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Artificial Intelligence Applications for Achieving Economic Stability and Sustainable Growth in the Modern Era
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In recent years, the steady stream of artificial intelligence into economic systems has become a torrent. It is changing how we generate wealth and grow anew. Manufacturing, finance, health care energy, agriculture and education are just a few of the areas where AI may result in dramatic increases in productivity as well as innovation and sustainability. Predictive analytics, AI, robotics and natural language processing have significantly contributed in the improvement of resource allocation mechanisms and decision making as well as reaching SDGs. The concept of Artificial Humanity is also introduced in the paper. It shows how AI could become a global cognitive network to foster knowledge. By comparison and references of the literature, this paper has shown the function of AI in economic diversity transformation and sustainable growth.

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Development of Iraqi License Plate Recognition System based on Canny Edge Detection Method
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny

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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Engineering
Influence of Using Various Percentages of Slag on Mechanical Properties of Fly Ash-based Geopolymer Concrete
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In order to implement the concept of sustainability in the field of construction, it is necessary to find an alternative to the materials that cause pollution by manufacturing, the most important of which is cement. Because factory wastes provide siliceous and aluminous materials and contain calcium such as fly ash and slag that are used in the production of high-strength geopolymer concrete with specifications similar to ordinary concrete, it was necessary for developing this type of concrete that is helping to reduce CO2 (dioxide carbon) in the atmosphere. Therefore, the aim of this study was to study the influence of incorporating various percentages of slag as a replacement for fly ash and the effect of sl

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Wed Apr 01 2026
Journal Name
Case Studies In Construction Materials
Performance Evaluation of Modified Hard-Grade Asphalt Binder Using Waste PVC Derived from Flex Banners
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Hard-grade asphalt binders, such as AC 20–30, offer excellent resistance to permanent deformation but are inherently brittle, making them highly susceptible to fatigue and low-temperature cracking. While polymer modification addresses these issues, virgin polymers remain expensive. Despite the growing interest in recycled plastics, the rheological impact of complex waste streams, specifically polyvinyl chloride (PVC) derived from flex banners containing plasticizers, on excessively stiff binders within the complete Superpave Performance Grading (PG) framework remains critically underexplored. This study introduces a novel valorization approach by utilizing solvent-extracted flex banner waste (WPVC) as a dual-action modifier. It leverages

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Publication Date
Fri Nov 01 2019
Journal Name
Iop Conference Series: Earth And Environmental Science
Seed priming of sorghum cultivars to tolerate salt stress
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A laboratory experiment was carried out in the laboratories of College of Agricultural Engineering Sciences, University of Baghdad in 2017. Three factors were studied; Sorghum bicolor L. cultivars (Inqath, Rabeh and Buhoth70), primed and unprimed seed, and salt stress (0, 6, 9 and 12 dS.m−1). The aim was to improve germination and seedling growth under salt stress. The results showed significant superiority of Buhoth70 cultivar compared to others, significantly superiority of primed seed compared to the unprimed and significant negative impact as long as increasing levels of salt stress at germination ratio, plumule length, dry seedling weight and seedling vigor index. The interaction between cultivars, priming and salt stress showed that

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Publication Date
Mon Sep 20 2021
Journal Name
Key Engineering Materials
Effect of Partial Substitution of Sr by Ba on the Structural Properties of Tl<sub>0.8</sub>Ni<sub>0.2</sub>Sr<sub>2-x</sub>Br<sub>x</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>9-δ</sub> System
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In this manuscript, the effect of substituting strontium with barium on the structural properties of Tl0.8Ni0.2Sr2-xBrxCa2Cu3O9-δcompound with x= 0, 0.2, 0.4, have been studied. Samples were prepared using solid state reaction technique, suitable oxides alternatives of Pb2O3, CaO, BaO and CuO with 99.99% purity as raw materials and then mixed. They were prepared in the form of discs with a diameter of 1.5 cm and a thickness of (0.2-0.3) cm under pressures 7 tons / cm2, and the samples were sintered at a constant temperature o

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
التطورات العالمية وانعكاساتها على تنافسية الصناعة في العراق دولياً - بحث نظري
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خلال الربع الأخير من القرن العشرين ، شهد الاقتصاد العالمي تحولا في مختلف المجالات التجارية والتكنولوجية والمالية التي غيرت هيكلها وأنتجت وضعا جديدا يتمثل بشكل رئيس في زيادة حركة رأس المال الأجنبي والتوسع السريع للإنتاج الدولي والتجارة بالإضافة إلى التطور التكنولوجي الهائل ونقل التكنولوجيا ، مما أدى إلى هوس الدول بالمنافسة على المستوى العالمي والسعي لدخول الأسواق الدولية وتحسين قدرتها التنافسية. وت

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Publication Date
Fri Nov 21 2025
Journal Name
Journal Of Advances In Information Technology
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata
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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
أثـر الأدوات الداخلية لحوكمة الشركة على رأس المال الـعـامـل وانعكاسهما علـى القيـمـة الاقتصـادية المضـافـة: دراســة تطبيقيـة علـى عينــة مـــن الشـركــات الصنــاعــيــة المـدرجــة في بورصــة عـمّــان لــلأوراق المـالـيـة
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Abstract

Objective of this research focused on testing the impact of internal corporate governance instruments in the management of working capital and the reflection of each of them on the Firm performance. For this purpose, four main hypotheses was formulated, the first, pointed out its results to a significant effect for each of corporate major shareholders ownership and Board of Directors size on the net working capital and their association with a positive relation.  The second, explained a significant effect of net working capital on the economic value added, and their link inverse relationship, while the third, explored a significant effect for each of the corporate major shareholders ownershi

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