Modern Scientific Press

ABSTRACT: This paper investigates exact solutions of two dimensional incompressible Navier-Stokes equations (2D NSEs) for a time dependent pressure gradient term using Orlowski and Sobczyk transformation (OST) and Cole-Hopf transformation (CHT).Separation of variables method is applied to find the solutions of 2D heat equation.

ABSTRACT: Deterministic model was used to determine the depletion of water storage vessels dissolving in the stored water of pH value of 6.6. Stability analysis was carried out and it showed that there is instability in the depletion of the vessels. The numerical analysis showed that the depletion is in the form of negative exponential curve. Metal Vessel depletes the most at all levels of concentration of the input of toxic metal values, followed by earthen vessel, then Cement Reservoir and the least is Plastic vessel. Negative exponential curve well fits the generated data for each level of concentration of the input toxic metal values for each vessel. The estimated rates of depletion of vessel at each level for each vessel are also significant. The estimated rate of depletion of metal vessel is the highest, followed by the estimated rate of depletion of earthen vessel. The least estimated rate of depletion among the four vessels is plastic.

ABSTRACT: Diabetes is a disease of metabolism whose essential feature is excessive sugar in the blood and urine. Second order differential equation has been formulated to describe the performance of BGRS during GTT and its solution has been shown over here. Interesting point is that the sociological factors play an important role in the Blood Glucose Regulatory System.

ABSTRACT: Transportation plays a vital role in financial development of the country. Mixture of transportation and mobility are directly involved with development of financial system of the country and for that mature transportation infrastructure is required. This paper analyzes bi-objective transportation problem and an alternative approach is proposed to solve the problem. It has been established that all the efficient pairs of values of the objective function can be attained at the extreme points of the feasible region. Based upon some related linear programming problems, a convergent algorithm is proposed to generate all the efficient pairs. The method is illustrated through a numerical example.

ABSTRACT: We utilized the periodic likelihood ratio test statistic to assess the evidence that any estimated outlier for a given period is an outlier. The conditions are that the timing of the occurrence of an outlier is known or assumed and the magnitude of the outlier has been estimated or specified. While in February period, AO and TC outlier models respectively confirmed 30% significance of the weights of the outlier injected into the series, however, LS confirms significantly 40% significant of the weights injected displaying more powerful feat in capturing the time points of outliers. In October period, only IO outlier model confirmed significantly 20% of the weight of the outliers injected into the series. Our findings reveal that the AO, LS and TC models perform better in terms of their ability to capture the timing occurrence of outliers.

ABSTRACT: The practical problem is not why specification errors are made but how to detect them. There are number of tests for specification error in detecting the errors of omitted variables from a regression analysis. Using the observations on the dependent variables generated from Microsoft Excel according to the specification labeled true, a bootstrap simulation approach was used for the data generated for each of the models at different sample sizes 20, 30, 50, and 80 respectively each with 100 replications. Using bootstrapping experiment and some properties which estimators should possess if their estimates are to be accepted as good and satisfactory estimates of the parameters, namely, the bias, variance, mean square error, and root mean square error. The models investigated in the bootstrapping experiment consist of the problem of omitted variables. For the models considered, the experiment reveals that the estimated changes the effect of omitted variable as the coefficient varies in the different models. The effect of omitted variable becomes unstable which produces a bias and inconsistent.