This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researchers have reached several conclusions, the most prominent of which is that applying accounting information systems based on artificial intelligence in the accounting world is an inevitable trend that will bring about significant changes and developments in detecting and preventing the manipulation of earning. Using the Beneish model and one of the Data Mining techniques, namely the logistical regression technique, can effectively identify earnings management situations and enhance the functionality of accounting information systems. This includes improving system speed and efficiency, ensuring accurate output, and enhancing system security. Researchers strongly call for using and developing artificial intelligence within accounting information systems, especially the Beneish model. This will make it easier to detect earning manipulation and enhance cybersecurity measures, ultimately protecting the integrity and reliability of the computer system. The authors use the Benish model on a sample of economic units including (5) units and logistic regression on a sample including (5) Iraqi private banks. The result of applying these two methods was that using the Benish model led to one company that practices earnings management. However, when applying the logistic regression technique, there are two ratios, namely cash/total deposits and the creditors/total debts ratio, in which there is earnings management in private Iraqi banks. Accountants should continuously increase their knowledge and experience through training and continuing education to prepare themselves for greater responsibility in achieving the Sustainable Development Goals.
This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used
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The research aims to identify the role of scientific planning of inventory by determining the quantity of economic demand and the number of times of purchase and associated annual total costs to achieve a sufficient and appropriate level of inventory . The research was based on the case study methodology. Materials of increasing demand in the Institute of Technical Management and knowledge of the degree of conformity of the procurement plan with the standard indicators adopted in a scientific method ,its include economic order quantity and number of purchasing times .
one of The main results of the research was the existence of a large difference between the quantity of the economic purchase of ea
This work presents a five-period chaotic system called the Duffing system, in which the effect of changing the initial conditions and system parameters d, g and w, on the behavior of the chaotic system, is studied. This work provides a complete analysis of system properties such as time series, attractors, and Fast Fourier Transformation Spectrum (FFT). The system shows periodic behavior when the initial conditions xi and yi equal 0.8 and 0, respectively, then the system becomes quasi-chaotic when the initial conditions xi and yi equal 0 and 0, and when the system parameters d, g and w equal 0.02, 8 and 0.09. Finally, the system exhibits hyperchaotic behavior at the first two conditions, 0 and 0, and the bandwidth of the chaotic
... Show MoreMetaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char
... Show MoreThis research aims to demonstrate the knowledge pillars of the product life cycle assessment technique and how to measure the cost according to this technique, and to clarify its role in reducing costs, improving product quality and optimizing the use of available resources, and a set of results has been reached, the most important of which are: The separation of environmental costs through the use of product life cycle assessment technique helps the Management in handling the increase of these costs, reducing the rates of environmental pollution and preserving resources, which contributes to achieving the sustainability of the product, and based on the results obtained, a set of recommendations were presented, the most important of which w
... Show MoreAttention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w
... Show MoreThe study aims to verify the independence of auditors working in companies and offices of the Iraqi audit, and measure the level of accounting conservatism in the financial statements of banks and insurance companies listed on the Iraq Stock Exchange, as well as a statement after the independence of the auditor on accounting conservatism in the financial statements of banks and insurance companies listed on the market Iraq Stock Exchange, as it has been measuring the independence of the auditor using the survey form was auditors working in the Iraqi audit firms were measured the level of accounting conservatism for companies sample using a form( Basu) was a statement after variables through the use of statistical models in a mann
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