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.
Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte
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The test considers from important methods and tools when we using the evaluation because it is a basic role in diagnosis & classification & motive & selection &guiding &prediction and the problem was formatted in some questions like ( what is physical variables that tall players needs n the game and effect on the game ? what is the tests that measures these variables also the defense rebound variable and is there a references standard specialized in that ?) , the aims of research represented by knowing to some physical abilities for tall players in basketball school and their tests and putting new tests to measure defense rebound to one player and tow tall players also limiting the standards degrees ( modified un following method ) to resul
... Show MoreBackground: Waterpipe tobacco smoking has become common especially among young people, Waterpipe smoking misconcepted as a safer mean of smoking, so in this study we will highlight the effect of Waterpipe smoking ‎on periodontal and oral health.‎ Materials and method. The selected ‎‎‎100 male subjects of 30-40 years, ‎categorized into 4 groups (each group ‎‎25 subject): Waterpipe smoker ‎with ‎healthy periodontium, ‎Waterpipe smoker ‎‎with chronic periodontitis, Non-‎‎smoker ‎with healthy periodontium and Non-smoker ‎with chronic periodontitis. Whole ‎unstimulated ‎saliva was collected. Clinical measurements: plaque ‎index
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Background: H1N1 influenza pandemic or swine flu was an influenza pandemic first described in Iraq in October 2009 .The virus appeared to be anew strain of H1N1 causes wide range of morbidity and mortality among different genders and age groups as part of worldwide pandemics.Seasonal flu is a contagious respiratory illness caused by influenza viruses that infect the nose, throat, and lungs. It can cause mild to severe illness, and at times can lead to death. The best way to prevent the flu is by getting a flu vaccine each year.
Objectives: Is to determine the morbidity and mortality in different age groups in patients with H1N1 influenza versus those patients with seasonal influenza who were admitted at the same time to AL-kindy
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Background: Invasion in oral cancer involves alterations in cell-cell and cell-matrix interactions that accompanied by loss of cell adhesion. Catenins stabilize cellular adherence junctions by binding to E-cadherin, which further mediates cell-cell adhesion and regulates proliferation and differentiation of epithelial cells. The Wnt/β-catenin pathway is one of the major signaling pathways in cell proliferation, oncogenesis, and epithelial-mesenchymal transition. Aims of the study: to detect immunohistochemical distribution pattern and different subcellular localization of β-catenin in oral squamous cell carcinoma and relate such expression to Bryne’s invasive grading system. Materials and Methods: This study included 30 paraffi
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
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Abstract
Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.