The process of evaluating and measuring tax performance is critical to support the tax collection process. The comparison of the amount of revenue collection with what is expected and the process of measuring tax performance continuously by the tax administration leads to increase the collection of tax, determine the size of deviations and stand and know the reasons and take the necessary measures to address them to get a better result in the future. According to the different tasks assigned to them, criteria and indicators for measuring the tax performance vary from one organization to another. These are indicators or criteria that measure tax revenue (i.e., amounts). One of the research's main findings was to raise the tax collection level, increase the number of employees to get good performance, and impose sanctions on tax evaders. They are detecting the manipulators with the other accounts submitted to the General Authority for Taxes to evade the tax and achieve the taxpayers' greatest possible profit. The most important recommendations reach the research. The attempt to introduce technology and advanced information systems to cope with developments in the field of taxation, to give more importance to the process of assessment and measurement of tax performance because of the positive impact in the process of collection of tax collection.
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t
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Diabetes mellitus caused by insulin resistance is prompted by obesity. Neuropeptide Nesfatin-1 was identified in several organs, including the central nervous system and pancreatic islet cells. Nesfatin-1 peptide appears to be involved in hypothalamic circuits that energy homeostasis and control food intake. Adiponectin is a plasma collagen-like protein produced by adipocytes that have been linked to the development of insulin resistance (IR), diabetes mellitus type 2 (DMT2), and cardiovascular disease (CVD). Resistin was first identified as an adipose tissue–specific hormone that was linked to obesity and diabetes. The aim of this study was to estimate the relationship between human serum nesfatin-1, adiponect
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This study utilizes streamline simulation to model fluid flow in the complex subsurface environment of the Mishrif reservoir in Iraq's Buzurgan oil field. The reservoir faces challenges from high-pressure depletion and a substantial increase in water cut during production, prompting the need for innovative reservoir management. The primary focus is on optimizing water injection procedures to reduce water cuts and enhance overall reservoir performance. Three waterflooding tactics were examined: normal conditions without injectors or producers, normal conditions with 30 injectors and 80 producers and streamline simulation using the frontsim simulator. Three main strategies were employed to streamline water injection in targeted areas.
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New ligands, N1, N4-bis (benzo[d]thiazol-2- ylcarbamothioyl) succinamide (L1) and N1, N4- bis (benzylcarbamothioyl)succinamide (L2), derived from succinyl chloride and 2-amino benzothiazole or benzylamine, respectively, have been used to prepare a set of transition metal complexes with the general formula [M2(L)Cl4], where L=L1 or L2, M = Mn(II), Ni(II), Cu(II), Cd(II), Co(II), Zn(II) or Hg(II). The synthesized compounds were characterized using various analytical techniques including TGA, 13C NMR, mass spectroscopy, 1H and Fourier-transform infrared (FTIR) spectroscopy, magnetic measurement, molar conductivity, electronic spectrum, (%M, %C, %H, %N) and atomic absorption flame (AAF) analysis. The results showed that (L1, L2) bin
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خلفية البحث: مرض السكري هو عامل خطر لأمراض القلب والأوعية الدموية وتصلب الشرايين وسبب مهم للوفاة. يرتبط خلل الدهون في الدم بشكل شائع بمرض السكري من النوع الثاني ويعتبر مؤشر تصلب الشرايين في البلازما علامة قوية للتنبؤ بخطر الإصابة بتصلب الشرايين وأمراض القلب التاجية. الهدف من البحث: دراسة ارتباط المؤشرات الدهنية لتصلب الشرايين لدى المرضى العراقيين المصابين بالسكري من النوع الثاني ولديهم أمراض قلبية وعائ
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In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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This study focused on the synthesis of novel polymers incorporating the 1,3,4-oxadiazole ring. Four polymers were specifically prepared by blending polymers (6-9) with polyvinyl alcohol (PVA) in defined ratios, resulting in the formation of blended polymers (10-13). The synthesized polymers were characterized using Fourier Transform Infrared (FTIR) spectroscopy and proton nuclear magnetic resonance (1H-NMR). The results showed that the structure aligned with the proposed synthetic polymers. Furthermore, the physical and thermal properties were studied using scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and Differential Scanning Calorimetry (DSC). Additionally, the biological activity was examined against two s
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