Consistent "with the thought of tax talk is unified tax natural evolution for him, as the application leads to the inclusion of tax all branches of income and its sources and through truncated part of this entry through the application of price ascending it, it means the procedures of tax reform. Taxes on total income characterized by giving a clear picture of the total income of the taxpayer and its financial situation and its burden family which allows granting exemptions, downloads, and application of prices that fit this case. This requires reconsideration of the structure of the tax system in force and the transition from a system specific taxes to the tax system on the total income of the integration of income from the rental of re

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

QA Sarhan, University of Anbar Sport and Physical Education Sciences, 2019

The study consisted in the development and use of a practical method to detect and
monitor, analyze and produce maps of changes in land use and land cover in the district of
Mahmudiya in Baghdad during the period 1990-2007 using the applications of remote sensing
techniques and with the assisstant of geographic information systems (GIS),as a valuable
contribution to land degradation studies.
This study is based maiuly on the processing on two subsets of landsat5 TM images picked up
in August 1990 and 2007 respectively in order to facilitate comparision and were thengeometrically and radiometrcally calibrated ,to used for digital classification purposes using
maximum liklihoods classification or six spectral bands of

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

Abstract: In this paper, a U-shaped probe with a curvature diameter of half a centimeter was implemented using plastic optical fibers. A layer of the outer shell of the fibers was removed by polishing to a D-section. The sensor was tested by immersing it in a sodium chloride solution with variable refractive index depending on solution concentrations ranging from 1.333 to 1.363. In this design, the sensor experienced a decrease in its intensity as the concentration of the solution increased. The next step The sensor was coated with a thin layer of gold with a thickness of 20 nm, and the sensor was tested with the same solutions which resulted in a shift in wavelengths where the shift in wavelength was 5.37 nm and sensiti

The designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

Abstract Metabolic syndrome (MS) is a group of clinical and biological abnormalities included risk of insulin resistance , disorders in glucose metabolism , abdominal obesity and abnormal lipid profile these features confer a greater risk of cardiovascular diseases . Anyway, the co-occurrence of diabetes mellitus and metabolic syndrome potentiates the cardiovascular risk associated with each of the two conditions. The present study aimed to determine a relationship between prolactin level in type -2- diabetic Iraqi women and metabolic syndrome, as well to find a relationship between prolactin level and other studied biochemical markers. seventy menopausal diabetic women with metabolic syndrome with age in range (45-50) years were enrolled i