The research aims to study the contribution of tax information systems to increase tax revenues, and to identify how efficiently used information systems currently by the tax authority and their effectiveness in the detection of irregularities by the tax payers such as the cleclaration of incorrect statements that do not show real results of their business activities or hide information from sources related to their income subject to tax, which would negatively affect the outcome of tax revenues and thus damage important sourse of the public treasury of the states resources. The data of research was collected by studying and analysing the tax information systems used by the General Commission of taxs and its branches and a number of prac

The water supply network inside the building is of high importance due to direct contact with the user that must be optimally designed to meet the water needs of users.  This work aims to review previous research and scientific theories that deal with the design of water networks inside buildings, from calculating the amount of consumption and the optimal distribution of the network, as well as ways to rationalize the use of water by the consumer.  The process of pumping domestic water starts from water treatment plants to be fed to the public distribution networks, then reaching a distribution network inside the building till it is  provided to the user.  The design of the water supply network inside the building is

Abstract

The research problem Focused about extent adoption of the financial reporting obligations and assets of the deferred income tax attributable to the concepts of accounting theory and whether the tax laws or accounting principles as well as local accounting rules to recognize the obligations and assets of deferred income tax in the financial statements, and what is the impact of the financial reporting of liabilities and assets Deferred tax in the quality of accounting information, and research aims to the statement of the accounting concepts of the theory of financial reporting obligations and assets of deferred income tax, view and analyze the differences in reporting, resulting from a discrepanc

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

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

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.