Utilizing the Turbo C programming language, the atmospheric earth model is created from sea level to 86 km. This model has been used to determine atmospheric Earth parameters in this study. Analytical derivations of these parameters are made using the balancing forces theory and the hydrostatic equation. The effects of altitude on density, pressure, temperature, gravitational acceleration, sound speed, scale height, and molecular weight are examined. The mass of the atmosphere is equal to about 50% between sea level and 5.5 km. g is equal to 9.65 m/s2 at 50 km altitude, which is 9% lower than 9.8 m/s2 at sea level. However, at 86 km altitude, g is close to 9.51 m/s2, which is close to 15% smaller than 9.8 m/s2. These results have been compared with an international standard atmosphere. The presumed atmosphere model differs significantly from the actual atmosphere because weather fluctuations are not taken into consideration in this model.
Samples of Bi1.6Pb0.4Sr2Ca2Cu3O10+δ superconductor were prepared by solid-state reaction method to study the effects of gold nanoparticles addition to the superconducting system, Nano-Au was introduced by small weight percentages (0.25, 0.50, 0.75, 1.0, and 1.25 weight %). Phase identification and microstructural
characterization of the samples were investigated using XRD and SEM. Moreover, DC electrical resistivity as a function of the temperature, critical current density Jc, AC magnetic susceptibility, and DC magnetization measurements were carried to evaluate the relative performance of samples. x-ray diffraction analysis showed that both (Bi,Pb)-2223 and Bi-2212 phases coexist in the samples having an orthorhombic crystal struct
In this research The study of Multi-level model (partial pooling model) we consider The partial pooling model which is one Multi-level models and one of the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly among the stations in Iraq. We use Akaik′s Informa
... Show MoreIn this paper, a harvested prey-predator model involving infectious disease in prey is considered. The existence, uniqueness and boundedness of the solution are discussed. The stability analysis of all possible equilibrium points are carried out. The persistence conditions of the system are established. The behavior of the system is simulated and bifurcation diagrams are obtained for different parameters. The results show that the existence of disease and harvesting can give rise to multiple attractors, including chaos, with variations in critical parameters.
In this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).
The aim of this research is to find out the influence of Daniel's model on the skills of the twenty-first century among the students of the scientific-fifth grade at the secondary and preparatory government morning schools for the academic year 2022- 2023. Two groups were chosen out of five groups for the fifth-scientific grade, one of which represents the experimental group that is taught by the Daniel model, and the other is the control group that is taught in the traditional method. The equivalence of the two research groups was verified with a set of variables. As for the research tool, a scale was developed by the researchers for the skills of the twenty-first century, in which they adopted the framework of the Partnership Organizat
... Show MoreIn this research The study of Multi-level model (partial pooling model) we consider The partial pooling model which is one Multi-level models and one of the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly among the stations in Iraq. We use Akaik′s Informa
... Show MoreThe parametric programming considered as type of sensitivity analysis. In this research concerning to study the effect of the variations on linear programming model (objective function coefficients and right hand side) on the optimal solution. To determine the parameter (θ) value (-5≤ θ ≤5).Whereas the result، the objective function equal zero and the decision variables are non basic، when the parameter (θ = -5).The objective function value increases when the parameter (θ= 5) and the decision variables are basic، with the except of X24, X34.Whenever the parameter value increase, the objectiv
... Show MoreSAGD is a thermal recovery process in which steam oil ratio, SOR, is a key parameter that can affect the economic outcome of the process. Reservoirs with underlying or overlying lean bitumen present challenges for SAGD as they can act as a heat sink. Water has higher heat capacity than the bitumen and thus requires more steam to heat up the reservoir leading to higher SOR. The potential outcome of operating SAGD in these conditions may be lower bitumen rate and higher steam injection rate, both of which affect plant throughput and thus the economic matrix of SAGD. This paper looks at the performance of SAGD process in the presence of top lean bitumen. It will examine the theoretical CSOR that is needed to produce the bitumen with different
... Show MoreGroupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff
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