This research dealt with shedding light on the nature of material misrepresentations, in addition to knowing the extent to which the quality of accounting information systems contributes to reducing material misrepresentations On the theoretical side, a number of sources were relied upon in dealing with the research problem and presentation of the topic, while in the practical side, it was relied on the questionnaire form, where the research sample was (accountants and auditors), where 50 forms were distributed and 50 were received, and the data was analyzed and hypotheses tested through the program Statistical spss to show the relationship between the variables. The research reached a number of conclusions, the most important of which is the accounting information system works to reduce the cases of fraud and error that the accounting information is exposed to.
Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University
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Cantilever beams are used in many crucial applications in machinery and construction. For example, the airplane wing, the microscopic probe for atomic force measurement, the tower crane overhang and twin overhang folding bridge are typical examples of cantilever beams. The current research aims to develop an analytical solution for the free vibration problem of cantilever beams. The dynamic response of AISI 304 beam represented by the natural frequencies was determined under different working surrounding temperatures ((-100 ℃ to 400 ℃)). A Matlab code was developed to achieve the analytical solution results, considering the effect of some beam geometrical dimensions. The developed analytical solution has been verified successful
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The aim of this research is to adopt a close range photogrammetric approach to evaluate the pavement surface condition, and compare the results with visual measurements. This research is carried out on the road of Baghdad University campus in AL-Jaderiyiah for evaluating the scaling, surface texture for Portland cement concrete and rutting, surface texture for asphalt concrete pavement. Eighty five stereo images of pavement distresses were captured perpendicular to the surface using a DSLR camera. Photogrammetric process was carried out by using ERDAS IMAGINE V.8.4. The results were modeled by using a relationship between the photogrammetric and visual techniques and selected the highest coefficient of determination (R2). The first techniqu
... Show Moreهدفت الدراسة الحالية الى التعرف ما اذا كان هناك تقبل اجتماعي للتلاميذ بطيئي من قبل اقرانهم العاديين؟ وكذلك معرفة ما اذا كان هناك فروق ذات دلالة في التقبل الاجتماعي بين افراد عينة الدراسة على وفق المتغيرات الاتية:
أ- العمر (9-13)
ب- الجنس (ذكور –اناث)
ج- المرحلة الدراسية
د- الحالة الاقتصادية (جيدة –متوسطة –جيدة جدا)
ولغرض تحقيق اه
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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Stroke is the second largest cause of death worldwide and one of the most common causes of disability. However, several approaches have been proposed to deal with stroke patient rehabilitation like robotic devices and virtual reality systems, researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. In this study, the electroencephalography (EEG) dataset from post-stroke patients were investigated to identify the effects of the motor imagery (MI)-based BCI therapy by investigating sensorimotor areas using frequency and time-domain features and to select particular methods that help in enhancing the MI-based BCI systems for stroke patients using EEG signal processing. Therefore, to detect
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Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.
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Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras
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