Standards of audit have been defined issued them by professional organizations the audit risk is: Failure of the auditor inadvertently to amend his opinion on the financial statements in suitable method, although these statements are Interpolated Essentially. As result the deep impacts caused by electronic operating systems in the accounting data in the audit process which audit risk has gained attention of many professional sides, especially the audit process and quality is relating with level of discovery the auditor for the mistakes of origin (misrepresentations) all their types and give the necessary confidence for the auditor to express his technical opinion in fidelity and certified financial statements which prepared electronicall

الملخص: لتحقيق أهداف البحث قامت الباحثة اعداد مقياس التلكؤ الاكاديمي اعتمادا على نظرية (باندورا) وتكون المقياس بصورته النهائية من (21) فقرة ، وطبق المقياس على عينة البحث البالغة (100) طالب وطالبة تم اختيارهم بالطريقة العشوائية البسيطة من مجتمع البحث ،وبعد جمع البيانات تم معالجتها باستعمال الوسائل الإحصائية المناسبة، توصل البحث الى النتائج الأتية : الى ان الطلبة ليس لديهم تلكؤ اكاديمي و اعلى من المتوسط، لا توج

أن الغرض من هذه الدراسة هو التحليل الهيكلي لبنية مقياس الصحة النفسية لطلبة الجامعة الذي طورته الجنابي (1991) باستخدام التحليل العاملي. إن 66 طالبا و95 طالبة من كلية التربية في الجامعة المستنصرية قد استجابوا لفقرات المقياس. وقد أظهر التحليل العاملي وجود خمسة عوامل فسرت 30% من التباين, وان هذه العوامل هي الإستقرار العائلي، والأمن الاقتصادي، والمسؤولية الإجتماعية، وتقدير الذات، والأمن النفسي.

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

    Coral reef area in northwest of the Arabian Gulf was investigated for mineralogy and geochemistry to throw lights on such unique Iraqi Marine Environment; six specimens of two main species of coral reefs, Platygyra pini Chevalier, 1975 and Octocoral Menella were collected at two sites. While eight samples of the surrounding sediments are chosen from other two sites. The mineralogy is determined by XRD, and reveals that calcite, low magnesium-calcite, and aragonite are the main minerals that comprise the Octocoral Menella in site 1, whilst aragonite and calcite are dominate in the P. pini coral reef at site 4.

    The non–carbonate fractions indicate that thes