International Journal Of Nonlinear Analysis And Applications
Volume:14 Issue: 6, Jun 2023

In this paper, we develop a second-order optimality condition for optimal regular-singular control in the integral form of McKean-Vlasov stochastic differential equations. The coefficients of the dynamic depend on the state process as well as on its probability law. The control process has two components, the first being regular and absolutely continuous and the second is an increasing process (componentwise), continuous on the left with limits on the right with bounded variation. The regular control variable is allowed to enter into both drift and diffusion coefficients. The control domain is assumed to be convex. Our main result is proved by applying the L-derivatives with respect to probability law.

Let $G_{\tau }=\left(V,\ E\right)$ be a topological graph which is a finite, simple, undirected, connected graph without isolated vertices. In this paper, several bounds and domination parameters are studied and applied to it: bi-domination, doubly connected bi-domination and pitchfork domination. The dominating set and domination number with its inverse for all these types are calculated. Also, some figures from the topological graph are introduced.

In the present paper, the acceptance single sampling plan is developed by the generalized intuitionistic fuzzy numbers. The $\alpha_1$-cut and $\alpha_2$-cut sets of the generalized intuitionistic fuzzy numbers are applied to construct the acceptance single sampling plan. We also investigate the operating characteristic curve, where the parameter is considered the generalized intuitionistic fuzzy number. The $(\alpha_1,\alpha_2)$-cut set of generalized intuitionistic fuzzy operating characteristics is constructed. The bands are represented with upper and lower bounds instead of curves for operating characteristics and evaluated in detail. Finally, the numerical example is given to illustrate the proposed approach.

Today, globalization, the growth of technological complexity and environmental changes have encouraged the organization to change their attitude from closed innovation to open innovation and prioritize open innovation as a developing approach to gain competitive advantage. This study identifies and analyzes open innovation strategies and provides a model for that in small and medium-sized manufacturing enterprises. This research is practical in terms of purpose and descriptive survey in data collection and mixed in the method. First, effective factors were identified according to the literature review and confirmed by 15 experts in the field of innovation. Then, a matrix questionnaire was prepared and given to 83 experts of small and medium-sized manufacturing enterprises in Yazd city in Iran. Data analysis was done using Fuzzy Cognitive Mapping (FCM) techniques, and the final model was depicted using social networks. The findings related to analyzing data obtained from the experts' opinions indicate that the strategies of external relationships, internal relationships, support infrastructure systems, and technology absorption are more central than other ones because the effectiveness and susceptibility of these strategies are more than other factors. Thus, these strategies should be more emphasized.

Although computational strategies for taking care of Non-linear Regression Based on Hybrid Algorithms (EPNRHA) to Estimation of Parameters have always been available for years, the further application of Evolutionary Algorithms (EAs) to such difficulties provides a framework for addressing a wide range of Multi-Objective Conflicts (MOPs).  NRPSOGSA is an Estimation of Parameters of Non-linear Regression Gravitational Search Algorithm with Practical Swarm Optimization that involves the synthesis of hegemony by using the hybrid algorithm (PSOGSA) approach is utilized. Whilst Gravitational Search Algorithm with Practical Swarm Optimization Since the leader hiring process uses the Tchebycheff Strategy as a criterion, simplifying the multi-objective problem (MOP) by rewriting it as a set of Tchebycheff Approach, solving these issues at the same time within the GSA context may lead to rapid resolution. Dominance is important in constructing the leader's library because it allows the chosen leaders to encompass fewer dense places, reducing global optimization problems and producing a more diverse approximated Pareto front. 6 non-linear standard functions yielded this result. PSOGSA appears to be more productive than GSA, PSO, and BAT. All of the outcomes were completed. by MATLAB (R2020b).

Several studies have been conducted to accurately control the deformation of Shape Memory Alloys (SMAs) as an actuator, however, due to the non-linear relationship between the change of mechanical structure, including stress and strain, they have often been associated with a challenge. In the current study, a wire made of intelligent memory alloy (Nitinol) is used as an actuator of one degree-of-freedom mechanism. In order to observe the operation of the wire under electrical stimuli, a laboratory set-up is implemented. Our main goal is to accurately control the position of this nonlinear system with high precision by using optimal control. So, the nonlinear system equations are extracted and sorted into state-dependent matrices and the State-Dependent Riccati Equation (SDRE) is used to find the optimal control value. To verify the experiment three inputs including multiple steps, a low-frequency sine wave and a high-frequency sine wave, are applied to the system. The results, show the good performance of the controller in sustainability, fast response, and tracking of the desired position with low overshoot.

This study is aimed at investigating the possibility of combining the ranking period and maintenance period of classical momentum and reverse strategies and evaluating the performance of portfolios resulting from hybrid strategies in comparison with classical strategies. For this purpose, using the information of 120 companies listed on the Tehran Stock Exchange in the period 2011 to 2019, the amount of excess return, the explanatory power of excess return by risk factors of the seven-factor model Fama and French and the explanatory power of future return by excess return of each strategy Combined and classical are evaluated and compared. The results show that contraratum (contractionary hybrid strategy), which is ranked as long-term as reverse strategies but maintained in the medium term like momentum strategies, performs better than momentum and reverse strategies. By controlling risk factors (Fama and French seven-factor model), contractionary, reverse and momentum investment strategies in the Iranian capital market are profitable. Finally, the results of the present study support the explanatory power and more predictive power of the excess yield of the contractionary strategy than the classical strategies for future returns. Therefore, the contribution of the present study is to provide evidence of the excess return and performance of the new hybrid strategy are much higher than the classic investment strategies proven in the Iranian capital market.

Our main purpose of this paper is to study the relationship between multiplicative maps and almost multiplicative maps between probabilistic normed algebras. We first derive some properties of invertible elements and their relation with multiplicative maps. Then we show that every complex homomorphism on elements whose probabilistic norm is equal to 1, is bounded. In the following, we give an open problem about the functionally continuous of unital commutative probabilistic Banach algebra. Finally, we prove that every almost multiplicative map that is not a multiplicative map is continuous.

Due to machine learning-based infrared image and video collections, which enable computers to detect and categorize images with increasing accuracy, the field of image identification has experienced a revolution. This comprehensive research presents an overview of the most current advancements in the infrared image and video collections for computer vision and artificial intelligence. It has largely focused on the infrared picture and video collections that have been collected and categorized for computer vision applications such as object identification, object segmentation and classification, and motion detection. This article covers some of the most well-known machine learning methods, including deep learning, convolutional neural networks, support-vector machines, and decision trees. The basic problems with image identification are examined, and only a few of them include data augmentation, feature extraction, and picture segmentation. We also discuss some recent developments in the area of image identification, including ground-breaking deep learning methods like adversarial training and transfer learning. The discussion ends with a discussion of possible uses and the promise of machine learning for picture identification. Because it analyzes state of the art in machine learning for picture identification in-depth, this survey study is a vital resource for academics and entrepreneurs. We make a distinction between publicly accessible collections and those that are maintained in private, based on the various sensor types, image resolution, size, and research effort within that range. Include a glossary of words, including those for infrared radiation, infrared detectors, and infrared optics, that are crucial to comprehending infrared imaging, along with a description of their applications. This article explores the group's overall statistical relevance from a number of different perspectives. Researchers working in computer vision and artificial intelligence who are interested in managing spectra outside of the optical field might use this survey as a reference.

Studying the triangle impact of financial statements (financial manager, CEO, and auditor) on earnings response coefficient (ERC), based on economic aspects of information, financial reporting, and accounting system play a vital role in the capital market. So, the present research is an applied, methodological and causal study that aims to investigate the effect of the triangle of financial statement approval on ERC in the Tehran Stock Exchange. The statistical population was composed of the companies listed on the Tehran Stock Exchange out of which 166 companies were selected by the systematic sampling method. The time frame is from 2016 to 2020. This study used a panel data model to investigate the relationship of the triangle sides with ERC and their relationship with ERC in poor accounting conditions. The results showed that any changes in each of the triable sides had a significant effect on ERC. The single, dual, and triple substitution in the confirmation triangle significantly reduced the year-end ERC, and compared to the three replacement sizes, the sum of ERC for dual substitution was greater than that for single and triple substitution. Also, variations in each of the triangle sides under poor accounting conditions had a significant effect on ERC. The single substitution in the confirmation triangle increased ERC, but the dual substitution reduced ERC significantly, but the impact of the triple substitution was not significant.

The purpose of this study was to provide a proposed model affecting the environmental management accounting system in the petrochemical and metal industries in Iran. In order to conduct research, first, by studying the literature and research background with the method of documentary and library studies and the exploratory method, interview questions and research questionnaires have been identified. After analyzing the interviews, in addition to identifying the dimensions and factors affecting the research variables, it is possible to provide a model and conceptual framework for the research. The statistical population of the research in the qualitative sector is all knowledgeable managers in the petrochemical and metal industries and experts in the accounting profession in the country. The analysis consists of two parts: qualitative and quantitative. Interviews were conducted with 15 experts and theoretical foundations of the research, and in a small part of the work, a questionnaire was distributed and collected among 130 employees of petrochemical and metal industry experts. First, the validity and reliability of reagents and constructs were determined using different tests such as mean-variance and Cronbach's alpha. Then, the research variables were examined using the output of software algorithms (SmartPLS 3). These two outputs show the path coefficients between the variables and the value of the t-statistic. Prioritization of effective components on the implementation of environmental management accounting system in petrochemical and metal industries using Friedman analysis of variance showed that the environmental results component has a better rank and has the first rank and the customer environmental cooperation component ranks second and the management component The indoor environment ranks third.

The turnaround strategy refers to measures like cost reduction, selling assets and handing over the business with the aim of increasing efficiency, where the aim is to reduce the organizational size. However, there is no agreement regarding the causal relationship between any of the strategies used in organizational turnaround. Accordingly, the goal of this research is to design a causal model out of organizational turnaround for small and medium-sized enterprises (SMEs). Two types of questionnaires namely the identification of main and secondary strategies of organizational turnaround, and interpretive structural modeling were used, which were distributed among the statistical samples after their validity and reliability were approved. One-sample t-test, Confirmatory factor analysis and interpretive structural modeling were used to analyze and interpret the data. The research results show that six strategies of stopping crisis and stabilization of the business, new management, strategic orientation, crisis improvement process, organizational changes and financial restructuring are considered as the main strategies in organizational turnaround in the statistical population. Also, the results show the appearance of new management in fifth place as the main and most important strategy in organizational turnaround.

In this paper, the process of designing and comparing cascaded H-bridge (CHB) converter, modular multilevel converter (MMC), and five-level active neutral-point clamped (5L-ANPC) converter as a solid-state transformer (SST) utilized in the distribution network was investigated. The design was based on 1.7 kV IGBT modules (for CHB and MMC converters) and 3.3 and 4.5 kV IGBT modules (for 5L-ANPC converter). The converters were compared at voltage levels of 6.9, 11, and 20 kV and power levels of 0.5 and 2 MW. As well, when the number of MC voltage levels increases, the complexity of the control system, as well as the control algorithm, increases largely. In order to simplify the control system, a hierarchical control system is designed for these MCs. In the process of designing converters, thermal analysis and selecting smaller parts with lower losses due to enhanced efficiency were considered.

In this paper, we study a new system of generalized variational-like inclusion problems involving generalized $H(\cdot,\cdot)$-$\varphi$-$\eta$-accretive operators in real $q$-uniformly smooth Banach spaces. We define the resolvent operator associated with $H(\cdot,\cdot)$-$\varphi$-$\eta$-accretive operator and prove it is single-valued and Lipschitz continuous. Moreover, we suggest a perturbed Mann-type iterative algorithm with errors for approximating the solution of a system of generalized variational-like inclusion problems. Furthermore, we discuss the convergence and stability analysis of the iterative sequence generated by the algorithm.

This study aims at optimizing the portfolio of financial assets and in particular focuses on the stock market with conditional value at risk (CVaR) as the portfolio risk measure. This study uses generalized conditional heterogeneity variance methods, the dependency structure, the extreme value theory, and with the GARCH-EVT-Vine-Copula approach to optimize the portfolio and minimize the CVaR of a stock portfolio during a certain period by the re-weighting method. Modeling is based on the performance data of 7 companies among the top 50 listed companies during the period 2015 to 2021. The results show that considering the extreme values and structural dependence between the examined time series improves the risk identification between these markets. In addition, among the studied models, the out-of-sample results for the accumulated wealth function of different models show that when considering the dependence structure, the EGARCH-EVT model based on the Coppola Vine function results outperforms other models.

The stock market has played an undeniable role in economic growth and is a complement to the banking sector in allocating financial resources to manufacturing firms. Hence, the role and importance of the stock market in the economy have always been emphasized. There are several factors that affect stock market returns, one of which is the Rule of the law and the Regulatory Quality of countries. Therefore, in this study, the importance of the Rule of the law and the Regulatory Quality on stock returns has been studied in Iran and selected emerging countries in the period 2000-2021 by the system generalized method of moments. The results of this estimate show that at a significance level of 5%, the rule of law and Regulatory Quality have a positive and significant effect on stock returns. Also, the effects of inflation, exchange rate, and growth of industrial production have been positive and significant. The effect of crude oil prices is negative and significant, and trade openness has a positive effect on stock market returns, but this effect is not statistically significant at the significant level of 5%.

Since the prevalence of cardiovascular disease and consequent mortality has increased, accurate prediction of the disease status of individuals is of great importance. Therefore, models that have the least error and maximum reliability should be used. In recent years, the use of intelligent systems in engineering sciences and mechanics, especially in the prediction of diseases has increased dramatically. The diagnosis of disease by computer systems has become one of the important fields of study for researchers in this field. Diagnosis of heart disease is an attractive and challenging field of research because of the high sensitivity of communities to the death and life of the patient. The use of medical information such as age, gender, blood pressure, blood glucose level, weight, blood cholesterol levels, bio-signal of electrocardiogram, etc. can help physicians in predicting heart disease to prevent the progression of the disease, recurrent heart attacks, and consequently, reduce mortality. This data should be collected in an organized manner and used to integrate the disease prevention and diagnosis system. Evaluating these data and obtaining useful results and patterns in relation to it using data mining techniques and neural networks help to predict the early detection of this disease. This study presents a method of investigating factors influencing heart attacks using the recurrent rough group model of data handling (RRGMDH) neural network. We also compare the results of the proposed method to the results of five model of data handling neural network models, namely long short-term memory (LSTM), gated recurrent unit (GRU), redial basis function (RBF), probabilistic neural network (PNN) and recurrent group model of data handling (GMDH). The results indicate that the proposed method outperforms the five other methods.

Ethics is vital for the acceptance of any profession in society. Various factors affect certified public accountants’ decisions. Most people feel regret when they realize a different decision could have led to a better outcome. So not only the outcome of the current decision is important to them, but also the outcome they could have achieved if they had made a different decision. Therefore, the present study introduces an ethical model for certified public accountants based on the anticipated regret. Therefore, this study investigates influential dimensions and qualitative items on the ethical decision of certified public accountants based on anticipated regret. The statistical population includes two groups of experts: theorizing experts (i.e. university professors), and experienced experts (i.e. certified public accountants). Descriptive and inferential statistical methods are used to test the research hypotheses. In order to answer the main question of the research, first, the research items are identified using the fuzzy Delphi method and based on previous research on professional ethics, accounting and financial issues. The SEM method is used to measure the relationships between the research items and after the final data fit, the ethical decision-making model of certified public accountants based on anticipated regret is presented.

We introduce the notion of left (right) $\phi$-Connes biprojective for a dual Banach algebra $\mathcal{A}$, where $\phi$ is a non-zero $wk^*$-continuous multiplicative linear functional on $\mathcal{A}$. We discuss the relationship of left $\phi$-Connes biprojectivity with $\phi$-Connes amenability and Connes biprojectivity. For a unital weakly cancellative semigroup $S$, we show that $\ell^1(S)$ is left $\phi_{S}$-Connes biprojective if and only if $S$ is a finite group, where  $\phi_{S}\in\Delta_{w^*}(\ell^1(S))$. We prove that for a non-empty totally ordered set $I$ with the smallest element, the upper triangular $I\times I$-matrix algebra $UP(I,\mathcal{A})$ is right $\psi_\phi$-Connes biprojective if and only if $\mathcal{A}$ is right $\phi$-Connes biprojective and $I$ is a singleton, provided that $\mathcal{A}$ has a right identity and $\phi\in\Delta_{w^*}(\mathcal{A})$. Also for a finite set $I$,  if $Z({\mathcal A})\cap ({\mathcal A}-\ker\phi)\neq \emptyset$, then the dual Banach algebra $UP(I, {\mathcal A})$ under this new notion forced to have a singleton index

The emergence of mobile applications is forcing ambitious companies hoping to build loyalty for customers’ brands to rush towards marketing their brand applications. The present research was conducted with the aim of classifying loyal customers and measuring their loyalty level using data mining algorithms. The present research method is based on applied-descriptive and the statistical population included the customers of Asan Pardakht Company which were considered number ten thousand people and with the number of 700,000 transactions. These customers were separated by clustering operation and classified for performing different tests. By using the data of Fintech customers of Asan Pardakht Company, it was attempted by using the decision tree algorithm, in addition, to identifying active customers, to implement this algorithm, a way is made in order to increase customer loyalty and ultimately increase their profitability and create satisfaction among managers. In the present research, by implementing the different stages of Crisp methodology, clustering and testing different artificial intelligence algorithms, the most useful algorithm in order to identify the best customers and also to make them loyal and policies and implementable programs to be formulated in order to increase the satisfaction percentage and finally customers’ loyalty was explained and mentioned.

Let $\mathfrak{A}$ be an algebra. A \textit{derivation} on $\mathfrak{A}$ is a linear mapping $\delta:\mathfrak{A}\to\mathfrak{A}$ such that $\delta(ab)=\delta(a)b+a\delta(b)$ for every $a,b\in\mathfrak{A}$. As a dual to this notion, we consider a linear mapping $\Delta:\mathfrak{A}\to\mathfrak{A}$ with the property $\Delta(a)\Delta(b)=\Delta(\Delta(a)b+a\Delta(b))$ for every $a,b\in\mathfrak{A}$ and we call it an \textit{integration}. In this paper, we give some examples, counterexamples and facts concerning integrations on algebras. Furthermore, we state and prove a characterization for integrations on finite dimensional matrix algebras.

This study aimed to explain the effect of currency shock and the monetary policy of the central bank on the production gap during business cycles. A model with a threshold approach (LSTAR) was used based on the seasonal data of the Iranian economy from April 2001 to July 2019. According to the statistical tests related to the correct specification of the model, the currency shock rate is a threshold variable for changing the coefficients as its function. The results showed that the central bank intervention and the oil shock had more effects on the production gap. The nature of production in Iran's economy is oil, and its booms and busts are synchronized with the booms and busts of oil income. The injection of high oil revenues and the experience of high economic growth increase the GDP growth and reduce the production gap due to the low currency shock rate. The continuation of economic growth in the upper stages increases investment in production, decreasing the production cost and gap. In addition, the effect of currency shock increases with the foreign exchange interventions of the central bank and crossing the threshold and entering the non-linear sector. In other words, policymakers have tried to control the growth of currency shock by more reaction to the growth of the exchange rate. However, the reaction to exchange rate deviations decreases after crossing the threshold. Therefore, controlling the exchange rate becomes more robust with the increase of its growth rate in foreign exchange interventions.

In this paper, we consider a numerical method based on extended cubic B-spline basis functions for the determination of an unknown boundary condition in the inverse second-order one-dimensional hyperbolic telegraph equation. Extended cubic B-spline (ExCuBs) is an extension of cubic B-spline consisting of a parameter, we combined it with the Tikhonov regularization method to obtain a numerically stable solution. The convergence and stability of the technique are proved and shown that it is established under suitable assumptions and accurate order $O(k+h^2)$. The numerical results have been compared with those obtained by the cubic B-spline method to verify the accurate nature of our method.

This paper investigates the mediating role of knowledge commercialization process intervention on the relationship between companies’ selection and exit by Iran's incubators. The statistical population consists of 191 approved incubators and the statistical unit with 1337 members of the board of trustees of incubators. Descriptive and inferential statistical methods were used to analyze the collected data. Descriptive statistics methods (tables, graphs) were used to summarize, classify and interpret statistical data, and structural equation methods were used to test research hypotheses. The data collection tool was a questionnaire. The questionnaire's validity and reliability were assessed and approved and then distributed among the sample. The results (based on six factors extracted from ten Grimaldi characteristics) show that the selection method affects the incubators' intervention in Iran. Also, the intervention method affects the exit way by Iran's incubators, confirming the mediating role of the knowledge commercialization process.

Due to the higher importance of customer-orientedness, especially in the banking industry, the main goal of this study is to design a customer-oriented banking service model in Refah Bank with a content analysis approach. Although the previous research investigated the diverse aspects of customer-orientedness in the banking industry, designing a customer-oriented banking service model has not been touched upon. The purpose of this study is to provide a model of the influencing factors and consequences of designing a customer-oriented banking service model in Refah Bank with a content analysis approach.  This is qualitative and basic research in terms of its purpose. Furthermore, this is field research in terms of its data collection method. The statistical population of the research are university professors and banking experts. In the current study, theoretical sampling resorted; the sample size was 17 people according to theoretical saturation (Grounded theory saturation). The first group were the major factors influencing customer-oriented banking services. In other words, they were the components whose presence caused customer-oriented banking services (i.e., influencing components). The second group were impressive factors of the creation of customer-oriented banking services; these factors were taken into account as the consequences of the creation of customer-oriented banking services. Here, three consequences are assumed for the model.  The findings indicate that factors such as human resource management measures, differentiation in providing services, and integrated marketing communication (IMC) are considered antecedent factors; the factors such as particular brand value, communication quality, and financial performance are regarded as the consequences of customer-oriented banking services.

One of the causes of prosperity and success in the construction industry and one of the most common debonding is the debonding of the concrete cover and the separation of the concrete surface and the reinforcement plate. This paper evaluated the beams in the experiments due to an external force applied perpendicular to the longitudinal axis. The five reinforced concrete beams test specimen dimensions were 200×140×1300 mm, with rebar 10 for the bottom and 6 for the top, rebar 8 for the girders, and the concrete grade was considered 350. The final strength of 28 days with GFRP fibers in two layers, three classic layers, two layers, and three U-shaped layers are subjected to a four-point bending test. A control specimen was used for evaluation. The experimental results showed that the three U-shaped GFRP layers performed better than the other specimens and performed better in the biaxial bending test. The three U-shaped GFRP layers sheet had the most significant effect on flexural reinforcement and prevention of debonding compared to the classic U-shaped two-layer, three-layer, and two-layer GFRP sheets. In addition, Two U-shaped layers have more resistance to external load pressure than a U-shaped layer and have a more significant impact.

In this manuscript, we introduce new notions of generalized ($\mathfrak{f^{*}}, \psi)$-contraction and utilize this concept to prove some fixed point results for lower semi-continuous $\psi$-mapping satisfying certain conditions in the frame of G-metric spaces. Our results improve the results of [6] and [8] by omitting the continuity condition of $F\in \Im$ with the aid of the $\psi$-fixed point. We give an illustrative example to help accessibility of the got results and to show the genuineness of our results. Also, many existing results in the frame of metric spaces are established. Moreover, as an application, we employ the achieved result to earn the existence and uniqueness criteria of the solution of a type of non-linear integral equation.

In this paper, some new weak and strong convergence results of the Mann and Ishikawa iterative schemes for the class of enriched strictly psuedocontractive mappings are established in the setup of q-uniformly smooth Banach spaces. Further, demiclosedness principle for this class of mappings is obtained in the aforementioned space. The results obtained in this paper extend, improve, generalise and unify several well-known results currently announced in the literature.

Finding a zero of a maximal monotone operator is known as one of the most impressive problems which are associated with convex analysis and mathematical optimization. Akin to this is solving the fixed point problems of the class of nonexpansive mappings, which constitutes an important part of nonlinear operators with fascinating applications in several areas such as signal processing and image restoration. This study presents a monotone hybrid algorithm for finding a common element of the zero point set of a maximal monotone operator and the fixed point set of a family of a generalized nonexpansive mapping in a Banach space. Suitable conditions under which the algorithm converges strongly are established.

In this paper, we introduce a new iteration process for the approximation of fixed points. We show that our iteration process is faster than the existing iteration processes like the M-iteration process and the K-iteration process for contraction mappings. Also, we prove that the new iteration process is stable. Finally, we study the convergence of a new iterative scheme to a fixed point for the $(\alpha,\beta)$ -Reich-Suzuki nonexpansive type mappings in Banach space.