Abstract

      Value Added Tax (VAT) is one of the most important types of indirect taxes because of its advantages in achieving financial, economic and financial objectives. The introduction of VAT is part of the reform of the structure of the Lebanese public tax system aimed at reducing the fiscal deficit and resulting inflation, which still lacks a general consumption tax. There is also an urgent need to increase treasury revenues , Because of its broad tax base, as it imposes on the consumption of locally produced and imported goods, in addition to the role played by this tax in support of the local product              &nbs

This work aimed to design and testing of a computer program – based eyeQ improvement, photographic memory enhancement, and speed reading to match the reading speed 150 – 250 word per minute (WPM) with the mind ability of processing and eye snap shooting 5000WPM . The package designed based on Visual Basic 6. The efficiency of the designed program was tested on a 10 persons with different levels of education and ages and the results show an increase in their reading speed of approximately 25% in the first month of training with noticeable enhancement in the memory as well as an increase in the ability to read for longer time without feeling nerves or boring, a nonlinear continuously increase in reading speed is assured after the first mo

A dust storm in Iraq is a climatic phenomenon common in arid and semi-arid regions . The frequency of the occurrence has increased drastically in the last decade and it is increasing continuously .Baghdad city like the rest of Iraq is suffering from the significant increase in dust storms . In this research , the study of the phenomenon of dust storms for all types (Suspended dust , rising dust , dust storm) , and its relationship with some climate variables (Temperature , rainfall ,wind speed) .The statement of the impact of climate change on this phenomenon to Baghdad station  for the period (1981 – 2012) . Time series has been addressing the phenomenon of storms and cli

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Anumerical solutions is presented to investigate the effect of inclination angle (θ) , perforation ratio (m) and wall temperature of the plate (T_w) on the heat transfer in natural convection from isothermal square flat plate up surface heated (with and without concentrated hole). The flat plate with dimensions of (128 mm) length × (64 mm) width has been used five with square models of the flat plate that gave a rectangular perforation of (m=0.03, 0.06, 0.13, 0.25, 0.5). The values of angle of inclination were (0^o, 15^o 30^o 45^o 60^o) from horizontal position and the values of wall temperature (50^oC, 60 ^oC, 70 ^oC, 90 ^oC, 100^o<

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need