International Journal Of Nonlinear Analysis And Applications
Volume:13 Issue: 2, Summer-Autumn 2022

The aim of this paper is to construct a fractal of generalized Θ-Hutchinson Operator with the help of a finite family of Θ-contraction mappings, a class of mappings more general than contractions, defined on a complete metric space. Our results unify, generalize and extend various results in the existing literature.

In this paper, we prove some coupled fixed point theorems for nonlinear contraction type mappings in complete complex valued metric spaces endowed with partial order. We support our results by establishing an illustrative example. Also we give an application of this results to the solution of the Urysohn type integral equations.

In this paper, the solution of time-fractional Burgers and linked Burger's equations is obtained by using an effective analytical methodology termed the Elzaki homotopy perturbation method. Caputo sense is used to characterize the fractional derivatives. The recommended technique's answer is represented as a series that converges to the precise solution of the supplied issues. Furthermore, the outcomes of this strategy have revealed tight ties to the methods to the problems under investigation. The validity of the current strategy is demonstrated by illustrative instances.

The current paper investigates the fluctuations of macroeconomic variables on the resilience of pension funds in Iran. Thus, using the combined data model method with different frequencies (Midas), the present issue was investigated for different seasonal and annual time periods. In the forecasted model, the annual data of government debt, unemployment, and total Social Security expenditures and quarterly data of oil price fluctuations, exchange rate jumps, money supply and consumer price index for the years 1991-2016 have been used. Data related to 2019 were not used in the initial estimation of the relationship in order to test the predictive power of the model outside the estimation range. Based on the results; inflation rate, money supply, exchange rate jumps and crude oil price fluctuations have a statistically significant effect on the Social Security expenditures. In other words, in terms of economic structure and according to the principles of economics, a steady increase in the exchange rate causes economic prosperity in society, but if this increase is temporary, economic prosperity can not be observed. A floating and managed exchange rate increase will cause relative stability in the foreign exchange market, which in turn will increase the total Social Security expenditures in the long run. Exchange rate fluctuations lead to an increase in debt by companies and the government, and an increase in debt will lead to a general lack of liquidity, which in general, the lack of liquidity of enterprises has a negative effect on the situation of the Social Security and increase the total Social Security expenditures. Also, by comparing the predicted values with the realized values, the prediction accuracy of the model is higher and is closer to the real values.

This study aims to understand the characteristics of Supply Chain Integration (SCI) in home industries. This research used qualitative with a descriptive approach. Data was obtained by doing interviews with selected subjects. This study shows that not all home industries need a specific SCI platform, but sometimes home industries are less responsive to the needs of more advanced SCI. Therefore, we recommend that each home industry be able to carry out an independent assessment to measure the level of SCI's system and management needs. Also, it begins to implement knowledge sharing as an initial effort to increase the quality of human resources.

In this work, the idea of neutrosophic semi-regularization of neutrosophic topology is shown, as well as some of its characteristics. We show that for any neutrosophic set in neutrosophic topological space is a neutrosophic regular generalized α-closed set in (Ψ,τ) if and only if it is neutrosophic regular generalized closed set in (Ψ,τα), where τα is the family of all neutrosophic α-open sets in (Ψ,τ).

The aim of this study is the effectiveness of prediction models adjusting for foreign bankruptcy to bankruptcy prediction organizations in Iran. This study is applied and descriptive in nature of the relatives who would try to model bankruptcy, through models, model risk In their book, Dan and Broadstreet use the term ”failure” to refer to companies that are shutting down due to divestiture or bankruptcy, or abandoning loss-making business activities, or which are subject to change. Are legal by law. But in general, when a company's active business fails demands (demands) of creditors to satisfy, as the company failed to consider and if the debtor fails with its creditors to somehow reach an agreement should be based on the provisions of the Code of bankruptcy petition economy.

The main objective of this study is to develop a Digital Economy Index (DEI) for the case of Malaysia. The procedure used in this study to construct a composite indicator was from the ideas proposed by the Conference Board. This composite DEI is constructed by the high correlation component series with the various methods and procedures proposed by the previous researchers. This study shows that the DEI has the leading power, leading the reference series (ICTE) on average for 2.8 quarters. Thus, DEI can be the short-term forecasting tool to decide due to it can provide an early signal than the ICTE for significant economic events. Therefore, the construction of DEI is significant as it can be used by policymakers to predict and measure the digital economy performance for the country.

Recently, the study on weak Galerkin (WG) methods with or without stabilizer parameters have received much attention. The WG methods are a discontinuous extension of the standard finite element methods in which classical differential operators are approximated on functions with discontinuity. A stabilizer term in the WG formulation is used to guarantee convergence and stability of the discontinuous approximations for a model problem. By removing this parameter, we can reduce the complexity of programming on this numerical method. Our goal in this paper is to introduce a new stabilizer-free WG (SFWG) method to solve the Poisson equation in which we use a new combination of WG elements. Numerical experiments indicate that our SFWG scheme is faster and more economical than the standard WG scheme. Errors and convergence rates on two types of mesh are presented for each of the considered methods, which show that our numerical scheme has O(h2) convergence rate while another method has O(h) convergence rate in the energy norm and the L2-norm.

The objective of this article is, first, to introduce and investigate the notions of supra q-regular and supra q-normal by using the concepts of q-regularity and q-normality. Second, to introduce some types of supra q-regular and supra q-normal continuous mappings and investigate some properties and point out their main features of them. Finally, we introduce and investigate supra q-regular (resp; supra q-normal) homeomorphism and supra q-regular (resp; supra q-normal) irresolute map also supra q-regular (resp; supra q-normal) contra continuity map and investigate some properties of these mappings with several examples are presented.

In this paper, several novel inequalities are examined for the product of two s-convex functions in the fourth sense. Also, some applications regarding special means and digamma functions are presented.

The effect of surface roughness on the peristaltic motion of a non-Newtonian Jeffery fluid down a non-uniform inclined channel was carried out, and the analysis has been investigated in two-dimensional channel Cartesian co-ordinates by using a low Reynolds number and a long-wavelength approximation, the governing equations (continuity, motion, and temperature) were modeled and then simplified. Mathematica 11.3 was used to find an analytical solution for the fluid flow i.e. fluid velocity, temperature, pressure gradient, pressure rise, and flow streamlines. The impact of interesting included parameters on axial velocity, stream function, temperature, pressure gradient, and pressure rise is graphically described.

In this work, we shall give an upper bound for Jensen’s inequality (for uniformly convex functions). Also, we introduce a refinement for the generalized A−G−H inequality. Applying those results in information theory and obtain bounds for entropy.

This paper is devoted to the study of some properties of multiwavelet Bessel sequences in Sobolev spaces over local fields of positive characteristics.

In this paper, the Heston partial differential equation option pricing model is considered and the Legendre wavelet method (LWM) is used to solve this equation. The attributes of Legendre wavelets are used to reduce the PDEs problem into the solution of the ODEs system. The wavelet base is used in approximation due to its simplicity and efficiency. The method of creating Legendre wavelets and their main properties were briefly mentioned. Some numerical schemes have been compared with the LWM in the result.

In this paper, we introduce the class of (log,(s,m))-convexity on the co-ordinates, we establish a new identity involving the functions of two independent variables, and then we derive some fractional Hermite-Hadamard type integral inequalities for functions whose second derivatives are co-ordinated (log,(s,m))-convex.

Today, recognizing and retaining customers is one of the major challenges of customer-oriented organizations, especially in the field of banking, which has attracted the attention of many researchers. With the increasing growth of customers and the use of electronic devices that have led to the production of large volumes of data, customer behavior analysis can be considered as a competitive factor for them. In this paper, considering the varied density and data growth that leads to computational overhead, a combined approach is used of the RFM method , density-based clustering algorithm and Map-Reduce( which is an efficient and low-cost framework for running synchronous algorithms.) it is used. The results show that the proposed algorithm is more accurate than VDMR-DBSCAN. Also, the output of the algorithm is in the form of 5 clusters, the results of which can help managers in identifying valuable customers, and This method leads to increased revenue and reduced unnecessary costs that occur due to lack of recognition and incorrect segmentation of customers.

Let R be a commutative ring with identity, and let W be a unitary R-module. In this paper, we introduced the concept of a weakly semi-primary submodule as a generalization of the primary submodule, where a submodule X of W is called weakly semi-primary if the Rad(X:W)=(X:W)−−−−−−−√ is a weakly prime ideal of R, and from this work, we have provided some characteristics of weakly semi-primary submodule.

The present paper explains the dynamics of substitution tensions between fossil energy carriers in Iran: Policy guidelines for gas consumption in the industrial sector on the horizon 2025 using the space model and Kalman filter approach for the years 2006-2019 in the form of quarterly data. Based on the model estimation results; Price and revenue elasticity of kerosene, gasoline, gas oil, furnace oil and liquefied petroleum gas -0.14, -0.07, -0.46, -0.10 and -0.24 and 0.48, / 06 0, 0.17, 0.48 and 0.01. Because the price elasticity of all four products is less than one, increasing the prices increases manufacturers' costs, and increasing costs slow down the pace of gas replacement. There is a direct relationship between sales tariffs and natural gas demand, which means that with a one percent increase in sales tariffs and liberalization of kerosene, gasoline, gas oil, fuel oil and liquefied petroleum gas prices; Gas demand respectively; 0.46, 0.34, 0.004, 0.17 and 0.11 will increase. As a result, natural gas is a stretchable commodity in the long run. Also, the highest price elasticity and substitution elasticity among petroleum products with natural gas up to the horizon of 1404, respectively; related to gas oil, furnace oil, kerosene, gasoline and liquefied petroleum gas. In other words, as a result of the implementation of the above policies, the share of crude oil in the initial energy supply has decreased from 89.5 to 42.5 percent. Furthermore, the share of natural gas has increased from 8.5 to 63.5 percent. As a result, the country is currently far from the goals set out in the document.

In this paper, we consider a mathematical model that describes the quasi-static process of contact between a piezoelectric body and a deformable foundation. A nonlinear thermo-electro-viscoelastic constitutive law with long term memory and damage is used and the contact is described with the normal compliance condition and a version of Coulomb’s law of friction. We derive variational formulation for the model which is in the form of a system involving the displacement field, the electric potential field, the temperature field and the damage field, existence and uniqueness of a weak solution of the problem is proved. The proof is based on arguments of time-dependent variational inequalities, parabolic inequalities, differential equations and fixed points.

Let A be an arbitrary ∗-algebra with unit I over the real or complex field F that contains a nontrivial idempotent P1 and n≥1 a natural number and φ:A⟶A be a surjective map on A such that φ satisfies condition φ(P)∙n−1φ(P)∙φ(A)=P∙n−1P∙A, for every A∈A and projection P∈{P1, I−P1}, where A∙n−1A with repeat n−1 times A is the Jordan multiple ∗-product. Then φ(A)=φ(I)A for all A∈A and φ(I)2=I.

In this research, we will hide an image we call the secret image inside another image we call the repository. After converting the color values of both images from decimal to binary, we copy the stored images into four copies and use the eighth and seventh bits of these copies to hide the full bits of the secret image starting with the first. Two to be replaced in the eighth and seventh parts, respectively in the first version, then we hide the third and fourth bits of the secret image in the eighth and seventh parts, respectively, of the second version of the repository images, after that we hide the fourth and fifth parts of the secret image in the eighth and seventh parts of The third version of the repository image, then finally we put the last two bits of the secret image in the eighth and seventh parts of the fourth version of the image After that, we retrieve the color values of the images formed from the binary system to the decimal system so that we have four new warehouse images, but the secret image that did not show any features in the images roduced in order to strengthen the masking process, we encrypt those formed images using one of the mathematical analyzes within the field of analysis Numerical, which is the analysis of LU factors, which analyzes the image or divides it into two images, and we will see this through the working methodology.

Using the q-calculus operator we defined a new subclass of analytic functions Mq(ϑ,Φ) defined in the open unit disk Δ={z∈C:|z|<1} related with Bernoulli's lemniscate and obtained certain coefficient estimates, Fekete-Szeg\H{o} inequality results for f∈Mq(ϑ,Φ). As a special case of our result, we obtain Fekete-Szeg\H{o} inequality for a class of functions defined through Poisson distribution and further with the help of MAPLE\texttrademark\ software we find Hankel determinant inequality for f∈Mq(ϑ,Φ). Our investigation generalises some previous results obtained in different articles.

Data envelopment analysis (DEA) assigns a score to each unit of the decision-making units being analyzed indicating the efficiency or inefficiency of that unit over the other units. However, in the early DEA models, there is no strategy to improve the efficiency of the efficient units. Therefore, in Paradi & Sowlati's (2004) practical boundary theory, they tried to expand these models to increase the efficiency of the efficient decision-making units. They had a basis for improving performance to a certain extent, thus, they presented the P-DEA linear programming model to extend the efficiency of the efficient units. Because of the staff management in organizations, it is important to increase the efficiency units in order to improve the organization based on the possible changes in the level of input and output of decision-making units. This is done to produce newly advanced based on the efficiency of these new units. In this research, after studying the P-DEA model thoroughly, we identified its drawbacks and proposed a new method for determining the practical boundary by developing an additive model using an example.

In this paper, we proposed two numerical methods to solve the nonlinear integral equations of Hammerstein type on the half line. By using a Sinc-Nyström method based on Single-Exponential (SE) and Double-Exponential (DE) transformations, the problem is converted into a nonlinear system of equations. We provided an error analysis of the proposed schemes and showed that these methods have exponential convergence rates. Finally, several numerical examples are given to show the effectiveness of the methods.

The main goal of this article is to present some new refinements of the generalized classical Holder's inequality. As applications, we present some refinements to several inequalities for the (q,s)-Polygamma functions, the s-Extension of Nielsen's β-function, the derivatives of the s-Extension of Nielsen's β-function, the extended Gamma function, the r-Gamma functions and the r-Riemann Zeta function.

Based on projection pursuit and particle swarm algorithm, a new method of establishing a nonlinear system model and its algorithm implementation are proposed, and two simulation examples are given. The simulation results show that the method proposed in this paper is used to establish a nonlinear system model. It has the advantages of high prediction accuracy and good engineering practicability.

Achieving sustainable success and survival in today's challenging business conditions depends on the ability of organizations to cope with crises and return to normal conditions which mean organizational resilience. This study has been done aimed to design a performance management model, emphasising organizational resilience for Regional Electricity Companies. The exploratory mixed method has been used in this study. In the qualitative phase of the research, the Thematic Analysis strategy was used to design the model. Also, in the quantitative step, a survey strategy with a Structural Equation Modeling approach was used to test and validate it. In the qualitative phase, the statistical sample of the research encompasses 13 experts using Judgmental Sampling and in the quantitative step, it includes 205 employees of Khorasan Regional Electricity Company using Stratified Random Sampling. Based on the findings, the performance management model with organizational resilience approach was identified and confirmed in four elements including influencing factors on performance with organizational resilience approach, dimensions and components of performance with organizational resilience approach, strategies of the performance management with organizational resilience approach which lead to internal and external consequences such as productivity enhancement, performance sustainability, Improvement of service delivery and stakeholder satisfaction.

We will consider a type of elementary fuzzy partial differential equation that we wish to solve. The classical solution and the extension solution are discussed.

G. Lorentz}. In this paper, some new generalized sequence spaces on Aλ-almost null \& Aλ-almost convergent sequences by Orlicz function are introduced and extended to the paranormed sequence spaces. Some inclusion relation has also been established between the new spaces. In addition, the α-, β- and γ-duals of these spaces, and the characterization of (Aλ(f)(Δ,M,q):ν) \& (ν:Aλ(f)(Δ,M,q)) of infinite matrices are also given.

Succession is among the most optimal programs available to provide the most competent workforce for an organization's key positions when required. The primary objective of this research is to design a comprehensive model of succession management within the banking system. This study is a developmental and applied research in terms of its purpose classification. As far as its nature and method classification, it is a descriptive survey and exploratory research with the utilization of a questionnaire. The statistical population consisted of all banking sector staff members (executive, managerial, supervisory, experts, specialists as well as their assistants (Agricultural Bank). The number was approximately 340 people. In order to determine the number of samples and consistent with the statistical population table, the Krejcie \& Morgan decision-making model was utilized. In line with the statistical population, 180 samples were selected. The research model comprises of 5 indicators and 34 components. The model was validated/confirmed with the LISREL software. The components and indicators for succession in key occupations of the Agricultural Bank were identified and the final model was presented. The introduced model is the first such model for the Agricultural Bank. As a consequence of the comprehensiveness of its factors, it has a high capability to be generalized for other similar regulatory organizations.

The main aim of this work is to find the exact solution in the form of the Mittag-Leller function for the nonlinear time-fractional reaction-diffusion-convection equation via a new coupling method namely, the Aboodh variational iteration method (AVIM). The proposed method is a coupling of the Aboodh transform method with the variational iteration method and the fractional derivative defined with the Liouville-Caputo operator. Three different numerical applications are given to demonstrate the validity and applicability of the proposed method and compare it to existing methods. The results shown through figures and tables demonstrate the accuracy of our method. It is concluded here that the proposed method is very efficient, simple and can be applied to other nonlinear problems arising in science and engineering.

This work proposes a new metaheuristic technique that combines Differential evolution (DE) with gravity search in a consistent manner. Swarm intelligence benefits and the concept of tensile strength between two particles are combined to suggest superior meta-heuristic approaches for limitless optimization issues. The goal of this paper is to create a new algorithm that overcomes the shortcomings of the Gravitational search algorithm by leveraging the advantages of the Differential evolution algorithm in expanding search areas, overcoming early convergence problems, and improving the attractive algorithm's ability to converge towards the optimum. The GSA algorithm has been utilized in a search-oriented algorithm, whereas the Differential evolution algorithm is causing a high level of diversification in society, which leads to the establishment of search regions for the GSA algorithm. The effectiveness of the suggested approach was evaluated by solving a collection of 30 Real-Parameter Numerical Optimization problems that were presented at IEEE-CEC 2014. The findings are compared to 5 state-of-the-art unconstrained problem algorithms and 6 state-of-the-art unconstrained problem algorithms. The winner methods were also deduced from the results using the Wilcoxon signed test.

Let P(z) be a polynomial of degree n and for any complex number α, let DαP(z)=nP(z)+(α−z)P′(z) denote the polar derivative of P(z) with respect to a complex number α. In this paper, we prove some Lr inequalities for the polar derivative of a polynomial have all zeros in |z|≤1. Our theorem generalizes a result of Dewan and Mir [K. K. Dewan, A. Mir, {\it Inequalities for the polar derivative of a polynomial}, J. Interd. Math. 10 (2007), no. 4, 525--531] and includes as special cases several interesting many known results.

We describe here all those weight functions u such that Mu∈A∞(Q) for M the local Hardy-Littlewood maximal operator restricted to a cube Q⊂Rn. In a recent paper it is shown that for the maximal operator in Rn, Mu∈A∞ implies that Mu∈A1; here we see that the same is true for the local M but this imposes a stronger condition for weights in Q, that is, for M restricted to a finite cube Mu∈A∞ if and only if u∈A∞. This differs from the case in Rn where there are weights u not belonging to A∞ such that Mu is in A∞. As an application we get a new shorter proof of a result of I. Wik. We also give a characterization for those weights in terms the K-functional of Peetre.

Decision making can be considered as the brain of an organization and is able to give rise to individuals and organizations. On the other hand, it can lead to their failure. To do so, the aim of the current study is to evaluate psychological effects on accounting-related decision making (decision making styles). To examine psychological structures, these components were applied: shortsightedness, optimization, self-attribution bias, anchoring bias, ambiguity aversion. And to measure accounting-related decision making, decision making styles such as rational, intuitive, dependent, spontaneous and avoidant decision makings were used. In terms of purpose, this research is an applied one, and in terms of the method used for gathering data, it is descriptive-analytical as survey type according to structural modelling attitude. The population of the study is finance directors active in the capital market. To collect data standard questionnaire has been used. In this research, we put the light on the prediction of cause-and-effect relationships among (structure of corporate governance) and health of the company. The results showed that among psychological structures optimization has an influence on the intuitive decision, like that of imaginative power on spontaneous decision making, and self-attribution on spontaneous, avoidant, rational, intuitive, and dependent decision makings. Short-sightedness affects spontaneous, avoidant, and dependent decision making as well.

A novel technique called the Variational Adomian decomposition method (VIADM) is used to approximate an analytical solution for several types of non-linear fractional differential equations. Some examples are presented to back up our findings. The solution procedure and results indicated that the proposed method is very effective, reliable, and straightforward. The results show how effective and precise the present technology is at resolving various nonlinear problems in applied science. The MATLAB software carried out all the computations and graphics. Fractional derivatives are mentioned in Caputo Sense. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solution graphs are shown.

ln this paper, a new approach for finding common element of the set of solutions of the variational inequality problem for accretive mappings and the set of fixed points for asymptotically nonexpansive mappings is introduced and studied. Consequently, strong convergence results for finite families of asymptotically nonexpansive mappings and variational inequality problems are established in the setting of uniformly convex Banach space and 2-uniformly smooth Banach space. Furthermore, we prove that a slight modification of our novel scheme could be applied in finding common element of solution of variational inequality problems in Hilbert space. Our results improve, extend and generalize several recently announced results in literature.

Air traffic management is a sensitive and stressful job with various daily problems and obstacles. The aircraft landing problem is one of the most important issues addressed currently in flight surveillance. This issue has several optimal local points. Gradient-based algorithms cannot produce an optimal solution in a reasonable time to solve this problem. Meta-heuristic algorithms are used to solve such problems. Since landing earlier or later than the scheduled time will lead to higher costs for each aircraft, this article aims at minimizing the time deviation from the originally scheduled landing time of each flight. The Gray Wolf Algorithm is a new meta-heuristic algorithm inspired by wolf behaviour. However, it has a problem with global and local searches. To solve this problem, the fitness of each wolf is assigned a weight and the new member is obtained using those weights. In addition, in order to increase the local and global search capability of the algorithm, if a condition with a probability of 0.3 is met, a random search is performed around the position of the best wolf. Otherwise, by setting a condition with a probability of 0.1, a global search is performed as the mutation operator around a selected wolf. This improves the algorithm's ability to search globally and locally. In order to evaluate this algorithm in solving the problem, its result is compared with the algorithms of particle swarm optimization, firefly and the common Gray Wolf. The results show a very high performance of this algorithm compared to other similar algorithms.

In this paper, we aim to prove the existence, uniqueness of the solution to the random delay differential equation of fractional order involving the successive approximation method. Moreover, using the Gronwall inequality, we study the continuous dependence of solution in the mean square sense of the problem. Finally, the fractional ϵ-approximate solution in the mean square sense is also considered.

In this paper, we prove some fixed points properties and demiclosedness principle for mean nonexpansive mapping in uniformly convex hyperbolic spaces. We further propose an iterative scheme for approximating a common fixed point of two mean nonexpansive mappings and establish some strong and △-convergence theorems for these mappings in uniformly convex hyperbolic spaces. The results obtained in this paper extend and generalize corresponding results in uniformly convex Banach spaces, CAT(0) spaces and other related results in literature.

In this paper, we define the dynamic programming approach to solve quadratic programming problem when the objective function can be written as the product of two linear factors with single linear constraint. An algorithm is proposed for solving such problems, we also solved the problems by simplex method to obtained the exact solution as dynamic programming technique. To demonstrate our proposed method, numerical examples are also illustrated

The purpose of this paper is to obtain coincidence and common fixed point theorems for two pairs of weakly commuting self mappings in cone metric space over unital Banach algebra. Moreover, an example is given in the support of the main result and show that the result is more general than the results in present literature.

This paper presents the generalized 1-D linear telegraph equation. We have solved this equation by the Reproducing Kernel Hilbert Space (RKHS) method and compared it with other methods like fourth-order compact difference and alternating direction implicit schemes and meshless local radial point interpolation (MLRPI). Comparing the results of these three methods as well as comparing the exact solution, indicating the efficiency and validity of RKHS. The uniformly converges of the computed solution to the analytical solution are proved. Note that the procedure is easy to implement, and it no needs discretization, and is mesh-free too.

This paper presents an iterative analytic algorithm for the approximate solution of nonlinear fractional-order oscillators. The He fractional transform was applied to convert the fractional-order model, defined by a modified Riemann-Liouville derivative, to a model in continuous spacetime. Then, the approximate solution of the continuous model was applied to obtain an approximate solution for the fractional-order oscillator. The solution was obtained using the continuous piecewise linearization method (CPLM), which is a simple, accurate and efficient analytic algorithm. The applicability of the CPLM was demonstrated using representative examples in science and engineering and the maximum relative error of the approximate solution was found to be less than 0.2 per cent. This paper provides an analytical tool that can be applied in the study of fractional-order oscillations arising in various physical systems and technological processes.

In this research paper we studied strongly generalized-prequasi-invex function. Built on the new definition, k-Riemann–Liouville fractional integral inequalities for strongly generalized-prequasi-invex functions are estimated. A bunch of new Hermite–Hadamard type Inequalities in this direction via Katugampola fractional integrals are also derived.

Let t be an elements of order 3 in a finite simple group G. Let X=tG be a conjugacy class of t in G. The A4-graph, represented as A4(G,X), is a simple graph has X as a vertex set and two vertices x,y∈X, joined by edge whenever x≠y and xy−1=yx−1. In this paper, we investigate the discs structure and determine the clique number, girth and diameter of A4(G,X) when G is isomorphic to one of the untwisted groups G2(2)′,G2(3) or G2(4).

Changes in stock prices in the market are considered normal; but, the issue that always worries investors is the issue of sudden changes in stock prices. Also, one of the major sources of information used by capital market participants is the financial reports published by the companies, periodically made available to the public as the basis for the potential and actual investor decisions to buy and sell and invest in the stock market. Therefore, the ethical behaviour of managers in the organisation is considered as a key factor in the success of the organisation and gaining the trust of investors. Therefore, based on this argument, the purpose of this study is to design a model to examine the weak managers' ethical behaviours on stock price crash risk and financial reporting quality using a sample of 134 companies listed on the Tehran Stock Exchange from 2018 to 2020. Also, the research hypotheses test was conducted using structural equation modelling. The results showed that the weak ethical behaviours of managers in the companies increase stock price crash risk. The second hypothesis also shows that the weak managers' ethical behaviours also reduce financial reporting quality

This paper is concerned to establish new variants of the well-known Hermite-Hadamard (HH) inequality for 3-times differentiable functions. Under the utility of these identities, we establish some new inequalities for the class of functions whose absolute value of the third derivative are MT-convex. The results presented here would provide generalizations of those given in earlier works. Finally, we present applications of our findings for means of real numbers and applications for particular functions are pointed out.

A new technique which is known as Sumudu Transform Method (STM) is instituted for solving delay differential equations. STM is used to obtain the solutions of general nonlinear systems. The strength of STM is illustrated in reducing the complex computational work as compared to the well-known methods. This paper shows how to succinctly identify the Lagrange multipliers for nonlinear delay differential equations with variable coefficients, using the STM. The potency and suitability of the STM are exhibited by giving expository examples. The method is used to obtain the exact and approximate solutions of pantograph type equations with variable coefficients and nonlinear Volterra integro-differential equations of pantograph type.

In this paper, we present two new approaches to solve large-scale differential T-Lyapunov equations. The first one is based on the extended block Krylov subspaces, and the second is based on the extended global Krylov subspaces, using the first projection of the initial problem onto an extended block (or global) Krylov subspaces to get a small-scale differential T-Lyapunov equation. The latter problem is resolved by iterative methods (Rosenbrock or BDF method), then the obtained solution is used to create a low-rank approximate solution of the original problem. This process is being replicated, which increases the dimension of the projection space until some planned accuracy is achieved. We give some new theoretical results and numerical experiments then we compare the new approaches.

The idea of this paper is to study the arrow edge domination. The arrow edge dominating set De of a graph G is an arrow edge dominating set if every edge from D dominates exactly one edge from V−D and is adjacent to two or more edges from D. The arrow edge domination number γare (G) is the minimum cardinality of all arrow edge dominating sets in G. Several properties and bounds are introduced here. Our results are applied in some graphs such that the path graph, cycle graph, complete graph, wheel graph, complete bipartite graph, Barbell graph, helm graph, big helm graph, complement path graph, complement cycle graph, the complement of complete graph and complement of complete bipartite graph. An important fact given here is if G has no arrow vertex dominating set, then G may have an arrow edge dominating set and an example is given.

Due to the growing consumption of gold metal and its various applications, gold recovery is very important. The element gold is an electron-bearing particle that can be used in a variety of applications such as medicine, engineering, and biology by changing its surface activity and particle size. The purpose of this study is to recover gold metal in the form of gold nanoparticles from electronic solid waste. For this purpose and to better investigate the effect of factors affecting the extraction of gold nanoparticles, the response method has been used in the experimental design. The innovation is to make gold nanoparticles with the smallest particle size with the help of reducing materials and in a cost-effective way while saving energy and also the highest recovery rate. In order to make gold nanoparticles, there are different methods such as physical, chemical and biological methods. Among these three methods, the use of the chemical method has been selected for this research. The material for extraction was royal acid, and parameters such as pH, the amount of royal acid and the temperature of the solution on the gold extraction efficiency were examined. The final nanoparticles were analyzed using XRD, FESEM, EDX and TEM analyzes. In order to determine the effectiveness of each variable and to determine which of the studied variables has the greatest impact on the gold recovery process, statistical methods were used. The variables of pH, solution temperature and the amount of Soltani acid had the greatest effect on the recovery of gold nanoparticles, respectively. According to the information obtained from Design-Expert software, at a temperature of 60 ° C and a pH of 8 and 200 ml of Soltani acid solution, the recovery rate of gold nanoparticles was 97.3\%.

In this paper, we consider a more general class of rational functions r(s(z)), of degree mn, with s(z) being a polynomial of degree m. Our results not only generalize the results due to Wali and Shah [JOA, \textbf{25} (2017), no. 1, 43-53] but also improve the results obtained by Qasim and Liman [Indian. J. Pure Appl. Math. \textbf{46} (2015), no. 3, 337-348] and Mir [Indian J. Pure Appl. Math. \textbf{50} (2019), no. 2, 315-331].

The existence of nonlinear loads and switching converters for wind and solar energy systems create distorted sinusoidal waveforms in power systems. The distorted signals are comprised of harmonic and inter harmonic frequency sinusoidal components that create disturbances like flicker, overheating of equipment, electrical losses, control system and digital meter faults, weakening of electrical appliances and electromagnetic interferences with other apparatus. Accurate measurement of the inter harmonic distortion is significant to determine the quality of the power delivered. A novel method presented in this paper has been developed based on the hybridization of the sine wave correlation technique and multi sine-cosine algorithm (SWC-MSCA) for the estimation of inter harmonics. The suggested algorithm is validated with a standard power system test signal and compared with the other on similar competent algorithms given literature. The proposed estimator outperforms pertaining to exactness and computing effort. The suggested estimator is also employed for the prediction of inter harmonics on a grid-tied single-phase PV system.

Peristaltic motion of a magnetohydrodynamic Powell-Eyring fluid in an asymmetric channel with porous walls. medium is investigated in the present study. The modeling of Mathematic is created in the presence of a stable inclined magnetic field and the angle with the vertical axis can be made, using constitutive equations following the Powell-Eyring fluid model. In flow analysis, assumptions such as long wave length approximation and low Reynolds number are utilized. Closed form formulas for the stream function and mechanical efficiency are created. On the channel walls, pressure rise per wave length has been calculated numerically. The effects of the Hartman number (Ha), Darcy number (Da), material fluid (A), inclination of magnetic field (β), porous media parameter (w), amplitude ratio(∅), pumpinh, The effects of the magnetic field's inclination on axial velocity and entrapment are investigated in detail and graphically shown.

In this paper, we introduce and study (G,α)-univex functions by generalizing the α− univex functions and establishing relationships between vector variational-like inequality problems and vector optimization problems. Furthermore, we formulate equivalence among the vector critical points, weak efficient points of vector optimization problems and the solution of weak vector variational-like inequality problems under pseudo-(G,α)-univexity assumptions. An example is also constructed to validate the main result.

Earthquake is one of the natural disasters that, depending on the scale, location, preventive measures, etc, can have financial and human effects to a large extent. Natural disasters have an uncertain nature. In other words, regarding the statistics related to such events, it is not possible to comment with high accuracy, which reveals the need to predict and estimate the dimensions of the possible effects of natural disasters. It should be noted that predicting the demand for relief goods and estimating the number of injured and displaced people as a result of these disasters can increase the efficiency of rescue operations and reduce the duration of this process, resulting in more services and reducing casualties and costs. According to the mentioned cases and the necessity of conducting effective research from different aspects and in different fields, especially in the field of predicting and management of relief and disasters, this research was carried out. For this purpose, factors such as population ratios such as population density, texture erosion in different areas, earthquake time and earthquake intensity based on the Richter scale, taking into consideration the opinions of experts in the field of geology and relief rescue, were used as inputs to the fuzzy inference system and the output of this system is determined by items such as the demand for biological, food, pharmaceutical goods, as well as the number of displaced and injured people.

In this paper, we adopt the AU-iteration scheme introduced by Udofia et. al. [21] (U. E. Udofia, A. E. Ofem, and D. I. Igbokwe, Convergence Analysis for a New Faster Four Steps Iterative Algorithm with an Application, Open J. Math. Anal., 5 (2021), no. 2, 95--112) to approximate the fixed point of monotone α-nonexpansive mappings in ordered Banach space. Analytically and with a numerical example we show that this iteration process converges faster than some well known existing iteration processes in literature. Further, we apply the AU-iteration process to find the unique solutions of a delay differential equation.

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when diagnosing a tissue sample. Small, unnoticeable changes in pixel density may indicate the beginning of cancer or tear tissue in the early stages. These details even expert pathologists might miss. Artificial intelligence (A.I.) and D.L. revolutionized radiology by enhancing efficiency and accuracy of both interpretative and non-interpretive jobs. When you look at AI applications, you should think about how they might work. Convolutional Neural Network (C.N.N.) is a part of D.L. that can be used to diagnose knee problems. There are existing algorithms that can detect and categorize cartilage lesions, meniscus tears on M.R.I., offer an automated quantitative evaluation of healing, and forecast who is most likely to have recurring meniscus tears based on radiographs.

In this paper, we introduce the notion of Bipolar R-metric space that in a way enriches the present literature. Here, on associating a binary relation R with bipolar metric space, we obtain a fixed point result which is well supported with an illustrative example.

In this article, the double reduction method is used to find solutions to a (1+1) nonlinear partial differential equation that arises in the theory of dispersionless integrable systems. Four nontrivial conservation laws of the equation are constructed via the multiplier method, based on a particular form of admitted multipliers. Two of the constructed conservation laws are found to have associated Lie point symmetries and are utilised to construct invariant solutions.

This study's objective was to identify the factors impacting investment security. In light of the numerous changes in today's world, especially in developing countries encountering multiple threats, these nations require appropriate solutions to address their economic problems toward make optimal use of their natural capabilities, resources and wealth. In this regard, among the significant strategies is enhanced investment. Due to limited resources, improved investment security is one of the most important debates. This is an applied type of research. It is worth noting that investment security determinants have been undertaken based on the grounded-theory method and via interviewing 25 experts. Ultimately, 18 categories were obtained. Data collection was conducted utilizing a questionnaire. The statistical population of this study included university professors, managers/executives and investors of investment companies in 2020. Since official statistics on the statistical population were not available and are unlimited, Cochran's formula was utilized to calculate a sample size from an uncertain total population and the final number of 384 was arrived at. The findings revealed that causal factors have a positive and significant effect on the axial phenomenon of investment security and that the axial phenomenon as well as the contextual and intervening factors have a positive and significant impact on investment security strategic factors. In addition, it was discovered that strategic factors have a positive and significant effect on investment security outcomes. Moreover, the findings showed that strategic factors have a positive and significant effect on the consequences of investment security. According to the results obtained based on the data theory of the foundation (grounded theory), factors determining the investment security model have six main categories (causal conditions, pivotal phenomena, interventionist conditions, contextual conditions, strategies, and consequences). In general, the paradigm model of investment security was undertaken via interviews with 25 experts. The findings disclosed that the investment security model has 18 main categories and 129 sub-categories.

This study's objective was to identify the factors impacting investment security. In light of the numerous changes in today's world, especially in developing countries encountering multiple threats, these nations require appropriate solutions to address their economic problems toward make optimal use of their natural capabilities, resources and wealth. In this regard, among the significant strategies is enhanced investment. Due to limited resources, improved investment security is one of the most important debates. This is an applied type of research. It is worth noting that investment security determinants have been undertaken based on the grounded-theory method and via interviewing 25 experts. Ultimately, 18 categories were obtained. Data collection was conducted utilizing a questionnaire. The statistical population of this study included university professors, managers/executives and investors of investment companies in 2020. Since official statistics on the statistical population were not available and are unlimited, Cochran's formula was utilized to calculate a sample size from an uncertain total population and the final number of 384 was arrived at. The findings revealed that causal factors have a positive and significant effect on the axial phenomenon of investment security and that the axial phenomenon as well as the contextual and intervening factors have a positive and significant impact on investment security strategic factors. In addition, it was discovered that strategic factors have a positive and significant effect on investment security outcomes. Moreover, the findings showed that strategic factors have a positive and significant effect on the consequences of investment security. According to the results obtained based on the data theory of the foundation (grounded theory), factors determining the investment security model have six main categories (causal conditions, pivotal phenomena, interventionist conditions, contextual conditions, strategies, and consequences). In general, the paradigm model of investment security was undertaken via interviews with 25 experts. The findings disclosed that the investment security model has 18 main categories and 129 sub-categories.

In this paper, we find the zero free regions of bicomplex polynomial and related bicomplex entire functions with certain restrictions on the coefficients. Our results generalize many results already known in the literature.

In this article, we consider a logarithmic viscoelastic plate equation with distributed delay. Firstly, we study the local and global existence of solutions by using the energy method combined with Faedo-Galerkin method. Then, by introducing a suitable Lyapunov functional, we prove the asymptotic behavior of the solution. Our results are more general than the earlier results.

In this paper, we introduce generalized rational type Z-contraction maps for a single map f:X×X→X where X is a b-metric space and prove the existence and uniqueness of coupled fixed points. We extend it to a pair of maps by defining generalized rational type Z-contraction pair of maps and prove the existence of common coupled fixed points in complete b-metric spaces. We provide examples in support of our results.

The estimating returns to scale (RTS) and identifying the area in which the type of returns to the scale of a single decision maker unit (DMU) remains sustainable helps managers to have more accurate predictions about the size variations of a DMU. Contrary to theoretical studies and attitudinal surveys, the RTS-based econometric estimates of the panel data are derived from the time changes observed in inputs and outputs. Therefore the description of returns-to-scale based on the panel data is closer to those that are related to changes in demand and changes in the policy of managers during the sample period. it's clear that the use of the panel data, in addition to estimating returns to scale closer to the view of the managers, leads to a significant increase in the number of inputs and outputs for each DMU. Since we know that the DEA models have computational complexity for the great practical issues, use particularly when there are large numbers of outputs and inputs reducing the number of models will greatly help to solve these issues. In most articles, the returns-to-scale estimates for decision-making units (DMU) are performed with at least two LP models. Furthermore have problems in some cases and may not be able to investigate all DMUs. In this paper, a method has been proposed which determines returns-to-scale and identifies boundary units by solving only one model. In fact, unlike some articles which explore the boundary DMUs, the assessment area in this paper is all the DMUs observed in PPS (Production Possible Set). Therefore, based on this approach, identifying boundary units and estimating their returns-to-scale will be possible by solving only one LP model. Further, according to the proposed dual model, a different perspective has been proposed to identify and evaluate boundary units and to estimate the returns-to-scale by solving a single LP model. Additionally and according to numerous observations, the dual model is able to estimate the returns-to-scale of the image point of the inefficient units in the BCC model in the input orientation. The correctness of all content has been shown theoretically as well as intuitively, with due substantiation.

This paper deals with the study of a coupled system of generalized impulsive integro-differential evolution equations with periodic boundary value. We show the existence and uniqueness of the solution for the proposed problem using Banach fixed point theorem. Another way was used to show the existence result with the aim of breaking out of the widely used Theorems style, we take advantage Monch's fixed point theorem using a non-compactness measure that we introduced. Some examples are given to our obtained results.

Controlling and managing traffic signals at road intersections is a demanding task in the transportation system to ensure vehicular traffic safety and a consistent flow of traffic. Because of the significant increase in the number of vehicles on a daily basis, reducing road congestion has become a major concern in recent years. The urban transportation system requires effective solution techniques to cope with current traffic conditions and meet the ever-increasing demand for traffic. Changes to urban infrastructure will take years, and in some cases may not be feasible. As a result, optimizing traffic signal time (TST) is one of the quickest and most cost-effective strategies to reduce congestion at intersections and improve traffic flow in the metropolitan network. To improve TST, researchers have been working on a number of ways as well as the use of technology. This paper aims to analyze recent literature published between 2014 and 2022 for various traffic signal management systems that have been developed to improve real-time traffic flow at junctions by optimizing TST and Traffic Signal Control (TSC) systems and to provide insights, research gaps, and possible directions for future work for researchers interested in the field.

The contemporary theoretical inquest concerns itself with an updated mathematical model involving intraguild (IG) predation in which the IG predator acts as a generalist predator with the inclusion of harvesting in the resource population. Due attention is paid to the positivity and boundedness of the outcomes of the system under consideration. All the conceivable ecologically feasible equilibria are explored for their existence and stability under certain conditions. Special emphasis is put forward on the consequence of harvesting for the present model system. The occurrences of Hopf-bifurcation with respect to harvesting parameters involved in the harvesting effort of the model system are captured. The subsistence of the possible bionomic equilibria is, however, not ruled out from the present pursuit. The optimal harvesting policy is initiated and duly carried out with Pontryagin’s maximum principle. Numerical simulations are performed towards the end to comply with the objectives of the agreement of the numerical outcomes with their analytical counterparts and the applicability of the model is validated thereby.

In this article, we consider k-quasi-∗-class A operator T∈\bh such that TX=XS for some X∈\bkh and prove the Fuglede-Putnam type theorem when adjoint of S∈\bk is k-quasi-∗-class A or dominant operators. Among other things, we prove that two quasisimilar k-quasi-∗-class A operators have equal essential spectra.

The last decade differs from previous decades due to globalization and business competition. In the global dimension, markets for consumer products, industrial goods and services, or resource markets such as capital, materials, and technology are highly integrated. Simultaneously, the formation of multiple trade agreements and the disposition of open trade policies between countries has led to the annulment of protectionist tools and the suppression of trade barriers. In conclusion, in practice, almost all companies, regardless of national origin, size, or type of industry, are now encountered with the fact that not participating in global and regional markets might not be a long-term choice. The present article intends to designate the determinant factors of export performance development and define the necessary solutions to increase the province's exports while at the same time specifying the position of Ardabil province industries in the country. The participants of the study comprised 110 people. About 30.5\% of the participants are active in business, 37.5\% are active in manufacturing, and 32\% are active in the industry. Furthermore, 12\% of the participants had five or fewer years of work experience, 16\% of the participants had 6 to 10 years of work experience, 33.5\% of the participants had 11 to 15 years of work experience, and 38.5\% of the participants had more than 15 years of work experience. Overall, 57 factors were extracted from the interviews with experts. The results of exploratory factor analysis indicated that six factors were eliminated due to low factor loading. Besides, factor analysis performed on the remaining 51 variables identified 12 factors as the main factors explaining approximately 77\% of the variability (variance) of the variables. The research results unraveled that reviewing the legal and protection system structure of the relevant agencies involved in the export and definition of commercial companies might be a suitable solution. Furthermore, the results showed that creating the culture and the maturity of using commercial companies' services aligned with risk acceptance is neglected in the export field.

For over 15 years, palmprint identification technology has been developed and tested on a range of image resolutions (high and low). This study demonstrates the numerous varieties of palmprints and the difficulties associated with the palmprint recognition method. Furthermore, we go over the step-by-step process of developing a palmprint biometrics system, starting with image acquisition, preprocessing, feature extraction, and matching, as well as a summary of palmprint databases and their characterizations, as well as some palmprint recognition techniques and research works related to palmprint biometrics purposes. This paper focuses on comparing the types of systems in terms of deep learning, machine learning, and systems that require learning.

In this study, a mathematical model with optimal control measures was used to investigate the transmission dynamics of co-infection of hepatitis A virus and typhoid fever. A deterministic compartmental model was used and an analysis of the effect of various control measures was compared. The pathogen fitness that represents the epidemic indicator is obtained by using the next-generation matrix. We have shown the existence of two equilibrium states: the disease-free steady state in which there are no populations that are infected by the co-infection of hepatitis A virus and typhoid fever, the endemic state in which a co-infected population exists and is capable of transmitting the disease. The local and global stability conditions of the endemic equilibrium points were also proved. Further, it was proved that the co-infection of the model exhibited a backward bifurcation. Finally, a numerical simulation of the model was made and it reveals that prevention has a significant impact in reducing the transmission of the co-infection and applying all the control measures can successfully eliminate co-infection of hepatitis virus and typhoid fever from the community.

In this paper, we examine the controllability results for a class of multi-valued Sobolev type neutral stochastic differential equations that are steered by fractional Brownian motion BHt with non-instantaneous impulses for H∈(12,1) by assuming the controllability of the linear system. The results are obtained by utilizing the fixed-point theorem for multi-valued operators and stochastic analysis. At last, an example is given to represent the results of the theorem

Since human resources are the most valuable factor for manufacturing, and the most important capital of every organization today, human resource planning (HRP) is one of the most underlying organizational plans. Planning to achieve skill and educational needs, and improvement of human resources can be the underlying factor for human resource planning. Over the years, human resources have been changed into the focus point of leading organizations and managers. It can be regarded as the most underlying organizational capital, for which no alternative can be considered. This study is aimed at presenting a model to measure the capabilities of human resources strategies. At first, wide library investigations were done in this field and existing models. Then, a basic model was selected to measure the capabilities of human resources within the governmental organizations to switch the study. Interviews were done with academic, and government experts and other scholars to test the validity and reliability of the model. the qualitative model validation was done using interviews, and the sampling method was snowball sampling. The model revision was done using qualitative methods. For model designation, the interpretive-structural modelling (ISM) technique, and fuzzy approach were used. The research instrument in this study was a questionnaire. According to obtained results, the experts counted essential factors affecting the capabilities of human resource strategy as follows: value, scarcity, being inimitable, without substitution, taking required behaviours, having required competencies, sufficient motivation of personnel, and productivity.

The aim of this study is to introduce the new subclasses of bi-univalent functions coupled with subordination in the mirror of (p,q)-analogue of the modified sigmoid function in the unit disc U={z∈C:|z|<1}. The first two immediate Taylor-Maclaurin coefficients for the function belonging to these newly introduced classes are obtained. The results are new and a number of corollaries are developed by varying the parameters involved.

In this research, a suitable numerical simulation method is used to solve a non-linear system that contains multi-variables and multi-parameters with absent real data. The solution to such type of system needs a long time with some difficulty. Mean Latin Hypercube\_Runge Kutta (MLH\_RK4) propused method solve such system that has random parameters easily and fast. In addition, it is the appropriate method for solving the change in the values of the system coefficients with time. The mentioned system has been given realistic results with MLH\_RK4 that has been applied to the epidemic model. The COVID-19 model from 2020 in Iraq is the application under the research. The comparison study between the numerical results with the proposed numerical simulation results is shown in tables, and more clear graphically. The COVID-19 pandemic in our study will vanish in the next few years, according to the behavior of the epidemic for all its stages mentioned in our study. The proposed method can lessen the number of iterations for the used numerical method, and the number of repetitions of the used simulation technique. As well as it is a faster technique in the generation of parameters that appears as random variables using the Latin Hypercube sampling technique. The MLH\_RK4 method has been confirmed to be reliable, and effective to solve linear and nonlinear problems. The proposed method can predict the behavior of phases of the epidemic in the future of some epidemiological models.

In this paper we consider a transmission problem for one dimensional waves with nonlinear weights on the frictional damping and time delay. We prove first, the existence and the uniqueness of the solution using the semigroup theory. Second, we chow the exponential stability of the solution by introducing a suitable Lyaponov functional.

A metric modular on a set X is a function w:(0,∞)×X×X⟶[0,∞] written as (λ,x,y)↦wλ(x,y) satisfying, for all x,y,z∈X, the following three properties: x=y if and only if wλ(x,y)=0 for all λ>0; wλ(x,y)=wλ(y,x) for all λ>0; wλ+μ(x,y)≤wλ(x,z)+wμ(y,z) for all λ,μ>0. In this paper we define a Hausdorff topology on metric modular spaces and prove some known results of metric spaces including Baire's theorem and Uniform limit theorem for metric modular spaces.

In the present investigation, we introduce the two subclasses SαΣ(γ,ρ,λ,μ,ξ,δ) and SΣ(γ,ρ,λ,μ,ξ,δ;β) of normalized analytic bi-univalent functions defined in the open unit disk and associated with the Ruscheweyh's operator. Further, we obtain bounds for the second and third Taylor-Maclaurin coefficients of the functions belong to these subclasses. We also provide relevant connections with earlier investigations of other researchers.

The aim of this manuscript is to introduce the notion of ℜ-extended b-metric spaces and prove some fixed point results in this space. An extensive set of nontrivial examples is given to justify the claims.

In this article, Numerous new Jacobi elliptic function solutions for perturbed Gerdjikov-Ivanov equation with space-time conformable fractional derivative have been extracted using the new extended auxiliary equation method. Solitary and periodic solutions are retrieved from the Jacobi elliptic function solutions. These solutions’ existence is likewise guaranteed by the constraint criteria. In order to better understand the physical processes, we also show some graphical representations of the solutions

In this article, we suggest and analyze a viscosity approximation method to a zero of a monotone operator in the setting of Hadamard spaces. We derive the convergence of sequences generated by the proposed viscosity methods under some suitable assumptions. Also, some applications to solve the variational inequality, optimization and fixed point problems are given on Hadamard spaces.

In this paper, a new algorithms type three-step via projection Jungck Suzuki generalized mappings are introduced, and the convergence of projection Jungck- Zenor algorithm and projection Jungck P-algorithm are proved. On the other hand, we proved that the projection Jungck-Zenor algorithm converges to a common fixed point faster than of projection Jungck P- algorithm in Banach spaces.

In this paper, a new algorithms type three-step via projection Jungck Suzuki generalized mappings are introduced, and the convergence of projection Jungck- Zenor algorithm and projection Jungck P-algorithm are proved. On the other hand, we proved that the projection Jungck-Zenor algorithm converges to a common fixed point faster than of projection Jungck P- algorithm in Banach spaces.

In this article, a class of first order neutral delay differential equations with iterative terms is investigated. The proofs of the existence of positive periodic solutions rely on the Krasnoselskii's fixed point theorem together with the Green's functions method. Furthermore, by the aid of the Banach fixed point theorem and under an extra condition, we establish the existence, uniqueness and stability results. We provide an example to show the accuracy of the conditions of the obtained findings which extend and generalize earlier ones in the literature.

The use of commercial MIMO APs in RoF-DAS results in substantial throughput reduction. Efficient use of multi-antenna scheme algorithms allows for significant physical separation between the radio units, which results in decreased error rates and increased capacity. MIMO wireless communications in a DAS, which utilizes RoF to increase the overall wireless coverage and capacity have been the focus of this thesis. The main goal is to explore the factors that contribute to throughput declines in an RFDAS when commercial MIMO APs are utilized. Practical challenges are considered to examine the RoF-DAS. Single and multiple-use experience is taken for finding the experimental setup. The investigation revealed that the amount of data the system can transmit correlates with the imbalance in the received power, and the imbalance in the received power correlates with the amount of data the system can transmit.

The purpose of this paper is to construct an algorithm for approximating a common element of the set of solutions of a finite family of generalized mixed equilibrium problems, the set of f-fixed points of a finite family of f-pseudocontractive mappings, and the set of solutions of a finite family of variational inequality problems for Lipschitz monotone mappings in real reflexive Banach spaces.

The present article examines the effect of weakening the value of the national currency and macroeconomic indicators by considering the political effects of sanctions on stock prices and the SVAR structural self-regression model for the years 1370-1397. According to the SVAR estimates, an 89 percent increase in oil revenue will boost the stock price index, as well as a financial crisis and sanctions, a weakening of the national currency and a production gap of 11, 86, respectively. , 53 and 12 percent of the stock price index, also based on the results of immediate reaction functions, the shocks received by endogenous variables up to the first two periods; it goes up and then goes down. In terms of economic structure and the principles of economics, a steady rise in the dollar will lead to economic prosperity and a decrease in the stock price index, but if this increase is temporary, the economic boom in the stock market will not be observed. In general, due to the different infrastructures, patterns and economic conditions of the country, a separate study of how the Iranian stock market is affected by the uncertainty of government monetary policy, government fiscal policy and government foreign exchange policy can be in the country's major decisions. Provide an accurate view of how Iran's financial market is changing as a result of these fluctuations.

Considering two special families of regular functions in an open unit disk based on quasi-subordination, we present sharp bounds for initial coefficient estimates and also determine the classical functional of Fekete-Szegö of functions in these families. Further, we discuss subordination and majorization results for the associated families. Few known and several new consequences are established.

A violent behaviour detection system (VBDS) is an important application of intelligent video surveillance that performs a critical role in the field of public security and safety VBDS is a sort of behaviour recognition that seeks to determine whether the behaviours observed in the situation are violent, such as fighting or assault. This paper presents a survey of the existing approaches to VBDS. In this paper, the existing VBDS techniques are classified based on their framework, which includes the old-fashion framework and the end-to-end state-of-the-art deep learning framework. Finally, the VBDS methods' performance is assessed and compared.

This work deals with various qualitative analyses of solutions of a certain delay integro-differential equation (DIDE). We prove here six new theorems including sufficient conditions, on uniformly stability (US), boundedness, asymptotically stability (AS), exponentially stability (ES), integrability and instability of solutions, respectively. By defining a suitable Lyapunov function (LF) and using the Razumikhin method (RM), the proofs of the theorems are provided. We gave two examples to demonstrate applications of the established new conditions.

In this paper, we discuss atomic solutions of the second-order abstract Cauchy problem of conformable fractional type u(2α)(t)+Bu(α)(t)+Au(t)u(0)u(α)(0)===f(t)u0,u(α)0, % where A,B are closed linear operators on a Banach space X, f :[0,∞)→X \ is continuous and u is a continuously differentiable function on [0,∞). Some new results on atomic solutions using tensor product technique are obtained.

Clustering ensemble is a technique for improving clustering results' robustness and accuracy. Basically, this technique generates base clusterings and then combines them into a consensus solution whose quality is determined by the diversity of the base clusterings and the consensus function's performance. In order to improve the quality of consensus solutions, it is necessary to generate base clusterings with regard to quality and diversity. Novel techniques were employed in this study to generate diverse base clusterings for both low-dimensional and high-dimensional datasets, as well as new criteria to compute the diversity of base clusterings with respect to quality. The impacts of different levels of diversity on consensus functions were studied. The proposed methods generated diverse base clusterings, according to the findings of the experiments.

n this paper, we firstly obtain some identities via generalized fractional integrals which generalize some important fractional integrals such as the Riemann-Liouville fractional integrals, the Hadamard fractional integrals, etc. Then by utilizing these equalities we establish some Ostrowski and Trapezoid type inequalities for functions of bounded variation with two variables. Moreover, we give some inequalities involving Hadamard fractional integrals as special cases of our main results.

Human Activity Recognition (HAR) systems used in healthcare have attracted much attention in recent years. A HAR system consists of a wearable device with sensors. HAR has been used to suggest several machine learning (ML) algorithms. However, only a few research have looked at how to evaluate HAR to identify physical activities. Nevertheless, obtaining an explanation for their performances is complicated by two factors: the lack of implementation specifics and the lack of a baseline evaluation setup that makes comparisons unfair. For establishing effective and efficient ML–HAR of computers and networks, this study uses ten common unsupervised and supervised ML algorithms. The decision tree (DT), artificial neural network (ANN), naive Bayes (NB), k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), and XGBoost (XGB) algorithms are among the supervised ML algorithms, while the k-means, expectation-maximization (EM), and self-organizing maps (SOM) algorithms are among the unsupervised ML algorithms. Multiple algorithms models are presented, and the turning and training parameters in ML (DT, ANN, NB, KNN, SVM, RF, XGB) of each method are investigated in order to obtain the best classifier assessment. Differ from earlier research, this research measures the true negative and positive rates, precision, accuracy, F-Score as well as recall of 81 ML-HAR models to assess their performance. Because time complexity is a significant element in HAR, the ML-HAR models training and testing time are also taken into account when evaluating their performance efficiency. The mobile health care (M\_HEALTH CARE) dataset, which includes real-world network activity, is used to test the ML-HAR models. In general, the XGB outperforms the DT-HAR, k-NN-HAR, and NB-HAR models in recognizing human activities, with recall, precision, and f-scores of 0.99, 0.99, and 0.99 for each, respectively, for health care mobile recognition.

In this paper, we will study a type and refinement of Selberg type inequalities on semi-Hilbertian spaces, which is a simultaneous extension of the Bombieri type inequality in a semi-Hilbertian space. As applications, we give some examples of the Selberg inequality and its refinement on semi-Hilbertian spaces.

The capital level of insurance companies to meet shareholders' and the regulator's expectations is very important. This study was to estimate the VaR (Value at Risk) of insurance companies on the TSE (Tehran Stock Exchange) with RBC (Risk-Based-Capital) and EC (Economic Capital) approaches, nine insurance companies in TSE during 2011-2019 were selected. Historical simulation and MCS (Monte Carlo Simulation) methods were used to calculate VaR. In historical simulation, the probability of an insurance company's loss of more than 2.02\% of the asset value is 1\%. Meanwhile, the VaR obtained from MCS, at the confidence level of 99\%, VaR is 3.28\%. In CBA (Cost-Benefit-Analysis), the amount of capital desired by the shareholders is 1.25-1.3 of the existing capital. In SMR (Solvency Margin Ratio) the amount of capital desired by the regulator is 1.3 -1.4 of the existing capital. Finally, the target capital is 1.25-1.4 of the existing capital.

A unique common fixed point is obtained for compatible and non-compatible self-maps on a b-metric space, through the notion of conditional reciprocal continuity, due to Pant and Bist.

This paper is a survey of an effective routing enhancement for sensor nodes in WSNs. The adoption of WSNs has risen as a result of recent developments in wireless technology (WSNs). Because of its promising properties, such as low cost, low power, simple implementation, and ease of maintenance, a Wireless sensor network has become widely employed for monitoring and controlling applications in our daily lives. In general, scalable and dependable WSN models with shorter latency times, precise data transfer between nodes, low energy consumption, and longer life are required. The performance of a wireless sensor network greatly relies on the routing approach used, so that communications between multiple wireless sensor nodes are managed by routing protocols. To enhance routing in WSNs the following parameters should be considered: Shortest path, energy consumption, network lifetime, mean delay, Mean jitter, Packet delivery ratio, lost packets, throughput and the energy consumption of the entire WSN. The most important constraints of wireless sensor networks are energy consumption and network lifetime. We will use a capsule network to make the enhancement routing in WSNs by enhancing and optimizing routing protocols for WSNs.

In this manuscript, we study the fractional-order SIRC epidemiological model for influenza A in the human population in the Caputo-Fabrizio sense. The existence and uniqueness of the solution of the proposed problem are established using fixed point theory. The local stability of both disease-free equilibrium and endemic equilibrium points is investigated. Using the three-step fractional Adams-Bashforth scheme, an iterative solution of our system is generated. In the numerical simulation, many plots are given for different values of the fractional order to check the stability of equilibrium points. Also, the effect of varying some parameters of the model was presented. Furthermore, we compared our numerical solutions with those using Caputo fractional derivative model via graphical representations. The obtained results show the efficiency and accuracy of our approach.

Literature review indicates that there is a positive relationship between risk and audit fee. However, few studies have examined how auditors respond to the risk factors associated with senior management. In this study, we examine the relationship between Management capability and audit fee, taking into account the financial distress of firms. Accordingly, the necessary statistical tests are conducted through linear regression and 10Eviews, and 25SPSS software to test hypotheses and the information related to the firms listed on the stock exchange in 2009 - 2018. The multivariate regression method is used. The results indicate that Management capability negatively affects audit fee in firms with financial distress and has an inverse effect on firms without financial distress.

A zero-emission photovoltaic system is critical for efficient energy supply and environmental protection. Because of the intermittent nature of solar insolation and temperature, the maximum power point tracking controller for the photovoltaic system has become complicated. At each intermittent condition, the photovoltaic array has only one operating point with maximum power output. Therefore, a nature-inspired algorithm-based controller is needed to determine the actual maximum operating point at different environmental conditions; thus, it can increase the overall efficiency of the photovoltaic system. This paper proposes a novel maximum power point tracking controller based on a hurricane optimization algorithm hybridised with chaos to improve power tracking in photovoltaic systems. The proposed hybrid algorithm is created by combining chaotic search behaviour with the standard hurricane optimization algorithm in order to increase efficiency. The proposed controller generates the optimal duty cycle for controlling the DC-DC boost converter by tracing the exact maximum operating point on a regular basis. The simulation results show that the proposed HOA -chaos-based MPPT controller outperforms INC, P\& O, PSO and HOA based controllers in terms of efficiency and control.

A weakly completely prime graph of a near ring (WI(N)) was defined in this paper, the relationship between the elements of a near ring was determined by a definition of weakly completely prime ideal, so we studied many concepts related to the statements of the given near ring. We also found some theories related to previous graphs of our papers.

A three-parameter discrete analogue of the Alpha-power Weibull distribution (DAPW) is provided in this study. It has established some of its basic distributional and statistical properties. The probability mass function's form, moments, skewness, kurtosis, probability generating function, characteristic function, stress-strength reliability, and order statistics are all examples of this. The unknown parameters are estimated using the maximum likelihood and moments approaches. The bias and mean square error of the maximum likelihood are demonstrated via a simulated exercise. Two datasets are used to demonstrate the model's adaptability.

In this paper, we will study on some topologies induced by order convergence in a Riesz space. We will investigate the relationships of them.

Quantile regression is a powerful statistical method for modeling and analyzing the impact of explanatory and response variables at different points in the conditional distribution of the response variable. Many research papers have indicated that Quantile Regression (QR) estimator is only resistant to vertical outliers. Quantile regression like other regression M-estimators and Least Absolute Deviation LAD can be very sensitive to outliers in explanatory variables (Leverage Points). To~overcome this drawback, at first, we have to use a robust, effective and efficient method to identify high leverage points if there is masking and swamping problems. In literature, the usage of Generalized M-estimator (GM-estimator) is proposed to estimate the unknown parameters against high leverage points. In this paper, we proposed weighted~method's the generalized- M for quantile regression namely (GMQu), and improve the algorithm of this method by adapting the Improved Diagnostic Robust Generalized Potential (IDRGP) method. So that the calculation of the initial weights in this algorithm depends on (IDRGP), we're going to symbolize that method by (GMQuID). Simulation study and real data are considered to verify the performance of our proposed methods compared to other methods.

A soft model gives a vital mathematical tool for handling uncertainties and vague concepts. Soft models have been introduced. We give a new concept and investigate the soft ψ closed, soft αψ closed, and soft Iαψ closed set in soft topological structure It is also shown their properties. We provide some illustrated examples.

The aim of this paper is to investigate the Legendre spectral method for solving the diffusion equation with a source term and mixed initial-boundary value problem in a finite rectangle Ω2, we use some techniques to convert the problem to a system of ordinary differential equations and by an analysis matrical we find a general term defines all ordinary differential equations of this system, we solve this general term we get the desired approximate solution, we also present the error estimate.

Exchange rate stability in the market plays a key role in both competitiveness and as far as reducing economic uncertainty. The exchange rate in Iran has been fluctuating for several years now due to political factors, specifically economic sanctions. Utilizing the Markov switching method, this study has endeavoured to model the direct effects of sanctions on the exchange rate and the indirect impact of sanctions and inflation on the exchange rate between 1985-and 2021. The exchange rate in Iran is dual in nature, meaning there are two systems that govern it: 1-Characterized by low average exchange rates and high standard deviation; 2-High average inflation and low standard deviation. Hence, in this article, two models specified by Markov switching shall be used. The findings reveal the probability of staying in the low exchange rate system is higher than the probability of remaining in the high exchange rate one. In addition, the probability of transition from the low exchange rate system is higher than the opposite probability (due to the stability of the low exchange rate in the country). The findings also show that sanctions have a low and positive effect on the exchange rate. Moreover, the impact of inflation on the exchange rate is positive.

Introduce some ideas about applied of spatial regression models for independent and dependent fuzzy variables. while the parameters crisp values, which are estimated by the ordinary least squares method. This paper has been formulated fuzzy Pure Spatial Autoregressive Model (FPSAM) from a fuzzy general spatial model, and applied for trapezoidal fuzzy number in the domain traffic accidents for a number of cities in Iraq for the year 2018 and that after converting the Trapezoidal fuzzy number into crisp values by centroid method, calculations the results by Matlab language.

In this paper, Galerkin and iterated Galerkin methods are applied to approximate the linear second kind Volterra integral equations with weakly singular algebraic kernels using Legendre polynomial basis functions. We discuss the convergence results in both L2 and infinity norms in two cases: when the exact solution is sufficiently smooth and non-smooth. We also apply Legendre multi-Galerkin and iterated Legendre multi-Galerkin methods and derive the superconvergence rates. Numerical results are given to verify the theoretical results.

The scenario of this article is to introduce the space Rts(p,Δ) based on a general Riesz sequence space. Its completeness property is derived and its linear isomorphism property with ℓ(p) is proved. The K\"{o}the-dual property of the space Rts(p,Δ) is also derived. Furthermore, its basis is constructed and some characterization of infinite matrices are given.

The purpose of the present study was to provide a dynamic model of data envelopment analysis by utilizing from goal programming based on variables of population and education in order to evaluate the relative efficiency of industrial development in provinces of Iran during the years 2007 to 2016. For this purpose, the demographic, education and industry development variables were firstly determined with the help of 42 university and industry experts, then the research model was developed which included: objective function in the form of minimizing adverse deviations of goal constraints based on variations of units at different time periods, and model constraints in the forms of goal constraints and system constraints. In the next step, the model was solved through GAMS Software after designing and implementing dynamic and goal models of data envelopment analysis for provinces of the country in the mentioned period. The relative efficiency of industries development of the provinces was separately calculated for each of the understudy years, then the obtained values were used to calculate the relative efficiency of industry development for each province. According to results, Khuzestan province was ranked first and Sistan and Baluchistan province ranked last in term of average relative efficiency.

In this paper, an Economic Production Quantity (EPQ) inventory model for deteriorating items with price-stock dependent demand rate under complete and partial backlog is developed, in which the deterioration rate is controlled by investment in preservation technology. To fulfil the demand and to reduce the shortage we have considered the production rate proportional to the selling price of the product. This study is to maximize the total profit for seasonal deteriorating items by simultaneously determining the optimal selling price, the optimal production and the optimal preservation technology cost when the producer invests in the preservation technology to reduce the deterioration rate. We first show that for any given number of the production cycle, optimal selling price and preservation technology cost exists and are unique. Next, we show that the total profit is a jointly concave function of selling price and preservation technology cost. We provide some conditions to determine an optimal solution that maximizes profits for the EPQ model. We then provide a simple algorithm to figure out the optimality of total profit for the proposed model. Mathematical theorems are developed to determine optimal inventory policy. Numerical results demonstrate the advantages of the preservation technology, and further show the effects of different system parameters on the optimal variables and the maximal total profit. Finally, some managerial implications are provided.

Let R be a ring and M be a unital left R-module. We define μ∗-essential extension relation on the set of submodules of M and investigate its properties. Moreover, we define H-μ∗-essential-supplemented on M and investigate the relations between M and direct summand of its submodules.

In this paper, we introduce L-fuzzy α−ideals and L-fuzzy α−congruences on ADL A and we discuss the properties of these. Also, we prove that the homomorphic image and pre-image of an L-fuzzy α−congruence is also an L-fuzzy α−congruence on A under certain conditions. Finally, we establish a one-to-one correspondence between L-fuzzy α−ideals and L-fuzzy α−congruences on A.

The main purpose of this study is to provide appropriate tools for measuring the level of compliance with environmental criteria. In order to achieve this importance, the research process has been carried out in two separate stages. First, after studying the theoretical foundations of the research, in order to identify environmental criteria, a qualitative research method with a descriptive phenomenological approach was used. By conducting purposive sampling until reaching the saturation stage, complete interviews were conducted with 15 people and the validity of the results was obtained by using the research background, referring to the participants and obtaining their agreement. In the second stage, in order to determine the weight and importance of the identified criteria, this issue was addressed by designing a questionnaire and consulting environmental experts with the help of the fuzzy DANP (DEMATEL based ANP) technique. According to the identified criteria and determining the weight and importance of each of them by designing and introducing a standard questionnaire as a tool to measure the degree of compliance, the main purpose of the study was achieved. The result of the research in the first stage is identifying 20 criteria and classifying them into 4 general categories and in the second stage determining the weight and prioritization of each of the above criteria and introducing appropriate tools for observing environmental criteria. Findings of the research are effective in better knowledge and understanding of environmental criteria and the extent of their observance, development of environmental accounting standards by industry and encouraging organizations to implement green accounting and will have desirable consequences.

In this paper, we study a stochastic optimal control problem for a Markov regime switching jump-diffusion model. Sufficient and necessary maximum principles for optimal control under partial information in infinite horizon are derived. We illustrate our results by a problem of optimal consumption problem from a cash flow with regime.

Object tracking and detection are among the most significant jobs in computer vision, having many applications in areas, which includes autonomous vehicle tracking, robotics, as well as traffic monitoring. Several studies have been conducted in past years. However, since detecting various problems, for instance, fast motion, illumination variations, as well as occlusion, study in this field persists. Furthermore, deep convolutional neural networks (DCNNs) have grown increasingly significant for object detection as deep learning (DL) techniques have advanced. As a result, numerous approaches for object detection are studied in this research, as well as a comprehensive. This project encompasses backbone networks, loss functions and training strategies, classical object detection architectures, complex problems, datasets and evaluation metrics, applications, future development directions, as well as a review and analysis of DL-based object detection techniques conducted in previous years. Experts in the field of object detection will benefit from this review article.

The initial-boundary value problem for a plate equation with a nonlocal source and singular nonlocal damping terms is considered. By using the multiplier method and weighted integral inequalities, we prove that the energy decays exponentially when the damping term has a certain singular nonlinearity. The results of this paper improve the earlier results.

Data Envelopment Analysis (DEA) is a methodology to assess the performance of Decision Making Units (DMUs). In recent years, DEA has been used to measure the efficiency and effectiveness of various organizations. In the educational systems, one of the most important issues is choosing the best teaching method among the various educational patterns to teach difficult concepts to the students. For example, the fraction concept is one of the most difficult concepts in Mathematics. Learning this concept requires a series of mathematical procedures consisting of cognitive and skill-based procedures. Therefore, the important question that arises is which method is the best to teach the fraction concept? This study focuses on the effectiveness of the educational designs, Dick and Carey, Merrill and Control, on the students’ performance of the elementary schools to understand the fraction concept. For this purpose, we use some educational designs to teach the fraction concept to the sixth-grade students of an elementary school in Tehran in 2018-2019 and suggest a DEA model evaluate the effectiveness of the teaching design patterns on the students. Also, we present a statistical analysis for a more accurate comparison of the educational designs, Dick and Carey, Merrill and Control, on the students’ performance.

In this paper, we introduce the concept of C*-algebra valued partial metric as a generalization of partial metric and discuss the existence and uniqueness of fixed points for a self mapping defined on a C*-algebra valued partial metric space. We use these results to obtain some coincidence point and common fixed point results in this setting. Some examples are provided to justify our results.

In this paper, the regularity of bilinear Fourier integral operators on L2×L2 are determined in the framework of Besov spaces. Our result improves the L2×L2→L1 boundedness of those operators with symbols in the bilinear Hormander classes.

This article proposes the deep learning algorithm- Convolutional Neural Networks (CNN) for both Glioma tumor classifications and diagnosis process. This proposed CNN architecture is derived from the conventional CNN architecture to obtain the optimum classification and diagnosis accuracy. This proposed CNN architecture is derived from the conventional system for obtaining the high classification and diagnosis performance. This proposed methodology stated in this paper uses BRATS 2015 open access dataset for obtaining the brain Magnetic Resonance Image (MRI) for tumor region detection. The proposed methodology stated in this paper for tumor diagnosis achieves 97.7% of Jaccard Index (J) and 83.8% of Dice Similarity Index (DSI) and 99.025 of Diagnosis Rate (DR) using CNN algorithm.

Let Hμ=(μn+k)n,k≥0 with entries μn,k=μn+k induces the operator Hμ(f)(z)=∑∞n=0(∑∞k=0μn,kak)zn on the space of all analytic functions f(z)=∑∞n=0anzn in the unit disk D, where μ is a positive Borel measure on the interval [0,1). In this paper, we characterize the boundedness and compactness of the operator Hμ on Zygmund type spaces.

The importance of image encryption has considerably increased especially after the dramatic evolution of the internet of things (IOT) and due to the simplicity of capturing and transferring digital images. Although there are several encryption approaches, chaos-based image encryption is considered the most appropriate approach for image applications because of its sensitivity to initial conditions and control parameters. This research aims at generating an encrypted image free of statistical information to make cryptanalysis infeasible. Therefore, a new method was introduced in this paper called Multi-layer Chaotic Maps (MLCM) based on confusion and diffusion. Basically, the confusion method uses the Sensitive Logistic Map (SLM), Hénon Map, and the additive white Gaussian noise to generate random numbers to be used in the pixel permutation method. However, the diffusion method uses Extended Bernoulli Map (EBM), Tinkerbell, Burgers, and Ricker maps to generate the random matrix. The correlation between adjacent pixels was minimized to have a very small value (x10−3). Besides, the keyspace was extended to be very large (2450) considering the key sensitivity to hinder brute force attack. Finally, a histogram was idealized to be perfectly equal in all occurrences and the resulted information entropy was equal to the ideal value(8), which means that the resulted encrypted image is free of statistical properties in terms of histogram and information entropy. Based on the findings, the high randomness of the generated random sequences of the proposed confusion and diffusion methods is capable of producing a robust image encryption framework against all types of cryptanalysis attacks.

Let Ω be a bounded open subset of RN, N≥2. In this paper we give an existence result of bounded solution, in Musielak spaces, for unilateral problems associated to the nonlinear elliptic equation −diva(x,u,∇u)+g(x,u,∇u)=fin Ω, where the nonlinearity g does not satisfy the well known sign condition and f is an integrable source.

In this work, we investigate the inverse problem for differential pencils with spectral boundary conditions having jump conditions on (0; 1): Taking the Weyl function technique, we prove a uniqueness theorem from the interior spectral data.

We use some recent developments in Dynamics Programming Method to obtain a rigorous solution of the epidemic model formulated in E. Trélat [Controle optimal: théorie et applications, (online version 2020)] as an unsolved problem. In fact, this problem is proposed in the context of using Pontryagin’s Maximum Principle. We use a certain refinement of Cauchy’s Method of characteristics for stratified Hamilton-Jacobi equations to describe a large set of admissible trajectories and identify a domain on which the value function exists and is generated by a certain admissible control. The optimality is justified by using of one of the well-known verification theorems as an argument for sufficient optimality conditions.

Visualizing the scientific outputs in the field of nonlinear analysis (NA) and Mapping the co-author network of researchers in the Web of Science database (WOS) were the main purpose of this research based on scientometric methods. The rate of authors, source titles, Countries/Regions, research area and organizations in NA filed at WOS during 1985-2019 was determined. Co-author network, university co-authorship network and Country co-authorship network in NA filed at WOS during the time span investigated, also were identified by researchers. Totally, 12188 documents on NA subject were indexed on the web of science core collection from 1985 to 2019. The co-author network was mapped and analyzed. The results showed that there is an increasing rate of publishing documents in NA during the time of research.

In the development of networks, a new paradigm called flying adhoc networks (FANET) has evolved recently. FANET’s are comprised of unmanned aerial vehicles like drones, autonomous flights, etc. Drones are mainly used for surveillance, logistics, etc. On the verge of this FANET, many issues are arising regarding their proper usability, one among them being the routing of packets from the ground station to the destined drone. In this research work, we have developed a protocol for packet delivery called fuzzy adaptive routing protocol. This protocol uses factors like signal quality, signal to inference and noise ratio, hop count, and timestamp of the packet to decide on the broadcasting of route requests and reply messages. This protocol mainly contains two phases namely: controlled route request/reply broadcasting and optimal route selection for packet delivery. The performance of the proposed protocol is compared with recent techniques and the comparison depicts that the proposed protocol outperforms them and provides consistent service quality.

The goal of this research is to look at some of the sufficient conditions for approximate controllability in nonlinear resolvent integro-differential evolution control systems. We have considered that nonlinear term is satisfying Lipschitz continuity. To show the key results, we employ Gronwall's inequality, semigroup theory, and the resolvent operators. The main results have been discussed under two sets of assumptions. Application of common fixed point theorems such as Banach, Schauder, Sadovskii, etc. is avoided as discussed earlier by several researchers in the available literature. Finally, one case study based on the proposed problem is discussed in order to verify the theoretical findings.

By use of definition of a generalized fractional integral operators, proposed by Raina and Agarwal et.al, we establish a fractional  Hermite-Hadamard type inequalities for p−convex functions and an identity with a parameter. We derive several parameterized  integral inequalities associated with this identity, and provide two examples to illustrate the obtained results.

Let G be a compact Lie group. This article shows that a contraction pseudo-differential operator Aτ on Lp(G) has a Dominated Ergodic Estimate (DEE), and is trigonometrically well-bounded. Then we express ergodic generalization of the Vector-Valued M. Riesz theorem for invertible contraction pseudo-differential operator Aτ on Lp(G). For this purpose, we show that Aτ is a Lamperti operator. Then we find a formula for its symbols τ. According to this formula, a representation for the symbol of adjoint and products is given.

This paper deals with the existence of solutions to the system of nonlinear infinite-point fractional order boundary value problems by an application of n-best proximity point theorem in a complete metric space. Further, we study Hyers-Ulam stability of the addressed system. An appropriate example is given to demonstrate the established results.

Lasso regression model is a causal model based on providing a more accurate estimator through the model's dependence on shrinkage, in which the data values were reduced towards the data center. This model solves the problems of multicollinearity presence of high relationships between the explanatory variables of the model. In this research, a number of factors (sample size, number of explanatory variables and pollution rate) were adopted in order to observe the ability of these factors to effect Lasso regression.

Let A be a unital C∗-algebra. In this paper, we investigate the additive (u,β)-functional equation f(x)+u∗f(uy)+f(z)=β−1f(β(x+y+z)) for all unitary elements u in A and for a fixed nonzero complex number β. Using the fixed point method and the direct method, we prove the Hyers-Ulam stability of the additive (u,β)-functional equation (???) in Banach modules.

This paper presents a new numerical technique for solving stochastic Ito integral equations. A new operational matrix for integration of cardinal Legendre polynomials are introduced. By using this nexw operational matrix of integration and the so called collocation method, stochastic nonlinear integral equations are reduced to systems of algebraic equations with unknown coefficients. Only small dimension of Legendre operational matrix is needed to obtain a satisfactory results. Some error estimations are provided and illustrative examples are also included to demonstrate the efficiency of the new technisue.

The purpose of this applied research was to provide a Risk Assessment Model for Internet of Thing Based Technology Transfer in the Banking Area, and the Strauss and Corbin method is used to identify the initial model. In the qualitative section, by conducting in-depth interviews with 35 experts in the banking technology industry as well as technology-based banking, the information collected was analyzed in three stages open coding, axial coding, and selective coding. In a small part of the statistical population, experts and managers active in the Iranian banking industry, the sample size according to Morgan's table was 386. The results of structural equations and exploratory analysis showed that all relationships between causal factors and the main phenomenon, interfering factors and the main phenomenon The underlying factors and the main phenomenon, the main phenomenon and the strategy, and finally the relationship between the strategy and the results are evaluated in a high to medium level and in a positive and direct way.

Path planning with avoiding obstacles autonomously with a large of computing capabilities in an unknown dynamic environment is a difficult challenge for a mobile robot to solve. This research solves this challenge by combining deep Q-network (DQN) with cloud computing. To begin, a DQN is created and trained to predict the state-action value function of a mobile robot. The information collected from the original RGB image (pixels in the image) taken from the surrounding is fed into the DQN using a cloud computing platform, which reduces the algorithms high computation complexity; Finally, the action chosen policy picks the current optimal mobile robot action. To validate the DQN algorithm, we trained the robot in a dynamic environment with a simple and complex case. The simulation results show that, in a simple case of the environment, the DQN technique can converge to explore a path with fewer steps and higher average reward than in a complicated case and find a collision-free path with an accuracy rate of 89\% in the simple case and when the environment becomes more complex, the accuracy rate is 70 %.

In this paper, we give a new version of the reverse Minkowski inequality on time scales by applying diamond-αα calculus for two parameters p,qp,q and a weight function νν.

Recent developments in Basis pursuit solver algorithm have led to better beam forming techniques. Sparse representation of signal helps in better signal analysis. This paper examines how to compute the direction of arrival of non-uniform linear array using sparse computation. A comparison between traditional techniques and sparse representation to estimate the direction of arrival is also studied. A novel method is proposed based on basis pursuit denoising multichannel implementation (BPDN) to estimate the Direction of arrival. Simulation results are verified with the formulation developed for direction of arrival.

The conventional models of warm inflation include the two-stage field interaction mechanism where the inflation field interacts with other intermediate fields (bosonic and fermionic fields), which are coupled with other fields themselves. These heavy intermediate fields decay to light degrees of freedom. During these two-stage renormalizable interactions under adiabatic conditions and close to the thermal equilibrium state, the dissipative effects are produced and cause alterations in the inflationary dynamics. Interaction between the inflation, intermediate and radiation fields lead to the formation of a thermal bath during inflation, and therefore the effect of thermal and radiative corrections should also be addressed. In this work, by focusing on the regime in which the intermediate field mass is greater than temperature, a relationship is obtained for the dissipation coefficient based on the super-symmetric and numerical calculation models, which is originated from both real and virtual modes of the intermediate field. Moreover, it is indicated that the contribution of on-shell modes decay to the bosonic and fermionic radiation fields is more than expected. It is also demonstrated that there are strong dissipative effects in the validity range of a perturbative analysis.

This paper investigates an finite-time boundedness of stochastic nonlinear reaction-diffusion systems (SNRDSs) with time delays and exogenous disturbances via boundary control. Both SNRDSs with and without exogenous disturbances are discussed. We design boundary controller is efforts to achieve the required dynamic behaviors of such SNRDSs. By utilizing Lyapunov-Krasovskii functional (LKF), Wirtinger’s inequality, Gronwall inequality, and linear matrix inequalities (LMIs), sufficient conditions are derived to guarantee the finite-time bounded of proposed systems. Furthermore, the control gain matrices are defined for desired boundary controller. At last, two numerical examples are provided to demonstrate the efficacy and validity of obtained main results.

The aim of this paper is to introduce a new parameter of domination in graphs called "Rings Domination Number". Some properties and important boundaries of the rings dominating set and rings domination number have been discussed. Also, this number for certain graphs have been determined. Furthermore, some operations on two graphs as join, composition, cross product and corona, have been introduced and determined the rings domination numbers for each one of them.

This paper establish the existence of solution, and the Hyers-Ulam-Rassias stability of an Euler Lagrange type cubic functional equation using the fixed point method.

Abstract. The purpose of this paper is to establish weak and strong convergence theorems of new three-step iterations for I-asymptotically nonexpansive mappings in Banach space.Also we introduce and study convergence theorems of the three-step iterative sequence for three I-asymptotically nonexpansive mappings in an uniformly convex Banach space. The results obtained in this paper extend and improve the recent ones announced by Chen and Guo [1], S. Temir [14], Yao and Noor[16] and many others.

The outbreak of coronavirus worldwide has created many problems for companies. Companies are looking for a suitable solution to overcome this crisis. One of the measures that can reduce the negative effects of this crisis is the expansion of corporate social responsibility(CSR) activities. The purpose of this study was to investigate the protective role of the performance of CSR activities from stock returns and its effect on shareholder attention during coronary heart disease. This study is an event study that is considered for a period of six months from the beginning of the outbreak of coronavirus in Iran (February 2020) to the end of August 2020. The data analysis was performed using Eviews software and information of 33 sample member companies listed on the Tehran Stock Exchange, in three industries: pharmaceutical, food, and transportation, by least squares regression (OLS) method. The results show that the performance of CSR activities related to community indicators, employee relations, and human rights in the event periods have a positive role on the corporate stock returns and other activities do not play an effective role. The results also show that the performance of CSR has a positive and significant effect on the attention of shareholders. Using the obtained results, it can be concluded that corporations can attract stakeholders and protect the value of the companies by increasing the performance of CSR activities, especially in the community, employee relations, and human rights during the coronavirus pandemic disease period.

Image segmentation is a common technique in digital image processing and analysis that partitions an image into several regions or zones, frequently based on the pixels' attributes. Brain tumor segmentation is a crucial task in medical image processing. Early identification of brain tumors enhances treatment options and increases the patient's chance of survival. Brain segmentation from a significant number of MR images obtained in medical treatment is a challenging and time-consuming assignment for cancer diagnosis and other brain diseases. That is why it is crucial to establish an efficient automatic image segmentation system for the diagnosis of brain tumors and other prevalent nervous diseases. The goal of this research is to undertake a systematic review of MRI-based brain tumor segmentation approaches. Deep learning techniques have proven useful for automatic segmentation in recent years and gained prominence, as these methods produce superior results and are thus better suited to this task than other methods. Deep learning algorithms may also be used to process enormous volumes of MRI-based image data quickly and objectively. Many review papers on traditional MRI-based brain tumor image segmentation algorithms are available.

In this paper, the scale rate-limiting algorithmic approach namely the Token bucket algorithm is utilized to optimize the performance of cloud based software services. In distributed applications, higher availability and scalability have long been a critical challenge. In cloud computing, offering highly accessible services is critical for retaining client satisfaction, confidence and avoiding revenue losses. The gateway Zuul is considered as the entryway to various services in the Spring Cloud based software service must perform the rate-limiting process and make sure the service's reliability in the event of excessive scalability. The token bucket rate-limiting technique cannot ensure core service availability. To address this issue, this study developed an overload protection technique depending on a URI configuration file in conjunction with the Zuul gateway that may filter requests before obtaining tokens. The token bucket rate-limiting algorithm is implemented the traffic limitation function and ensured the cloud platform service's reliability and availability. The estimation of scalability, as well as availability, demonstrates the level of service supplied to consumers in response to their requests. The elasticity measures are used to assess the cloud based software services performance in terms of scalability. In the future, cloud computing improvements and expansion might increase cloud-based software services.

In this paper, a numerical method is proposed for the numerical solution of a linear wave equation with initial and boundary conditions by using the cubic B-spline method to determine the unknown boundary condition. We apply the cubic B-spline for the spatial variable and the derivatives, which generate an ill-posed linear system of equations. In this regard, to overcome, this drawback, we employ the Tikhonov regularization (TR) method for solving the resulting linear system. It is proved that the proposed method has the order of convergence O((Δt)2+h2). Also, the conditional stability by using the Von-Neumann method is established under suitable assumptions. Finally, some numerical experiments are reported to show the efficiency and capability of the proposed method for solving inverse problems.

In this paper, we proposed and studied a delayed HIV pathogenesis model with saturation incidence, both virus-to-cell and cell-to-cell transmission. We address the basic reproduction number R0, the characteristic equations, and local stability of feasible equilibria are established. Where the delay incorporates both virus-to-cell and cell-to-cell transmission. Moreover, we discuss the existence of Hopf Bifurcation when a delay is used as a bifurcation parameter. Numerical simulations are performed to satisfy our theoretical results.

Utilizing new models instead of traditional statistical models can be quite useful in this field. Examples include data mining, which possesses both high speed and accuracy as well as nonlinear and non-parametric properties Therefore, in the present study, the effects of performance criteria on social responsibility disclosure level was investigated and analyzed via utilization of data mining, Henceforth, a model will be presented aiming to estimate/project the optimal level of social responsibility disclosure grounded on performance criteria. The present study is applied in terms of its nature and purpose/objective as well as based on the field research method of data collection. The statistical population are companies listed on the Tehran Stock Exchange and the required data were collected and analyzed using six data mining methods during the 2013-2019 period. The findings reveal it is possible to classify and predict the optimal level of corporate social responsibility disclosure within the Iranian economic circumstances/environment. Moreover, the utilization of the classification algorithm in the vicinity of the nearest neighbor can accurately predict the optimal level of corporate social responsibility disclosure based on performance criteria. The findings of this study indicate that performance metrics can be a positive predictor of the optimal level of corporate social responsibility disclosure. In addition, due to the potent strength of the proposed model, the used model in this research can be utilized to rank/rate the level of corporate social responsibility disclosure.

MANETs (Mobile Ad-Hoc Networks) are fast-developing networks that gaining popularity in the recent period. They play an important part in a variety of applications, and as a result, they got a lot of attention. Routing remains a challenging problem in a MANET since it lacks infrastructure due to its self-configuration nature in addition to the frequent changes in topology due to node mobility. The requirement in MANET routing protocols is to send and receive information among the nodes with the best route with lower delay. Routing protocols are responsible for the efficient delivery of messages between mobile nodes with a focus on the use of limited resources. This paper investigates a group of the most prominent routing protocols of MANET and compares their performance in regard to different parameters such as (end-to-end delay, throughput, average jitter, and routing overhead). The protocols' performance is evaluated under different operating conditions, such as the terrain size that reflect different node density for various terrain dimensions. The amount of data exchanged is varied also through varying the number of bit-rate connections for the same network size. Results of the developed scenarios for the investigated protocols with the considered parameters are collected with the aid of the QualNet v5.2 network simulator.

In this paper, we introduce the generalized hyperbolic Jacobsthal numbers. As special cases, we deal with hyperbolic Jacobsthal and hyperbolic Jacobsthal-Lucas numbers. We present Binet's formulas, generating functions and the summation formulas for these numbers. Moreover, we give Catalan's, Cassini's, d'Ocagne's, Gelin-Cesàro's, Melham's identities and present matrices related with these sequences.

Let A be an F-algebra over the complex field. Let B be an F-algebra such that the intersection of kernels of all continuous multiplicative linear functionals on B is singleton zero. If any nonempty open subset of the collection M(B) of all continuous multiplicative linear functionals in the Gelfand topology contains uncountably many functionals or if B is a commutative Frechet algebra such that M(B) has no isolated points, then any homomorphism from A onto a dense finitely generated subalgebra of B is continuous. This result has been proved in this article which is similar to a result derived by R.L. Carpenter.

In this paper, by using the Schauder fixed point theorem, we obtain the existence of positive solutions for discrete fractional boundary value problem. Also, we establish upper and lower solution for this problem. Our results extend some recent works in the literature.

This research was conducted with the objective of developing a model for the adoption of electronic banking technologies based on the behavior of users in Shahr (City) Bank. The research method is qualitative and performed utilizing the Delphi Method. First, data from research papers/literature and interviews were analyzed and coded using MAXQDA software and 76 components were obtained. The extracted components were grouped into four dimensions: sociological, psychological, demographic and technical services plus 10 indicators of culture and norms, social class, social pressure, demographics, quality of technical services, ease/simplicity of technical services, behavioral, emotional, perceptual and personality. In two stages, the Delphi group reached a consensus on 74 dimensions, indicators and components. The findings of the DEMATEL technique demonstrated that the sociological dimension has the greatest impact on other dimensions as far as the acceptance/adoption of the technology. Indicators such as personality, perception, emotions, behaviors, service quality and culture and norms all have the largest impact. Compliant with the findings, the research model was devised/designed.

The purpose of this paper is to show some particularities that the differentiability sets generated from the norms have in the Banach spaces. In this sense, it will be shown that the Gaussian measure of the Fr'echet differentiability set of the norm of the space ℓ∞(R)ℓ∞(R) of real bounded sequences is zero and that in the case of the space BV[a,b]BV[a,b] of bounded variation functions its norm is not Fr'echet derivable in any element of this space.

In this paper, we found some methods for solving one of the bicriteria machine scheduling problems (BMSP). Our discussed problem is represented by the total completion and the total tardiness jobs times (1//(∑Cj,∑Tj)) simultaneously. In order to solve the suggested BMSP, some new heuristic and metaheuristic methods are proposed which are produced good results. The results of the new suggested methods are compared with the exact method; like the complete enumeration method (CEM) and Branch and Bound (BAB) method, then compared results of the heuristics with each other's to obtain to the most efficient method.

In this paper, the best proximity pair problem is considered with a cone metric. the conditions for the existence and uniqueness of the best proximity pair problem is discussed by using interesting relationships in Riesz spaces. This problem is studied for T-absolutely direct sets. Also, given the conditions considered for this problem, it is shown for the cone cyclic contraction maps, the best proximity pair problem is uniquely solvable.

The aim of this paper is to study the dynamics of the system of two rational difference equations: xn+1=αn+yn−kyn,yn+1=αn+xn−kxn,n=0,1,… where {αn}n≥0 is a two periodic sequence of nonnegative real numbers and the initial conditions xi,yi are arbitrary positive numbers for i=−k,−k+1,−k+2,…,0 and k∈N. We investigate the boundedness character of positive solutions. In addition, we establish some sufficient conditions under which the local asymptotic stability and the global asymptotic stability are assured. Furthermore, we determine the rate of the convergence of the solutions. Some numerical are considered in order to confirm our theoretical results.

Solitary waves are interesting phenomena arising in various fields of physics, chemistry, and biology. Nonlinear continuous and discrete models supporting wave solutions of solitary behaviour have received increasing attention in recent years. Some examples of such integrable systems include Korteweg de-Vries (KdV) equation, the nonlinear Schrödinger (NLS) equation, and the Manakov system (MS). In this paper, we propose a discrete nonlocal version of the nonlinear Manakov system which admits spatial and temporal PT-symmetry. PT-symmetry property gives relevance to various fields in physics and has received a lot of attention in the studies of integrable nonlinear equations. In this work, the time evolution of solitary and periodic wave solutions in the proposed system has been numerically investigated. Suitable initial conditions have been considered to construct bright and dark solitons. The variational iteration method (VIM) was used to simulate the solution of the system. The error measurement of the simulation demonstrates the efficiency of the numerical method in constructing the different types of wave solutions.

Of concern the present study deals with an updated food chain model in a natural environment with the inclusion of fear effect in the prey population through Holling type II functional response in presence of prey refuge effect. The present model is affluent with intra-specific competition among the hunter species having specific mortality. The model system emphasizes its characteristics in the proximity of the probable equilibrium position in the realm of biological dynamics. The response of the system is explored further for its stability analysis based on prerequisites and Hopf-bifurcation phenomena as well with respect to some significant model parameters. Extensive numerical simulation reveals the validity of the proposed model so as to indicate the ecological implications.

Considering a function f(z) which is the extremal function for p−valently starlike of order α in the open unit disk, two new classes S∗p(m,α) and Kp(m,α) are introduced. The object of the present paper is to discuss some interesting problems of functions f(z) concerned with S∗p(m,α) and Kp(m,α).

This paper investigates the consistency of bipolar max-TD Fuzzy Relation Equations (FREs) where TD is the drastic product with a specific drastic negation operator. We firstly study the bipolar max-TD fuzzy relation equation. Then the special characterizations of its feasible domain and its maximal and minimal solutions are presented. Furthermore, some necessary conditions and sufficient conditions are proposed for the solvability of a system of bipolar max-TD FREs. Some examples are also given to illustrate them.

In this paper by taking into account three trends prevalent in metric fixed point theory, namely, use of control functions instead of contraction constants, consideration of relational structure in the metric space and fixed point studies of discontinuous functions, we formulate and solve a new problem in relational metric fixed point theory. Our result extends the well known result of Kannan. The theorems are illustrated with examples. Further the proble is shown to have Hyers-Ulam-Rassias stability property. We make an application of our main result to a problem of a nonlinear integral equation.

Performance issues such as system resources leaking, application hang, and Software Aging (SA) can affect the system's reliability and minimize user experiences. Therefore, these issues need to be analyzed and forecasted to prevent incoming issues. Finding the root cause and analyzing the internal behaviors become troublesome due to the complexity of modern systems such as the Microsoft Windows Operating System OS. Microsoft builds multiple tools and platforms such as the Performance Monitor (PerfMon.exe) tool and Performance Counter for Windows (PCW) platform to monitor the activities inside Windows OS. This paper aims to use Windows OS tools for simulating performance issues in an experiment, data collection, and log format converting. In contrast to other works, the deep learning Long Short-Term Memory (LSTM) method and the Auto-regressive Integrated Moving Average (ARIMA) model were generated and compared. The best model that provides the lowest error rate of the prediction simulated performance issue was selected. The results declare the preference of using the ARIMA model with order (2,1,1) that provides the observed lowest error rate for both MAE and RMSE compared with other values in previous lags. And the observed LSTM has an error rate of 4.796, whereas the ARIMA model has an error rate of 0.0119. From those results, we can confirm of using the ARIMA model with its selected parameters can predict the small jump fluctuations behavior observed from the memory metric.

In this paper, we study some new common fixed point theorems for a pair of weakly compatible mappings satisfying the (CLRg) property in modular metric spaces. We also generalize and improve several results available from the existing literature. As applications of our results, we also provide some applications on the existence and uniqueness of the solution to integral type contraction and Volterra type integral equations.

In the present paper,  new subclasses of bi-univalent functions associated with q−q−calculus operator are introduced and coefficient estimates for functions in these classes are obtained. Several new (or known) consequences of the results are also pointed out.

The main purpose of this study is to investigate the effect of interactive and diagnostic approaches in the use of management control systems on the acceptance of new management accounting activities. This study also aims to determine the most appropriate modern management accounting techniques in public companies of Iran. The statistical population of the research, in the qualitative part, includes experts, and in the quantitative part includes financial managers and heads of industrial accounting in Iranian public companies. The snowball method based on the views of 15 experts is used in the qualitative section. 384 financial managers and heads of industrial accounting are selected based on Morgan's table in the quantitative section. In this study, the field method, with the help of library studies and interviews, is used to collect data and determine indices. In the quantitative part, data were collected using specialized questionnaires. After data collection, the hybrid method was used to combine the results of systematic review studies and interviews. Interpretive Structural Model (ISM) was used to determine the appropriateness and importance of the study activities. Qualitative content analysis was performed using MAXQDA software. Structural equation modeling with the technique of partial least squares (PLS) was also used to test hypotheses. The results of hypothesis testing showed that the difference between interactive and diagnostic approaches affects the application of management control systems, selection of new management accounting techniques and public companies, and a crucial role in the success of these techniques in public companies.

In this paper, we present a mathematical model of Stefan problem, this model is ice melting problem where the interface of solid/liquid moves along the y-axis, which is including time fractional derivative in Jumarie sense. The obtained solution of this problem is an approximate solution using fractional variational iteration method.  Graphically the results will be compared with an exact solution to the integer order derivatives.

Let φφ be a non-decreasing unbounded function and p,qp,q be any two positive integers with p≥q≥1.p≥q≥1. The relations between the growth of entire or meromorphic coefficients and the growth of entire or meromorphic solutions of general complex linear differential equation with entire or meromorphic coefficients of finite [p,q][p,q]-φφ order are investigated in this paper. Improving and extending some earlier results of J. Liu, J. Tu, L.Z. Shi, L.M. Li, T.B. Cao and others, we obtain some more results here.

In this paper, we study the nonsmooth multiobjective optimization problems with equilibrium constraints (MOMPEC). First, we extend the Guignard constraint qualification for MOMPEC, and then more constraint qualifications are developed. Also, the relationships between them are investigated. Moreover, we introduce the notion of primal Pareto stationarity and some dual Pareto stationarity concepts for a feasible point of MOMPEC. Some necessary optimality conditions are derived for any Pareto optimality solution of MOMPEC under weak assumptions. Indeed, we just need the objective functions to be locally Lipschitz. Further, we indicate our defined Pareto stationarity concepts are also sufficient conditions under the generalized convexity requirements.

An introduction of a new subclass of bi-univalent functions involving Sakaguchi type functions defined by (p,q)(p,q)-Derivative operators using Gegenbauer polynomials have been obtained. Further, the bounds for initial coefficients |a2||a2|, |a3||a3| and Fekete Szeg\"{o} inequality  have been estimated.

Machine learning plays a vital role in construction estimation which could make improve the project's safety, and reliability. Many studies have been proposed to explore the potential opportunities to review this technology in the construction cost in structure and transport fields. However, no comprehensive study to review the global research trends on this area's advancement in construction cost. The goal is to taxonomy, review, and summarize the state-of-the-art knowledge body on this topic in a systematic manner based on machine learning (ML) and deep learning (DL) approaches. To achieve this, this paper considered many studies in construction management related to bibliographic records retrieved from the Scopus database by adopting a quantitative analysis approach. This paper found that from 2017 to 2021, there has been a considerable increase in the number of publications in this domain. We categorized and explained civil projects into structures and transport cost, ML/DL as supervised and unsupervised approaches, and the evaluation metrics proposed to evaluate the performance of ML-Cost estimations in the civil area. The findings will help both professionals and researchers to understand and evolve the recent trend research ML/DL methodologies and their role played in the construction management domain.

We generalize the concept of diffusion equations on weighted graphs, which is also known as ωω-diffusion equations, to study fractional order diffusion equations on weighted graphs. More precisely, we replace the ordinary first order derivative in time by a fractional derivative of order αα in the sense of Riemann-Liouville and Caputo fractional derivatives. We prove the existence of solutions of fractional order diffusion equations on graphs using the concept of αα-exponential matrix and illustrate the solutions through numerical simulation in various examples.

In this paper, we propose a numerical scheme by using Least Squares Support Vector Regression (LS-SVR) for the simulation of the inverse Stefan problem, which has ill-posedness issues. The purpose of this paper is to express the temperature distribution in a homogeneous environment with a phase change. In the proposed machine learning approach, we apply the unconditionally stable Crank-Nicolson method to decrease the computational cost and reduce one of the dimensions. Therefore, we solve an ODE equation at each time step. The training points of the network are chosen as the Chebyshev roots, which have a normal distribution, and our constructed roots, which we describe more precisely later. In the proposed method, the regularization parameter of the SVM aims to overcome the instability issues, leading to convergent approximation. For the given method, both the primal and dual forms are investigated. The dual form of the problem is written in matrix form. Finally, some numerical examples are provided to illustrate the effectiveness and accuracy of the proposed method.

This paper aims to provide better approaches for segmenting and classifying brain tumours using Magnetic Resonance images (MRI). In this paper, the wavelet features are formed by the transformation of probability density function (PDF) to spectrogram images using Continuous Wavelet Transform (2D-CWT), which is a simple method for extracting features, whereas the Feature extraction methods (PDF and 2D-CWT) are improving the performance. In addition, a morphological operation for segmenting images and a convolutional neural network (CNN) are utilized as a classifier in order to increase the segmentation performance. On the BraTS2019 dataset, the method's performance is assessed in terms of F1-score and tumor region segmentation accuracy. This achieved the greatest results, with accuracy and F1-score of 97.37 \% and 97.43 \%, respectively.

In this paper, we introduce a new iteration method called inertial residual algorithm for finding a common fixed point of finite family of strictly pseudocontractive mappings in a real uniformly smooth Banach spaces. We also establish weak and strong convergence theorems for the scheme. Finally, we give numerical experiment to explain the proposed method. Our results generalize and improve many recent results in the literature.

In this paper, we study the initial value problem for a semi-linear heat equation with memory in nn-dimensional space RnRn. Under a smallness conditions on the initial data, the global existence and decay estimates of the solutions are established. Furthermore, time decay estimates in higher Sobolev space of the solution are provided. The proof is carried out by means of the point-wise decay estimates of the solution in the Fourier space and a fixed point-contraction mapping argument.

The aim of this paper is to present dual optimality conditions for the difference of two non-negative valued affine increasing and radiant (IR) functions. We first give a characterization of dual optimality conditions for the difference of two non-negative valued increasing and radiant (IR) functions. Our approach is based on the Toland-Singer formula.

The linear canonical transform (LCT) provides a unified treatment of the generalized Fourier transforms in the sense that it is an embodiment of several well-known integral transforms including the Fourier transform, fractional Fourier transform, Fresnel transform. Using this fascinating property of LCT, we in this paper construct associated wavelet frames. To be precise we introduce wavelet frames whose construction depends on the nonuniform multiresolution analysis associated with linear canonical transform(LCT-NUMRA) whose translation set is not necessarily a group. The translation set is taken for elements in Λ={0,r/N}+2Z,N≥1 (an integer) and r is an odd integer with 1≤r≤2N−1 such that r and N are relatively prime and Z is the set of all integers. Furthermore, we establish a necessary and sufficient conditions for such nonuniform wavelet frames associated with linear canonical transform.

Today, finger vein identification is gaining popularity as a potential biometric identification framework solution. Machine learning-based unsupervised supervised, and deep learning algorithms have had a significant influence on finger vein detection and recognition at the moment. Deep learning, on the other hand, necessitates a large number of training datasets that must be manually produced and labelled. In this research, we offer a completely automated unsupervised learning strategy for training dataset creation. Our method is intended to extract and build a decent binary mask training dataset completely automatically. In this technique, two optimization steps are devised and employed. The initial stage of optimization is to create a completely automated unsupervised image clustering based on finger vein image localization. In the second optimization, the retrieved finger vein lines are optimized. Lastly, the proposed system has a pattern extraction accuracy of 99.6\%, which is much higher than other common unsupervised learning methods like k-means and Fuzzy C-Means (FCM).

In this paper, parallel to the ideas based on Ahmadullah et al. [3, 4, 5], and Eke et al. [17], we prove the existence and uniqueness of the common fixed point for a pair of self-mappings employing (E. A.)-property in metric-like spaces for implicit contractive mappings related to binary relation. Henceforth, results obtained will be verified with the help of illustrative examples. As an application of the results, we solve two boundary value problems of the second-order differential equation.

In this paper, we propose a new monotone hybrid method for getting a common fixed point of a family of generalized nonexpansive mappings and prove a  strong convergence theorem for this family in the framework of Banach spaces. Using this theorem, we obtain some new results for the class of generalized nonexpansive mappings and finitely many generalized nonexpansive mappings. Using the FMINCON optimization toolbox in MATLAB, we give a numerical example to illustrate the usability of our results.

There are proved existence results for Ψ-asymptotic relationships between Ψ-bounded solutions of two Lyapunov matrix differential equations.

This paper attempts to study the vibration characteristics of a simply supported nth order rectangular nanoplate using the modified couple stress theory. The modified couple stress theory, which has only one length scale parameter, has been used to consider the small-scale effects. The basic and auxiliary equations of the nanoplate are obtained after determining the strain energy, kinetic energy, and external work and substituting them into Hamilton’s equation. Then, the vibrations of the simply supported nth order rectangular nanoplate with a thickness of h are investigated by substituting the boundary and force conditions into the governing equations. Navier’s method is used for the solution. The results indicate that the frequencies of the different modes of the nth order nanoplate decrease with an increase in the length-to-thickness ratio of the nanoplate. Furthermore, the frequency is the smallest when the effect of the size parameter is not considered (classical theory), and it increases with an increase in the size effect. In addition, the frequency is smallest for the first mode and increases for the subsequent modes. Also, the vibrational frequency increases with an increase in the order of the nanoplate.

In this article, the concept of n-sequences in topological spaces has been introduced which is new to the existing literature. We study the sequential limit aspect of statistical convergence for such sequences. Besides, the notions of subsequences, limit points, statistical limits points, and statistical cluster points in topological spaces have been given for n-sequences. This material contains a detailed explanation of inclusion relations between these points spaces and their basic properties. We also introduce sn and s∗n-convergent spaces and discuss some of their properties.

For any R-module W, Dj(W) presented as the total of all J-small sub-modules. If A and B are sub-module of W, we say A is ⨁ Dj'supplement of B in W if W=A+B=A⨁A´, for A´↪−−W, and A⋂B≪jDj(A). If every sub-module has ⨁ Dj-supplemented, then W is ⨁ Dj-supplemented A sub-module A of W. If a sentence is conclusive, it is said to be cofinite i.e., WA is finitely generated. Also we introduce cofinite ⨁ Dj-supplemented if every cofinite sub-module of W has ⨁ Dj-supplemented.

Fluctuations in asset prices and the resulting uncertainty are one of the most important macroeconomic variables that affect different sectors of the economy in various ways. Therefore, this study is conducted to identify and rank financial market risks in Iran. This study was performed in two parts: qualitative and quantitative. The statistical population in the qualitative section includes the University of Professors in the field of economics in Iran, where 1010 people were selected as a statistical sample by available sampling. The statistical population in the quantitative section were professors and doctoral students in the field of economics. By random sampling method, 3030 people were selected. Data collection tools are the Delphi questionnaire and pairwise comparison questionnaire. Data analysis was performed by fuzzy Delphi and AHP methods. In the results of the qualitative section, 7 components including 44 components for bad economic uncertainty and 33 components for good economic uncertainty were identified. In the results of the quantitative section, stock index uncertainty with a weight of 0.3910.391 and inflation uncertainty with a weight of 0.2760.276 rank first and second in bad economic uncertainty. Also, economic growth uncertainty with a weight of 0.4930.493 and liberalization of financial markets with a weight of 0.3110.311 rank first and second in good economic uncertainty, respectively.

In the present paper, we introduce new lacunary strong convergent vector-valued sequence spaces defined by fractional difference operator and Musielak-Orlicz function. We make an effort to study some topological properties and also prove some inclusion relations between these spaces.

The problems of a single product economy and reliance on oil revenues have affected an economy affected by foreign factors, especially the unstable oil revenues. Considering this characteristic of the Iranian economy, the importance and role of non-oil exports can be perceived. Studies on the developed countries indicated that all their economic and product developments have been due to small and medium enterprises. These industries play an effective role in the economic development of the countries through their significant exports. In addition, the intensification of global competition increased uncertainty, and the growing demand for diverse products have made these industries more popular. The current study aimed to investigate the effects of the firm characteristics and decision-makers on the banking and export activities of small and medium companies. It is an applied study in terms of the objective and a descriptive study in terms of method. The statistical population of the current study has been defined in two phases of the experts and authorities. The data were collected by interview and questionnaire in two stages. The Grand Theory method and the second phase, the structural equation model, have been used to analyze the information in the first phase. The results indicated that the management ability, management experience, management commitment, firm size, company financial capacity, company technological capacity, company knowledge capacity, scientific management capacity, purposeful management actions, company innovation capacity, and finally, human resource capacity are among the corporate management factors effective on the banking and export activities of the small and medium companies.

Assume a large microscopic internal bonding chemical structure of a substance designed like a Petersen graph where electrons are the vertices and edges representing the bonding energy levels in between them. For large structures, it is difficult to find out the average level of bonding energy between any pair of electron-proton microscopic structures. For a chemical scientist, it is a difficulty and a challenge both to find out what is the average amount of energy bounded between any subsequent pair of electron-proton bi-valent bond, trivalent bond, or tetravalent bond. This paper presents a sample-based estimation methodology for estimating the bonding energy mean value. A node-sampling procedure is proposed whose bias, mean-squared errors and other properties are derived. Results are supported by empirical studies. Findings are compared with particular cases and confidence intervals are used as a basic tool of comparison for robustness purposes.

The numerical technique for a two-dimensional time-dependent nonlinear Schrodinger equation is the subject of this work. The approximations are produced using the weak Galerkin finite element technique with semi-discrete and fully discrete finite element methods, respectively, using the backward Euler method and the crank-Nicolson method in time. Using the elliptic projection operator, we provide optimum L2 error estimates for semi and fully discrete weak Galerkin finite elements. Finally, we present numerical examples provided to verify our theoretical results.

In geometry, a conic is a plane curve whose coordinates satisfy a quadratic equation in two variables and can be expressed in matrix form. This equation allows deducing and expressing geometric properties of conic sections. In this article, we define certain subclasses UkS(λ,γ,τ,ρ) and UIkS(λ,γ,τ,ρ) of holomorphic mappings associated with the Janowski-type mappings. These functions are actually generalizations of some basic families of starlike and convex mappings. We study sufficient conditions for f∈UkS(λ,γ,τ,ρ) along with the characterization, coefficient bounds and other problems. Using certain conditions for functions in the class UkS(λ,γ,ϱ,σ), we also define another class and study some subordination related result.

In this work, we use the averaging theory of first order to study the periodic solutions of the perturbed fifth-order autonomous differential equation x(5)−λx....+(p2+1)x...−λ(p2+1)x¨+p2x˙−λp2x=εF(x,x˙,x¨,x...,x....), where λ, and ε are real parameters, p is rational number different from −1, 0, 1, ε is a small enough and F∈C2 is a nonlinear autonomous function. we present some applications to illustrate our main results.

In this article, we introduce a new class of multi-cubic mappings and then unify a system of cubic functional equations defining a multi-cubic mapping to an equation, as multi-cubic functional equation. Moreover, we show that the mentioned equation describes the multi-cubic mappings. Furthermore, we prove the Hyers-Ulam stability of multi-cubic mappings in non-Archimedean normed spaces by applying a known fixed point theorem.

In this work, we introduce a partial ordering on a Banach space induced by a real valued function and prove some convergence theorems for αα-nonexpansive mapping in a ordered Banach space to a fixed point of mapping using this partial ordering. Moreover we give example to furnish the definition of the partial ordering induced by a real valued function.

The digital society has developed in recent years drastically as artificial intelligence has taken on a greater role. Plural companies have begun to see the potential of applying artificial intelligence in digital marketing purposes with customers. Despite the benefits of artificial intelligence, there are concerns many people that human interaction decreases. One reduction of human interaction can in turn complicate the creation of trusting customer relationships about artificial intelligence gets an advantage. This thesis obtains a qualitative research method and the empirical material was gathered through semi-structured interviews with seven respondents.

With the Internet being the dominant tool for global communication in today’s world, the issue of Internet information security has become quite a significant challenge. Wireless sensor networks, like other systems, can be penetrated and it appears that natural communities, due to their adequate capabilities in information processing, can be utilized as a model in these networks. Accordingly, in this study, we shall analyze a model that uses the energy and operational power of the three meta-heuristic algorithms GA, PSO & GSO that occur in natural communities. Furthermore, we introduced four Dos, D-dos, Wormhole, and Sinkhole attacks to these algorithms, and thereafter examined their latency, throughput, and energy. The findings revealed that among these algorithms, the GA algorithm has the highest energy and the PSO algorithm has the highest throughput.

One of the factors affecting the economic growth and development of countries is an investment, so it is very important to pay attention to the growth and expansion of investment and the factors affecting it. Therefore, the main purpose of this study is to investigate the impact of the development of Islamic banking and inflation on an investment. This research is descriptive in nature and applied in purpose. The relationships between the variables have been studied using the data panel method based on statistical data from Iran, Malaysia and Turkey for the period 2005 to 2020. To collect the necessary data and information to test the hypotheses, the data of the Central Bank of Iran and the World Bank have been used. Findings show that the variable of Islamic banking development has a positive and significant relationship with investment in selected countries and the variable of inflation rate has a significant but negative relationship with investment. Also, based on the results, a positive and significant relationship between GDP variables, the degree of trade openness with investment was determined.

The main purpose of this paper is to consider the best approximation in fuzzy cone normed linear space and study its related results. We introduce quotient fuzzy cone normed linear space and proved some results of approximation in such spaces. We also discuss the relation in proximity and Chebyshevity of a given space and its quotient space.

Traditional techniques of the Helmert model are known to be used for the purpose of smoothing the data. Therefore, the special Helmert robust technique is adopted in this research to reach the internal and external reliability and suitability for the data using observed points and corresponding weights, which form the objective of this study. The least-squares method poorly performed in the presence of outliers, in comparison with the use of the robust traditional techniques, to reduce the outliers’ impact. Geodetic reliability consists of two basic components: internal reliability and external reliability, which are critical measures of validating the model. Through the analyses, the internal reliability values represented by the minimum detectable bias become larger, increasing the reliability value and decreasing the probability of error. After comparing the two methods, the best method was chosen based on the final value of the probability of error. The values of the measuring parameters were modified accordingly. This method is essential to determine the reliability of the model and is bound by the effect of observations on the estimated variance of the parameters. Depending on the using various methods to estimate the reliability of the Helmert model, the results indicated that the suggested robust M method is the most accurate. And in this contribution, the minimum detectable bias was used to determine the outliers in the Gauss-Helmert model. The results showed that the robust M method has the ability to detect outliers and reduce their impact by calculating the value of the Mean Absolute Percentage Error.

In the present paper, the effects of radiation, variable viscosity, and the inclination of the artery on copper nanofluid through composite stenosis with chemical reaction are discussed. The viscosity of blood is varied with temperature as represented in the Reynolds viscosity model. The coupled nonlinear equations of the nanofluid model are simplified by considering the mild stenosis case. The governing equations are solved numerically by applying the Finite Difference Method. The effects of the physical parameters on the velocity, temperature, and concentration along the radial axis have been studied and are physically interpreted for medical applications. The effect of shear stress along the increasing height of stenosis has been explained with the help of graphs. The proposed work will be beneficial to clinicians, hematologists, and biomedical engineers because they serve as useful approximations, which are capable of throwing some light toward the understanding of the genesis of pathological states, like arteriosclerosis as well as the mechanism of gaseous exchanges that take place within arteries and capillaries.

The purpose of the present study was to investigate the effectiveness of e-learning systems in teaching mathematics to tenth-grade students in both fields of study mathematical physics and experimental sciences disciplines in North Khorasan province (Northeastern Iran). This research was conducted as applied research and by a descriptive-survey method. The statistical population of the present study includes all tenth-grade students of both mathematical physics and experimental sciences in North Khorasan province (2900 students) and finally, about 340 students were selected using Krejcie and Morgan selection table. The research data collection tool is the standard e-learning questionnaire of Watkins et al. \cite{24}. This questionnaire includes 25 questions and 6 factors (access to technology, motivation, ability to learn through the media, Internet group conversations, and important issues for success in e-learning). In order to test the research hypotheses, the structural equation modelling method with LISREL software version 8.8 was used. The results of factor analysis showed that among the items of skills and continuous communication only two items were ma1 and ma4, among the items of motivation, only item a1, among the items of access to technology only item d2, and among the items of the ability to learn through the media, the two items t1 and t2, among the items of Internet group conversations, only the item g3 and among the items of important issues for success in e-learning, the two items m1 and m3 were approved. Because the factor load of these items is more than 0.4 and also the value of the computational t-statistic is more than the standard value of 1.96. In other words, the more students are equipped with these items, the more successful they will be in learning mathematics through electronic systems. The results also showed that among the variables affecting the evaluation of the success of electronic systems, only the value of the motivation t-statistic (1.97) is higher than the standard value of 1.96. In other words, the results indicate that the more motivated students are, the more they will learn mathematics through electronic systems.

In this paper, we study zero-preserving character of a linear operator on the space of complex-polynomials which also preserve Bernstein-type inequalities for polynomials.

The concept of Cˇech fuzzy soft bi-closure space (Cˇfs bi-csp) (U,L1,L2,S) is initiated and studied by the authors in \cite{6}. The notion of pairwise fuzzy soft separated sets in Cˇfs bi-csp is defined in this study, and various features of this notion are proved. Then, we introduce and investigate the concept of connectedness in both Cˇfs bi-csps and its associated fuzzy soft bitopological spaces utilizing the concept of pairwise fuzzy soft separated sets. Furthermore, the concept of pairwise feebly connected is introduced, and the relationship between pairwise connected and pairwise feebly connected is discussed. Finally, we provide various instances to further explain our findings.

In this paper, we show that the following three-dimensional rational system of difference equations xn=zn−1zn−3bxn−2+azn−3, yn=xn−1xn−3dyn−2+cxn−3, zn=yn−1yn−3fzn−2+eyn−3, n∈N0, where the parameters a,b,c,d,e,f\ and the initial values x−i,y−i,z−i, i∈{1,2,3}, are real numbers, can be solved in explicit form. In addition, the solutions of aforementioned systems according to the special cases of the parameters are given in closed form. Later, the forbidden set of the initial values for aforementioned system is described. Finally, an application and numerical examples to support our results are given.

The present study aimed to investigate the effect of business process reengineering on information technology management improvement in knowledge-based IT organizations according to statistical analysis methodology in SPSS. The statistical population consisted of two general groups, first, knowledgeable professors, and second, ITIL experts, or similar positions in knowledge-based IT organizations. After distributing 100 questionnaires, the sample size of the research was equal to 96 available and cooperative experts who were collected by a combination of two methods, namely non-probability purposive (judgmental) sampling, and snowball sampling, in the spring of 2019. According to the important result of the study "Investigating the Effect of business process Reengineering on the promotion of ITM", since the slope of the regression line was the correlation coefficient sign, there was a positive significant relationship between IT design process reengineering (X2) and IT transfer process reengineering (X3) variables because the statistical correlation coefficient between them was calculated to be 0.913, and there was a statistical correlation coefficient of 0.778 between the IT strategy process reengineering (X1) and continuous IT improvement process reengineering (X5), and a correlation coefficient of 0.836 between the IT design process reengineering (X2) and the IT strategy process reengineering (X1), and the correlation coefficient equal to 0.838 between the IT operation process reengineering (X4), and IT transfer processes reengineering (X3). The impact of business process reengineering on IT management improvement can be comprehensively evaluated due to the high correlation between research variables and indices.

In this paper, a new algorithm is proposed to solve pseudo-monotone variational inequalities with the Lipschitz condition in a real Hilbert space. This problem is an exceptionally general mathematical problem in the sense that it consists of a number of the applied mathematical problems as a special instance, such as optimization problems, equilibrium models, fixed point problems, the saddle point problems, and Nash equilibrium point problems. The algorithm is formulated around two algorithms: the extra gradient algorithm and the inertial algorithm. The proposed algorithm uses a new step size rule based on local operator information rather than its Lipschitz constant or any other line search strategy and operates without any knowledge of the operator's Lipschitz constant. It presents the strong convergence of the algorithm. Finally, we conduct a number of numerical experiments to determine the performance and superiority of the described algorithm.

In this work, the fractional natural transform decomposition method (FNTDM) is employed to obtain approximate analytical solutions for some time-fractional versions of the nonlinear Swift-Hohenberg (S-H) equation with the fractional derivatives taken in the sense of Caputo. The S-H equation models problems arising from fluid dynamics and describes temperature dynamics of thermal convection as well as complex pattern formation processes in liquid surfaces bounded along a horizontally well-conducting boundary. To explore the applicability, simplicity, and efficiency of the FNTDM, numerical simulations are provided for each of the considered problems to demonstrate the behavior of the obtained approximate solutions for different values of the fractional parameter index. The obtained simulations show a similar resemblance with those in existing related literature and further confirm the applicability of the considered method to even complex problems arising in diverse fields of applied mathematics and physics.

‎In the present paper‎, ‎a novel two-step iterative method‎, ‎based on real interval arithmetic‎, ‎is produced‎. ‎By using this method‎, ‎we obtain enclosures of roots of systems of nonlinear equations‎. ‎Discussion on the convergence analysis for the produced method is presented‎. ‎The efficiency‎, ‎accuracy‎, ‎and validity of this method are demonstrated by its application to four implemented examples with INTLAB and by comparing our results with the results obtained by other methods available in the literature‎.

In this paper, we investigate the existence and uniqueness of solutions for nonlinear implicit Hilfer-Hadamard fractional differential equations involving both retarded and advanced arguments and nonlocal mixed boundary conditions. We also use the Banach contraction mapping principle and Schaefer’s fixed point theorem to show the existence and uniqueness of solutions. The results obtained here extend the work of Benchohra et al. [10] and Haoues et al. [18]. An example is also
given to illustrate the results.

Drones or unmanned aerial vehicles (UAVs) have rapidly spread all over the world and are becoming widely popular in major cities for personal and commercial use. It has also been widely used for military purposes in the last decade. Thus, it has become difficult to maintain control over them and the risks they pose to privacy and security. In this paper, we present a solution to detect drones before they can reach a sensitive area or residence using the latest YOLOv4 deep learning algorithm while using Darknet as a backbone. We trained our model on different images at different distances and climatic conditions and trained our model to detect birds and aircraft that are very similar to drones at higher distances that may cause confusion, and also train the system at close distances and at very low and high image quality. For all available cases, our dataset was collected from three global and certified datasets in aircraft detection systems and the result was a dataset containing all cases. However, the collection of drones, birds and aircraft datasets is not easy to obtain. The proposed method achieved an accuracy of 98.3\% with the main challenge of detecting similar small objects near and far in all conditions.

In this paper, we investigate the existence, asymptotic, Hyers-Ulam, and semi-Hyers-Ulam-Rassias stability results for the Hilfer fractional initial value problem involving the (p1,p2...pn)-Laplacian operator by using the fixed point arguments.

In recent years, the issue of power consumption in parallel and distributed systems has attracted a great deal of attention. Regarding the ever-increasing  development data and computing centers due to the contribution of cloud computing systems in such sectors, power consumption has always been of the  concerns due to Carbon dioxide emissions and consequently the Negative impact on the environment. In recent years, the notion of power and also "Green  Computing" has found a crucial spot in the tasks scheduling in cloud data centers. The clustering technique, as well as Dynamic Voltage and Frequency  Scaling (DVFS) techniques, have focused on the reduction of the consumption of power particularly, and the optimization of the performance parameters.  Concerning scheduling Directed Acyclic Graph (DAG) of a data center processors equipped with the technique of DVFS, this paper proposes a power and time  aware algorithm called PATCDD, to apply the combination of the strategies for clustering along with the distribution of slack-time among the tasks of a  cluster. The first phase studies the slack time for non-critical tasks of DAG, extends their execution time and reduces the energy consumption without increasing the task’s execution time as a whole. The main idea of the proposed algorithm involves the achievement of a maximum reduction in power  consumption in the second phase. To this end, the slack time is distributed among non-critical dependent tasks. Eventually, a set of data established for  conducting the examinations and also different parameters of the constructed random DAG were assessed to identify the efficiency of our proposed  algorithm.

In this paper, we introduce a new subclass of analytic and te-univalent functions in the open unit disc associated with the operator Tλ,p,qζ, which is defined by using the (p,q)-derivative. We obtain the coefficient estimates and Fekete-Szeg\H{o} inequalities for the functions belonging to this class.The various results presented in this paper would generalize and improve those in related works of several earlier authors.

Let S be a semiring with identity and U be a unitary left S-semimodule. The co-intersection graph of an S-semimodule U, denoted by Γ(U), is defined to be the undirected simple graph whose vertices are in one-to-one correspondence with all non-trivial subsemimodules of U, and there is an edge between two distinct vertices N and L if and only if N+L≠U. We study these graphs to relate the combinatorial properties of Γ(U) to the algebraic properties of the S-semimodule U. We study the connectedness of Γ(U). We investigate some properties of Γ(U) for instance, we find the domination number and clique number of Γ(U). Also, we study cycles in Γ(U).

We introduce the concept of TβTβ-contractive mappings in the framework of bounded metric spaces and prove the existence of a fixed point for such mappings without using neither the compactness nor the uniform convexity of the space. Furthermore, a fixed point theorem for TβTβ-weakly contractive maps has been given. We point out that, these results generalize and improve many previous works in the literature.    Ultimately, one of our theoretical results has been implicated to study the existence of the solution to a class of functional equations arising in dynamic programming under new weak conditions.

The current paper aims at structuring the implementation of operational budgeting using performance information to allocate budget resources in the country's municipalities. This is a development-applied, exploratory (causal) and cross-sectional survey. The statistical population of the study in the qualitative stage included university experts specializing in government budgeting and accounting. Experimental municipality elites were also used as experts, and finally, 30 experts were selected. In the quantitative stage of research; 420 employees working in the administrative and financial departments of municipalities were selected. The sample size of 200 people was estimated using the Krejcie -Morgan table. Purposeful and random sampling methods were used in the qualitative and quantitative sections. Experts' opinion determined 8 main indices as the main indices for evaluating operational budgeting in municipalities. These indices are (implementation, organizational performance, efficiency and effectiveness, planning, cost management, organizational change management, reward and accountability management, statistics and information management), each of which consists of several components through coding. The mean expert opinions for the first component, i.e. the method of implementation in the operational budgeting of municipalities, are such that the maximum and the minimum impact from the expert opinions are 9.6 and 5.9, respectively, while most opinions are in the range of 8.1 to 9.2. The opinions are very influential, taking into account the opinions and trapezoidal fuzzy numbers diagrams. Given the significance level of the Friedman test, because the probability value is (0.000) and is less than 0.05, it shows that the variables are significantly different from each other. The results also show that the management component of the reward and accountability system has the maximum rank and the management and statistics management component has the minimum rank. The results of the model evaluation showed that there was a significant difference and effect with respect to the mean and the difference between the means obtained from the comparison of indices and the indices affecting operational budgeting in municipalities. The significance level is less than 0.01 and has been confirmed at the confidence level of 0.99. The magnitude of this effect is (B = 0.72)), (B = 0.77), (B = 0.54), (B = 0.87), (B = 0.46), (B = 0.51), (B = 0.49), (B = 0.47)) for Implementation Method, Organizational Performance, Efficiency and Effectiveness, Planning, Cost Management, Organizational Change Management, Reward and Accountability System Management, Statistics and Information Management, respectively.

In this article, we define a q-derivative operator of univalent functions associated with the q-exponential function. Moreover, we introduce differential subordination and differential superordination for the subordination class defined by this operator. Sandwich-type theorems of several known results also are derived by applying these results.

In this paper, we will use the SIRD model to discuss the development of the Corona pandemic in Iraq; through a system of non-linear differential equations, we will use the (Runge-Kutta) method as a solution to the system of various non-linear equations such as the SIRD model, and the parameters used are based on This paper deals with confirmed cases of injury, recovery and deaths from the accurate data available for the period from (February 24, 2020) to (February 22, 2022), and we also present an estimate of the Basic Reproduction number (R0) for the (SIRD) model.

The present dissertation is based on a contextual approach and in order to provide a model based on the risk and complexity of board interaction as a pillar of corporate governance with information based on grounding theory. In order to validate the field research and in fact, as a kind of initial practice, a pilot sample has been used. In addition to the interviews, in this research, field notes were also used, which were also recorded and coded in the field. These notes produced a total of 46 codes with a total of 96 sources, and the final reviews produced 76 codes and 142 sources. The pilot interview highlighted the need to focus more on listening during the interview and to ensure that the coding was done effectively in the research and that trends and activities were examined. The first stage of the survey was to draw potential study lines and one-page feedback was prepared for the interviewees the second stage of the survey was received from the interviewees in four stages by e-mail. In addition, two of the initial interviewees were re-interviewed based on the findings. The other three interviews at this stage were conducted using a one-page report for the structure of the interview.

The study of atmospheric internal waves which occur inside a fluid rather than on the surface is represented by a mathematical model named the atmospheric internal waves model. Under the shallow-fluid assumption, internal atmospheric waves are modeled by a nonlinear partial differential equation system. The proposed shallow flow model is based on the assumption that waves spread out horizontally before rising vertically. The Aboodh transform homotopy perturbation method (ATHPM) has been applied to obtain an approximate solution for a given model. This model helps to understand global atmospheric modeling, which has applications in climate and weather predictions. The ATHPM solution is compared with the  EADM solution, HAM solution, FRDTM solution, and q-HAShTM solution to examine the accuracy and efficiency of the suggested method.

Appraising and evaluating the financial performance of companies as well as the extent to which they achieve their specified objectives are among the important methods for identifying weaknesses, ameliorating them, as well as making financial decisions. However, specialized performance analysis requires the deployment of accurate and comprehensive performance evaluation criteria. In this study, the financial performance of car companies active on the Tehran Stock Exchange shall be reviewed and evaluated. The automotive industry is one of the oldest industries in the country's economy as well as the capital market. Due to its strategic significance as well as creating countless job opportunities and being among the ``mother industries'', despite multiple problems and obstacles, this industry has always been supported and valued by the government. This support and backing is likely to continue. It is estimated there are approx 60 companies operating in this industry. Hence, for this analysis, upon conferring with relevant experts, 50 financial ratios were utilized (49 ratios were finalized). The ratios were classified into 6 categories: conjunctive, economic, leverage, liquidity, profitability and activity. These ratios were weighted and prioritized by experts. The analysis was conducted utilizing the \textbf{\textit{ligo}} software and via the multivariate decision criteria of best/worst and the Aras technique. Ultimately, the companies were ranked. The assessment was performed on companies whose ratios were available. The findings demonstrated that the Mashhad Ring Manufacturing Company, Saipa Azin and Iran Khodro companies were ranked 1 to 3, respectively. Meanwhile, Irandor Foundry Industry Company was ranked in the last place.

Many health systems face extraordinary problems because of the ongoing COVID-19 outbreak and new variations. Multiple regulatory authorities have made it mandatory to maintain a safe distance, particularly in public settings where large groups of people are likely to come into contact, such as sports arenas, public transportation, workplaces as well as shopping malls. Nevertheless, keeping a safe distance (two meters), adjusting multiple model detection errors or accuracy as well as deployment prerequisites, great number of people, facial expression, view angle, low-resolution images, detection model deployment on computers having restricted processing power, and the shortage of a real-world dataset have all made compliance and adherence to proper distancing social difficult. As a result, this survey examines and contrasts the most important past deep learning (DL)-based social distance research. Here, the survey presents a new fine-grained taxonomy that classifies the present state-of-the-art DL-based object detection for detecting distance in terms of several dimensions, such as detection, input data, evaluation methodologies, as well as testing, based on a thorough review. Each facet is then divided into categories based on a variety of factors. In addition, this survey analyses and evaluates the associated experimental techniques suggested as DL-based object detection. Finally, this survey examines DL's role in social distance, object detection datasets impact, as well as the proposed approaches efficacy by assessing the experimental research. The results show that more work is needed to enhance the existing state-of-the-art. Ultimately, open research difficulties are recognized, as well as prospective DL research areas are suggested for future research.

Many awareness programmes are suggested by health care agencies to reduce the adverse effects of swine flu infection on society. These awareness programmes help to create fear for behavioural changes, which may control the spread of various diseases. Several mathematical models have been studied by many researchers earlier. In this manuscript, we suggest an SEIR mathematical model see the impact of awareness and fear on swine flu infection. The bounded region has been carried out in which, disease-free equilibrium point and endemic equilibrium point exist. The basic reproduction number has been evaluated to determine the local and global stability conditions around equilibrium points. Sensitivity analysis of the basic reproduction number is done to find out the dominant parameters that have a significant impact on infection level. Moreover, suitable graphs are obtained and it is found that awareness is more effective than fear to reduce the risk of swine flu infection.

‎Animal model is a type of mixed-effects model‎, ‎where covariance among data points comes from genetic and environmental effects‎. ‎In this paper, the multivariate normal distribution is assumed for the genetic random effects. A new approximate maximum likelihood method is proposed to obtain the estimates of the genetic variance components and heritability‎. ‎The effectiveness of the proposed method is illustrated through a simulation study.

In the paper, we study the value distribution of the differential polynomial ϕfnf(k)−1, where f(z) is a transcendental meromorphic function, ϕ(z)(≢0) is a small function of f(z) and n(>2),k(≥1) are integers. We prove an inequality which will give an upper bound for the characteristic function T(r,f) in terms of reduced counting function only.

In the electricity industry, load forecasting is one of the most important tasks in planning, distribution, operations management, and providing appropriate solutions for power systems. Power consumption plays an important role in the planning and optimal use of power systems. With the existing technology, it is not yet possible to store this energy in large dimensions, so accurate forecasting of consumption can play an important role in the economic use of electricity. The amount of electrical charge consumption is not constant but is complex and nonlinearly a function of several parameters. Due to the variable amount of electrical charge consumption, power companies must anticipate it in different timelines of the information needed to make decisions. In this article, a new method is presented according to the efficiency of short-term load prediction, which can be from the next few hours to a week or a few weeks. Due to the efficiency of evolutionary methods in setting the parameters of forecasting methods, in this paper, the SALP optimization algorithm is used as an algorithm with high convergence accuracy to improve the neural network of the radial base function. Therefore, in this paper, a comparison between the method of improving the neural network of the radial base function with the SALP optimization algorithm for short-term load prediction by considering meteorological factors with other combined methods of optimization algorithms is shown. The results of comparison between predictions in the proposed model (improved neural network with SALP algorithm) compared to other combined methods of load prediction, show that the proposed neural network method improves the radial base function with SALP (RBF-SSA) better. Other combined methods improve the results.

APT (Advanced Persistent Threat) attack is a dangerous, targeted attack form with clear targets. APT attack campaigns have huge consequences. Therefore, the problem of researching and developing the APT attack detection solution is very urgent and necessary nowadays. On the other hand, no matter how advanced the APT attack, it has clear processes and lifecycles. Taking advantage of this point, security experts recommend that could develop APT attack detection solutions for each of their life cycles and processes. In APT attacks, hackers often use phishing techniques to perform attacks and steal data. If this attack and phishing phase is detected, the entire APT attack campaign will be crash. Therefore, it is necessary to research and deploy technology and solutions that could detect early the APT attack when it is in the stages of attacking and stealing data. This paper proposes an APT attack detection framework based on the Network traffic analysis technique using open-source tools and deep learning models. This research focuses on analyzing Network traffic into different components, then finds ways to extract abnormal behaviors on those components, and finally uses deep learning algorithms to classify Network traffic based on the extracted abnormal behaviors. The abnormal behavior analysis process is presented in detail in section III.A of the paper. The APT attack detection method based on Network traffic is presented in section III.B of this paper. Finally, the experimental process of the proposal is performed in section IV of the paper

Nowadays, artificial neural networks are widely used to solve large-scale and complex problems. The purpose of this study is to use artificial intelligence techniques such as artificial neural networks and simulated annealing algorithm, to optimize the solar energy system in order to maximize its economic benefits. Here, a new nonlinear computational model has been presented to predict the thermal performance of compound parabolic concentrator (CPC). In this regard, three models of artificial neural network (ANN) including radial-basis function (RBFANN), multi-layer perception (MLPANN) as well as adaptive neuro fuzzy inference system (ANFIS) are used to identify the nonlinear relationship between input and output parameters of the system. The optimal nonlinear structure of the model is determined through the simulated annealing (SA) method. Validation of the proposed models is performed on a CPC. The results show that all the three models are efficient. In particular, statistical analyses show that the ANFIS model is more accurate in the process of predicting thermal efficiency. So, the given models can be effectively applied in practical fields.

In this paper, we present a new generalization of Nadler's fixed point theorem for multivalued relation-theoretic graph contractions on relational metric spaces. Our results extend and generalize the result of Shukla and Rodriguez-Lopez (Questiones Mathematiae, (2019) 1-16), Nadler (Pacific J. Math. 30 (1969), 475-488), Alam and Imdad (J. Fixed Point Theory and Appl., 17(4) (2015), 693-702) and many others in the existing literature of fixed point theory. Some illustrative examples are also provided to illustrate the usefulness of our main results. Moreover, we have an application to generalized coupled fixed point problems.

In this work, a paradigm for drugs and addiction is put forth and examined. It is a given that the model took the impact of governmental policies and the addict's control into account. The designer's solution's availability, uniqueness, and bounds should be first addressed. Second, we investigated each equilibrium pointe's existence and localized stability. Additionally, some of the prerequisites for the optimistic equilibrium's global stability are identified. Finally, a computational domain is used to illustrate the theoretical result.

In this paper, a non-linear mathematical model is proposed and analyzed to study the role of vaccination and control measures on the spread of vector-borne diseases. It is assumed that susceptible hosts can be infected either directly or indirectly. In the modelling process, it is considered that only a susceptible person can be vaccinated. The existence of the control problem is proved and later used to investigate effective control efforts for the prevention of direct and indirect transmission of disease. The model is analyzed using Hurwitz and Sylvester’s criterion. The analysis of the model reveals that, if the vaccination reproduction number RvRv is less than one, the disease can be eradicated provided, and the vaccine is highly efficient.

Real option is a systematic approach in which economic modeling can be done using financial theories, economic analysis, operations research, decision theory, and statistics. The aim of this study is to design an optimal model for selecting real  options in knowledge-based companies. This research is conducted with a mixed approach in two parts: qualitative and quantitative. In the qualitative section, by interviewing tools and qualitative content analysis method, the components of real option selection in knowledge-based companies are identified. The statistical population in this section includes university specialists and experts, managers of knowledge-based companies and competent individuals with executive positions in these companies who have executive backgrounds at decision-making levels. The sample size is obtained by purposive sampling equal to 12 people. Based on the results of the qualitative section, 11 main components and 103 sub-components are identified to select real options in knowledge-based companies. After identifying the components of real options’ valuation in knowledge-based companies, the obtained qualitative model is tested by the Black-Scholes method. To this end, the qualitative section variables are converted to computable data for knowledge-based companies and then, the relevant statistical data are collected for 50 knowledge-based companies. Quantitative section variables include operating profit, depreciation, capital expenditures, working capital and, finally, the free cash flow of knowledge-based companies. The results show that the Black-Scholes method has more valuation than the traditional method.

In this paper, we make a start by considering the automorphisms of strong semilattice of π-groups, relating them to the automorphisms of underlying π-groups. We also provide a condition under which an automorphism of strong semilattice of π-groups can be constructed.

The principal goal of this article is to investigate the effect of operating cash flow on decision-making considering the variables of the financial statements in the listed companies on the Iranian stock exchange. From the viewpoint of accounting standards, information content is applied to the particulars that will result in the information presented within the financial report being useful in the decision-making. The amount of data content for accounting for making a useful decision was evaluated in this article using the Ohlson model (1995) [35]. To realize the research objective, financial reports from 167 enterprises were accepted/listed on the Tehran Stock Exchange between 2011 and 2020. In addition, the research hypothesis was tested by applying multiple regression models with mixed data. The results show that the variable “operating cash flow” has a significant influence on the relationship between earnings per share, the book value of the share, and the stock price. This matter is in line with the information content theory. In other words, operating cash flow includes information content and will lead to an improvement in effective decision-making.

Phenomena depending on their past history or their past state have received more importance. The mathematical models of these phenomena can be described by differential equations of a hereditary or a self-referred type. This paper is devoted to study the solvability of a state-dependent or self-referred integral equation via Chandrasekhar kernel. The investigation of this problem is motivated by the results from, Eder [10], Feˇckan [11] and Buica [3] who initiated the study of state dependent differential equations. Here, the existence and the uniqueness of the solution of this state-dependent integral equation via Chandrasekhar kernel have been discussed. The data dependency of the solution on some functions has been studied.

This paper examines suitable borderings and modification techniques for finding some special properties of a class of real heptadiagonal symmetric Toeplitz matrices and anti-heptadiagonal persymmetric Hankel matrices with perturbed corners as the zeros of explicit rational functions. An orthogonal diagonalization, inverse and determinant, and a formula to compute its integer powers for these matrices are shown. Then, these results are expanded for the corresponding Toeplitz-plus-Hankel matrices with perturbed corners.

In this paper, we consider the existence of weak solutions for some p(u)-Laplacian problems with Dirichlet boundary conditions. Here the exponent of nonlinearity p depends on the solution u itself. Existence results for the associated boundary-value local problem are given by using a singular perturbation technique combined with the theory of Sobolev spaces with exponent variables.

This paper proposed a model and method for multi-area economic/emission dispatch in the presence of renewable energy sources (RESs) and electric vehicles (EVs). The economic/Emission load dispatch model includes uncertain modeling of wind and solar renewable energy sources along with an uncertain model of electric vehicles and network demand with the objective of reducing economic and pollution costs of generation units. In this paper, the day-ahead electricity market is modeled on a 24-hour time period. Since it will be very difficult to solve the problem by increasing the time period and the number of generation units as well as considering the uncertainty, a meta-heuristic algorithm with the ability to solve large-scale problems and Investigate the concept of affordability based on the application of a thorough researched fast convergence has been presented. A modified particle swarm optimization (MPSO) algorithm has been proposed to solve the proposed problem due to the rapid convergence of hard optimization problems and achieve the optimal global result. A case study with four areas has been considered for the analysis of the proposed model and method, and two different approaches have been presented to illustrate the multi-area economic/emission dispatch and the results indicated the efficiency of the proposed model and method.

The aim of this paper is to introduce the notion of interval ap-Sequential Henstock integral(shortly, the ap-ISH . Some interesting properties of ap-ISH are investigated.

In this present article, the q-derivative operator and the subordination principle are use to define a class of functions that are analytic and bi-univalent in the open unit disk. Our aim for this class is to obtain the upper bound for the second Hankel determinant for functions in this new subclass of analytic and bi-univalent functions.

In this research, we prove the results of n-tuple fixed point in partially ordered cone metric spaces. We will impose some conditions upon a self-mapping and a sequence of mappings via α-series. This series are wider than the convergent series. Also, at the end of this paper, an example is provided to illustrate the results.

The electromagnetic properties of some even neutron rich Sulfur-isotopes 32−42 S are studied through the electric quadrupole transition (0+1→2+1). In particular, excitation energies Ex, occupancies, electric quadrupole moments Q, transition strengths B(E2), deformation parameters β2 and the coulomb inelastic electron scattering form factors are calculated for the adopted isotopes within the framework of shell model. The shell model calculations are performed with full sd-model space, psd - and sdpf - cross shell, using different interactions. The results are based on sdba and psdmk interactions for sulfur with N≤20, while sdpfk and sdpfu interactions are dependent for sulfur with N>20. The core polarization effects (CP) are included through the Boher-Mottelson (B−M) and standard (ST) effective charges to obtain a reasonable description of the electric quadrupole moments and C2 form factors. The results of psdmk and sdba-interactions fail to reproduce the measured B(E2) strengths and deformation β2 for 32−36 S, except for 36 S nucleus is close to the measured value. The results for 38−42 S with both sdpfk and sdpfu interactions nicely confirm the measured values of B(E2) strengths and deformation β2 within the experimental error. The influence of the nuclear deformation parameter β2 on the location of the diffraction minima of C2 form factors are also indicated.

In this paper, we present a redundancy allocation problem (RAP) with series-parallel sub-systems and repairable components. The repairmen will go on multiple vacations. In repairable systems, a fundamental aspect to be considered is to predict the reliability of the systems under study. Set a reliability model for repairable systems, however, is still a challenging problem when considering the dependency This paper aims to evaluate the number of components and repairmen in each sub-system. Because this RAP belongs to Np. Hard problems, also, a Genetic algorithm to solve the presented model.

In this paper, we prove some hyperstability results of the bi-Cauchy-Jensen functional equation: $2f\left( x+y,\frac{z+w}{2} \right) = f(x,z) + f(x,w) + f(y,z) + f(y,w)$ in Banach spaces by using fixed point method.

In this paper, we consider the inverse spectral problem for the impulsive Sturm-Liouville differential pencils on $\left[ 0,\pi\right] $ with the Robin boundary conditions and the jump conditions at the point $\dfrac{\pi}{2}$. We prove that two potentials functions on the whole interval and the parameters in the boundary and jump conditions can be determined from a set of eigenvalues for two cases: (i) The potentials are given on $\left(0,\dfrac{\pi}{4}\left( \alpha+\beta\right) \right) .$ (ii) The potentials is given on $\left( \dfrac{\pi}{4}\left( \alpha+\beta\right) ,\dfrac{\pi }{2}\left( \alpha+\beta\right) \right) $, where $0<\alpha<\beta<1$ and $\alpha+\beta>1$, respectively.

This paper presents a method for determining the actual rank of the coefficients matrix in the reduced rank multivariate regression model. The method is constructed using the singular value decomposition and the Likelihood Ratio Test(LRT). Some illustrative examples are given to verify this method.

Let $\Gamma=(V, E)$ be a simple graph. A set $C$ of vertices $\Gamma$ is an identifying set of $\Gamma$ if for every two vertices $x$ and $y$ the sets $N_{\Gamma}[x] \cap C$ and $N_{\Gamma}[y] \cap C$ are non-empty and different. Given a graph $\Gamma,$ the smallest size of an identifying set of $\Gamma$ is called the identifying code number of $\Gamma$ and is denoted by $\gamma^{ID}(\Gamma).$ Two vertices $x$ and $y$ are twins when $N_{\Gamma}[x]=N_{\Gamma}[y].$ Graphs with at least two twin vertices are not identifiable graph. In this paper, we study identifying code number of some Cayley graphs.

In this article, we formulate a new mixed-type dual problem for a mathematical program with vanishing constraints. The presented dual problem does not involve the index set, however, the dual models contain the calculations of index sets, which makes it difficult to solve these models from an algorithm point of view. The weak, strong and strict converse duality theorems are discussed in order to establish the relationships between the mathematical program with vanishing constraints and its mixed type dual under generalized convexity. To validate the results, a non-trivial example is discussed. Our dual model unifies the dual models discussed in [Q. Hu, J. Wang, Y. Chen, New dualities for mathematical programs with vanishing constraints, Annals of Operations Research, 287 (2020) 233-255].

Diabetic retinopathy can be defined as an eye disease that occurs specifically in diabetic patients and results in damaging the small blood vessels of the retina because of high and low blood sugar. Delayed detection and treatment often lead to blindness, so one of the most significant issues is early detection of this disease, which is necessary for successful treatment. Many deep learning methods have been suggested for diabetic retinopathy detection and classification. Manual inspection of the fundus images to check diabetic retinopathy is highly tedious and time-consuming work. Thus, an automatic method for early diabetic retinopathy diagnosis utilizing the fundus images is very useful tool that helps experts. In this review paper, several deep learning models that are widely used in literature investigated diabetic retinopathy classification will be presented and discussed. In addition, a comparative analysis for classification performance accuracy of diabetic retinopathy using these deep learning models will be reviewed comprehensively. Thus, an automatic approach for early diabetic retinopathy diagnosis utilizing the fundus images is a very useful tool that helps the experts.

In this paper, we prove some theorems about the Hyers-Ulam-Rassias stability of linear isometries. In particular, this paper will address the stability of the orthogonality equation, $\langle f(x), f(y) \rangle = \langle x, y \rangle$, on the restricted domains.

The present study analyzes the effects of financial cycles and their components on the real sector of Iran’s economy and more precisely on the unemployment rate and income distribution inequality. The theoretical reason behind juxtaposing unemployment and income distribution, is the positive correlation between the two variables under the job-search models, along with their challenging and problematic natures. Employing a multiple-stage methodology, over the 1985-2020 period, this study commences with creating a time-varying index based on the “power cohesion” of dependent and independent variables and then continues by determining their joint-distribution by the Kalman-filter approach. At the second stage, it tries to find the degree of coincidence (or asynchrony) between real sector and financial-credit indices by generating a composite index consisting of cohesive joint-distributed components, yielded in the last phase. In the final phase, it benefits from non-linear models for robustness and validity checking. The results emerging from the second stage illustrate that the values indicating counter-cyclical movement (or improving) among financial cycles, on the one hand, and real sector cycles, unemployment, and Gini-Coefficient, on the other hand, are 0.61, 0.71, and 0.64, respectively. Also, there is an improvement and significant movement between credit cycles and the real sector variables. However, the significance is weak for credit cycles generated from so-called “Directed credits.” The validity of the second stage results is verified by the outcomes of the third phase using some standard and more detailed models which are estimated by non-linear methods. The third stage has considerable policy implications for decision-makers.

The well-known Erdos-Lax and Turan-type inequalities, which relate the uniform norm of a univariate complex coefficient polynomial to its derivative on the unit circle in the plane, are discussed in this paper. We create some new inequalities here when there is a restriction on its zeros. The obtained results strengthen some recently proved Erdos-Lax and Turan-type inequalities for constrained polynomials and also produce various inequalities that are sharper than the previous ones known in a very rich literature on this subject.

Image segmentation is an important part of image processing, and one of the most common approaches is threshold segmentation. A new segmentation technique with each pixel in the image has its own threshold is developed in response to the fact that standard threshold-based segmentation algorithms only establish one or many thresholds, making it difficult to extract the complex information in an image. This work employs image segmentation tools to examine images of thin blood smears data set. The goal is to explore options for a noniterative-based and automated system for detecting parasites in blood smears. This can be achieved by detecting the presence of a parasite in thin blood smears and quantifying the portion of red blood cells in the sample that are infected. First, we try segmenting the individual red blood cells from the background using the color thresholder. Next, we clean up the obtained cell mask and examine cell properties using the image region analyzer function, which allows quickly filling in region holes and filtering out regions based on their properties such as area dimensions or eccentricity. Then quickly gauge and specify the expected diameter range of the cells in pixels and indicate that the circles are dark relative to the background. Finally, we've combined the code for finding circles matching image histograms and the parasite threshold detection logic into a single function to quickly examine the performance of this function on the other images using the image batch processing technique. The proposed detection function labels the detected cells with blue circles the parasites are marked in red and the infected cells are highlighted in green. The proposed algorithm has appropriately compensated for the variability in image quality.

In this paper, we introduce and discuss multi-objective interval-valued E-convex programming using gH-symmetrical differentiability. We prove nonlinear optimality conditions of Fritz John type for this context and construct an example to verify our results. Furthermore, we define LU-sE-pseudo convexity and LU-sE-quasi convexity for interval-valued functions and study some of their properties.

Among the most significant management and policy-making elements is improving the efficiency of businesses and companies active in various parts of the industry, as well as management processes and systems. Various methods and models have been proposed to measure the efficiency of firms, processes and systems in a sector. One of the most important models used is network data envelopment analysis, the most widely utilized in measuring the efficiency and productivity of businesses, processes and systems. This is founded on mathematical programming and moreover is among the most powerful techniques for performance evaluation and optimization. In this study, while mathematically modeling and measuring the performance of the study sample, utilizing dynamic network data envelopment analysis, a suitable model for measuring performance, taking into account the stability of the conditions, was designed to be a framework for leading the system to higher objectives. Via utilization, it provides the basis for improving and reducing the adverse effects of the system. Therefore, the data envelopment analysis model in this research is designed as a framework for measuring, analyzing and promoting activities at the network level with the game theory approach as well as in uncertain conditions. Executives/managers will be able to understand the strengths and weaknesses of the system to strengthen and eliminate existing weaknesses plus undertake requisite planning and actions.