In this study, an investigation is carried out for laminar steady mixed 2D magnetohydrodynamic (MHD) flow of micropolar Casson fluid with thermal radiation over a horizontal circular cylinder with constant surface temperature. In the present study, an investigation is carried out on the effects of physical parameters on Casson fluid non dimensional numbers. The governing nonlinear partial diffe...

The logistic, Gompertz, Richards and asymmetric logistic growth curve models were fitted to body weight data of local Ghanaian chickens and French SASSO T44 chickens. All four growth models provided good fit for each sex by genotype growth data with R2 values ranging from 86.7% to 96.7%. The rate constant parameter, k, ranged between 0.137 and 0.271 and were significantly different from zero fo...

In this paper, a robust autopilot is proposed using stable interpolation based on Youla parameterization. The most important condition of stable interpolation between local controllers is the preservation of stability so that each local controller can ensure stability for an open neighborhood around a nominal point. The proposed design used fixed-order robust controller with parameter-dependent...

We fit 10 PIRLS testlets with standard item response and testlet response theory model. The variances of testlet effects are examined and compared. Item parameters and ability parameters estimated from the two different models are compared. The results indicate that variances of testlet effects range from .168 to .489. Item parameters as well as ability parameter estimated from two approaches c...

MHD boundary layer flow of two phase model nanofluid over a vertical plate is investigated both analytically and numerically. A system of governing nonlinear partial differential equations is converted into a set of nonlinear ordinary differential equations by suitable similarity transformations and then solved analytically using homotopy analysis method and numerically by the fourth order Rung...

We introduce a new nonparametric regression estimator that uses prior information on regression shape in the form of a parametric model. In eeect, we nonparametrically encompass the parametric model. We obtain estimates of the regression function and its derivatives along with local parameter estimates that can be interpreted from within the parametric model. We establish the uniform consistenc...

We introduce a new nonparametric regression estimator that uses prior information on regression shape in the form of a parametric model. In e!ect, we nonparametrically encompass the parametric model. We obtain estimates of the regression function and its derivatives along with local parameter estimates that can be interpreted from within the parametric model. We establish the uniform consistenc...