International Journal Of Nonlinear Analysis And Applications
Volume:14 Issue: 8, Aug 2023

The pantograph equation is a special type of delay differential equation with applications in quantum mechanics and electrodynamics. A generalized hybrid pantograph equation of fractional order involving deformable derivative is considered in this work to carry out the stability analysis. The existence of solutions is established by employing the measure of noncompactness and Darbo's fixed point theorem while the contraction mapping principle is used for proving the uniqueness of the solution.  The link between the right-hand term of the given equation and the order of the deformable derivative is established. The paper presents the results on Ulam-Hyers stability and the generalized Ulam-Hyers stability of the proposed equation. Numerical simulations are provided to demonstrate the performed theoretical analysis.

In this paper, we obtain some characterizations of range symmetric matrices and utilize them to study the partial ordering of range symmetric matrices with respect to the indefinite inner product. As a consequence of this, different characterizations of partial orders on range symmetric matrices are obtained.

In this paper, we introduce a new class of arcwise $\rho$-$K$-connected, arcwise $\rho$-$K$-quasi connected and arcwise $\rho$-$K$-pseudo connected functions which encapsulate already known functions. Necessary and sufficient optimality conditions are established for a vector optimization problem over cones by involving these functions. Wolfe type and Mond-Weir type duals are formulated and corresponding duality results are also proved using these functions.

Based on the theoretical underpinnings and opinions of industry experts, key variables in the field of new product development have been identified, and cause-and-effect relationships between these variables have been drawn in this study to identify and analyze the dynamics of factors affecting the success of new product development. The intended system has been replicated in the steel industry corporation using the mathematical correlations between these variables that have been established based on the linkages in the backdrop. The strategies of expanding managerial support, investing more in R\&D, and increasing and enhancing product development planning have been recommended to increase the company's performance, and the outcomes of these scenarios have been simulated. The findings indicated that the first level is where the factors related to product development, technology development, research and development activities, the presence of complementary resources, long-term relationships with suppliers, transparent procedures, managerial competence, information sharing, conflict management, risk management, and problem-solving. The second level of the paradigm also includes pursuing power, caving to rivals, inspiring motivation, technical proficiency, technology knowledge transfer, customer happiness, market capacity, and marketing activities. The third level of the model was then used to group the following factors: market penetration, inter-industry compatibility, collaboration, mutual trust, business competence, the appearance of new rivals, change in consumption rate, awareness of environmental concerns, and business competence. This can contribute to the excellence and success of small and medium-sized metal sector businesses.

In this paper, we consider some differential subordinations and superordinations results for univalent functions by using the operator $(H_{\sigma,\rho,\tau,\mu,y,n})$ Also, we introduce some sandwich theorems.

Due to the spread of the Internet and its pervasiveness, ``big data" is created daily. Processing this amount of data requires a system with high processing power. In fact, the production and collection of data from a wide range of different equipment and tools lead to the creation of large-scale databases. In dealing with large and unstructured databases and their management, there are always challenges. This study aims to present a model to increase the clustering accuracy of big data using a fuzzy clustering system based on data mining in a MatLab programming environment. For this purpose, first, the importance of each variable in the decision tree models in SPSSModeler software is determined, then with the help of these results, fuzzy rules are explained and a fuzzy inference system is formed in MATLAB software. This study uses data mining techniques such as C\&R Tree, Chaid and C5.0 to study the development of the FCM method to increase clustering accuracy in high volume data and related factors such as data preparation indicators, data type Data quality, data dimensions, data volume and number of clusters were evaluated as inputs and clustering accuracy index was evaluated as output. Then, with the help of these results, the rules of forming a fuzzy inference system were determined and by explaining the membership functions of the decision model, it showed what effect each input index has on the output index.

In this paper, an efficient method is developed for the approximate solution of a benchmark non-smooth dynamical system. In the proposed method, the trapezoidal method is utilized for solving the Tacoma Narrows Bridge equation. For this purpose, at first, the integral form of the dynamical equation is considered. Afterwards, the obtained integral equation is discretized by the trapezoidal method. The accuracy and performance of the proposed method are examined by means of some numerical experiments.

In this study, a support vector machine (SVM) based technique for timing irrigation projects is presented, and one of the most accurate predictive models in calculating the final project duration within the contract documents, where the research problem is projects are not completed within the contract period because most of the total project duration is determined In an unthoughtful manner by the employer. Linear regression models were applied to data and information for several projects, and a significant improvement in forecast accuracy was obtained.

In spite of the various advantages of Business Intelligence Systems (BIS), implementing them brings different challenges. Implementing BIS without considering the related challenges and determinants will increase the total cost and decrease added value for the organization. In this study, a questionnaire is developed to identify the critical factors affecting the implementation of BIS in automotive parts manufacturing companies and analyzed through a data mining technique, namely association rules, and the WST-WFIM algorithm on weighted data. The algorithm aims to extract sets of frequent rules and their weights (determined according to their importance) obtained from an expert panel. Taguchi method was adapted to design the algorithm's optimized parameters in order to obtain more effective rules. After applying the new algorithm to effective weighted factors, the relation and importance of each collection of effective factors are analyzed. The findings showed that, from the experts' viewpoint, the most important factors for successful implementation of BIS include (1) Removing potential negative resistances and barriers in spite of the various advantages of the Business Intelligence Systems (BIS), implementing them brings different challenges. Implementing BIS without considering the related challenges and determinants will increase the total cost and decrease added value for the organization. In this study, a questionnaire is developed to identify the critical factors affecting the implementation of BIS in automotive parts manufacturing companies and analyzed through a data mining technique, namely association rules, and the WST-WFIM algorithm on weighted data. The algorithm aims to extract sets of frequent rules and their weights (determined according to their importance) obtained from an expert panel. Taguchi method was adapted to design the algorithm's optimized parameters in order to obtain more effective rules. After applying the new algorithm to effective weighted factors, the relation and importance of each collection of effective factors are analyzed. The findings showed that, from the experts' viewpoint, the most important factors for successful implementation of BIS include (1) Removing potential negative resistances and barriers to implement BIS, (2) alignment between business strategy and BIS characteristics; and (3) system reliability, flexibility, and scalability. implement BIS, (2) alignment between business strategy and BIS characteristics; and (3) system reliability, flexibility, and scalability.

In this paper, we have introduced a computational method for a class of two-dimensional nonlinear Volterra integral equations, based on the expansion of the solution as a series of Haar functions. To achieve this aim it is necessary to define the integral operator. The Banach fixed point theorem guarantees that under certain assumptions this operator has a unique fixed point, we have introduced an orthogonal projection and by interpolation property, we have achieved an operational matrix of integration. Also, by using the Banach fixed point theorem, we get an upper bound for the error of our method. Since our examples in this article are selected from different references, so should be the numerical results obtained here can be compared with other numerical methods.

Financial policies, which are applied with the means of government spending and tax revenues, are among the government's effective levers on macroeconomic variables, which are carried out in order to stabilize economic fluctuations or accelerate economic growth. And for the effectiveness of financial policies, through the application of positive and negative impulses in government spending, to investigate the asymmetric effects of these policies on the variables of total production, private sector production, public sector production, private sector consumption and sector investment. private, using dynamic stochastic general equilibrium models, during the time period of the first quarter of 2019 to the fourth quarter of 2013. The general purpose of this research is to design a stochastic dynamic general equilibrium model for the Iranian economy in order to investigate the effects of fiscal policy impulses on the real production of the Iranian economy. ?" It seems that the effects of positive and negative financial policy impulses on economic growth are significant. The technique used in this research is the Dynamic Stochastic General Equilibrium (DSGE) model, and in order to analyze the data, the dynare program was used in Matlab and Eviews software. The result of the research shows that the positive and negative impulses of government spending have significant but asymmetric effects on macroeconomic variables. Also, the negative impulse effect of government spending (contractionary fiscal policy) is decreasing and greater than the increasing effect of a positive impulse of government expenditures (expansionary fiscal policy).

Making economic decisions and allocating resources optimally without the presence of valid and reliable data is not possible. Capital flows towards superior economic activities when capitalist decisions rely on timely, relevant and reliable information. In this regard, auditing plays a vital role in determining the validity of information; in other words, given the accountability requiring the presence of valid and reliable data, it can be stated that auditing is one of the fundamental accountability processes. In the current research, an optimum prediction method for independent auditor's report types is selected and two approaches of the J48 algorithm and random forest are compared. This research has been conducted on 84 corporates during 2008-2017. In order to train, test and investigate the research variables, Weka software was used. The dependent variable is the auditor's report type. Results indicated that the accuracy of the J48 algorithm has been 72.61% and 60.42% in training and test sections, respectively and the accuracy of the random forest has been 94.57% and 63.09% in training and test sections, respectively; so, the random forest model is more effective.

In this study, we establish some best proximity point results for generalized cyclic contraction mappings in partially ordered metric spaces. We also prove some best proximity point theorems by introducing the $T$-restriction property and generalized pointwise cyclic contraction mapping. Some illustrations are provided to support our results.

The healthcare sector is one of the main sectors of a country's economy which is considered as an infrastructure for the process of development, so most countries believe in special care for this sector. Due to this fact, in this study, the TVP-DMA model is used to identify the affective factors of healthcare expenditures in Iran's economy. Regarding the subject and purpose of the research, the appropriate method in this research is a regression-type correlation. In this study, seasonal data from (1991-92) to (2015-16) was used. The results of the research based on the output of TVP, DMS, and DMA models reflect the fact that the growth rate of liquidity 30, the economic growth rate 50, unemployment 11, the exchange rate 49, the financial development index 66, oil revenues 54, the misery index 7, the deficit budget of 84 periods out of 104 periods which were under study, All have a significant effect on the factors affecting the healthcare expenditures. It can be stated that budget deficit, financial development index, oil revenues and economic growth are the highest and most important indicators for predicting healthcare expenditures in Iran.

The Islamic banking system, which is based on Islamic values and worldviews, is a part of the Islamic economic system, enabling the analysis of the philosophy of Islamic banking within the framework of studying the philosophy of Islamic economics. This research aims to explore the outcomes of the optimal allocation of resources in Islamic banking. To conduct the research, after collecting literature, theoretical foundations, and literature review from library studies, data gained from the opinion of scholars in various groups involved in the issue of Islamic banking were collected using interview instruments, and to analyze the content of interviews, conceptualization, and extraction of categories was used through a systematic method. To analyze the data, open coding, axial coding, and selective coding were carried out in three stages, and the model of the optimal allocation of resources based on Islamic banking was presented using MAXQDA software. Findings suggested that the consequences cannot always be predicted, and they are not necessarily those that people intended. Outcomes may be incidents and phenomena, take a negative form, be accurate or implied, and take place in the present or future.

The ultimate goal of this performance study is to provide a  proposed scheme for solving the time-fractional stochastic advection-diffusion equation (TFSADE) of order $\alpha (0\le \alpha <1)$. In this proposed scheme, we utilize an approach based on cubic trigonometric B-spline collocation methods (CTBSCM).  In this study, we replace the existing fractional derivative with the fractional Caputo derivative for time discretization and then replace the first and second derivatives of the equation using cubic trigonometric B-spline functions for spatial discretization. Applying this proposed scheme to TFSADE causes the equation to reduce to the linear system. In the end, the examples show that the order of convergence of the proposed method is $O(\tau ^{2-\alpha}+h^2)$ where $h$ and $\tau$  are the spatial and time step lengths, respectively.

Today, partially due to the current crisis and the high rate of youth unemployment, the labor market is increasingly returning to the issue of entrepreneurship education; Therefore, academic education is facing new challenges that include preparing students to enter the labor market. Although entrepreneurship education has been integrated into new university academic degrees as a result, it is not enough to strengthen entrepreneurship among students and there is a need to develop the level of entrepreneurship of students. Therefore, universities are one of the most important centers for teaching entrepreneurial skills and encouraging students towards entrepreneurial attitudes. This article has focused on the design of an effective entrepreneurial attitude model on the entrepreneurial intention of students with an emphasis on entrepreneurship education. This research is applied in terms of purpose and qualitative in terms of method. The qualitative research community consists of 10 university professors and experts. To analyze the qualitative data, the qualitative method of theme analysis and MAXQDA software were used. The qualitative findings of the research showed that the level of entrepreneurship was placed in 5 main themes and 15 strategic components were obtained in the field of entrepreneurship. The components are creativity with 3 components (idea generation ability, experience acquisition, knowledge acquisition), innovation with 4 components (absorption and development of new technologies, innovative manpower, market knowledge and analysis, competitiveness), self-esteem with 3 components (self-knowledge, self-belief, improving psychological characteristics), risk-taking with 3 components (uncertainty conditions, risk-taking strategic measures, financial support) and perceived behavior control with 2 components (perceived internal behavior control, perceived external behavior control) and is aimed at creating an entrepreneurial attitude in morale students. Risk taking should be emphasized in them. Finally, according to the conceptual model presented in this research, an Interpretive Structural Modelling was performed in the leveling of the components.

Natural resources, especially crude oil, play a vital role in the economic development and sustainable growth of countries. In general, oil and non-oil resources are considered as major indicators of government revenue for many economies around the world (Basnet and Opadiya, 2015), because economic programs that are compatible with economic policies and oil prices play a central role in They have the formation of a country's internal policy (Lardick and Mignon, 2008). The purpose of this study is to investigate the asymmetric impact of oil and non-oil incomes on financial development in Iran. In this regard, the non-linear autoregression method with distributed breaks (NARDL) has been used for the time period of 1971-2018. The findings indicate that the positive and negative shocks of oil revenues have a positive effect in the long term, and the positive and negative shocks of non-oil revenues have a negative effect on financial development. Based on this, the government can play a more active role in encouraging the expansion of credit for the financial sector, a more efficient intermediary role in mobilizing domestic savings and directing them towards productive investments in various economic sectors.

In this paper, we present some gradient projection algorithms for solving optimization problems with a convex-constrained set. We derive the optimality condition when the convex set is a cone and under some mild assumptions, we prove the convergence of these algorithms. Finally, we apply them to quadratic problems arising in training support vector machines for the Wisconsin Diagnostic Breast Cancer (WDBC) classification problem.

Consumption of chicken and poultry as a source of animal protein in human nutrition has grown significantly in recent years in the world. Based on this, the present study was conducted with the aim of investigating the factors affecting the price of poultry and poultry meat in the market of Sari city by the generalized Leontif function. The statistical population is broiler production units in Mazandaran province (Sari city) with a history of more than ten years. Non-probability sampling and available type were obtained based on 50 production units. This study is equal to the information obtained on final production cost, producer selling price and consumer purchase price (main variables in this study). The price of chicken and poultry was paid. The generalized Leontif function was estimated by seemingly disordered equations (SUR) and Eviews11 software in the period 1991-1999. The results of short-term estimates showed that the intersection of technology and labor, the intersection of capital and labor, and the intersection of capital are 0.486, 0.615 and 1.141, respectively. The results of long-term estimation showed that the intersection of technology and labor, the intersection of capital and labor, the intersection of capital and technology and the intersection of capital in the long run are 0.458, 0.658, 0.451 and 1.125, respectively.

This study aimed to assess the relationship between exchange volume and share market Volatility. The present research measured exchange volume and shared market volatility variables and analyzed the data. The Statistical population is all companies accepted to the Tehran Stock Exchange. Sampling has been performed by the Systematic Elimination method. The data needed to test the research hypotheses were collected from the Stock Exchange reports (annual financial statements and Explanatory Notes) and daily share market statistics through the Stock Exchange websites for five years (2017-2021) and stored in a database to calculate the research variables. Data software of the Tehran Stock Exchange, including Rahvard and Tadbir Pardaz software, have been used to monitor and control information. Descriptive Statistics, Inferential Statistics, and the Granger causality approach were used for statistical analysis. The research variables were calculated after collecting information and data by entering information in Excel. Then, the results of measuring the variables were entered into the EVIEWS software for statistical calculations. The results show a significant relationship between trading volume and share market volatility.

In this article, we study the nonlocal $p(x)$-Laplacian problem of the following form$$\left\{\begin{array}{ll}M\Big (\int_{\Omega}\frac{1}{p(x)}(|\nabla u|^{p(x)}+|u|^{p(x)})\,dx\Big)\Big(-\mathrm{div}(|\nabla u|^{p(x)-2}\nabla u+|u|^{p(x)-2}u\Big) =\lambda f(x,u) &\text{ in } \Omega,\\M\Big (\int_{\Omega}\frac{1}{p(x)}(|\nabla u|^{p(x)}+|u|^{p(x)})\,dx\Big)|\nabla u|^{p(x)-2}\nabla \frac{\partial u}{\partial \nu}=\mu g(x,u) & \textrm{ on } \partial\Omega,\end{array}\right.$$By means of a direct variational approach and the theory of the variable exponent Sobolev spaces, we establish conditions ensuring the existence and multiplicity of solutions for the problem.

Green financing is a strategy for the financial sector in the direction of sustainable development, which is being considered all over the world today. Green mortgages, green car loans, alternative energy ventures, eco-friendly deposits, and green credit cards are just a handful of innovative green financial products currently being offered in the world. In this regard, the main purpose of this research is to identify green financing strategies in Iran's banking sector and their political effects on the structural changes of the industry sector. In this research, there are two main questions: 1. What are the green financing strategies in Iran's banking sector? 2. What is the policy effect of green financing on the structural changes in the industry sector? In this research, the data needed to test the research hypothesis has been collected using the questionnaire tool as well as the library method. Descriptive statistics and inferential statistics methods have been used to analyze the collected data. In the inferential analysis part of the research, the gray relation analysis method has been used. The results show that the green financing index is most closely related to the investment level of the industry sector; Also, there is the lowest intensity of the relationship between green finance and the index of the added value share of value added in the industry sector. All, the evidence shows that green financing is related to many structural variables of the industry; but the intensity of the relationship will be different depending on the type of variable.

The pressures caused by the multiplicity of problems and challenges in the contemporary life of cities have led to the need to reactivate identities and their role in improving economic, social and cultural realities. In addition, making it one of the competing cities towards excellence, using cultural assets and resources, the establishment and promotion of events such as festivals, performances, religious practices and sports tournaments have become a contributing element to urban development strategies around the world, this has always required innovative actions and measures to surround this type of practice. This research attempts to delve into this field to introduce the most importantly effective and influential strategies in the revitalization of cities through events. The problem of research has been identified in the limited knowledge data in dealing with events as an effective strategy in revitalising cities, so the aim of the research seeks to raise the cognitive aspects surrounding the possibilities that contribute to the revitalization and prosperity of cities, through the event as an effective strategy. Moreover, extract the most important dimensions and indicators that include this, as knowledge added to the features of strategic use within the broader development plan and research methodology. To reach conclusions regarding the recommendations of the city of Najaf as a case study in this field.

Due to the vast number of electronic attacks that occur on a daily basis, protecting users' data is extremely important in this age of technology. Nowadays, cyber security is regarded as a top priority. Thus, the preservation of user privacy and data security is essential. The SQL vulnerability isn't a new form of website attack; it's been around for a long time. However, it is a new attack nowadays. ML algorithms were used to solve the problem of detecting SQL Injection attacks on websites. By training seven ML algorithms on a batch of data comprising SQL injection queries, including (Naive Bayes, Neural-Network, SVM, Random-Forest, KNN, and Logistic Regression) and choosing the best model that gives the highest accuracy. In comparison to previous studies, high-precision data were obtained, with the Naive-Bayes algorithm achieving 0.99 accuracies, 0.98 precision, 1.00 recall, and a 0.99 f1-score. In this paper, experiences, work schedules, and outcomes are examined. Compared to other methods, this naive Bayes approach has proven to be quite accurate in identifying SQL injection threats.

The travelling salesman problem is one of the well-known NP-hard problems, and there are various versions of the problem with respect to its different specifications of the constraints and assumptions. Especially, the symmetric travelling salesman problem has been considered in numerous routing models. The critical node detection problem has received increasing attention throughout the routing models. The critical node has the most important role in the routing problems, and if it is out of service then the optimal solution will be hit by a large undesirable cost. The critical node is defined as the node whose deletion from the network results in the largest decrease in the optimal cost. It is proved the critical node of the network is the critical node for the optimal tour, too. Thus, the critical node is considered to obtain a good approximate solution in a reasonable iteration. The 2-opt heuristic is applied by the critical node in the symmetric traveling salesman problem and the iterations are reduced significantly. Then, the pseudo-critical node is defined and detected in the approximate solution, whose removal results in the largest decrease of the approximate cost. So, the 2-opt heuristic is applied by the pseudo-critical node and the optimal or a nearby optimal solution is obtained.

In the early ages, architecture was part of the natural environment, so it had no impact on it until it became an environment of itself. A built-up environment that humans had to live and work in it. Architects changed the architectural design process, from a natural design in a natural environment to an environmental design in a buildup environment. The buildup environment does not consider nature and causes negative environmental impacts and nature pollution. Therefore, bringing architecture back to being the natural environment for humans is a must. However, architects still finding ways to decrease the impact of architecture on nature, forgetting that the design process itself misses some points that could help to reach a real environmental architecture and a natural design from the beginning. This paper aims to deduct guidelines for a Humanitarian Environmental Design, in a form of a checklist that helps architects in the early process of design. Therefore, this paper reviews some of the environmental architecture approaches and the principles their definitions depended on to achieve an environmental design. Consequently, the aspects that the study assumed to be taken into consideration are revealed. The deducted guidelines were applied to Taziry indigenous eco-hotel in Siwa to illustrate how they could increase the humanity of the architectural design environmentally. The paper concludes that the deducted guidelines should be considered before the design take a construction process, as some of its aspects cannot be applied after the building is constructed. On the other hand, humans are recommended to be the core of the design and they must be under focus as one of the resources in the ecosystem.

This paper is devoted to proper linear mappings on generalized matrix algebras and by obtaining their general form, we could obtain good results for commuting mappings and Lie centralizer and Lie triple centralizers, which are clearly established for triangular algebras and nest algebras as well.

Data envelopment analysis (DEA) is a widely-used method in measuring the relative efficiency of sets of homogeneous decision-making units with the same inputs and outputs. In classical DEA models, the whole system is usually considered as a decision-making unit (DMU) to calculate its efficiency, and the communication of separate processes within the system is ignored. However, the internal communication of different sectors of a decision-making unit can have various structures that cause complexity in evaluating its efficiency. To this end, the Network DEA (NDEA) model is developed using communication variables to communicate the internal structures of the decision-making units, in which the production process has two or more stages and considers according to the communication of the internal sectors and sub-units of a decision-making unit as a network structure, and the efficiency of each internal process and the whole process is calculated independently. Therefore, the present research aimed to evaluate the efficiency and ultimately rank the decision-making units and it thus used the dynamic network data envelopment analysis (DNDEA) model using game theory to examine and solve a problem of capital market investors, which was the correct selection of stocks in the efficient companies compared to the stocks of companies with low-efficiency. After developing the proposed model, the performance of 25 active companies in the petrochemical industry was evaluated for three years of 2016-2018 and the efficiency of each stage was calculated along with their overall efficiency. The results indicated that the proposed model had solved the shortcomings of the previous models and the new approach to the evaluation of efficiency in the stock market could provide a more accurate understanding of the performance and efficiency of active companies in this field.

In this paper, we establish fixed point results for two pairs of functions with the assistance of CLR property in the context of $\mathcal{G}$-metric space. Our sequel generalizes various existing fixed-point results that are given in the literature. An illustrative example is likewise given to demonstrate that our speculation from metric space to $\mathcal{G}$-metric spaces is genuine.