Journal of Applied Mathematics

In this study, the steady hydromagnetic flow of two immiscible couple stress fluids through a uniform porous medium in a cylindrical pipe with slip effect is investigated analytically. Essentially, the flow system is divided into two regions, region I and region II, which occupy the core and periphery of the system, respectively. The flow is driven by a constant pressure gradient applied in a direction parallel to the cylinder’s axis, and an external uniform magnetic field is applied in the direction perpendicular to the direction of fluid motion. Instead of the classical no-slip condition, the slip velocity along with vanishing couple stress boundary conditions is taken on the surface of the rigid cylinder, and continuity conditions of velocity, vorticity, shear stress, and couple stress are imposed at the fluid-fluid interface. The governing equations are modeled using the fully developed flow conditions. The resulting differential equations governing the flow in the two regions are converted to nondimensional forms using appropriate dimensionless variables. The nondimensional equations are solved analytically, and closed-form expressions for the flow velocity, flow rate, and stresses are derived in terms of the Bessel functions. The impacts of several parameters pertaining to the flow such as the magnetic number, couple stress parameters, Darcy number, viscosity ratio, Reynolds number, and slip parameter on the velocities in respective regions are examined and illustrated through graphs. The flow rate’s numerical values are also calculated for different fluid parameters and displayed in tabular form. It is found that increasing the magnetic number, viscosity ratio, Reynolds number, and slip parameters decreases the velocities of the fluids whereas increasing the couple stress parameter, Darcy number, and pressure gradient increases fluid velocities. The results obtained in this paper show an excellent agreement with the already existing results in the literature as limiting cases.

In this paper, we consider a multivariate statistical model of accident frequencies having a variable number of parameters and whose parameters are dependent and subject to box constraints and linear equality constraints. We design a minorization-maximization (MM) algorithm and an accelerated MM algorithm to compute the maximum likelihood estimates of the parameters. We illustrate, through simulations, the performance of our proposed MM algorithm and its accelerated version by comparing them to Newton-Raphson (NR) and quasi-Newton algorithms. The results suggest that the MM algorithm and its accelerated version are better in terms of convergence proportion and, as the number of parameters increases, they are also better in terms of computation time.

Networks are prevalent in real life, and the study of network evolution models is very important for understanding the nature and laws of real networks. The distribution of the initial degree of nodes in existing classical models is constant or uniform. The model we proposed shows binomial distribution, and it is consistent with real network data. The theoretical analysis shows that the proposed model is scale-free at different probability values and its clustering coefficients are adjustable, and the Barabasi-Albert model is a special case of in our model. In addition, the analytical results of the clustering coefficients can be estimated using mean-field theory. The mean clustering coefficients calculated from the simulated data and the analytical results tend to be stable. The model also exhibits small-world characteristics and has good reproducibility for short distances of real networks. Our model combines three network characteristics, scale-free, high clustering coefficients, and small-world characteristics, which is a significant improvement over traditional models with only a single or two characteristics. The theoretical analysis procedure can be used as a theoretical reference for various network models to study the estimation of clustering coefficients. The existence of stable equilibrium points of the model explains the controversy of whether scale-free is universal or not, and this explanation provides a new way of thinking to understand the problem.

In this study, we applied an approximate solution method for solving the boundary value problems (BVPs) with retarded argument. The method is the consecutive substitution method. The consecutive substitution method was applied and an approximate solution was obtained. The numerical solution and the analytical solution are compared in the table. The solutions were found to be compatible.

A country’s economic development relies on different features such as export/import, industrial processes, and tourism. Rural tourism is a discussion-centric research field for analyzing its contribution to a country’s economic growth. This field generates voluptuous data for tourists, expenditure, location, etc. analysis; the information increases over the years and the density of visiting tourists. Therefore, this article introduces an optimized reinforcement data analysis approach (ORDAA) for generating precise guidance information. This information is two-faced, namely, summarized data for tourist guidance and summarized data for the country’s economic development. Data augmentation’s steep rise and downfall are analyzed using reinforcement learning, wherein decision agents are precise for a relevant summary. The relevance is identified using associated development targets over varying years. Besides, the guidance information that identifies low tourist summary or nonachievable development targets is separately identified. The identified targets are analyzed using reinforcement agents for economic growth improvements compared to the previous tourist densities. This improves the focus on rural tourism sights and economic contributions to an optimal level.

In this paper, we introduce a new generalized inverse, called the G-MPCEP inverse of a complex matrix. We investigate some characterizations, representations, and properties of this new inverse. Cramer’s rule for the solution of a singular equation is also presented. Moreover, the determinantal representations for the G-MPCEP inverse are studied. Finally, the G-MPCEP inverse being used in solving appropriate systems of linear equations is established.