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Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certainly visible. This criterion was used on the dataset for ANN learning to compare its efficiency with the actual moon visibility events.

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Hydrology
Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology
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Publication Date
Mon Jan 01 2024
Journal Name
Studies In Systems, Decision And Control
The Effect of Using an Accounting Information System Based on Artificial Intelligence in Detecting Earnings Management to Enhance the Sustainability of Economic Units
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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 researche

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Publication Date
Wed Sep 20 2017
Journal Name
Mechanical Sciences
Comparative experimental investigation and gap flow simulation in electrical discharge drilling using new electrode geometry
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Abstract. This study presents experimental and numerical investigation on the effectiveness of electrode geometry on flushing and debris removal in Electrical Discharge Drilling (EDD) process. A new electrode geometry, namely side-cut electrode, was designed and manufactured based on circular electrode geometry. Several drilling operations were performed on stainless steel 304 using rotary tubular electrodes with circular and side-cut geometries. Drilling performance was characterized by Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Tool Wear Ratio (TWR). Dimensional features and surface quality of drilled holes were evaluated based on Overcut (OC), Hole Depth (HD), and Surface Roughness (SR). Three-dimensional

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Publication Date
Wed Dec 25 2024
Journal Name
الذكوات البيض
Artificial Intelligence and its Impact on Education and Media
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Abstract Objectives: This research seeks to highlight one of the important topics artificial intelligence and its impact on education and media. This issue has received considerable attention from international institutions and organizations in order to keep pace with the world's current progress. The study provided an overview of the concept of artificial intelligence, its definitions, its importance and characteristics and its impact on education in general and on the student and teacher in particular, as well as linking the subject of education to the media because social media that is one of the media has a great impact on the academic community. Methods: This study relied on the analytical descriptive curriculum where one of the curr

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
FINITE ELEMENT ANALYSIS OF HUMAN AND ARTIFICIAL ARTICULAR CARTILAGE
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Joint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerative
conditions, this three-dimensional finite element model is a useful tool for understanding of the stress d

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Publication Date
Tue Dec 31 2024
Journal Name
Frontiers In Health Informatics
The Implementation Of Artificial Intelligence In Education: Systematic Analysis
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Background: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-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

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Publication Date
Sun May 08 2011
Journal Name
Journal Of Planner And Development
the reality of the transportation network in Iraq
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Transportation network could be considered as a function of the developmental level of the Iraq, that it is representing the sensitive nerve of the economic activity and the corner stone for the implementation of development plans and developing the spatial structure.
The main theme of this search is to show the characteristics of the regional transportation network in Iraq and to determine the most important effective spatial characteristics and the dimension of that effect negatively or positively. Further this search tries to draw an imagination for the connection between network as a spatial phenomenon and the surrounded natural and human variables within the spatial structure. This search aiming also to determine the nat

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Publication Date
Sat Jan 01 2011
Journal Name
Trends In Network And Communications
Header Compression Scheme over Hybrid Satellite-WiMAX Network
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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Modified W-LEACH Protocol in Wireless Sensor Network
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In this paper, a Modified Weighted Low Energy Adaptive Clustering Hierarchy (MW-LEACH) protocol is implemented to improve the Quality of Service (QoS) in Wireless Sensor Network (WSN) with mobile sink node. The Quality of Service is measured in terms of Throughput Ratio (TR), Packet Loss Ratio (PLR) and Energy Consumption (EC). The protocol is implemented based on Python simulation. Simulation Results showed that the proposed protocol provides better Quality of Service in comparison with Weighted Low Energy Cluster Hierarchy (W-LEACH) protocol by 63%.

  

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