the banking system's business in various states (positive, negative and two-way) are effective on the performance of commercial and non-commercial banks. Therefore, the moderating factors moderate the relationship between the factors of boom and business boom in the banking system. By identifying the moderating factors and business boom and jump factors, a new model can be presented in the Iranian commercial banking system.

In financial markets, according to the mechanism of information exchange between sender and receiver (user of information), the knowledge and awareness of the receiver are always limited to the amount of information sent by the sender. Therefore, in this research, an attempt has been made to design the model of information entropy in the financial reporting of companies by the method of grounded theory. This research is qualitative and exploratory. This research was carried out by interviewing experts in the field of theoretical foundations of behavioral and psychological financial theories and the field of the capital market, and it reached saturation by conducting 14 interviews in 2021 using the snowball sampling method. The findings of this research showed that for the model of financial reporting with the role of information behavior, strategies such as establishing a financial reporting committee with the role of information behavior and training the category of financial reporting with the role of information behavior are adopted. Finally, the coherent model showed that financial reporting with the role of information behavior leads to consequences such as increasing social trust and confidence, growth and development of the company, and increasing the quality of financial information.

In any country, economic growth and the GDP are among the key most important indicators of progress as well as economic growth/development of that nation. Consequently, it is crucially significant to study and assess factors affecting the GDP. Therefore, the primary objective of this study is to investigate and analyze the impact of exchange rates and inflation on GDP. The objective of this article is to assess and analyze the impact of exchange rates and inflation on the GDPs of Iran, Iraq and Turkey during the period between 2005-2020. This research is descriptive in nature and applied in purpose. The relationships between the variables have been studied utilizing the data panel method compliant with statistical data from Iran, Iraq and Turkey (from 2005-2020). Data from the Central Bank of Iran, as well as the World Bank, were used for collect testing the hypotheses. Findings revealed that the exchange rate has no effect on GDP in these countries, while inflation has a significant/meaningful plus negative relationship with GDP.

The detection of the application of Game theory, a method of applied mathematics, has been tried out with different topics and has attracted the view of many researchers. Its application to literary genres proves to be highly novel and interesting. Characterization as the major element of the dramatic genre has proved to lend itself to this theory. If one detects literary materials as a series of decisions in which each character's decision or action relies on the previous thoughts and wishes of others, it sounds to be a game, based on the formal game-theory introduction. Hence, implausible decisions or deeds prove to be rational in the course of a game. The current study has tried to appraise Pinter’s plays, Birthday Party and Caretaker, in light of the game theory and model them in trees and matrices. These plays prove to be nonzero-sum Games in which the characters' dominant strategies are associated with Nash Equilibrium, none of the characters is a winner at the end, and they sound to be involved in the absurd and endless game of life controlled by invisibly menacing systems and forces.

In this paper, the modified matrix exponential (MME) method under zero-order hold (ZOH) assumption, is applied to solve systems of stiff ordinary differential equations. Some examples are given to illustrate the accuracy and effectiveness of the method. We compare our results with results obtained by matrix exponential (ME) method and by the Matlab ode23 solver.