Tax fraud is following different methods of tax evasion (bypassing the laws, instructions and regulations related to tax) by not showing the real taxable income by using laws, instructions and regulations improperly, and because of the weak basic role of forensic accounting in detecting and reducing tax fraud, the problem has become more influential on the state general tax income. The main objective of the research is to identify forensic accounting and the extent to how it can be applied in the General Tax Authority to assist forensic authorities in issuing judgments in fraud cases. To achieve the objectives of the research, the descriptive analytical approach was used to reach the topic of the research, and a questionnaire (co

Abstract:

The aim of the research is to demonstrate the impact of the professional specialization of the audit companies in the detection of fraud in the financial statements of the economic units listed in the Iraqi market for securities for the period 2014-2015 through the application of the model (Carcello) to test the hypothesis of research on the impact of professional specialization of audit companies in the detection of fraud in lists The effect of the variables was revealed through the use of statistical models of logistic regression model and correlation coefficient. After testing the hypotheses of the research, a number of conclusions were reached. The most important was the existence of a signi

The research deals with an analytical approach between new media and traditional one in the light of the changes imposed by technology, which has been able to change a number of common concepts in the field of communication and media. The researcher tries to find an analytical explanation of the relationship between technology by being an influential factor in building the information society, which is the basis of new media, and the technical output that influenced the forms of social relations and linguistic construction as a human communication tool. The research deals with an analytical approach between new media and traditional one in the light of the changes imposed by technology, which has been able to change a number of comm

The concept of employees voice has received a great deal of attention by researchers in the field of organizational behavior and human resources management especially in the last three decades of the twentieth century , this importance has deep ranges limits in terms of its discussion history, so it became a behavioral variable received a great attention and care in managerial and organizational studied and basic pillar in the success and excellence of organizations in maintaining its human resources, the research explain the concept and benefits of paying attention to the voice of employees in business organizations , and the theories interpreted to employees voicing and clearing the motivations behind employees voicing, and dis

Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t

In this work, a fiber-optic biomedical sensor was manufactured to detect hemoglobin percentages in the blood. SPR-based coreless optical fibers were developed and implemented using single and multiple optical fibers. It was also used to calculate refractive indices and concentrations of hemoglobin in blood samples. An optical fiber, with a thickness of 40 nanometers, was deposited on gold metal for the sensing area to increase the sensitivity of the sensor. The optical fiber used in this work has a diameter of 125μm, no core, and is made up of a pure silica glass rod and an acrylate coating. The length of the fiber was 4cm removed buffer and the splicing process was done. It is found in practice that when the sensitive refractive i