International Journal Of Nonlinear Analysis And Applications
Volume:12 Issue: 2, Summer-Autumn 2021

In this paper, we will discuss the existence of bounded positive solutions for a class of nonlinear  differential systems. The objective will be achieved by applying some results and techniques of  functional analysis such as Schauder's fixed point theorem and potential theory tools.

The purpose of this paper is to propose the spectral collocation method to solve linear and nonlinear stochastic It^o-Volterra integral equations (SVIEs). The proposed approach is different from other numerical techniques as we consider the Legendre Gauss type quadrature for estimating It^o integrals. The main characteristic of the presented method is that it reduces SVIEs into a system of algebraic equations. Thus, we can solve the problem by Newton's method. Furthermore,  the convergence analysis of the approach is established. The method is computationally attractive, and to reveal the accuracy, validity, and efficiency of the proposed method, some numerical examples and convergence analysis are included.

In this paper, we define and investigate Mittag-Leffler-Hyers-Ulam and Mittag-Leffler-Hyers-Ulam-Rassias stability of Prabhakar fractional integral equation.

In this paper, some fixed point results for generalized Geraghty type $α$-admissible contractive mappings and rational type generalized Geraghty contraction mappings are given in partially ordered partial  $b_{v}(s)$-metric spaces. Also, a modified version of a partial  $b_{v}(s)$-metric space is defined and a fixed point theorem is proved in this space. Finally, some examples are given related to the results.

This is a new lifetime Exponential "distribution using the Topp-Leone generated family of distributions proposed by Rezaei et al. The new distribution is called the Topp-Leone Exponential (TLE) distribution". What is done in this paper is an estimation of the "unlabeled two parameters for Topp-Leone Exponential distribution model by using the maximum likelihood estimator method to get the derivation of the point estimators for all unlabeled parameters according to iterative techniques as Newton $-$ Raphson method, then to derive Ordinary least squares estimator method". "Applying all two methods to estimate related probability functions; death density function, cumulative distribution function, survival function and hazard function (rate function)". When examining the numerical results for probability survival function by employing mean squares error measure and mean absolute percentage measure, this may lead to work on the best method in modeling a set of real data.

‎In the present paper‎, ‎we define two subclasses $Sigma(lambda‎, ‎alpha‎, ‎beta)$‎, ‎$Sigma_{mathcal C}(alpha‎, ‎beta)$ of meromorphic univalent functions and subclass $Sigma_{{mathcal B},{mathcal C}}(alpha‎, ‎beta‎, ‎lambda)$ of meromorphic bi-univalent functions‎. ‎Furthermore‎, ‎we obtain estimates on the general coefficients $|b_n|~(n ge1)$ for functions in the subclasses $Sigma(lambda‎, ‎alpha‎, ‎beta)$‎, ‎$Sigma_{mathcal C}(alpha‎, ‎beta)$ and estimates for the early coefficients of functions in subclass $Sigma_{{mathcal B},{mathcal C}}(alpha‎, ‎beta‎, ‎lambda)$ by associated subordination‎. ‎The results obtained in this paper would generalize and improve those in related works of several earlier authors‎.

In this paper, we obtained the estimation corresponding to the expected mean square rate of repeated measurement model depend on maximum likelihood method (MLM), restricted maximum likelihood method (REMLM) and modied restricted maximum likelihood method (MREMLM), and got eight  cases that were classified into three types.

In this paper, firstly we show that some classical properties for Cauchy dual and Moore-Penrose inverse of composition operators, such as complex symmetric and Aluthge transform on $L^{2}(Sigma)$. Secondly we give a characterization for some operator classes of weak $p$-hyponormal via Moore-Penrose inverse of composition operators. Finally, some examples are then presented to illustrate that, the Moore-Penrose inverse of composition operators lie between these classes.

The aim of this paper is to give sufficient conditions for $Psi$-instability of trivial solution of a nonlinear Lyapunov matrix differential equation with integral term as right side.

In this paper, a new iterative method of successive approximations based on Haar wavelets is proposed for solving three-dimensional nonlinear Fredholm integral equations. The convergence of the method is verified. The error estimation and numerical stability of the proposed method are provided in terms of Lipschitz condition. Conducting numerical experiments confirm the theoretical results of the proposed method and endorse the accuracy of the method.

Identifying the interaction between the drug and the target proteins plays a very important role in the drug discovery process. Because prediction experiments of this process are time consuming, costly and tedious, Computational prediction can be a good way to reduce the search space to examine the interaction between drug and target instead of using costly experiments. In this paper, a new solution based on known drug-target interactions based on bilateral local models is introduced. In this method, a hybrid support vector machine based on the decision tree is used to decide and optimize the two-class classification. Using this machine to manage data related to this application has performed well. The proposed method on four criteria datasets including enzymes (Es), ion channels (IC), G protein coupled receptors (GPCRs) and nuclear receptors (NRs), based on AUC, AUPR, ROC and running time has been evaluated. The results show an improvement in the performance of the proposed method.

With the rapid development of technology, this development led to the emergence of microarray technology. It has the effect of studying the levels of gene expression in a way that makes it easier for researchers to observe the expression levels of millions of genes at the same time in a single experiment. Development also helped in the emergence of powerful tools to identify interactions between target genes and regulatory factors. The main aim of this study is to build models to predicate the relationship (Interaction) between Transcription Factors (TFs) proteins and target genes by selecting the subset of important genes (Relevant genes) from original dataset. The proposed methodology comprises into three major stages: the genes selection, merge datasets and the prediction stage. The process of reducing the computational space of gene data has been accomplished by using proposed mutual information method for genes selection based on the data of gene expression. In the prediction, the proposed prediction regression techniques are utilized to predict with binding rate between single TF-target gene. It has been compared the efficiency of two different proposed regression techniques including: Linear Regression and Random Forest Regression. Two available data sets have been utilized to achieve the objectives of this study: Gene’s expression data of Yeast Cell Cycle dataset and Transcription Factors dataset. The evaluation of predictions performance has been performed depending on two performance prediction measures (Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) with (10) Folds-Cross Validation.

In this paper, we investigate the spectrum and fine spectrum of the upper triangular double-band matrix $Delta ^{uv}$ on $cs$ sequence space. We also determine the approximate point spectrum, the defect spectrum and the compression spectrum of this matrix on $cs$.

In this paper we have established fixed point theorems for $dq$-rectangular $b$-cyclic-Banach and $dq$-rectangular $b$-cyclic-Kannan contraction mappings in dislocated quasi rectangular $b$-metric spaces. We have also presented examples to support some of our results.

In this paper, we study monotonicity for the first eigenvalue of a class of $(p,q)$-Laplacian. We find the first variation formula for the first eigenvalue of $(p,q)$-Laplacian on a closed Riemannian manifold  evolving by the Ricci-harmonic flow and construct various monotonic quantities by imposing some conditions on initial manifold.

We consider the following quasilinear elliptic system in a Sobolev space with variable exponent: [-text{div}(a(|Du|)Du)=f,] where $a$ is a $C^1$-function and $fin W^{-1,p'(x)}(Omega;R^m)$. We use the theory of Young measures and weak monotonicity conditions to obtain the existence of solutions.

In this paper we prove the existence and approximation theorems for the initial value problems of first order nonlinear impulsive differential equations under certain mixed partial Lipschitz and partial compactness type conditions. Our results are based on the Dhage monotone iteration principle embodied in a hybrid fixed point theorem of Dhage involving the sum of two monotone order preserving operators in a partially ordered Banach space. The novelty of the present approach lies the fact that we obtain an algorithm for the solution. Our abstract main result is also illustrated by indicating a numerical example.

The main purpose of this paper is consider Newton-Taylor polynomial solutions method in numerical solution of nonlinear system of differential equations. We apply Newton's method to linearize it. We  found Taylor polynomial solution of the linear form. Sufficient conditions for convergence of the numerical method are given and their applicability is illustrated with some examples.In numerical examples we give two benchmark sample problems and compare the proposed method by the famous Runge-Kutta fourth-order method. These sample problems practically show some advantages of the Newton-Taylor polynomial solutions method.

In this paper, we suggested an optimal pricing policy for deteriorating items. To reduce the rate of  deterioration, we apply a preservation technology and calculate the optimal preservation technology  investment. The demand function is dependent on time, stock and selling price. Shortages are allowed in our consideration, and two cases are studied, first complete back-ordering and the second one is partially back-ordering. Our main objective is to find the optimal cycle length, ordering frequency the optimal preservation technology investment and the optimal selling price that maximizes the total profit. This model proves that the total profit is a concave function of the selling price, ordering frequency, preservation technology investment and time cycle. Numerical examples are provided to illustrate the features and advances of the model. A sensitivity analysis is performed in order to assess the stability of the proposed model.

Let $G=(V, E)$ be a finite, simple, and undirected graph without isolated vertex. We define a dominating  $D$ of $V(G)$ as a total pitchfork dominating set, if $1leq|N(t)cap V-D|leq2$ for every $t in D$ such that $G[D]$ has no isolated vertex. In this paper, the effects of adding or removing an edge and removing a vertex from a graph are studied on the order of minimum total pitchfork dominating set $gamma_{pf}^{t} (G)$ and the order of minimum inverse total pitchfork dominating set $gamma_{pf}^{-t} (G)$. Where $gamma_{pf}^{t} (G)$ is proved here to be increasing by adding an edge and decreasing by removing an edge, which are impossible cases in the ordinary total domination number.

In this article, we discuss the piecewise polynomial based Galerkin method to approximate the solutions of second kind Volterra-Hammerstein integral equations. We discuss the convergence of the approximate solutions to the exact solutions and obtain the orders of convergence $mathcal O(h^{r})$ and $mathcal O(h^{2r}),$ respectively, for Galerkin and its iterated Galerkin methods in uniform norm, where $h, ~r$ denotes the norm of the partition and smoothness of the kernel, respectively. We also obtain the superconvergence results for multi-Galerkin and iterated multi-Galerkin methods. We show that iterated multi-Galerkin method has the order of convergence $mathcal O(h^{3r})$ in the uniform norm. Numerical results are provided to demonstrate the theoretical results.

In this paper by applying the measure of noncompactness a common fixed point for the maps $T$ and $S$ is obtained, where $T$ and $S$ are self maps continuous or commuting continuous on a closed convex subset $C$ of a Banach space $E$ and also $S$ is a linear map.

In this paper, we discuss the existence of fixed points for Banach and Kannan contractions defined on $G$-metric spaces, which were introduced by Mustafa and Sims, endowed with a graph. Our results generalize and unify some recent results by Jachymski, Bojor and Mustafa and those contained therein. Moreover, we provide some examples to show that our results are substantial improvement of some known results in literature.

In this article, we are going to study the stability and bifurcation of a two-dimensional discrete time vocal fold model. The existence and local stability of the unique fixed point of the model is investigated. It is shown that a Neimark-Sacker bifurcation occurs and an invariant circle will appear. We give sufficient conditions for this system to be chaotic in the sense of Marotto. Numerically it is shown that our model has positive Lyapunov exponent and is sensitive dependence on initial conditions. Some numerical simulations are presented to illustrate our theoretical results.

In this typescript, we study the existence and uniqueness for a class of nonlinear summation equation with delay. Furthermore, we present Hyers–Ulam stability(HUS), generalized Hyers–Ulam stability(GHUS), Hyers–Ulam–Rassias stability(HURS) and generalized Hyers–Ulam–Rassias stability(GHURS) of the mentioned equation by utilizing discrete Gr¨onwall lemma. We finalized our manuscript through examples to help our primary outcomes.

In this paper, a simple proof is presented for the Convergence of the algorithms for the class of relaxed (u,v)-cocoercive mappings and α-inverse strongly monotone mappings. Based on α-expansive maps, for example, a simple proof of the convergence of the recent iterative algorithms by relaxed (u,v)-cocoercive mappings due to Kumam-Jaiboon is provided. Also a simple proof for the convergence of the iterative algorithms by inverse-strongly monotone mappings due to Iiduka-Takahashi in a special case is provided. These results are an improvement as well as a refinement of previously known results.

In this work, we have considered a new multi-parametric family of modified Newton-like methods(MNL) of order three to approximate a zero of a nonlinear operator in $mathbb{B}$-space (Banach space). Here, we studied the semilocal convergence analysis of this family of methods by using a new type of majorant condition. Note that this majorant condition generalizes the earlier majorant conditions used for studying convergence analysis of third order methods. Moreover, by using second-order directional derivative of the majorizing function we obtained an error estimate. We also established relations between our majorant condition and assumption based on Kantorovich, Smale-type and Nesterov-Nemirovskii-type, that will show our result generalize these earlier convergence results.

In this paper we prove several sharp inequalities that are new versions and  extensions of Jensen and $H-H$ inequalities. Then we apply them on means.

In this manuscript, we initiate an almost $alpha$-$F$-contraction and an almost $alpha$-$F$- weak contraction in the setting of partial metric spaces and establish adequate conditions for the presence of fixed points. The obtained results generalize the classical and recent results of the literature, which are validated by suitable examples. As applications of these established results, we solve a nonlinear fractional differential equation and a boundary value problem.

In this paper, we introduce the concept of sequential bipolar metric spaces which is a generalization of bipolar metric spaces and bipolar b−metric spaces and in view of this concept we prove some fixed point theorems for a class of covariant and contravariant contractive mappings over such spaces. Supporting example have been cited in order to validity of the underlying space. Moreover, our fixed point results are applied to well-posedness of fixed point problems.

The aim of this paper is to prove a nonunique common fixed point theorem of Rhoades type for two self-mappings in complete b-metric spaces. This theorem extends the results of [17] and [49]. Examples are furnished to illustrate the validity of our results. We apply our theorem to establish the existence of common solutions of a system of two nonlinear integral equations and a system of two functional equations arising in dynamic programming.

This paper introduces some properties of separation axioms called $alpha$ -feeble regular and $alpha$ -feeble normal spaces (which are weaker than the usual axioms) by using elements of graph which are the essential parts of our $alpha$ -topological spaces that we study them. Also, it presents some dependent concepts and studies their properties and some relationships between them.

In this research article, we establish several Hermite-Hadamard type inequalities for tgs-convex functions via conformable fractional integrals and new fractional conformable integral operators.

Let $H$ be a real Hilbert space with the inner product $<.,.>$ and the norm $|cdot|$. In this paper, we introduce hybrid algorithms for generating cyclic, non-expansive mapping of H. Also, we discuss about necessary and sufficient conditions on subsets of Hilbert space to be remotal or uniquely remotal. Moreover, we give the basic concepts and theorems of farthest points of Bounded subsets of H. In the end, we will provide examples to illustrate our results.

A lot of data in this world are very important and no matter how simple it can be. Hence the number of data conveyed through the internet still increasing due to the rapid development of computer technology. In order to save the data over the internet, cryptography is a technique for conveying information securely between two parties without interference from outside elements. The Vigenre cipher is a technique of encrypting alphabetic text via using a sequence of different Caesar ciphers depend on the letters of a keyword. It is a simple form of polyalphabetic replacement. In this paper, the traditional way for the Vigenre method is enhanced by using two keys for text encryption. The first key is used to format the table of the alphabet (26 characters) and second keys are used to encrypt the plain text like the original Vigenre cipher. The result shows the proposed method is efficient and stronger against the kasiski and Friedman attack to find the length of the key.

In this study, a predator-prey model (PPMD) was formulated and studied along with infectious onpopulations of prey and predator, since each one is splited into two sub-populations i.e., healthy andinfected. It is presumed that only healthy predator of ability to predate the healthy prey and consumeboth healthy and prey being infected. Mathematically, the model solutions uniqueness, existence,and boundedness are conversed. All probable equilibrium model points are defined. The stabilityanalyses as local and the regions of worldwide stability of each point of equilibriums are inspected.Lastly, few simulations as numerical were offered for validation the geted results theoretically.

In this paper, we study some maps from a $C^*$-algebra into a Banach algebra or a Banach module. Under some conditions, by extending on unitization of Banach algebras, we prove that the maps defined into Banach algebras are homomorphisms and the others defined into Banach modules are derivations. Applications of our results in the context of $C^*$-algebras are also provided.

In this article, we investigate the relation between dominating sets and 1-perfect codes. We also study perfect colorings of some Johnson graphs in two colors using linear programming problem.

The Kalman filter (KF) compare with the ridge regression backpropagation algorithm (RRBp) by conducting a numerical simulation study that relied on generating random data applicable to the KF and the RRBp in different sample sizes to determine the performance and behavior of the two methods. After implementing the simulation, the mean square error (MSE) value was calculated, which is considered a performance measure, to find out which two methods are better in  making an estimation for random data. After obtaining the results, we find that the Kalman filter has better performance, the higher the randomness and noise in generating the data, while the other  algorithm is suitable for small sample sizes and where the noise ratios are lower.

Let $mathcal{A}$ and $mathcal{B}$ are $C^{{huge ast}} $-algebrastextbf{.} Atextbf{ }linear map $phi:mathcal{Arightarrow B}$ is $C^{ast}$-Jordan homomorphism if it is a Jordan homomorphism which preserves the adjoint operation. In this note we show that $C^{ast}$-Jordan
homomorphisms -under mild assumptions- preserving covariance set and covariance coset in $C^{ast}$-algebras.

Let M be a unitary left R-semimodule where R is a commutative semiring with identity. The  small intersection graph G(M) of a semimodule M is an undirected simple graph with all non-  small proper subsemimodules of M as vertices and two distinct vertices N and L are adjacent if  and only if N ∩ L is not small in M. In this paper, we investigate the fundamental properties  of these graphs to relate the combinatorial properties of G(M) to the algebraic properties of the  R-semimodule M. Determine the diameter and the girth of G(M). Moreover, we study cut vertex,  clique number, domination number and independence number of the graph G(M). It is shown that  the independence number of small graph is equal to the number of its maximal subsemimodules.

In this paper, we investigate the problem of finding a common element of the solution set of convex minimization problem, the solution set of variational inequality problem and the  solution set of fixed point problem with an infinite family of quasi-nonexpansive mappings in  real Hilbert spaces. Based on the well-known proximal point algorithm and viscosity approximation method, we propose and analyze a  new iterative algorithm for computing a common element. Under very mild assumptions, we obtain a strong convergence theorem for the sequence generated by the proposed method. Application to convex minimization and variational inequality problems coupled with inclusion problem  is provided to support our main results.,Our proposed method is quite general and includes the iterative methods considered in the earlier and recent literature as special cases.

The Sumudu homotopy perturbation method (SHPM) is applied to solve fractional order nonlinear differential equations in this paper.The current technique incorporates two notable  strategies in particular Sumudu transform (ST) and homotopy perturbation method (HPM). The  proposed method’s hybrid property decreases the number of the quantity of computations and  materials needed. In this method, illustration examples evaluate the accuracy and applicability of the mentioned procedure. The outcomes got by FSHPM are in acceptable concurrence with the specific  arrangement of the problem.

In that paper the fuzzy equality co-neighborhood domination and denoted by $gamma_{en}(G)$ for a new definition of domination was described for the fuzzy graph. This new definition was studied in a strong fuzzy graph and constraints were found for many several graphs. Complementary strong fuzzy graphs of the same graphs were examined and studied in detail.

In this article a mathematical model with twin objectives is presented. The objectives are considered as:Minimization of the maximum tardiness of tasks completion time and the total early tasks penalties. Since tasks timing is a tardy and indefinite factor in cloud computing; therefore problem solving model is used as the combined Meta-heuristic innovative algorithm of multi objective swarm of particles based Parto archive has been used. The suggested algorithm with genetic operators as well as the directed and repeated counterpart structures in the format of multi operators are taken to assess the algorithm application. The results will be sorted based on quality, distraction, integrated, the number of non-defeated solutions and the gap from the ideal one is compared with the evolutionary algorithm results titled genetic algorithm. The final results of solved model indicate that firstly, this algorithm is stronger than NSGA-II algorithm but is weaker in timing, norms and scales. In other words, the suggested algorithm, is more capable to discover solutions, accordingly.

In this paper, we obtain a generalization of Titchmarsh's theorem for the Bessel transform for functions satisfying the $(psi,p)$-Bessel Lipschitz condition in the Lebesgue space $L_{p,gamma}(mathbb{R}^{n}_{+})$ for $1< pleq2$, $gamma>0$.

This paper is dedicated to studying the repeated measurements model (RMM). We investigate the analysis of variance (ANOVA) of the model and identify the confidence intervals of the variance components and identify the analytic form of the likelihood- ratio test for the model.

This paper concerns with the nonlinear instability analysis of double interfaces separated three perfect, incompressible cylindrical magnetic fluids. The cylindrical sheet is acted upon by an axial  uniform magnetic field. The current nonlinear approach depends mainly on solving the linear governing equations of motion and subjected to the appropriate nonlinear boundary conditions. This procedure resulted in two nonlinear characteristic equations governed the behavior of the interfaces deflection. By means of the Taylor expansion, together with the multiple time scales, technique, the stability analysis of linear as well as the nonlinear is achieved. The linear stability analysis reveals a quadratic dispersion equation in the square of growth rate frequency of the surface wave. On the other hand, the nonlinear analysis is accomplished by a coupled nonlinear Schrödinger equation of the evolution amplitudes of the surface waves. The stability criteria resulted in a polynomial of the eleventh degree in the square of the magnetic field strength, together with resonance transition curves. Several special cases are reported upon appropriate data choices. The stability criteria are numerically discussed, at which regions of stability and instability are identified. In the stability profile, the magnetic field intensity is plotted versus the wave number. The influences of the parameters on the stability are addressed. The nonlinear stability approach divides the phase plane into several parts of stability/instability. The nonlinear stability shows an in contrast mechanism of the role of the sheet thickness.

Through the use of subband analysis, the article presents a method for selecting pauses in speech communications. An additive blending of normally distributed noise was used in the sensitivity analysis. In various noise / signal respects, the probability of making a bad decision has been identified. The findings show that the proposed sub-band method is stable when subjected to additive noise effects.

In this paper, we have studied the degree of approximation of certain bivariate functions by double factorable matrix means of a double Fourier series. Four theorems are proved using single rest bounded variation sequences, single head bounded variation sequences, double rest bounded variation sequences, and two non-negative mediate functions. These results expressed in terms of two functions of modulus type and two non-negative mediate functions, imply many particular results as shown at last section of this paper.

The common coupled coincidence points and common coupled fixed points in fuzzy semi-metric spaces are investigated in this paper. In fuzzy semi-metric space, the symmetric condition is not necessarily assumed to be satisfied. In this case, regarding the non-symmetry of metric, there are four kinds of triangle inequalities that can be considered. In order to investigate the common coupled coincidence points and common coupled fixed points, the fuzzy semi-metric space is further assumed to satisfy the so-called canonical condition that is inspired from the intuitive observations. The sufficient conditions for guaranteeing the common coupled coincidence points and common coupled fixed points will be different for the four different kinds of triangle inequalities.

This work is devoted to study of  the stability analysis of generalized fractional nonlinear system including the regularized Prabhakar derivative. We present several criteria for the generalized Mittag-Leffler stability and the asymptotic stability of this system by using the Lyapunov direct method. Further, we provide two test cases to illustrate the effectiveness  of  results. We apply the numerical method to solve the generalized fractional system with the regularized Prabhakar fractional systems and reveal asymptotic stability behavior of the presented systems by employing numerical simulation.

In this work first we establish some fixed point theorems for $bot-$Mizoguchi-Takahashi contractions mappings in the setting of orthogonal metric spaces. Next, we investigate the existence of solution for certain fractional differential equation via some integral boundary value conditions and obtained fixed point results.

In this article, a new generalization of the Topp-Leone distribution with a unit interval, namely Mixed Topp-Leone-Kumaraswamy distribution is defined and studied. The mathematical properties of this mixing distribution are described. Moments, quantile function, R?nyi entropy, incomplete moments and moments of residual are obtained for the new Mixed Topp-Leone - Kumaraswamy distribution. The maximum likelihood (MLE), Crans (CM) , Percentile (PM) and Particle Swarm Optimization(PSO) estimators of the parameters are derived. The percentile Method is more efficient method as compred to the others. Two real data sets are used to illustrate an application and superiority of the proposed distribution.

In the present paper, we introduce new types of convergence of a sequence in left dislocated and right dislocated metric spaces. Also, we generalize Banach contraction principle in these newly defined generalized metric spaces.

‎The Lotka-Volterra model is an important model being employed in biological phenomena to investigate the nonlinear interaction among existing species‎. ‎In this work‎, ‎we first consider an integer order predator-prey model with negative feedback on both prey and predator‎. ‎Then by introducing a fractional model into the existing one‎, ‎we give them a specified memory‎. ‎We also obtain its discretized counterpart‎. ‎Finally‎, ‎along with giving the biological interpretation of the system‎, ‎the stability and dynamical analysis of the proposed model are investigated and the results are illustrated as well‎.

In this paper, an estimation of the parameters of the Kink regression model was made by relying on higher order from the general maximum entropy method with two measures Tsallis and Renyi ($alpha=3,~alpha=4,~alpha=5,~alpha=6$), A practical application has been made to data for a real phenomenon in the Iraqi economy, which is inflation with the Debt/GDP ratio and a statistical analysis of it.  After making a comparison with other estimation methods, as the results showed that the explanatory variable for the kink point is equal to (5), and the results show a decrease in the Debt/GDP ratio after observations Kink.

The aim of this paper is to introduce and study the notion type of fibrewise topological spaces, namely fibrewise fuzzy j-topological spaces, Also, we introduce the concepts of fibrewise j-closed fuzzy topological spaces, fibrewise j-open fuzzy topological spaces, fibrewise locally sliceable fuzzy j-topological spaces and fibrewise locally sectionable fuzzy j-topological spaces. Furthermore, we state and prove several Theorems concerning these concepts, where $j={delta, theta, alpha, p, s, b, beta}$.

Medical images are generated in a huge number in the research centers and hospitals every day. Working with the medical images and maintain the storage needs an efficient fund and huge storage space. Retaining the quality of the medical image is also very essential. Image compression without losing its quality is the only term to achieve the desired task. Achieving the desired task using the integer Karhunen Loeve transform attains a quality output and also with less storage space. JPEG and JPEG 2000 are also challenging to the integer transform based compression. Resulting the compression quality in terms of peak signal noise ratio, compression ratio is attained. Proposed method of compression is compared with the other efficient algorithms. Thus this proposed method can be used efficiently for the medical image in order to store and retrieve in healthcare industry.

The theory of general topology view for continuous mappings is general version and is applied for topological graph theory. Separation axioms can be regard as tools for distinguishing objects in  information systems. Rough theory is one of map the topology to uncertainty. The aim of this work is to  presented graph, continuity, separation properties and rough set to put a new approaches for  uncertainty. For the introduce of various levels of approximations, we introduce several levels of  continuity and separation axioms on graphs in $G_m$-closure approximation spaces.

The  main  purpose  of  this  paper  is  to  introduce  a  some  concepts  in  fibrewise  totally topological space which are called fibrewise totally mapping, fiberwise totally closed mapping, fibrewise weakly totally closed mapping, fibrewise totally perfect   mapping fibrewise almost totally perfect  mapping.  Also  the  concepts as  totally adherent  point, filter, filter  base, totally converges to a subset, totally directed toward a set, totally rigid, totally-H-set, totally Urysohn space, locally totally-QHC totally topological space are introduced and the main concept in this paper  is  fibrewise  totally  perfect  mapping  in  totally  topological  space.  Several  theorem  and characterizations concerning with these concepts are studied.

The integral equations are computed numerically using a Bezier curve. We have written the  linear  Fredholm integral equation into a matrix formulation by using a Bezier curves as a piecewise polynomials of degree n and we use (n+1) unknown control points on unit interval to determine Bezier curve. two examples have been discussed in details.

In this paper, we are concerned with a class of fractional integral inequalities of Gronwall type. New integral results with some generalizations are proved. Then, some applications on hybrid differential equations with Hadamard derivative are established.

In this paper, we aim to study the Ulam-Hyers stability and Ulam-Hyers-Rassias stability of the fuzzy delay differential equation under some suitable conditions by the fixed point technique and successive approximation method. Moreover, we provide two illustrative examples of application of our results.

In this paper, we investigate a shrinking algorithm for finding a solution of split monotone variational inclusion problem which is also a common fixed point problem of relatively nonexpansive mapping in uniformly convex real Banach spaces which are also uniformly smooth. The iterative algorithm employed in this paper is design in such a way that it does not require prior knowledge of operator norm. We prove a strong convergence result for approximating the solutions of the aforementioned problems and give applications of our main result to split convex minimization problem. The result present in this paper extends and complements many related results in literature.

We give a topology on a ring part of IS-algebra, by define prime ideals of a commutative ring part of IS-algebra and study some of its properties.

We offer a new complex integral transform, the complex SEE transform, in this paper. The properties of this transform are investigated. This complex integral transform is also used to reduce the core problem to a simple algebraic equation. The answer to this primary problem can then be obtained by solving this algebraic equation and using the inverse of this complex integral transform. Finally, the complex integral transform is used to solve higher order ordinary differential equations. Also, we introduce, some  important engineering and physics applications.

‎In this paper‎, ‎the linear support vector regression approach is proposed for solving the regression problem with interval data‎, ‎which is called interval support vector regression(ISVR)‎. ‎The ISVR approach is equivalent to solving a linear constrained quadratic programming problem (QPP) with an interval cost coefficient in which the value of the objective function is in an interval‎. ‎Instead of solving an interval QPP‎, ‎we solve two QPPs and prove that the cost values of these two problems are the lower bound and the upper bound of the target value of the interval QPP‎. ‎We show these two mentioned QPPs are equivalent to two support vector regression problems which the first problem applies the lower bound of data and the second problem considers the upper bound of the data‎. ‎to obtain the regression function‎. ‎Some experiments are made to demonstrate the performance of our method compared with the known algorithms on several artificial‎, ‎benchmark and real practical datasets‎.‎‎‎

With the growing number of cyber security threats affecting the business environment of many organizations, especially the IT environment. With the growing number of cyber security threats affecting the business environment of many organizations, especially the IT environment. Managed protection systems, including SOC, are highly sought after. Managed protection systems, including SOC, are highly sought after. The problem with SOC is that when building up their own SOC or hiring a third-party to provide SOC, organizations are not able to apply adequate criteria or standard frameworks. The aim of the study is to lay the foundations for developing a modern system of systematic operation centers for the next generation (NGSOC) for IIoT climate. This paper contains thorough, qualitative literature survey on the implementation of a Security Operation Centre (SOC). A comparative study is carried out using a variety of previous research sources and a literature review. The findings from the report show that previous research is not adequately guided, especially in the safety and technical aspects of the building block of the SOC. It is hoped that by proposing the framework, cybersecurity threat prevention and identification would be strengthened even further. The success of the NGSOC will ultimately be determined by the integration of individuals, procedure, and technology.

Many results introduced for the absolutely convergence of Fourier series in terms of absolutely continuous functions. Here we study the convergence of Fourier series in terms of $p$-integrable functions series.

In this paper, an inverse triple effect domination is introduced for any finite graph $G=(V, E)$ simple and undirected without isolated vertices. A subset $D^{-1}$ of $V-D$ is an inverse triple effect dominating set if every $v in D^{-1}$ dominates exactly three vertices of $V-D^{-1}$. The inverse triple effect domination number $gamma_{t e}^{-1}(G)$ is the minimum cardinality over all inverse triple effect dominating sets in $G$. Some results and properties on $gamma_{t e}^{-1}(G)$ are given and proved. Under any conditions the graph satisfies $gamma_{t e}(G)+gamma_{t e}^{-1}(G)=n$ is studied. Lower and upper bounds for the size of a graph that has $gamma_{t e}^{-1}(G)$ are putted in two cases when $D^{-1}=V-D$ and when $D^{-1} neq V-D .$ Which properties of a vertex to be belongs to $D^{-1}$ or out of it are discussed. Then, $gamma_{t e}^{-1}(G)$ is evaluated and proved for several graphs.

In late 2019,  a virus appeared suddenly he claims Covid-19, which started in China and began to spread very widely around the world. And because of its effects, which are not limited to human life only, but rather in economic and social aspects, and because of the increase in daily injuries and significantly with the limited hospitals that cannot accommodate these large numbers, it is necessary to find an automatic and rapid detection method that limits the spread of the disease and its detection at an early stage in order to be treated more quickly. In this paper, deep learning was relied upon to create a CNN model to detect COVID-19 infected lungs using chest X-ray images. The base consists of a set of images taken of lungs infected with Covid-19 disease and normal lungs, as the CNN structure gave accuracy, Precision, Recall and F-Measure 100%

The early school dropout is very significant portents that controls the future of societies and determine the nature of its elements. Therefore, studying this phenomenon and find explanations of it is a necessary matter, by finding or developing appropriate models to predict it in the future. The variables that affect the early school dropout Iraq takes a large size and multiple sources and types due the political and economic situation , which attributes it as a sort of Big Data that must be explored by using new statistical approaches. The research aims at using one Covariate at a Time Multiple Testing OCMT Method to analyze the data from surveys collected by the Central Statistical Organization IRAQ, which contains many indicators related to school dropout and meaningfully affect the life of the Iraqi persons. The Ridge Regression Method as well as the OCMT method were chosen to analyze data and the Mean Square Errors MSE was used to compare the two methods and From the results we find that OCMT estimator is better than Ridge estimator with Big Data conditions.

In this paper we define and study new concepts of fibrwise totally topological spaces over B namelyfibrewise totally compact and fibrwise locally totally compact spaces, which are generalization of wellknown concepts totally compact and locally totally compact topological spaces. Moreover, we studyrelationships between fibrewise totally compact (resp, fibrwise locally totally compact) spaces andsome fibrewise totally separation axioms.

The dye extracted from the plant is already well used in optoelectronic applications for its easy and safe handling. This study is to demonstrate the effect of magnetized distilled water on dye extracted from Anchusa-Italica flowers. The results of its optoelectronic behavior reveal that the use of magnetized water in the extraction process results in different and better properties than processes in which ordinary water was used. The structural analysis of Anchusa-Italica dye thin-film was performed using the Fourier-transform infrared technique (FT-IR). The optical responses, such as the absorption coefficient, absorption spectra, both standard and refractive indices, and electronic properties (optical energy gap) were studied using Ultraviolet-Visible transmittance spectra range 300–900 nm. The calculated energy band gap of the dye extracted using magnetized water was decreased from 3.23 to 2.35 eV and turned into the preferred direct band gap to make a useful contribution to optical sources. The optical absorption spectra of the dye extracted using magnetized water appear to have a better efficiency compared to that extracted with ordinary water. A significant evolution in the absorption coefficient was obtained by employing magnetized water to extract the dye. The magnetized extraction process also modified the electronic transmission values (indirect to direct). The effect of magnetized water on the resonance mode and transparent indication was deduced by studying the complex refractive index. An increase appeared in the spectrum of the absorption index at a wavelength of 570 nm, whereas a small attenuation coefficient was observed as well. The important effects of magnetized dye extraction will highly benefit the field of optoelectronic applications.

The matrix-variate generalized hyperbolic distribution belongs to the family of heavy-tailed mixedprobability distributions and is considered to be one of the continuous skewed probability distributions. This distribution has wide applications in the field of economics, especially in stock modeling.This paper includes estimation the parameters of the multivariate semi-parametric regressionmodel represented by the multivariate partial linear regression model when the random error follows the matrix-variate generalized hyperbolic distribution, using the Bayesian method when non￾informative prior information is available and under the assumption that the shape parameters andthe skewness matrix are known. In addition, the bandwidth parameter is estimated by a suggestedway based on the normal distribution rule and the proposed kernel function based on the mixedGaussian kernel function and studying the findings on the generated data in a way suggested forthe model, comparing the estimators depending on the criterion of the mean sum of squares error.The two researchers concluded that the proposed kernel function is better than the Gaussian kernelfunction in estimate the parameters.

In this paper, we estimate the four parameters of Weibull Lindley burr distribution by using ordinaryleast square method and multiple regression least square method. The survival estimate made byusing ordinary least square estimator (OLSE) and multiple regression estimator (MRE).

Due to the competitiveness of the banking industry and the importance of profitability, access to customer information is essential for establishing effective relationships that serve the interests of both parties. Establishing long-term customer relationships and building brand equity are pivotal in modern banking, and thus improving relationship quality plays a key role in development of new services and customer lifetime value (CLV) measurement. The purpose of the present research is to provide a new model for CLV measurement in the banking industry with an emphasis on brand equity. This study is descriptive and a question naire is used to collect data. The population consists of all the customers of Refah Bank of Iran (with an average annual resources of at least 500m rials), of whom 382 are randomly selected as the sample. Data are analyzed using de-scriptive statistics in SPSS and partial least squares structural equation modeling (PLS-SEM) in SmartPLS. The results indicate the strong fit of the overall model (GOF = 0.782) and show the significant positive effect of brand equity on CLV.

Kicking movement is process of moving position on leg. Biomechanical analysis explains kick performance which influenced by kinematics and kinetics factors. The research purpose analyzed biomechanical long pass movement. This research is both qualitative and quantitative. The researchsample are 11 Indonesian woman football players who were taken by saturated sampling. Data inthe form of long pass kick video with airborne ball test. Data analyzing used Kinovea software todetermine the flexion angle of backswing kick leg, hip angle, and distance to target, then lookingfor the force, power, and energy in kick motion. The motion analysis shown that sample 3 producesclosest distance to target as far as 0.65 m which done with flexion angle of backswing knee is 740and hip angle of 640. The force exerted by sample 3 is 10.09 N, resulting in a ball speed of 22.42m/s and a kinetic energy of 113.12 Joule, potential energy of 14.64 Joule and mechanical energy of127.76 Joule. It can be concluded that accuracy of long pass kick are influenced by flexion angle ofbackswing kick knee, hip angle, power and force as well as producing energy in the form of kinetic,potential, and mechanical energy.

The present research aims at identifying the level of representation of some learning styles in thecontent of mathematics books for 4th preparatory (scientific and literary). In order to achieve thegoal of the research and answer his questions, the researcher has adopted the descriptive researchmethod and the content analysis method for the research sample. By using the content analysis cardwith indicators of virtual validity. It includes categories of analysis or axes of analysis and representsLearning methods and the their indicators according to the Filder - Silverman model of learningstyles, which classified students’ learning styles into several methods ( Sensing Learners vs IntuitiveLearners , visual Learners vs verbal learners , inductive learners versus deductive learners , activelearners vs contemplative learners, sequential learners versus holistic learners).The researcher has conducted the content analysis process for mathematics books for 4th preparatoryclass (scientific and literary) according to specific steps and controls. To determine the level ofrepresentation of some learning styles, using frequencies and percentages. As the results of theanalysis, it is obvious that the frequency totals for learning styles and their indicators are unequal,and the percentages of their representation level in the content of mathematics books for the 4thpreparatory class (scientific and literary) are below the required level and this is realistic evidencethat some students’ learning styles have not been taken into consideration. The consideration whenpreparing mathematics books for the 4th preparatory class (scientific and literary). Therefore, theresearcher recommends the need to pay attention to it and take into account the inclusion of allstudents ’learning methods when preparing mathematics curricula in particular and books in general.</sup>

The primary objective of this paper is to present a new concept of fibrewise topological spaces over Bis said to be fibrewise slightly topological spaces over B. Also, we introduce the concepts of fibrewiseslightly perfect topological spaces, filter base, contact point, slightly convergent, slightly directedtoward a set, slightly adherent point, slightly rigid, fibrewise slightly weakly closed, H.set, fibrewisealmost slightly perfect, slightly∗.continuous fibrewise slightly∗topological spaces respectively, slightlyTe, locally QHC, In addition, we state and prove several propositions related to these concepts.

The goal of this study is to expand the usage of a collection method based on shifted Legendre polynomials in matrix form to approximate the derivative to obtain numerical solutions for the unsteady state one-dimensional bioheat equation. The proposed methodology is used to two examples to illustrate its utility and accuracy. The numerical results shown that the techniques used are effective as well as gives high accuracy and good convergence

Secure message transformation promote the creation of various cryptography systems to enable re￾ceivers to interpret the transformed information. In the present age of information technology, the secure transfer of information is the main study of most agencies. In this study, a particular symmetric cryptography system, Hill Cipher method, is enhanced with the help of encryption and decryption algorithms of the asymmetric RSA cryptography system to avoid certain problems. Previous results show that the original Hill algorithms are still insufficient because of their weakness to known plaintext attack, and a modification of the Hill Cipher cryptography system is therefore presented to increase its invulnerability. The enhancement focuses on implementing the RSA algorithms over the Hill Cipher to increase its security efficiency. The suggested method relies on the security of the RSA and Hill Cipher cryptosystems to find the private decryption keys, and thus is much more secure and powerful than both methods applied separately. Also secure and dynamic generation of the Hill Cipher matrix instead of using static matrix are proposed. This new approach is composed of a public key cryptosystem that has a shared secret key (between participants only), public key (announced to all), and two private keys (for each person). Therefore, this new modification can increase the invulnerability of the Hill Cipher against future attacks during transmission of information between agencies in this age of information technology

This article deals with the dynamical behaviors for a biological model of epidemic diseases with holling type III treatment function. A Crowley-Martin formula to transmission of disease with coverage media programs effect on the population are introduced and investigated. Through some basic analyses, an explicit formula for the basic reproduction number of the model is calculated, and some results such as the stability analysis and instability of all equilibrium points for the model are established. The local bifurcation occurs near all equilibrium points for the model under some special cases that are studied. The numerical simulations are executed to confirm the theoretical results

In this work, we apply the notion of a filter of a KU-Algebra and investigate several properties. Thepaper defined some filters such as strong filter, n-fold filter and P-filter and discussed a few theoremsand examples

In this paper, by using the notion of locally segment-dense subsets and sequentially sign property for bifunctions, we establish existence results for a common solution of a finite family of equilibrium problems in the setting of Hausdorff locally convex topological vector spaces. Also similar results obtain for vector equilibrium problems.

In this paper, we provide certain conditions under which guarantee the existence of a common fixed point for weakly contractive mappings defined on orthogonal modular spaces. Also, Banach fixed point theorem on an orthogonal modular space without completeness is obtained.  To prove much stronger and more applicable results,  some strong assumptions such as the convexity and the Fatou property of a modular are relaxed.

Face recognition is one of the most important tools of identification in biometrics. Face recognition has attracted great attention in the last decades and numerous algorithms have been proposed. Different researches have shown that face recognition with Sparse Representation based Classification (SRC) has great classification performance. In some applications such as face recognition, it is appropriate to limit the search space of sparse solver because of local minima problem. In this paper, we apply this limitation via two methods. In the first, we apply the nonnegative constraint of sparse coefficients. As finding the sparse representation is a problem with very local minima, at first we use a simple classifier such as nearest subspace and then add the obtained information of this classifier to the sparse representation problem with some weights. Based on this view, we propose Weighted Non-negative Sparse Representation WNNSR for the face recognition problem. A quick and effective way to identify faces based on the sparse representation (SR) is smoothed $L_0$-norm $(SL_0)$ approach. In this paper, we solve the WNNSR problem based on the $SL_0$ idea. This approach is called Weighted Non-Negative Smoothed $L_0$ norm $(WNNSL_0)$. The simulation results on the Extended Yale B database demonstrate that the proposed method has high accuracy in face recognition better than the ultramodern sparse solvers approach.

Let  $P$ be the complex polynomial of the form $P(z) = z prod_{j=1}^{n-1}(z-z_{j})$, with $|z_{j}|geq 1$, $1 leq j leq n-1.$ Then according to famous Brown's Conjecture $p'(z) neq 0$, for $|z| < frac{1}{n}.$ This conjecture was proved by Aziz and Zarger [1]. In this paper, we present some interesting generalisations of this conjecture and the results of several  authors related to this conjecture.

In the present article, we prove some result using $C_*$-class function in the notion of C*-algebra valued metric space which is more general than metric space. The obtained results extend and generalize some of the results in the literature.

Robot spray painting process can improve the quality, productivity and provide clean environment in addition to minimize the labour and cost. This process is being used in automobiles, home appliances, etc. There is a need to specify optimal spray painting process parameters to improve the quality of paint coating considering the performance indicators as thickness variation, surface roughness and film adhesion. Compared to the Taguchi orthogonal array and gray rational analysis, a simple modified Taguchi approach is adopted here to identify optimal spray painting process parameters (such as distance, pressure and speed) and obtain minimum thickness variation, minimum surface roughness and maximum film adhesion. Empirical relation for thickness variation, surface roughness and film adhesion are presented. Test data are close-to/within the estimated range.

In this paper, the study detects the nutritional deficiencies from these leaves using Internet of Thing (IoT) based image acquisition and nutrition analyser devices. The former captures the color of the leaf and the latter helps in finding the nutrients in each zone based on the image captured by the device. The study uses an improved convolutional neural network to detect automatically the nutrients present in a leaf. The type of leaf is considered from the plants including coriander, tomato, pepper, chili, etc. The Convolutional Neural Network (CNN) is used to extract the patterns of leaf images from the data capturing IoT devices and nutrition analyser device. The system stores and process the data in cloud, where the CNN integrated in Virtual Machines enables the process of input data and process it and sends the report to the authority. A total of 3000 images are collected out of various disorders in five different plants. A 5 fold cross-validation is conducted on training and testing dataset. The system is tested in terms of accuracy, sensitivity, specificity, f-measure, geometric mean and percentage error. The comparison made with existing models shows an improved detection accuracy by CNN than other deep learning models.

The community's rise, public opinion network's popularity, and emergency personnel's advancement have changed drastically. Individuals can now go online from any place and through communications systems to share their opinions and attitudes more efficiently and more often. As illustrated by the preceeding network approach, public sentiment on neural networks and IoT is critical for the public sector, the public interest, and a special event in an emergency (IoT). In terms of data security and anonymity, the proposed program is not safe and has environmental problems. Network public opinion's approach is based on FPGAs and machine education. FPGAs (Field Programmable Gate Array) Instant perspectives, possible future themes, knowledge exchange, excellent content and Team variance are used to build machine learning. In this popular sentiment network, several disasters have seriously threatened the security of our community. Public views on disaster networks in all type of internet media, such as internet news, blogs and webpages, are inextricably connected with society. This plays into unprecedented stress the ability of the government to deal with crises and their consequences.

This study is concerned with estimating random data and in the presence of noise, as we used the Kalman filter estimation method through the backpropagation algorithm to estimate these data. This is because modern estimation methods have become more important as they were in the past years due to the expansion of the field of science and technology and the increasing data Therefore, the interest became in estimation methods that solve the noise problems that occur in the data. The Kalman filter has become one of the most popular and most reliable estimators in case of data noise. This study tests the use of the Kalman filter and Back Propagation algorithm to estimate the data containing noise and compare the results with the proposed method on the same data. The data is generated randomly in the simulation study. The results showed that Kalman is more efficient in filtering noise from the data and giving a lower mean square error compared to the backpropagation algorithm, but the results of the proposed method outperformed the results of the Kalman filter and the backpropagation with the least possible error.

The analytical solutions for an important generalized Nonlinear evolution equations NLEEs dynamical partial differential equations (DPDEs) that involve independent variables represented by the (2 + 1)-dimensional breaking soliton equation, the (2 + 1)-dimensional Calogero--Bogoyavlenskii--Schiff  (CBS) equation, and the (2 +1)-dimensional Bogoyavlenskii's breaking soliton equation (BE), and some new exact propagating solutions to a generalized (3+1)-dimensional KP equation with variable coefficients are constructed by using a new algorithm of the first integral method (NAFIM) and determined some analytical solutions by appointing special values of the parameters. In addition to that, we showed a new variety and unique travelling wave solutions by graphical illustration with symbolic computations.

Some properties of the geometric stochastic process (GSP) are studied along with those of a related process which we propose to call the Double geometric stochastic process (DGSP), under certain conditions. This process also has the same advantages of tractability as the geometric stochastic process; it exhibits some properties which may make it a useful complement to the multiple Trends geometric stochastic process. Also, it may be fit to observed data as easily as the geometric stochastic process. As a first attempt, the proposed model was applied to model the data and the Coronavirus epidemic in Iraq to reach the best model that represents the data under study. A chicken swarm optimization algorithm is proposed to choose the best model representing the data, in addition to estimating the parameters a, b, (mu), and (sigma^{2}) of the double geometric stochastic process, where (mu) and (sigma^{2}) are the mean and variance of (X_{1}), respectively.

Financial fraud is a serious problem in banking system. Credit card fraud is growing with increasing Internet usage, as it becomes very simple to collect user data and do fraud transaction. Fortunately, all records including fraud and legit transactions are present in the financial record. Improved data mining techniques are now capable to find solutions for such outlier detections. Financial data is freely available in many sources, but this data has some challenges like,1) the profile of legit and fraudulent behavior changes constantly, 2) there is a class imbalance problem in dataset, because less than 3% transaction are fraud, 3) transaction verification latency is also one more problem. All this data issues are handled using pre-processing techniques like cleaning and reduction. Main aim of this research is to find out, output attribute "is Fraud", with better time complexity. To this end, K-means, Random Forest and J48 algorithm is used, and its accuracy rates are compared to find best fit pre-processing and machine learning algorithm. It is observed that accuracy rate of Random Forest is 93.8% when both global and local dataset is used.

An analysis is made to examine the viscous dissipation and thermal effects on magneto hydrodynamic mixed convection stagnation point flow of Maxwell nanofluid passing over a stretching surface. The governing partial differential equations are transformed into a system of ordinary differential equations by utilizing similarity transformations. An effective shooting technique of Newton is utilize to solve the obtained ordinary differential equations. Furthermore, we compared our results with the existing results for especial cases. which are in an excellent agreement. The effects of sundry parameters on the velocity, temperature and concentration distributions are examined and presented in the graphical form. These non-dimensional parameters are the velocity ratio parameter $(A)$, Biot number $(Bi$), Lewis number $(Le)$, magnetic parameter $(M)$, heat generation/absorption coefficients $left(A^*,B^*right)$, visco-elastic parameters $left(betaright)$, Prandtl number $(Pr)$, Brownian motion parameter $(Nb)$,  Eckert number $left(Ecright)$, Radiation parameter $left(Rright)$ and local Grashof number $(Gc; Gr).$An analysis is made to examine the viscous dissipation and thermal effects on magneto hydrodynamic mixed convection stagnation point flow of Maxwell nanofluid passing over a stretching surface. The governing partial differential equations are transformed into a system of ordinary differential equations by utilizing similarity transformations. An effective shooting technique of Newton is utilize to solve the obtained ordinary differential equations. Furthermore, we compared our results with the existing results for especial cases. which are in an excellent agreement. The effects of sundry parameters on the velocity, temperature and concentration distributions are examined and presented in the graphical form. These non-dimensional parameters are the velocity ratio parameter $(A)$, Biot number $(Bi$), Lewis number $(Le)$, magnetic parameter $(M)$, heat generation/absorption coefficients $left(A^*,B^*right)$, visco-elastic parameters $left(betaright)$, Prandtl number $(Pr)$, Brownian motion parameter $(Nb)$,  Eckert number $left(Ecright)$, Radiation parameter $left(Rright)$ and local Grashof number $(Gc; Gr).$

In this paper, we define $phi$-contraction, after that; we obtained the common best proximity point results for different types of contractions in the setting of complete metric spaces by using weak p-property and proved the uniqueness of these points. Also, we presented an example to support our results.

In this paper, we discuss some common fixed point theorems for compatible mappings of type $(E)$ and $R-$weakly commuting mappings of type $(P)$ of a complete $b-$multiplicative metric space along with some examples. As an application, we establish an existence and uniqueness theorem for a solution of a system of multiplicative integral equations. In the last section, we introduce the concept of $R-$multiplicative metric space by giving some examples and at the end of the section, we give an open question.

In this paper, we introduce the concept of weak $mathcal{MT}-K$ rational cyclic and weak $mathcal{MT}-C$  rational cyclic conditions and a combination of both conditions in what we call weak $mathcal{MT}-KC$ rational cyclic condition. We investigate some best proximity points theorems for a pair of mappings that satisfy these conditions that have been established in $b$-metric spaces. Our results include an application to the nonlinear integral equation as well.

‎In this paper‎, ‎we are concerned with the optimization of a dynamic investment portfolio when the securities which follow a multivariate Merton model with dependent jumps are periodically invested and proceed by approximating the Condition-Value-at-Risk (CVaR) by comonotonic bounds and maximize the expected terminal wealth‎. ‎Numerical studies‎, ‎as well as applications of our results to real datasets‎, ‎are also provided‎.

In this paper, we introduce a condition on mappings and show that the class of these mappings is broader than both the class of mappings satisfying condition (C) and the class of fundamentally nonexpansive mappings, and it is incomparable with the class of quasi-nonexpansive mappings and the class of mappings satisfying condition (L). Furthermore, we present some convergence theorems and fixed point theorems for mappings satisfying the condition in the setting of Banach spaces. Finally, an example is given to support the usefulness of our results.

Due to the high sampling rate, the recorded Electrocardiograms (ECG) data are huge. For storing and transmitting ECG data, wide spaces and more bandwidth are therefore needed. The ECG data are also very important to preprocessing and compress so that it is distributed and processed with less bandwidth and less space effectively. This manuscript is aimed at creating an effective ECG compression method. The reported ECG data are processed first in the pre-processing unit (ProUnit) in this method. In this unit, ECG data have been standardized and segmented. The resulting ECG data would then be sent to the Compression Unit (CompUnit). The unit consists of an algorithm for lossy compression (LosyComp), with a lossless algorithm for compression (LossComp). The randomness ECG data is transformed into high randomness data by the failure compression algorithm. The data's high redundancy is then used with the LosyComp algorithm to reach a high compression ratio (CR) with no degradation. The LossComp algorithms recommended in this manuscript are the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). LossComp algorithms such as Arithmetic Encoding (Arithm) and Run Length Encoding (RLE) are also suggested. To evaluate the proposed method, we measure the Compression Time (CompTime), and Reconstruction Time (RecTime) (T), RMSE and CR. Simulation results suggest the highest output in compression ratio and in complexity by adding RLE after the DCT algorithm. The simulation findings indicate that the inclusion of RLE following the DCT algorithm increases performance in terms of CR and complexity. With CR = 55% with RMSE = 0:14 and above 94% with RMSE = 0:2, DCT as a LossComp algorithm was utilized initially, followed by RLE as a LossComp algorithm.

Relation between China and the US is one of the most complex relations among the major powers in the world. The aim of this paper is to model China and the US economic relations. We used the new system named Dynamic system of strategic games for this purpose.

This survey involves the examination of the rate change that is the right to have insurance is one three parametric models (premium rate, experience and age of retirement in financing social security organization by using actuary knowledge and computational software such as ILO-PENS. The statistical population of this survey is the social security organization of the Islamic Republic of Iran. The population and community, are variables because they are huge, there is not statistical sample. And to achieve the hypothesis goal which is based on the total number of the insured persons, pensioners and the source of income of the organization from 2013 – 2019as well as estimating the number of resources available in order to fulfil long term commitment it is actuarial calculations in long term period for commitment payment in long term. In this study the effect of change in rate, insurance right is 1%-5% and the effect is considered over 70 years’ time, on the sustainability resource of the organization and it is measured and examined. In addition, considering the limitation and risk taken from these implements of the parameter are described below and according to the results obtained in case of application, the point of balance was postponed until 1413, and during this time, the necessary resources for paying the commitment is provided. The short gap is an opportunity for the social security organization, to have enough time for long term planning which is a structured reform.

In this paper, the invariant subspace method is generalized and improved and is then used together with the Chebyshev polynomial to approximate the solution of the non-linear, mixed fractional partial differential equations $FPDEs$  with constant, non-constant coefficients. Some examples are given here to illustrate the efficiency of this method.

In this paper, we develop the existence and uniqueness theory of fractional differential equation involving Riemann-Liouville differential operator of order $0 < alpha< 1$, with advanced argument and integral boundary conditions. We investigate the uniqueness of the solution by using Banach fixed point theorem, we apply the comparison result to obtain the existence and uniqueness of solution by monotone iterative technique also by using weakly coupled extremal solution for the nonlinear boundary value problem (BVP). As an application of this technique, existence and uniqueness results are obtained.

In this paper, we establish some common fixed point theorems of a new class of compatible mappings satisfying an implicit relation via inverse $C$-class function.

In this paper, we introduce a new space which is a generalization of function weighted metric space introduced by Jleli and Samet [On a new generalization of metric spaces, J. Fixed Point Theory Appl. 2018, 20:128] where namely function weighted $mathcal{G}$-metric space. Also, a Hausdorff $Delta$-distance is introduced in these spaces. Then several fixed point results for both single-valued and multi-valued mappings in such spaces are proved. We also construct some examples for the validity of the given results and present an application to the existence of a solution of the Volterra-type integral equation.

Machine learning is fast evolving, with numerous theoretical advances and applications in a variety of domains. In reality, most machine learning algorithms are based on optimization issues. This interaction is also explored in the special topic on machine learning and large-scale optimization. Furthermore, machine learning optimization issues have several unique characteristics that are rarely seen in other optimization contexts. Aside from that, the notions of classical optimization vs machine learning will be discussed. Finally, this study will give an outline of these particular aspects of machine learning optimization.

This paper analyzes differences in speed of adjustment (SOA) across three life cycle stages of European listed firms: introduction, growth, maturity, decline, and fall. Dickenson's model based on cash flow has been used to divide different periods. For this purpose, the role of four determinants of profitability and intangible assets, growth opportunities, and size on SOA was investigated using the GMM (generalized torque) method. For this purpose, 153 firms listed firms on the Tehran Stock Exchange in the ten years 2009-2019 were selected, and data were analyzed by Stata and Eviews software. The results do not support by trade-off theory (TOT) and pecking order theory (POT) because according to these theories, the SOA of financial leverage is not completed during different stages of the life cycle. Higher speed in the introduction stage provides a different analysis than the growth stage. In addition, results show a lower increase in costs for firms that change from growth to maturity than for firms that change from introduction to growth.

In this paper, we present the properties and meaning of the new indispensable change, called complex SEE the change. Farther, we use the complex SEE integral change to solve systems of ordinary differential equations (ODEs).

Compatibility of type (E) and weak subsequential continuity is utilized in a fuzzy metric space for the existence of a common fixed point. Illustrations and an application are stated to elucidate our outcomes.

In recent decades air pollution and its associated health risks are in growing numbers. Detecting ‎air pollution in the environment and alarming the people may accomplish various advantages ‎among health monitoring, telemedicine, and industrial sectors. A novel method of detecting air ‎pollution using supervised learning models and an alert system using IoT is proposed. The main ‎aim of the research is manifold: a) Air pollution data is preprocessed using the feature scaling ‎method, b) The feature selection and feature extraction process done followed by performing a ‎Recurrent Neural Network and c) The predicted data is stored in the cloud server, and it provides ‎the end-users with an alert when the threshold pollution index exceeds. The proposed RNN ‎reports enhanced performance when tested against traditional machine learning models such as ‎Convolutional Neural Networks (CNN), Deep Neural Networks(DNN), and Artificial Neural ‎Networks(ANN) for parameters such as accuracy, specificity, and sensitivity.‎

Electronic Health Record (EHR) holds immensely sensitive information and consisting of ‎crucial data related to the patients.  Storing and organizing such data is highly arduous task.  ‎Researches still going on to improve the Quality of Service (QOS) of such data. Existing ‎study focused only on improving the system throughput, privacy and latency issues.  But they ‎did not tend to scrutinize the scalability and privacy of such data records.  In this paper, we ‎propose a novel deep learning framework to improve the Quality of Service using block chain ‎technology.  Initially the data is classified into high priority and low priority based on its ‎nature by using Recurrent Neural Network (RNN).  Then, the classified high priority data is ‎further allowed to each block of a block chain and the low priority data is stored and ‎maintained as log file. Finally, the results are compared based on the evaluation metrics ‎which demonstrates our proposed novel deep learning framework achieves better accuracy.

In bioinformatics systems, the study of genetics is a popular research discipline. These systems depend on the amount of similarity between the biological data. These data are based on DNA sequences or raw sequencing reads. In the preprocessing stage, there are several methods for measuring similarity between sequences. The most popular of these methods is the alignment method and alignment-free method, which are applied to determine the amount of functional matching between sequences of nucleotides DNA, ribosome  RNA, or proteins. Alignment-based methods pose a great challenge in terms of computational complexity, In addition to delaying the time to search for a match, especially if the data is heterogeneous and its size is huge, and thus the classification accuracy decreases in the post-processing stage. Alignment-free methods have overcome the challenges of alignment-based methods for measuring the distance between sequences, The size of the data used is 1000 genomes uploaded from National Center for Biotechnology Information (NCBI), after eliminating the missing and irrelevant values, it becomes 860 genomes, ready to be segmented into words by the k-mer analysis, after which the frequency of each word is counted for each query. The size of a word depends on a value of k. In this paper we used a value of k =3 ….8, for each iteration will count times of frequencies words.

In this paper, an efficient GV1-CG is developed to optimizing the modified conjugate gradient algorithm by using a new conjugate property. This is to increase the speed of the convergence and retain the characteristic mass convergence using the conjugate property. This used property is proposed to public functions as it is not necessary to be a quadratic and convex function. The descent sharp property and comprehensive convergence for the proposed improved algorithm have been proved. Numerical results on some test function indicate that the new CG-method outperforms many of the similar methods in this field.

Language Impairment in Alzheimer's disease can occur because of deficits in semantic levels of language processing. It can be studied using computational models of language such as complex semantic networks which are strongly related to semantic memory. We hypothesize that the concept of resilience in scale-free semantic networks can truly model and predict semantic language deficit in Alzheimer's disease. We suggest that increasing the variety of words in the lexicon of patients with Alzheimer's disease, improves the resilience of their semantic networks through breakdowns. Moreover, enlarging the size of the semantic networks of patients with Alzheimer's disease can make these networks more resilient.

The phased array antenna is one of the most significant applications in fifth-generation mobile networks. It is one of the most important applications in fifth-generation networks. An electric power source that powers the whole application, including the antenna's root, is required. Even with the most outstanding design, if the programme does not have a sound power supply system with minimal packet loss and can't Path find performance, it will be rendered ineffective. When seen from the perspective of the multiplex information, Machine Learning comprises a communication network based on the Internet that transmits information to the control centre via the objects (IOT). To put it another way, the proposed communication infrastructure, via the provision of, and the chance micro-grid state to collect, analyze, and two-way communication link control information, offers the chance to resolve the voltage regulation issues. This cutting-edge communication infrastructure, as well as a suggested state estimation filter focused on improving speed and performance in renewable energy production, are both examples of creative communication infrastructure. Current research is focused on analyzing and enumerating a range of energy abundances in the context of smart grids, which are now in their fifth generation. Rather than concentrating on the future development plan, which should be a problem of illusion, it should concentrate on the composition of the future potential of smart grid communications framework. An in-depth investigation to give evidence to the Machine learning will help intelligent networks in the future conduct a thorough evaluation.

In this article‎, ‎we extended an efficient computational‎ ‎method based on Walsh operational matrix to find an approximate‎ ‎solution of nonlinear fractional order Volterra integro-differential‎ ‎equation‎, ‎First‎, ‎we present the fractional Walsh operational‎ ‎matrix of integration and differentiation‎. ‎Then by applying this‎ ‎method‎, ‎the nonlinear fractional Volterra integro-differential‎ ‎equation is reduced into a system of algebraic equation‎. ‎The‎ ‎benefits of this method are the low-cost of setting up the equations‎ ‎without applying any projection method such as collocation‎, ‎Galerkin‎, ‎etc‎. ‎The results show that the method is very accuracy and ‎efficiency.‎

In this paper, we show the maximum sieved probability of each of the finite Dimensional parameters in a marginal Proportional Hazards risk model with bivariate current position data. We used the copula model to model the combined distribution of bivariate survival times. Simulation studies reveal that the proposed estimations for it have good finite sample properties.

In this article, two numerical methods based on Touchard and Laguerre polynomials were presented to solve Abel integral (AI) equations. Touchard and Laguerre matrices were utilized to transform Abel integral equations into an algebraic system of linear equations. Solve this system of these equations to obtain Touchard and Laguerre parameters. Four examples are given to demonstrate the presented methods. The solutions were compared with the solutions in the literature.

Social media has become a new orientation and attitude for businesses today. Tools and methods for communicating with the customers have changed enormously with the revelation of social media and it has become a channel and an instrument that marketers can extend their marketing campaigns to a wider range of consumers. The research purpose of this article is to analyze the impact of diffusion of innovation model on behavioral intention in adopting social media marketing with the moderator role of subjective norms in Iranian users.  By making use of an online exploration, this study gathers data from 253 experienced social-media users in Iran. We have utilized partial least squares structural equation modeling to examine the links between items of diffusion of innovation model, social media marketing adoption, behavioral intention and subjective norms. The results revealed that diffusion of innovation influence was found as a nominative determinant of users’ behavioral intention to adopting social media marketing while behavioral intentions were also found to have positive significant association towards users’ behavioral intention to adopt social media marketing. In addition, the results of the empirical study showed that subjective norms moderated the relation between diffusion of innovation and customer behavioral intention.

To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was ‎proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the ‎exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the ‎modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact ‎solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which ‎shows the reliability and applicability of the proposed approach. ‎

In this article some applications of independent compatible edges topology τ</span>ICE </span></sub>on directed graphs are introduced. This application includes some aspects. Firstly, medical applications such as voluntary movement of the muscle, work of heart, and pathway involving with neural sensation and motor response. Secondly, vital applications such as world wide web and operational problems recovery in airlines.</span>

The main purpose of this paper is to study and investigate some results of right Γ-n-derivation on prime Γ-near-ring G which force G to be a commutative ring.

Medical Clouds (mCloud) utilized various wearable devices and sensors for better care for patients by encouraging the perspective of the clouds. It gives a more versatile way to centrally and in real-time compare the patients’ profiles in the conventional health-offline system. However, due to the lack of appropriate security measures in low-power computers, there are obstacles to data protection. The limitation made the data vulnerable to hacking and tamper when it transfers from one device to another. In available solutions, the devices send unencrypted data to a central server where it encrypts and forwards, on-demand, to requesting devices. There are two primary challenges in the approach: first, the data link is still vulnerable between the source device and central server; second, the response time of the server gets slower with an increasing number of devices. This manuscript proposes a secure and faster-distributed method, which shares a patient’s data by various devices connected to the mCloud with health caregivers without the need for the centralized server. The research harnesses the power of other locally available mCloud and related devices that have more computational capability. Our experimental results demonstrate that with the number increasing of mCloud devices on the network, the percentage of encrypted data transmissions also increase since there are more chances to find a nearby secure device. Results further shows a decrease in the total response time from 0.6ms to 0.4ms utilizing the proposed distributed vs centralized system.

This research uses a statistical method to assess the efficiency and performance of Islamic and conventional banks.  The Iraqi banks have been chosen as a case study in the period from 2006 to 2011. The data collected from, banks' financial reports, IMF database, the cost function and Seemingly Unrelated Regression were used to analyse the Iraqi bank's elasticity of substitution between inputs. It has been shown that the conventional banks in Iraq have better substitution than Islamic banks.  In conclusion, the Islamic and conventional banks are exposed to a similar degree of risks, but different in nature; and the Islamic banks have less security than conventional banks to financial shocks. Since the Islamic banks cannot charge a fixed, predetermined return, and can't borrow from the financial market, so the Islamic banks could face more risk and volatile returns on their assets. The implication of that an excessive management modernization of Islamic banks is necessary to achieve a higher level of efficiency. This will give privilege for Islamic banks over the conventional bank. For conventional banks, they have to invent similar techniques to reduce cost and keep their position in the market.

In this paper, the invariant subspace method is generalized and improved and is then used to have an exact solution for a wide class of the linear/ non-linear mixed fractional partial differential equations $(FPDEs)$; with constant, non-constant coefficients.  Some examples are given here to illustrate the efficiency of this method.

To achieve real competition in the global market requires the manufacturers to have the ability to meet the needs and demands of their customers, which comes from the optimal planning of the supply chain. In this paper, consideration is given to the supply chain with multi-providers of raw materials, multi-manufacturing locations, multi- centres of selling products to customers in multiple, with instability (fuzzy) of customer demands, holding costs, costs of appointment, retire and training of workforce After building a mathematical model for the supply chain that aims to maximize the net profit and reduce all costs that include production costs, labour, raw materials, storage, transportation, and the cost shortage, the model was improved through a proposal that the decision-maker has a desire to prefer one manufacturing location over another, as the proposal relied on developing a pairwise comparison in the Analytic Hierarchy Process (AHP) when the degree of comparison between factory locations is a fuzzy nature. The results of the proposed model were applied to actual data taken from an industrial organization.

This article aims to introduce the concept of $p-mathrm{clean ring}mathrm{s}$ as a generalization of some concepts such as $mathrm{clean rings}$ and $r-mathrm{clean rings}$. As the first result, we prove that every $mathrm{clean ring}$ is a $p-mathrm{clean ring}$ and every $r-mathrm{clean ring}$ is a $p-mathrm{clean ring}$. Furthermore, we give the relation between von Neumann $mathrm{local ring}$ and $p-mathrm{clean ring}$. Finally,  we investigate many properties of $p-mathrm{clean ring}mathrm{s}$.

This paper introduces a combination of three methods including a modified RSA cryptography, hidden text using steganography, and selection of random pixel from image to improve the general security level of the system. In this regard, the image is a carrier of the information transmitted through the media, and the fluid motion image is used to hide the information after it was encoded using modify RSA technique that before hiding it in a random way, because the image of fluid motion possesses the sinusoidal waves and turbulent motion.  In this paper, a combination of three techniques is utilized in order to prevent the intruders and attackers from detecting the information and sharing it with others. LSB technique is used for hiding the message in image-based steganography. In addition, pseudo number to choose the random number of pixel when hiding the message after encryption. Four measures including Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM), and histogram are used to compare the original image and stego-image. The results demonstrated the outperformance of the proposed method so that neither the attacker nor the intruder could discover the information contained within the image, due to the large value of the PSNR, very small value of the MSE, stability of the SSIM, and matching the histograms.

For any two entire functions $f$, $g$ defined on finite complex plane $mathbb{C}$, the ratios $frac{M_{fcirc g}(r)}{M_{f}(r)}$ and $frac{M_{fcirc g}(r)}{M_{g}(r)}$ as $rrightarrow infty $ are called the growth of composite entire function $fcirc g$ with respect to $f$ and $g$ respectively in terms of their maximum moduli. Several authors have worked about growth properties of functions in different directions. In this paper, we have discussed about the comparative growth properties of $fcirc g$, $f$ and $g,$ and derived some results relating to the generalized order $(alpha ,beta )$ after revised the original definition introduced by Sheremeta, where $alpha ,$ $beta $ are slowly increasing continuous functions defined on $(-infty,+infty )$. Under different conditions, we have found the limiting values of the ratios formed from the left and right factors on the basis of their generalized order $(alpha ,beta )$ and generalized lower order $(alpha,beta ),$ and also established some inequalities in this regard.

The aim of this article is to study the dynamical behavior of an eco-epidemiological model. A prey-predator model comprising infectious disease in prey species and stage structure in predator species is suggested and studied. Presumed that the prey species growing logistically in the absence of predator and the ferocity process happened by Lotka-Volterra functional response. The existence, uniqueness, and boundedness of the solution of the model are investigated. The stability constraints of all equilibrium points are determined. The constraints of persistence of the model are established. The local bifurcation near every equilibrium point is analyzed. The global dynamics of the model are investigated numerically and confronted with the obtained outcomes.

In this article, we propose a hybrid semi-supervised boosting algorithm to sentiment analysis. Semi-supervised learning is a learning task from a limited amount of labeled data and plenty of unlabeled data which is the case in our used dataset. The proposed approach employs the classifier predictions along with the similarity information to assign label to unlabeled examples. We propose a hybrid model based on the agreement among different constructed classification model based on the boosting framework to assign a final label to unlabeled data. The proposed approach employs several different similarity measurements in its loss function to show the role of the similarity function. We further address the main preprocessing steps in the used dataset. Our experimental results on real-world microblog data from a commercial website show that the proposed approach can effectively exploit information from the unlabeled data and significantly improves the classification performance.

Nowadays, several security architectures in cloud computing were employed in several applications, but they failed to secure the cloud data entirely. The current approaches use the ensemble algorithm for the decryption and encryption purpose to enhance the security technique. The input medical dataset is usually raw and might contain redundant packets and missing values. Initially, the data is preprocessed by means of the normalization technique. By using Enhanced Principal Component Analysis (EPCA) method, various attributes of the data can be obtained. After the extraction process, the classification mechanism is carried out for recognizing the attacks. The attack is predicted and is classified by means of the Adaptive AlexNet CNN classifier algorithm. A hybrid cryptographic technique in a cloud environment for improving the security rate and providing privacy preservation of the medical data in the cloud environment is presented. The proposed work mainly concentrates mostly on implementing hybrid cryptographic schemes which include AES algorithm, enhanced honeypot algorithm, SHA3 hashing and OTP in the cloud environment. It enhances the security of the data to a great extent. Thus, the presented technique is secured effectively that makes the intruders difficult to access the system as they need to attain control over servers.

In this paper, we introduce the concept of orthogonal contractive mappings and prove some fixed point theorems for such contractions. We establish our results in orthogonal bounded complete metric spaces via the notion of$tau-$distances. Moreover, an application to a differential equation is given.

We will add new types of modules over a ring $mathfrak{R}$ called $mathit{g}-$ small completely stable module and $mathit{g}-$ small duo module, assuming $mathfrak{R}$ is a ring with identity and $mathcal{M}$ is a unitary left $mathfrak{R}$-module. We also present the $mathit{g}-$ small dual stable module, which is a duality. We show that our new ideas have characterization and a few properties.

We consider the following two-dimensional differential system: [ left{begin{array}{l} dot{x}=ax^{2}+bxy+cy^{2}+Phi(x,y) ,, \ dot{y}=dx^{2}+exy+fy^{2}+Psi(x,y) ,, end{array} right.] in which $lim_{(x,y)rightarrow(0,0)}frac{Phi(x,y)}{x^{2}+y^{2}} = lim_{(x,y)rightarrow(0,0)}frac{Psi(x,y)}{x^{2}+y^{2}}=0$ and $Delta=(af-cd)^{2}-(ae-bd)(bf-ce)neq0 $. By calculating Poincare index and using Bendixson formula we will find all the possibilities under definite conditions for classifying the system by means of kinds of sectors around the origin which is an equilibrium point of degree two.

In this paper, a prey-predator-scavenger model is proposed and analyzed. It is assumed that the model considered the effect of disease on the prey. Firstly, the existence, uniqueness and boundedness of the solution of the model are discussed. Secondly, we studied the existence and local stability of all equilibrium points. Furthermore, some of the Sufficient conditions of the global stability of the positive equilibrium are established using suitable Lyapunov functions. Finally, those theoretical results are demonstrated with numerical simulations.

Assume that $X$ is a subset of the finite group $G$. The A4-graph is known as a simple graph denoted by $ mathcal{A}_4 (G, X) $ having $X$ as a vertex set and two vertices $ x, y in X,$ is linked by an edges if $ xneq y $ and $ {xy}^{-1} = {yx}^{-1} $. In this paper, we consider $ mathcal{A}_4 (G, X) $ when $G$ is either Tits group T or Mathieu group $M_{20}$ and $X$ is $G$-conjugacy class of elements of order three. Valuable results reached, for example, disc structure, girth, clique number, and diameters of the A4-graph.

In this study, a mathematical model consisting of four species: first prey and second prey with stage structure and predator in the presence of toxicity and anti-predator has been proposed and studied using the functional response Holling's type IV and Lotka Volttra. The solution's existence, uniqueness, and boundedness have all been studied. All possible equilibrium points have been identified. The stability of this model has been studied. Finally, numerical simulations have been used to verify our analytical results.

In this article, an ecology toxicant food chain system with Lotka-Volterra functional response for predator population includes prey protection zone has been suggested and studied. Toxins are excreted by all organisms as a form of defence. The prey follows the logistic growth law. The equilibrium points have been established. The analytic approach has been used to investigate the local stability for each acceptable equilibrium point. The global dynamics of this model was studied using the Lyapunov function. Lastly, numerical simulations and graphical illustrations were used to back up our analytic results.

This article aims to introduce some concepts such as $P$-contraction and  $G-P$-contraction which are defined on Banach spaces as stronger forms of the concepts of  $P$-contraction and '{C}iric type generalized $P$-contraction defined on complete metric spaces, respectively. Furthermore, the relationship between these concepts have been discussed. Finally, the uniqueness of fixed point for the presented concepts has been investigated.

Cross-docking refers to the practices of unloading materials from inbound vehicles and then loading them directly into outbound ones. Removing or minimizing warehousing costs, space requirements, as well as inventory utilization, cross-docking simplifies supply chains and makes them deliver goods to markets in a faster and more efficient manner. Accordingly, a mixed-integer linear programming ($MILP $) model is developed in the present study to schedule transportation routing and cross-docking in a reverse logistics network ($RLN$). Furthermore, different traffic modes are also considered to reduce fuel consumption, which reduces emissions and pollution. The proposed model is a multi-product, multi-stage, and non-deterministic polynomial-time that is an NP-hard problem. We use the non-dominated sorting genetic algorithm II ($NSGA-II$) to solve the model. A numerical example has been solved to illustrate the efficiency of the method.

In this article, we have designed a novel 4:2 QCA Compressor with a nonlinear effect. This can be considered as a new vision to design approximate Majority circuits with more than five-input. The main advantages of these ideas are the reduced number of QCA cells as well as power dissipation, increased speed, and improved cell area In addition, a novel hierarchy is introduced to optimize digital systems. The 4:2 Compressor circuit is selected as a benchmark. This circuit is simulated with some technologies such as CMOS, CNT, and QCA in different architectures. All results from power respective were compared. We have used QCADesigner and QCAPro for QCA Circuits, Hspice with 20nm-nfet PTM-MG model for CMOS circuits and Stanford CNFET 20nm model for CNT circuits as simulation tools to evaluate circuits.

In this paper, we develop the notion of $(psi, F)$-contraction mappings introduced in cite{wad1} in $b$-metric spaces. To achieve this, we introduce the notion of generalized multi-valued $(psi, S, F)$-contraction type I mapping with respect to generalized dynamic process $D(S, T, x_0),$ generalized multi-valued $(psi, S, F)$-contraction type II mapping with respect to generalized dynamic process $D(S, T, x_0),$ and establish common fixed point results for these classes of mappings in complete $b$-metric spaces. As an application, we obtain the existence of solutions of dynamic programming and integral equations. The results presented in this paper extends and complements some related results in the literature.

The relationship between economic growth and inflation a concern for many countries in the developed and developing world, and erected in developed countries, a lot of research to laparoscopy relationship in order to overcome the problems that may be exposed to the States as a result of this association. The current research is an attempt to explore the trends in this relationship in Iraq in order to determine the ranges that can affect or be affected by growth as a result of inflation, period $(1990-2020)$ was adopted to range time frame in which you can determine the nature of the relationship between the two variables as well have been taking data at their nominal value as terms of GDP growth for the accurate diagnosis of the impact of inflation has been relying on time-series analysis to prove the direction of the relationship, and the paper confirmed the conclusion that there are two methods of fundamental bond that link inflation and economic growth in Iraq.

This paper aims to investigate the geometry of the projective curvature tensor and to obtain some
identities for this tensor. Several three classes of nearly infinite </span>C</span>(</span>λ</span>) are distinguished and studied.</span>

‎The purpose of this article is to introduce the notion of an $mathfrak{A}$-meter‎, ‎as an operator-valued distance mapping on a set $X$ and investigating the theory of $mathfrak{A}$-metric spaces‎, ‎where $mathfrak{A}$ is a noncommutative $C^*$-algebra‎. ‎We demonstrate that each metric space may be seen as an $mathfrak{A}$-metric space and that every $mathfrak{A}$-metric space $(X,delta)$ can be regarded as a topological space $(X,tau_{delta})$‎.

In this paper, the time series data for the number of deaths from Coronavirus (COVID-19) patients in Iraq were analyzed for the period from 4/3/2020 to 18/2/2021. ARCH, GARCH, and TGARCH models were applied due to the changing volatility of the series leading to a heteroscedastic variance. The appropriate models for the series were diagnosed and the best model was chosen and used for forecasting by the exponential smoothing methods. The comparison criterion used was the Root Mean Squared Error and the Sum of Squared Residuals. The most appropriate model for modeling and forecasting the Coronavirus deaths series in Iraq was diagnosed as TGARCH (1,1). Finally, the method of Holt-winter-additive forecasting was the best method among the

This paper aims to define and study a new class of sets called NGRMCS in NTS. The basic properties of NGRMCS are also studied. Finally, we investigate the relationship among NGRMCS, NMCS, NCS, NGRCS, NRCS MCS and NMCS.</span>

This paper deals with comparing three different estimators of fuzzy reliability estimator of one scale parameter Rayleigh distribution were first of all the one scale parameter Rayleigh is defined. Afterwards, the cumulative distribution function is derived, as well as the reliability function is also found. The parameters θ is estimated by three different methods, which are maximum likelihood, and moments, as well as the third method of estimation which is called percentile method or Least Square method, where the estimator $(hat{vartheta}_{pec})$ obtained from Minimizing the total sum of the square between given C DF, and one non-parametric estimator like $hat{F}(ti,theta)=frac{i}{n+1}$ after the estimator of $(theta)$, which $(hat{theta})$ is obtained. We work on comparing different fuzzy reliability estimators and all the results are explained besides different sets of taking four sample sizes $(n= 20, 40, 60, and 80)$.

In this research, Jaya optimization algorithm has been introduced to develop and enhance the performance of the Automatic Voltage Regular system that known as (AVR) system with proposed techniques equilibrium optimizer and rider optimization algorithm which is contributed as additional algorithms to assist PID controller to find the optimum values for the controller in order to improve the performance of the AVR control system to achieve high stability and best for both rising times and settling time and these the best coefficients that made the proposed system work in the greatest performance in addition to that the step response on AVR control system also has been presented in this research and all these techniques implemented on MATLAB Simulink with optimized techniques.

In this paper, we debate queueing systems with N-policy and single vacation. We consider these systems when the vacation times have Erlang distribution. Moreover, we adapted the input by studying two different kinds: first, an ordinary Poisson input, and second, type 2 geometric batch input. We derive the probability generating function of the number of units in the system in two cases by using fluctuation analysis.

In this paper, we give a family of rational maps whose Julia sets are quasicircles also we the boundaries of $I_0 , I_infty$ are quasicircles , we have the family of complex rational maps are given by begin{equation}label{e1} mathcal{Q}_alpha(Z)=2alpha^{1-n} Z^n -frac{z^n left(z^{2n}-alpha^{n+1}right)}{z^{2n}-alpha^{3n-1}}, end{equation} where $ngeq 2$ and $alpha in Cbackslash {0},$ but $alpha^{2n-2}neq 1,;;alpha^{1-n}neq 1.$

The purpose of this study is to determine if it is possible to use the class of $delta_g-$close sets and $delta-$closed sets to find a new class of close sets, namely $iidelta_g-$close sets and $iidelta-$close sets. We use these new classes to arrive at the separation axiom, which is the separation axiom of $ii-T_{3/4}.$  We also use the properties of $delta hat{g}-$closed sets to find new class of close sets, namely $iidelta hat{g}-$closed set. We use it to create a new type of separation axiom. The study found new closed sets, namely: $iidelta hat{g}-$closed sets is introduced for topological space. We will also prove that category falls between the class of $iidelta-$closed set and the class of $iigs-$closed set. As well study the relationship between it and other closed sets, such as the closed set of type $iigs-$ as well as the closed set of type $iig$, and then, through these closed sets, we will study new types of the axiom of separation, which are $ ii- T_{3/4}$ space and $ ii- hat{T}_{3/4}$ space, and also clarify the relationship between the axiom of separation, and some of the closed and open sets previously studied. The study also included the relationship between the axiom of separation, of type $ii-T_{1/2}$ space and $ii- T_{3/4}$ space as well as the axiom of separation of type  $ii- T_{3/4}$ space and $ ii hat{T}_{3/4}$ space. The study included some important proofs. The study also included a chart, showing the relationship between closed sets of types that were studied and can be used.

In this article, we extended an efficient computational method based on Walsh operational matrix to find an approximate solution of fractional diffusion equations, First, we present the fractional Walsh operational matrix of integration and differentiation. Then by applying this method, the Fractional diffusion equations are reduced into a system of an algebraic equation. The benefits of this method are the low cost of setting up the equations without applying any projection method such as collocation, Galerkin, etc. The results show that the method is very accurate and efficient.

This research aimed to provide a model for backgrounds and implications of customer experience management in dental centers considering the variable role of word of mouth using a phenomenological approach. In this mixed-method study, the researcher used a phenomenological approach to identify the components of the customer experience in dental centers and then tested the model by a quantitative method. The data collection instrument was in-depth interview and protocol with 23 dental clinic managers and clients with which the researcher reached theoretical saturation. In the next stage, the required data were distributed among 320 patients of the dental clinic in District 2 and 4 of Tehran Municipality, and the results were analyzed by PLS software. Finally, the researcher extracted 152 open source codes, coded and selected them based on the theoretical literature, and presented the results in six main dimensions and 28 sub-dimensions. The researcher has presented the research results in the form of a model with six main dimensions, including customer experience, satisfaction of the medical staff, word of mouth of various dental services, strengthening the clinic brand, satisfaction with the clinical environment, and 28 sub-dimensions. Customer experience has had a positive and significant effect on word of mouth.

In this paper, two types of diseases in the predator population in an ecological model are proposed and analyzed. The first (SIS infectious disease) transmitted horizontally, spread by contact between susceptible individuals and infected individuals. And the second (SI disease) is transmitted vertically from mothers to offspring with the effect of an external source (environmental effect). No transmis￾sion of the diseases can happen from predator to prey by predation or contact. Linear functional response and Holing type-II for describing the predation of the susceptible and the infected preda￾tors respectively also linear incidence for describing the transition of diseases are used. All possible equilibrium points were analyzed for this model. Locally and globally dynamics of the model have been discussed, numerical simulation is used to investigate the effect of the diseases on the system’s dynamics.

Maskan Bank is one of the state-owned banks with a wide range of banking services, including financing for housing and construction, financing plans of the government development programs in housing development, inclusive public banking services to conduct its inherent mission, and banking businesses requiring financing from standard methods and banking marketing. This research aimed to provide Maskan bank marketing model using an integrated supply chain approach considering the financial and credit turnover in the construction and housing industry. The Grounded theory strategies, including reading documents, in-depth interviews with experts and extracting concepts, and open, axial, and selective coding, were used in the qualitative section using the mixed method. Then, a paradigm model was presented with 6 dimensions and 42 components. The descriptive survey method was used in the quantitative part, and PLS software was used to test the proposed model. The results were confirmed and fitted in a model for Maskan bank marketing using an integrated supply chain approach in the construction and housing industry.

In this article, we consider queueing model with bilevel hysteretic control and multiple vacations. This system's mechanism depends on the queue size and the facility where the server goes to the series of vacation trips when the line is empty and returns but waiting in the system when the number of units is more than level (M). In this case, the server doesn't start a new busy period unless this size is more than another level (N > M). Furthermore, we employ N-policy and first excess level analysis to derive the probability generating function of queue size. Additionally, we assume that the vacation times are exponentially distributed random variables, and arrival batches are type 1 geometrically distributed random variables.

Several scientific and engineering applications are usually described as integral equations. We propose a numerical approach for solving the type of Fredholm nonlinear boundary value problems in a finite domain. The paper aims to use the q-homotopy analysis method to estimate the solution to test the efficiency of the proposed method. Comparison with updated work is exacted. The obtained results show that the proposed method is very effective and convenient for nonlinear Fredholm integral equations. The interval of convergence of homotopy analysis method, if exists, is increased when using q-homotopy analysis method is more to converge. The result reveals that the q- homotopy analysis method is considered a good method for solving NFIES.

In this article, we introduce the notion of $(h,k)$-convex functions and their operator form. Moreover, we derive Hermite–Hadamard-type, and Fejer-type inequalities for this class.

Interpretability of word vector components is very important for obtaining conceptual relations. Word vectors derived from counting models are interpretable but suffer from the high-dimensionality problem. Our goal in this study is to obtain interpretable low-dimensional word vectors in such a way that the least accuracy loss occurs. To achieve this goal, we propose an approach to reduce the dimensions of word vectors using a labeling method based on the BPSO algorithm and a voting method for selecting final context words. In this approach, we define several different base models to solve the labeling problem using different data and different objective functions. Then, we train each base model and select 3 of the best solutions for each model. We create the target word vectors of the dictionary based on the context words labeled "1". Next, we use the three best solutions of each base model to build the ensemble. After creating the ensemble, we use the voting method to assign the final label to the primary context words and select N final context words. In this study, we use the corpus ukWaC to construct word vectors. We evaluate the resulting word vectors on the MEN, RG-65, and SimLex-999 test sets. The evaluation results show that by reducing the word vectors dimensions from 5000 to 1507, the Spearman correlation coefficient of the proposed approach has been reduced to a lesser extent compared to each base model. Therefore, the accuracy drop of the proposed approach is justified after reducing the dimensions from 5000 to 1507. It is not a large penalty because the resulting word vectors are low-dimensional and interpretable.

The Internet has become one of the most important daily social, financial and other activities. The number of customers who use the Internet to conduct their business and purchases is very large. This results in billions of dollars being transferred every day online. Such a large amount of money attracts the attention of cybercriminals to carry out their illegal activities. “Fraud” is one of the most dangerous of these methods, especially phishing, where attackers try to steal user credentials using fraudulent emails, fake websites, or both. The proposed system in this paper includes efficient data extraction from the web file through data collection and preprocessing. and web usage mining procedure to extract features that demonstrate user behavior. And feature-extracting URL analysis to detect website phishing addresses. After that, the features from the above two parts are combined to make the number of features sixty-three. Finally, a classification algorithm (Random Forests) is applied to determine if website addresses are phishing or legitimate. Suggested algorithms performance is determined by using a confusion matrix that shows the robustness of the proposed system.

In this paper, an analysis is conducted on the data transmitted through the edge computing technique. The research creates a trust model that establishes direct, indirect, and mutual trust between the source and destination blocks when data is sent. That is, the study integrated blockchain as a model to transmit the data in a secured way through the blockchains, however, the intrusion in blockchains can be avoided based on trust based model. The simulation is conducted on various testbeds and with existing blockchain mechanisms. The findings reveal that the suggested trust-based paradigm is successful at safeguarding data sent over the edge.

The growing use of Internet technology and the attack on computer networks have made intrusion detection systems an essential part of computer security. Conventional intrusion control methods such as firewalls or access control systems are no longer alone able to withstand attacks. Therefore, the need to detect new attacks and anomalies is inevitable. The dataset used in this paper is called NSL-KDD which includes 5 classes: one of them is normal and the other four classes are attacks. In the presented work, an ensemble classifier based on the mean probability of attacks is adopted. The true detection rate of the proposed system is $99.89%$ which is more than other competing methods. Moreover, the ensemble classifier achieved an F1-measure of $92.48%$. To improve the F1 measure, we used a meta-classifier called meta-cost which incorporates a cost matrix to transform the original classifier into a cost-sensitive classifier. By this idea, we achieved an F1-measure of $94.1%$ which outperforms than non-cost sensitive ensemble classifier. These results show that the proposed system can be used as a suitable defence tool to detect intrusion against cyber-attacks.

In this paper, a three-species food chain model is proposed and studied. It is assumed that there are fear costs in the first two-level due to predation risk and there exists an alternative source of food for a top predator. Holling’s disc function is adopted to describe the food transition throughout the chain. All the solution properties are discussed. The conditions of local stability and persistence of the model are established. The Lyapunov function is used to specify the basin of attraction for each equilibrium. Local bifurcation analyses are studied. The global dynamics of the model are investigated numerically. Different bifurcation diagrams and attractors are obtained. It is obtained that the system is rich in dynamics that include chaos.

This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species.  This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.

Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision-makers to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick--Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and the Fourier model, and the expected trend is obtained using simple linear regression models. Actual and generation data were used for the performance evaluation of the proposed model. The results of the current model, with improvement, showed higher accuracy as compared to ARIMA model performance.

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things.  We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper, we introduce a semi-parametric method for prediction by making a combination of NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in designing the model; the data was collected from a nursing home hospital for period 11/7/2021- 23/7/2021, the sample size is 100 covid positive patients with 12 females & 38 males out of 50, while 26 female & 24 male are non-COVID out of 50. The input variables of the NN model are identified as the ferritin and a gender variable. The higher results precision is attained by the multilayer perceptron (MLP) networks when we applied the explanatory variables as the inputs with one hidden layer, which covers 3 neurons, as the planned many hidden layers are with one output of the fitting NN model which is used in stages of training and validation beside the actual data. We used a portion of the actual data to verify the behavior of the developed models, we find out that only one observation is a false predictive value. This means that the estimation model has significant parameters to forecast the type of Covid cases (Covid or no Covid).

The GLS and ML methods are the most common methods for estimating SEM but require multivariate normality. Therefore, methods robust to standard errors and quality of fit indexes to Chi-square have been proposed: MLR and they are considered superior to ML and GLS methods analyzing ordinal data. When we have a five-way Likert scale, the data is treated as continuous by calculating the covariance matrix as inputs for ML, GLS, and MLR. However, outliers are familiar because modeling requires a large sample size, either because of the input of data or answers more than is expressed within a particular category. Their presence affects even methods with robust corrections, where the accuracy of estimating parameters, standard errors, and fit indicators may be compromised the quality of fit indexes and inappropriate solutions, where a robust algorithm is proposed to clean the data from the outlier, as this proposed algorithm calculates the robust correlation matrix robust RFCH Reweighted Fast Consistent and High Breakdown, which consists of several steps and has been modified by taking the clean data before calculating the robust RFCH correlation matrix.  It was also suggested to make a comparison between the three methods before the treatment process with the presence of outlier values and note the extent of their impact on the methods and after using the robust RFCH method, and note the extent of improvement in estimations, standard errors and the overall quality of fit indexes for each of the Chi-square index, CFI, TLI, and RMSEA, SRMR and CRMR, with the robust corrections in the Chi-square index for each of the methods MLR. Through the simulation experiment, the researcher reached the power of the proposed method robust RFCH in improving the quality of parameter estimation, standard errors, and overall fit indexes quality.

The hearing-impaired community uses gestures to communicate. Gestures can also be used in interactions between man and computer. However, gestures become increasingly complicated in a comparatively complex environment. A recognition algorithm with a choice of function based on the improved genetic algorithm is proposed to improve the ability to identify gestures. The recognition process includes retailing, extraction, and feeding functions before classifying the neural network. After learning gestures, the proposed method is compared with traditional methods that use the classic genetic algorithm. The proposed method demonstrates the effect of optimization and sensitivity of the function.

Nowadays, energy consumption is curtailed in an effort to further protect the environment as well as to avoid service level agreement (SLA) breach, as critical issues in task scheduling on heterogeneous computing centers. Any reliable task scheduling algorithm should minimize energy consumption, makespan, and cost for cloud users and maximize resource utilization. However, reduction of energy consumption leads to larger makespan and decreases load balancing and customer satisfaction. Therefore, it is essential to obtain a set of non-domination solutions for these multiple, conflicting objectives, as a non-linear, multi-objective, NP-hard problem. This paper formulates the energy efficient task scheduling in green data centers as a multi-objective optimization problem so that fuzzy Non-dominated Sorting Genetic Algorithm 2 (NSGA-II) has been applied using the concept of Dynamic Voltage Frequency Scaling (DVFS). In this procedure, we adopted fuzzy crossover and mutation for optimal convergence of initial solutions. For this purpose, the binary variance function of gene values and the mean variance function of objective values are proposed for fuzzy control of mutation rate, increasing the variation in the optimal Pareto front as well as the correct frequency variance function of the processors engaged in scheduling to control the crossover rate. This serves to add the objective of indirect load balancing to the optimization objectives, thereby to replace the three-objective optimization process with four-objective optimization. In the experiments, the proposed NSGA-II with fuzzy algorithm is compared against the NSGA-II algorithm, involving three scheduling strategies namely Green, Time and Cost Oriented Scheduling Strategy. The simulation results illustrate that the newly method finds better solutions than others considering these objectives and with less iteration. In fact, the optimal Pareto solutions obtained from the proposed method improved the objectives of makespan, cost, energy and load balance by 4%, 17%, 1% and 13%, respectively.

This paper is primarily committed to three primary angles concerning photovoltaic based DG. The fundamental perspective being the reduction of influence changes in daylight based photovoltaic and the Reduction of influence distribution in the framework of the system. According to the unpredictable changes credited to the wide range of sun situated radiations. Further, the sizing related issues and region of an SPV based DG may cause a ton of influence concerns effecting the overall DG system operation and its efficiency. The second region of concern is the method used in the control of the DG and its feasibility to diminish framework influence issues. Another area of concern is network interconnection, through the appropriate introduction of RES into the ordinary grid for supportable and stable activity. This has been managed through an extensive contextual analysis of an operational system.

The security is demanded to transport important data over the network. In this work a hybrid encryption depending on playfair cipher and RSA algorithm is proposed to give more confidentially and get rid of the defects of the two methods. The first cipher text is obtained by playfair cipher by using (812) expanded key matrix that is filled by decimal ASCII characters of Alphabets, numbers and common characters of ASCII table while the final cipher text is obtained by RSA cryptosystem by applying it for blocks of two characters. The proposed hybrid encryption avoids to take large numbers in RSA algorithm and performs complex operations that need a long time to do. The proposed hybrid cipher is tight security that is difficult to analyze and detect from hackers and intruders.

Through this treatise, a study has been submitted about modified of Szasz-Mirakyan-Schurer-Kantrovich operators which that preserving (e^{- bx },b > 0) function. We interpret and study the uniform convergence of the modern operators to (text{ f}). Also, by analyzing the asymptotic conduct of our operator.

The present study deal with the effective heat transfer with the activity of connected inclined magnetic field of the asymmetric channel through the porous medium. The effect of sliding speed on channel walls was taken into account and the effect of nonlinear particle size was analyzed applying long wavelength and low Reynolds count estimates. The mathematical expression of axial velocity, stream function and pressure rise was analytically determined. The effect of the physical parameter is included in the present model on the computational results. They are presented in chart form by applying for the Mathematica program.

In this paper, we study and discussion new kinds of Sesquilinear functional which is fuzzy soft Sesquilinear functional and given some properties with characterization and also theories related on fuzzy soft Sesquilinear functional have been given. Additionally, we present the relationship between this kind and other kinds

Financing decisions for investment are one of the important tasks of the company in determining the best composition. On the other hand, how to finance the company’s assets for individuals and institutions is important, and how much debt and stocks the company has used to finance its assets, is important because it depends on the company’s financing decisions will be affected. This study investigates the application of nonlinear mathematical modeling in panel data analyses of the pecking order theory in capital structure using multiple regression in the Tehran stock exchange. The research period is from 2014 to 2019. In this research, panel data regression has been used to test the hypotheses. To collect information and data, the library method, and to test the research hypotheses, panel data and panel analysis using multiple regression have been used. The main hypothesis of this research is based on the fact that in order to Management decisions about the optimal capital structure of the company can be based on the theory model of the pecking order. In the results of this study, it seems that the companies in question to finance themselves, in fact, follow the mathematical model used in the theory of pecking order.

Endometriosis is the anomalous progress of cells at the outer part of the uterus. Generally, this endometrial tissue stripes the uterine cavity. The existence of endometriosis is identified through procedures known as Transvaginal Ultra Sound Scan (TVUS), Magnetic Resonance Imaging (MRI), Laparoscopic procedures, and Histopathological slides. Minimal Invasive Surgery (MIS) Laparo-scopic images are recorded in a small camera. To assist the surgeon in identifying their presence of endometriosis, image quality (characteristics) was enhanced for more visual clarity. Deep learning has the ability in recognising the images for classification. The Convolutional Neural Networks (CNNs) perform classification of images on large datasets. The proposed system evaluates the performance by a novel approach that implements the transfer learning model on a well-known architecture called ResNet50. The proposed system train the model on ResNet50 architecture and yielded a training accuracy of 91%, validation accuracy of 90%, precision of 83%, and recall of 82%, which can be applied for larger datasets with better performance. The presented system yields higher Area Under Curve (AUC) of about 0.78. The proposed method yields better performance using ResNet50 compared to other transfer learning techniques.

In this paper, we consider some nonlinear contraction for set-valued operators and prove some fixed point results in the case of set-valued operators are ordered-close and not ordered-close, and in the case of set-valued operators are UCAV (LCAV) in quasi-ordered $PM$-spaces. Moreover, we present two examples and an application to show the validity of the main theorems.

This manuscript focuses on the impact of early treatment programs on swine flu disease transmission among the population. In this manuscript, a nonlinear Susceptible-Exposed-Infected-Recovered (SEIR) model with early Treatment programs are developed to examine the transmission dynamics of Swine flu infection with the help of the system of ordinary differential equations. The characteristics of the model are investigated by the basic reproduction number. We analyzed that the model exhibits using stability theory of differential equations, the disease-free equilibrium is linearly stable for R01. Also, conditions for non-linear stability are derived. Sensitivity indices for basic reproduction and also optimal control measures for swine flu are obtained. Further, numerical simulation for the model is supported by relevant graphs.

In this article, ant lion optimiser algorithm is proposed for resolve the working of the electro-hydraulic position servo control scheme on controlling in the general position when compared with local position like the mechanism of work that inspired from particle swarm optimization algorithm in additional to that servo valve contributed by ant lion optimizer algorithm that enhanced and improved the hydraulic cylinder working by using the conventional proportional integral derivative (PID) controller in utilize the optimized algorithm that works as attractive solution added as artificial intelligent algorithm to enhanced the proposed system to achieve best performance for the PID controller and the results analysis achieved for maximum overshooting, rising time, settling time 0 %, 0.020 (sec), 0.0115 (sec) respectively and this work is implemented using MATLAB Simulink

The aim of the presented study is to introduce and verify two new spaces called $mathcal{P}_$ compactness and  $mathcal{P}_$connectedness using $mathcal{P}_$open sets and some of their properties. Moreover, we study the relationship between these spaces. Another purpose of this study is to examine a new form of separation axioms, by using $mathcal{P}_$open set namely $T_{mathcal{P}i}$-spaces where $(i=0,1,2)$. The pertinence between them has been discussed and several features of these spaces are demonstrated as well.

Nowadays, information security has become a very important and difficult matter. Security cameras are widespread in banks, ATMs, airports, universities, offices, and anywhere with a security system. The face recognition process is one of the most demanding image analysis and computer vision tasks. Faces are biometric systems that utilized a digital image of a person to identify or authenticate that person. This system is employed in the field of security. The face recognition system is required to detect and recognize the face in the image automatically. It works by extracting and then recognizing its attributes, irrespective of expression or illumination, transitions (translation, rotation and scaling of the image) and ageing, which is a difficult task. The proposed system records the facial features of the person standing in front of the camera, such as the size, position of the nose, eyes, jawbones, and cheekbones structure. This program also allows the user to evaluate and analyze the image. This system does not require long training for technicians because it is easy to use and gives quick and accurate results compared to biometric techniques the other. It is worth noting that Matlab roll was used in the design of this program.

In this study, a structure has been proposed implementing the optical Plasmonic logic gates (OR, NOR, AND, NAND, NOT) using the linear Plasmonic waveguide and the double ring resonator. The results of these gates were analyzed and simulated by means of Comsol Multiphysics (5.6) using Finite Element Analysis (2-FEM). These gates were implemented in the same structure depending on the characteristic of constructive and destructive optical interference between the signals propagating in the input ports and the control port, the phase and direction of those signals, as well as the positions of these ports. Hence, the performance of these gates was measured according to two criteria, first, the optical transmission ratio and the second, the contrast ratio, which is the ratio between the transmitter ON state of logic (1) and OFF for logic (0).

This study aimed to identify strategies for implementing social responsibility in banking services to stakeholders considering the compliance auditing and determine barriers. The Grounded Theory was used to develop the model, and banking experts were interviewed using a purposive sampling method to collect qualitative data. A total of 336 certified public accountants were selected in the quantitative part using a random sampling method. A questionnaire was used for data collection, and the analysis of variance (ANOVA) and t-test and Friedman test were used to analyze the data. The essential executive strategies were to increase welfare services proportional to the inflation rate to employees, implement a meritocracy system in the banking system, accept the workforce with government testing and supervision, increase actual stock returns and distributive profits, provide transparent, timely, and reliable information with simultaneous access for all, development of electronic banking, and justice in equal services to all customers with high quality and speed. In addition, the critical barriers were the lack of prioritizing compliance with social responsibilities at the top of organizational goals and the private or public nature of banks. Considering the confirmation of the five hypotheses, the compliance with social responsibilities in customer service had the most significant effect, and the other stakeholders service had the least effect in reducing the stakeholders’ expectation gap.

In this paper, we are concerned with the existence of a solution u 2 K for the variational inequality problem $ V I(A; psi, phi, g;K)$. Furthermore, we propose some conditions that ensure the well-posedness of this problem. We study an operator type $g - ql$ which extends the linear problem. Finally, we investigate the existence of solutions for general vector variational inequalities in the inclusion form.

It is known that there are disk-cyclic operators that are not satisfy the disk-cyclic criterion. This work introduce weakly disk-cyclic operators, which are kind of disk-cyclic operators, and study its relation with disk-cyclic criterion with several results and properties.

The problem of finding the Artin character and Artin indicator for the groups ({SUT}(2, p)), where (p)= 3, 5, 7 from the induced character from the cyclic subgroups for these groups determined in this work where ({SUT}(2, p)) is the special upper triangular group.

To consider (R) is a commutative ring with unitary, (X) be a non--Zero unity left (R - module); (X) is known hollow module if each proper sub module of (X) is semi small local hollow module if (X) has a unique maximal submodule which contains each semi small submodule. The current study deals with this class of modules and give several fundamental properties related with this concept.

The application of structural reliability analysis has become very important to ensure the strength of the studied structural design, as it presents results that help in giving evidence about the acceptance of that design according to the materials used under specific operating conditions. In this research an experiment was done, to find out the effect of G.U.M mouthwash on cured and re-cured Visible Light Cured (VLC) composite dental filling material, made according to agreed international standards, where many studies have documented that the surface of restorative materials placed on the tooth may also be affected by the chemical effect of different types of oral health care products, and the experiment was analyzed mathematically by applying structural reliability analysis to know the probability of structural failure when dental filling were exposed to the mouthwash G.U.M (Operational conditions), using analysis technique: the D-vine copula. The results were that the probability of structural failure gave an indication from which to infer the extent to which the experiment was accepted or rejected.

The $delta$-integral with respect - $delta$ - fuzzy measure has significant practical applications such as economic, data mining, etc. In this paper, we define $delta$-fuzzy measure and studied the measurable function with respect to $delta-$ fuzzy measure, also we defined an integration on a type of measurement, which is called the $delta-$ integral because of its importance in many other applications, we studied the properties of this integration and proved some important theories, Besides that, the convergence theorems are studied and the obtained results are proved.

This paper aimed to identify the organizational entrepreneurship barriers of the Gymnastics Federation of the Islamic Republic of Iran. The mixed method and Brown and Clark method were used in the research. The population consisted of two sections, including gymnastics experts and university professors (180 people), and the sample size was 16 people based on the theoretical saturation index and 120 people based on the Cochran formula. Three structural 14, behavioral 13, and contextual barriers with 5 indicators were identified by qualitative data analysis. The research instrument in the quantitative part was a questionnaire that was extracted from the codes of the qualitative part using LISREL and SPSS software. The results confirmed the items and factors in the first and second confirmatory factor analysis tests. Three barriers were identified, and 32 indicators were obtained as the measurement tool. The model was fitted using the structural equation method (SEM) based on path coefficient and t-statistic. The effect of three independent variables was significant (1.00, 0.90, and 0.97), indicating the model’s high estimation power. The results showed that underlying barriers had the most significant effect on the failure of organizational entrepreneurship.

In this paper, we use an irreducible plane-cubic curves in the projective plane $PG(2,q)$ to construct (k,3)-arcs of size $4nu$ where $lceil frac{q+1-2sqrt{q}}{4}rceilleqnuleqlfloor frac{q+1+2sqrt{q}}{4} rfloor$. Each of these arcs gives rise to an error-correcting code that corrects the maximum possible number of errors for its length. Furthermore, we discuss the completeness of each arc. The isotropy subgroup of each arc are determined. All Griesmer codes that correspond to plane-cubic curves are given for $7leq qleq 37,q$ is a prime.

In dense traffic Wireless Sensor Network (WSN), traffic congestion can increase routing overhead and packet loss, which restricts the entire network performance, therefore a traffic-aware and congestion-control data delivery is required to control the traffic. The proposed Energy-efficient Q-learning and Kullback Sparse Encoder (EQ-KSE) method is used for traffic-aware routing and congestion-control data delivery method for WSN. The method enforces a traffic balancing strategy using the energy-efficient reward function and estimates the wireless link quality by the Energy-efficient and Q-Learning Routing algorithm. On the basis of the estimation of each wireless link, the Energy-efficient Q-Learning based Traffic-aware Routing model makes routing decisions through energy and queue length to reduce routing overhead and time significantly. With the obtained optimal routes data aggregation are performed at the sink node, causing a proportionate amount of congestion. To handle this issue, a Kullback Leibler Sparse Auto Encoder (KL-SAE) Congestion-control Data Delivery method is proposed. This KL-SAE model with the aid of the reconstruction loss function, through divergence reduces the congestion, therefore contributing to packet loss, and packet delivery ratio. Simulation results show that EQ-KSE method performs traffic-aware routing by minimizing both the route selection time and overhead. In high node density scenarios, it also betters the state-of-the-art methods in packet delivery ratio and packet loss rate.

In this article, first we introduce six types of power graphs related to a graph (or directed graph), with the help of set theory. Then we show that these newly defined power graphs are pairwise distinct by a few examples. Finally, we discuss the relation between Eulerian being the base graph and these six power graph types. Moreover, we express the relation between pairwise Eulerian of these power graphs.