In this paper, we have considered the blood flow in a curved channel with abnormal development of stenosis in an axis-symmetric manner. The constitutive equations for incompressible and steady non-Newtonian TANGENT HYPERBOLIC FLUID have been MODELed under the mild stenosis case. A perturbation technique and homotopy perturbation technique have been used to obtain analytical solutions for the wall shear stress, resistance impedance to flow, wall shear stress at the stenosis throat and velocity profile. The obtained results have been discussed for different tapered arteries i.e., diverging tapering, converging tapering, non-tapered arteries with the help of different parameters of interest and found that tapering dominant the curvature of the curved channel.

In this paper, first the space of HYPERBOLIC TANGENT functions is introduced and then the universal approximator property of this space is proved. In fact, by using this space, any nonlinear continuous function can be uniformly approximated with any degree of accuracy. Also, as an application, this space of functions is utilized to design feedback control for a nonlinear dynamical system.

Introduction: In recent years, groundwater level has been descending due to climate change as well as method and use of them, especially in arid and semi-arid regions. According to the United Nations studies, Iran is considered one of the countries facing a shortage of water. In terms of climatic conditions, much of the country is but arid and semiarid regions. Water Table level control using observation wells are the main source of information to investigate the hydrological changes in these areas. Due to the recent drought and water shortages on a wide area of the country, the importance and sensitivity of groundwater management is increasing. Predicting the Water Table level using mathematical and statistical MODELs can contribute significantly to proper planning and decisions to provide long-term water supply. In this study, the level of underground water using the gradient network and the transfer function of TANGENT has been tried. Because of recent decades, neural network MODEL studies show the high capability of this MODEL in exploring the relationship between data and the recognition of patterns. Coppola and al (2003) investigated the possibility of predicting the level of 12 observation wells in different climatic situations, using artificial neural networks, in an area near the Temba Bay of Florida. Their results showed that, in MODELing of the waters of the limestone and karstic areas, neural networks performed appropriate performance. diacplous et al. (2005)conducted an investigation to predict 18 months of groundwater level to predict an underground water level in the Mesrar Valley in Crete, Greece. The results indicate that the lonenberg algorithm is the most appropriate MODEL. Methodology: The recent multi-year drought in the province of hormozgan has resulted in the aggravation of drought conditions and the imposition of many problems on water resources in particular in the underground reservoirs in particular. Sarkhoon Plain plain is one of the areas close to the provincial capital of hormozgan. In this paper, prediction of the spatial MODEL of the Water Table plain of Sarkhoon Plain plain using artificial neural network method and HYPERBOLIC rule is used to investigate the fault level of this MODEL. in this study, the data of ten observation wells during the 25-year period of 1990-1387 to 1392-1392 of the regional water organization of hormozgan province have been used. Artificial neural networks are one of the computational methods that utilize the learning process using called Nero, by adjusting the weights, using the input-output samples that are available. This MODEL is subsequently used to estimate the output value for the new data. The weight of the hidden layer and the output layer are changed so that the error rate is min. This error is represented as follows. (1) E = 1 / 2 [(y-O) ^ 2]The following algorithm is illustrated in order to train the neural network. η > 0 and E > 0After implementation of neural network algorithms with different neurons in matlab software, the results of predicting the water height of Sarkhoon Plain with HYPERBOLIC transformation functions were obtained to determine the best spatial MODEL of different levels of groundwater depth, the soil water MODELs were used. in order to choose the best extrapolation method in this study, eight methods were used and finally the MODEL that had the lowest fault was considered as optimal MODEL. Results: In this study, neural network MODEL was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network MODEL was selected as the top MODEL with 40 neurons in the latent layer and with its extension to observation wells a spatial prediction MODEL was obtained from groundwater level. The very low error and the high correlation of this MODEL, from the results of the test data, shows its efficiency in predicting the level of groundwater level. Using this algorithm for data of ten wells, water height was predicted for twelve months of 1400 year. The results of this research have proved the superiority of neural networks to numerical MODELs, This spatial MODEL can be used to control the rate of water harvesting in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evapotranspiration in predicting groundwater levels. Discussion and conclusion: In this study, neural network MODEL was implemented with different neurons to predict the level of groundwater level. After reviewing the evaluation criteria, the neural network MODEL was selected as the top MODEL with 40 neurons in the latent layer and with its extension to observation wells, a spatial prediction MODEL was obtained from groundwater level. The results of diacplous et al. (2005) showed the superiority of lonenberg neural network over other MODELs that have sufficient layers of latent layers, while it seems that the use of multiple latent layers with multiple neurons in different MODELs leads to error reduction and the choice of superior MODEL selection. Toarimino, Chua and Sethi (2012) emphasize the short-term forecasts of groundwater fluctuations. They have used the parameters of precipitation, evaporation-evapotranspiration and water level in the neural network MODEL. Despite the higher parameters, the absolute mean of their superior MODEL error has been higher than the average MODEL error of the present research. It is probably due to the low intensity of the hidden layer neurons as well as their short time ranges. The results of the study indicate that the use of a neural network algorithm with the number of static neurons cannot be a measure of the performance evaluation of a MODEL. This spatial MODEL can be used to control the rate of water Picked up in different locations for sustainable water resources management, to determine the structure of input parameters of the neural network, the effects of drought periods and the effects of parameters such as rainfall, temperature and evatranspiration in predicting groundwater levels.

Mixed convection flow of TANGENT HYPERBOLIC liquid over stretching sheet is explored. Joule heating, double stratification, non-linear thermal radiation, Brownian motion and thermophoresis are present. Phenomenon of mass transfer is examined by activation energy along with binary chemical. Computations of convergent solutions are carried out for the nonlinear mathematical system. Graphical representation is employed for outcome of sundry variables on velocity profile, temperature field and concentration of nanoparticles. Moreover, Nusselt number, coefficient of drag force and mass transfer rate are examined. It is observed that velocity decays for larger Weissenberg number. Concentration of FLUID enhances for higher activation energy parameter.

The current study investigates the mixed convective flow of MHD TANGENT HYPERBOLIC nanoFLUID due to a stretching surface with motile micro-organisms via convective heat transfer and slip conditions. The flow analysis's governing equations were converted into a non-dimensional relation by using the proper alteration. The PDE MODEL equations are computed for these transformed equations using the MATLAB- bvp4c scheme. Skin friction, Sherwood number, Nusselt number, and the profiles of motile microorganisms are engineering-relevant quantities when compared to various physical variables. In comparison to recent literature, Skin friction is consistent for magnetic parameter; the results demonstrated a good consistency. Furthermore, an enhancement in the radiation and mixed convection parameter's magnitude enhances the velocity profile. Weissenberg number and magnetic field are used to study the reverse impact. The impact of thermal radiation parameter, Brownian movement, and thermophoretic effects are additional factors that frequently improve heat transfer. Through graphical and tabular explanations, the physical interpretation has been presented.

The present paper focuses on a numerical study for an inclined magnetohydrodynamic effect on free convection flow of a TANGENT HYPERBOLIC nanoFLUID embedded with carbon nanotubes (CNTs) over a stretching surface taking velocity and thermal slip into account. Two types of nanoparticles are considered for the study; they are single and multi-walled nanotubes. The presentation of single-parameter group (Lie group) transformations reduce the independent variable number by one, and hence the partial differential governing equations with the supplementary atmospheres into an ordinary differential equation with the appropriate suitable conditions. The obtained ordinary differential equations are then numerically solved by employing the fourth-order Runge-Kutta technique along with the shooting method. The effects of the various parameters governing the flow field are presented with the help of graphs. The investigation reveals that the non-Newtonian MWCNTs TANGENT HYPERBOLIC nano-liquid reduces the friction near the stretching sheet contrasting SWCNTs. This combination can be used as a friction lessening agent/factor. The usage of CNTs shows an excellent performance in enhancing the thermal conductivity of the nanoliquid and that single-wall carbon nanotubes (SWCNTs) have a higher thermal conductivity in comparison to multi-wall carbon nanotubes (MWCNTs) even in the presence of radiative heat transfer and heat source. The comparison with existing results available in the literature is made and had an excellent coincidence with our numerical method.

Canny algorithm is an optimal algorithm to detect edges in images. Canny edge detector (CED) commonly uses the differential of Gaussian (DoG) filters to estimate the edge information. Although, DoG provides better tradeoff between smoothing level  s and edge detection, its smoothness affect the performances of edge detection (ED). In particular, when the smoothing parameter is greater than one, the localization, and detection performances are degraded. This proposed approach makes use of a second order differential HYPERBOLIC TANGENT filter to determine the gradients, and provides well-localized edge features than DoG filter. Mean squared error (MSE) and Figure of Merit ' F' parameters are used to measure the detection and localization performances.This algorithm is tested on 44 different natural images, and improves the ' F' to 0.9787 and reduces the average MSE to 0.2752 while the conventional CED has ' F' as 0.9422 and MSE as 0.2905.

Numerical MODELing of compressible two-phase flow is a challenging and important subject in practical cases and research problems. In these problems, mutual effect of shock wave interaction creates a discontinuity in the FLUID properties and interface of two FLUIDs as a second discontinuity lead to some difficulties in the numerical approximations and estimating an accurate interface during the hydro-dynamical capturing process. The main objective of this research is accurate capturing of the interface and numerical study of shock wave during gas-gas and gas-liquid interface of two-phase flows. For these purposes , HLLC Riemann solver and Godunov numerical method was used for a HYPERBOLIC two-pressure two-FLUID MODEL where programming was conducted in two-space dimensional with the second order accuracy. Various one and two-dimensional problems were simulated such as compression and expansion shock tubes, shock wave interaction with R22/air bubble, underwater explosion and hypersonic shock with M=6 interaction with a cylindrical water column. The numerical results obtained from this attempt exhibit very good agreement with the experimental results, as well as the previous numerical results presented by the other researchers based on the other numerical methods.