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Using Artificial Intelligence and Metaverse Techniques to Reduce Earning Management
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This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of data, cost savings, and the pace of business completion. Therefore, relying on auditing a large volume of financial data is insufficient. The Metaverse is a novel technological advancement seeking to fundamentally transform corporate operations and interpersonal interactions. Metaverse has implications for auditing and accounting practices, particularly concerning a company’s operational and financial aspects. Economic units have begun to switch from traditional methods of registration and posting to using software for financial operations to limit earnings management. Therefore, this research proposes applying one of the Data Mining techniques, namely the logistical regression technique, to reduce earning management in a sample of Iraqi private banks, including (11) banks. Accounting ratios were employed, followed by Logistic Regression, to achieve earnings management within the proportions.

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Publication Date
Thu Aug 07 2025
Journal Name
Journal Of Image And Graphics
Analysis Evolution of Image Caption Techniques: Combining Conventional and Modern Methods for Improvement
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This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod

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Publication Date
Sat Aug 10 2024
Journal Name
Full Text Book Of Istanbul Congress 7
NARRATIVE TECHNIQUES AND THEIR APPLICATIONS IN ANDALUSIAN MAQAMAT/ EID MAQAMAT AS AN EXAMPLE
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Publication Date
Sun Oct 22 2023
Journal Name
مجلة الدراسات المستدامة
Strategies, Techniques and Activities Used by English Language Teachers in Employing Online Teaching
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Publication Date
Sun Jan 01 2017
Journal Name
Research Journal Of Pharmacy And Technology
Estimating the plain and negative tendonography techniques for evaluating injured tendon in rabbit
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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Wed Mar 15 2023
Journal Name
Al-academy
The Developed Materials and Techniques and Its Role in Exposing the Aesthetic Of Art Work
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This study is targeting the new developed materials and techniques and how they were affected by the scientific and technological developments that contributed to revelated new and varied developed materials and techniques. And from the artist’s formulation by using the materials and techniques and through its embodiment and sensor the values, artistic and aesthetic standards by breaking from the familiar in aesthetic contemporary way.
The studies on questioning what’s the role of The New Developed Materials and Techniques in exposing the aesthetic of the art work?

This study is to show the aesthetic of the art work through the new developed materials and techniques. Which was based on descriptive analyzing method and hig

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Publication Date
Fri Nov 29 2024
Journal Name
Chemical Engineering Research And Design
Comprehensive review of severe slugging phenomena and innovative mitigation techniques in oil and gas systems
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of The College Of Education For Women
Knowledge Management at Kindergartens Managers
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The task of an educational institution such as kindergartens need to run by managers possess the knowledge to manage the administration of the importance in the development of kindergarten has been the goal of research to identify knowledge management at Riyadh managers, and achieve the objectives of Search selected sample of directors of kindergartens in the city of Baghdad was (160) director was Akhtarhn simple random way, been building measure for knowledge management and presented to the group of experts and extracted stability in a way re-testing and Alvakronbach and reach search to a discrepancy between managers Riyadh in knowledge management and put the researcher set of recommendations including the establishment of seminars and

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Publication Date
Sun Jan 01 2017
Journal Name
Professional Safety
Technology’s role in Safety Management
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