The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

In this paper will be applied to a probability model of inventories periods of multiple stores of raw materials used in the cement industry, cement factory in Samawah and basic materials are limestone, soil normal, iron soil, fuel oil and gypsum. It was built of this model after the test and determine the distribution of demand during the supply period (waiting period) for each subject and independently of the rest of the material as it is not affected by any of the materials above interrelated in the process of supply, this test has been using the Statistical Package of (SPSS) and then was determining the amount of request optimum seeking in each batch and each substance known volume of economic optimization of

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

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

In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

       The multimetric Phytoplankton Index of Biological Integrity (P-IBI) was applied throughout Rostov on Don city (Russia) on 8 Locations in Don River from April – October 2019. The P-IBI is composed from seven metrics: Species Richness Index (SRI), Density of Phytoplankton and total biomass of phytoplankton and Relative Abundance (RA) for blue-green Algae, Green Algae, Bacillariophyceae and Euglenaphyceae Algae. The average P-IBI values fell within the range of (45.09-52.4). Therefore, water throughout the entire study area was characterized by the equally "poor" quality. Negative points of anthropogenic impact detected at the stations are: Above the city of Rostov-on-Don (1 km, higher duct Aksai) was 38.57 i

This work consists of a numerical simulation to predict the velocity and temperature distributions, and an experimental work to visualize the air flow in a room model. The numerical work is based on non-isothermal, incompressible, three dimensional, k turbulence model, and solved using a computational fluid dynamic (CFD) approach, involving finite volume technique to solve continuity, momentum and energy equations, that governs the room’s turbulent flow domain. The experimental study was performed using (1/5) scaled room model of the actual dimensions of the room to simulate room air flow and visualize the flow pattern using smoke generated  from burnt herbs and collected in a smoke generator to delivered through