This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

In this work, effects of using different evaporative cooling pads (ECPs) on the energetic and exergetic efficiency of a direct evaporative air cooler (DEAC) have been theoretically and experimentally investigated. Three types of ECPs were used, i.e., honeycomb cellulose cooler pad (HCCP), shading-cloth cooler pad (SCCP), and aspen wood wool cooler pad (AWWCP). For SCCP and AWWCP, a 3-cm pad thickness was used, while for the HCCP, three different values of pad thickness were used, i.e., 3, 5, and 7 cm. Tests were carried out using air velocities of 8, 14, and 19 m/s, measured at the DEAC outlet. Engineering equation solver (EES) used for performing the required calculations of the various parameters affecting the thermal performance of the D

One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried

E-learning applications according to the levels of enlightenment (STEM Literacy) for physics teachers in the secondary stage. The sample consists of (400) teachers, at a rate of (200) males (50%), and (200)females (50%), distributed over (6) directorates of education in Baghdad governorate on both sides of Rusafa and Karkh. To verify the research goals, the researcher built a scale of e-learning applications according to the levels of STEM Literacy, which consists of (50) items distributed over (5) levels. The face validity of the scale and its stability were verified by extracting the stability coefficient through the internal consistency method “Alf-Cronbach”. The following statistical means were used: Pearson correlation coefficient,

In this research thin films from SnO2 semiconductor have been prepared by using chemical pyrolysis spray method from solution SnCl2.2H2O at 0.125M concentration on glass at substrate temperature (723K ).Annealing was preformed for prepared thin film at (823K) temperature. The structural and sensing properties of SnO2 thin films for CO2 gas was studied before and after annealing ,as well as we studied the effect temperature annealing on grain size for prepared thin films .

The dose rate for bremsstrahlung radiation from beta particles with energy (1.710) MeV and (2.28) MeV which comes from (32P and 90Y) beta source respectively have been calculated through six materials (polyethylene, wood, aluminum, iron, tungsten and lead) for first shielding material with thickness (x=1) mm which are putting between beta sources and second shield (polyethylene, aluminum and lead) with thickness (1, 2 &4) mm have been calculated. The distance between beta source and second shield is constant (D=1) cm. This dose rate was found by program called Rad Pro Calculator (version 3.26). The results of dose rate of beta particles were plotted as a function to the atomic number (Z) for first shield materials for each