Taxes are an essential axis in the economy as the most effective and effective economic tool in any country (economy). Expanding the scope of taxation without adequate study has produced a dangerous result with a negative impact that is almost apparent, namely (tax evasion), which stands as a barrier preventing the state from reaching Therefore, the research sought to study strategic tax planning and its importance in reducing tax evasion, and the research aims from that to prove the importance of adopting strategic planning in the field of taxes according to modern and effective scientific foundations to reduce tax evasion to enhance the achievement of tax evasion. The financing objective is in addition to the other objectives, and the research problem is summarized in the extent to which the tax system follows the strategic planning of taxes in order to achieve the tax objectives and the effectiveness of this planning (strategic planning) in reducing tax evasion, and therefore the research sample was taken to include (specialists, workers, and taxpayers) and it was The sample is 105 individuals, and accordingly the study came out with results, the most important of which are; The importance of strategic planning in relation to reducing tax evasion, the existence of a weak correlation that is close to being of medium strength with a statistical significance between strategic planning and its importance in reducing tax evasion reflects the lack of interest of the sample in question in strategic planning, there was a significant statistically significant effect between strategic planning For taxes and the reduction of tax evasion, the decrease in the relative importance of taxes in general for the state, especially in the financing aspect, if, during the past 15 years, its contribution to the state’s general budget did not reach 4%, which is less than a shy percentage. The increase in tax revenues is an unreal increase, as it is As a result of the increase in government spending and the increase in inflation rates.
The enhancement of ZnSe/Si Heterojunction by adding some elements (V, In and Cu) as impurities is the main goal because they contribute to the manufacturing of renewable energy equipment, such as solar cells. This paper describes the preparation of thin films ZnSe with V, In and Cu doped using thermal evaporation method with a vacuum of 10–5 Torr. The thin film was obtained from this work could be applied in heterojunction solar cell because of several advantages including high absorption coefficient value and direct band gap. The samples prepared on a glass and n-type Si wafer substrate. These films have been annealed for 1 h in 450 K. X-ray diffraction XRD results indicated that ZnSe thin film possesses poly-crystalline structure after
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Background: Pain, swelling and trismus are the main minor complications encountered after surgical extraction of impacted third molars, minimizing these postoperative complications is the center of many studies, one proposed method is the prophylactic administration of corticosteroids, the aim of this study is to evaluate the effect of prophylactic Dexamethasone administration on facial swelling and trismus after surgical extraction of impacted third molars. Materials and methods: 20 patients were included in this study, they were randomly divided into 2 groups of 10 patients each; a study group in which patients were given 8 mg. Dexamethasone 1 hour before surgical extraction of impacted third molar and 4 mg. 6 hours postoperatively, and a
... Show More<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in
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Background Parkinson’s disease (PD) is currently the fastest-growing neurological disorder in the world. Patients with PD face numerous challenges in managing their chronic condition, particularly in countries with scarce healthcare infrastructure. Objective This qualitative study aimed to delve into neurologists’ perspectives on challenges and gaps in the Iraqi healthcare system that influence the management of PD, as well as strategies to mitigate these obstacles. Method Semi-structured interviews were conducted with neurologists from five different Iraqi provinces, working in both hospitals and private neurology clinics, between November 2024 and January 2025. A thematic analysis approach was employed to identify the main challenge
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In this paper, double Sumudu and double Elzaki transforms methods are used to compute the numerical solutions for some types of fractional order partial differential equations with constant coefficients and explaining the efficiently of the method by illustrating some numerical examples that are computed by using Mathcad 15.and graphic in Matlab R2015a.
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Gypseous soil covers approximately 30% of Iraqi lands and is widely used in geotechnical and construction engineering as it is. The demand for residential complexes has increased, so one of the significant challenges in studying gypsum soil due to its unique behavior is understanding its interaction with foundations, such as strip and square footing. This is because there is a lack of experiments that provide total displacement diagrams or failure envelopes, which are well-considered for non-problematic soil. The aim is to address a comprehensive understanding of the micromechanical properties of dry, saturated, and treated gypseous sandy soils and to analyze the interaction of strip base with this type of soil using particle image
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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