Abstract: Tin oxide thin films were deposited by direct current (DC) reactive sputtering at gas pressures of 0.015 mbar – 0.15 mbar. The crystalline structure and surface morphology of the prepared SnO2 films were introduced by X-ray diffraction (XRD) and atomic force microscopy (AFM). These films showed preferred orientation in the (110) plane. Due to AFM micrographs, the grain size increased non-uniformly as the working gas pressure increased.

The study aims to clarify the impact of growth in the industrial sector on economic growth in the Iraqi economics according to the methodology of Kaldor for (2017-2030) , taking into consideration the effect of the accumulation of capital in the calculation of growth rates in the economy through productivity estimate of Total Factor Productivity (TFP) to growth in the economy, which is why the study assumes a formula to comply with the laws of Kaldor growth models developed requirements. This study is the most important to find out  the development of the laws of Kaldor among Arabic studies, especially the first and third, so that the relationship between the growth of industrial production and economic growth as represented

Superconducting thin films of Bi1.6Pb0.4Sr2Ca2Cu2.2Zn0.8O10 system were prepared by depositing the film onto silicon (111) substrate by pulsed laser deposition. Annealing treatment and superconducting properties were investigated by XRD and four probe resistivity measurement. The analysis reveals the evolution of the minor phase of the films 2212 phase to 2223 phase, when the film was annealed at 820 °C. Also the films have superconducting behavior with transition temperature ≥90K.

This paper deals with the modeling of a preventive maintenance strategy applied to a single-unit system subject to random failures.

According to this policy, the system is subjected to imperfect periodic preventive maintenance restoring it to ‘as good as new’ with probability

p and leaving it at state ‘as bad as old’ with probability q. Imperfect repairs are performed following failures occurring between consecutive

preventive maintenance actions, i.e the times between failures follow a decreasing quasi-renewal process with parameter a. Considering the

average durations of the preventive and corrective maintenance actions a

In this paper, we present new algorithm for the solution of the nonlinear high order multi-point boundary value problem with suitable multi boundary conditions. The algorithm is based on the semi-analytic technique and the solutions are calculated in the form of a rapid convergent series. It is observed that the method gives more realistic series solution that converges very rapidly in physical problems. Illustrative examples are provided to demonstrate the efficiency and simplicity of the proposed method in solving this type of multi- point boundary value problems.

In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T