In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

Adolescence is considered to be one of the most dangerous and delicate stages that a juvenile goes through. It is a stage which the juvenile enters while he is a child, and emerges from it by being able to have children, but this does not mean the ability to become socially and psychologically mature

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

The research include a pulsed Nd: YAG Laser with (300µs) pulse duration in the TEM00 mode at (1.06µm) wavelength for energies between (0.5-3) J was employed to drill Brass material which is use in industrial applications. The process of drill was assisted by an electric field. This resulted in an increase in the hole aspect ratio by the value (45%) and decrease in the hole taper by the value (25%) of its value under ordinary drilling conditions using the same input energy.

The importance of the research comes from dealing with the problem of lack of traffic awareness, which causes accidents and the occurrence of human and material losses, and the research aims to study the role of satellite channels in forming traffic awareness among the public, and a sample was chosen from Baghdad consisting of (280) individuals, male and female, and used the questionnaire tool. To obtain the data, which included several questions, the results were analyzed statistically and several results were reached, the most important of which is that there is an interest among the public in following traffic programs at a rate of one to two hours to receive information through traffic programs and to identify and apply gener

In the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can b