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Artificial Intelligence Applications in Machine Translation and Their Role in Bridging Semantic Gaps Across Languages: A Comparative Analytical Study of Chat GPT and Deep Seek
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With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual and cultural quality. Our results show that our model, ChatGPT, consistently achieves performance gains over DeepSeek, especially when applied to technical and journalistic text and with higher BLEU scores and lower TER values. But neither these models nor any of the state-of-the-art models perform well for the literary texts, the ones that can hint to the difficulties these models face to deal with idiomatic expressions, metaphor, narrative tone. The results illustrate genre sensitivity in AI translation quality and emphasize the ongoing importance of human supervision, particularly in cultural and stylistic contexts. This work aims to contribute to the growing corpus of AI translation literature by providing a genrespecific, empirically grounded comparison of two of the most highprofile models, and to draw attention to the necessity of greater context-sensitive and culturally sensitive translation algorithms.

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Sun Jan 08 2023
Journal Name
Journal Of Planner And Development
Lebanese building law between texts, Application gaps and land scarcity
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This paper examines the gaps in Lebanese building law as well as the exploitation of contractors, stakeholders, and residents in order to make illegal profits at the expense of The Shape of urban agglomerations and their expansion in cities and rural areas, which is contrary to the principles of sustainable land development. It also emphasizes the amplification of the factors of vertical and horizontal building investments in the implementation of buildings contrary to the license, as well as the burden that this places on the city's resulting infrastructure and ability to absorb the activities and needs of its residents. The study then presents recommendations in the process of transformation in the technique of planning and application

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The reality of corporate tax and its role in the tax Revenues in Iraq: An analytical study for the years 2005-2010
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This study showed the basic features of corporate tax in Iraq by showing what was in the Income Tax Law in force .The study aims of this to indicate the role of tax corprates in tax revenue and then the possibility of strengthening the revenue of this tax as an important source of local funding sources in the form that is with him reduce dependence on oil revenues to finance the general budget in Iraq, the risks and the study found a number of conclusions from the most important: that the corporate tax comes in the introduction to the components of the income tax structure in terms of relative importance and formed a revenue source of prime The gross proceeds of the income tax in Iraq, where it contributed to more than a quarter of that

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Wed Apr 01 2026
Journal Name
كلية العلوم السياسية / جامعة الموصل / مؤتمرها العلمي الدولي الخامس والسنوي
The state's Orientation towards using sustainable electrical energy with the contribution of Artificial Intelligence (AI) / Geothermal energy As a model / contributes to strengthening the building of a future the state's strength "A study in political geography"
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المستخلص: هناك مشكلة تعاني منها الدولة وهي الأعتماد على الطاقات التقليدية الملوثة Abstract: The country suffers from a problem which is the reliance on traditional polluting and non-renewable energies and the failure to discover and exploit sustainable sources such as geothermal energy. The research hypothesis is whether the modern state’s orientation towards exploiting a modern energy source such as geothermal energy contributes in some way to achieving another source of energy and benefiting from it to enhance the building of a new type of state power from buried energy sources? And does artificial intelligence technology contribute to solving a specific problem by exp

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Publication Date
Tue Sep 30 2025
Journal Name
المجلة العراقية للعلوم السياسية
Spy vs.AI How Artificial Intelligence Will Remake Espionage
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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Transformational leadership and its role in organizational success An analytical study of the views of a sample of employees at the Faculty of Education, Samarra University
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This research aims to know the role of transformational leadership in the organizational success of the College of Education at Samarra University. The researcher adopted the analytical descriptive method in analyzing the research problem. The research included two main hypotheses that resulted in four hypotheses that were subjected to statistical tests. A sample of (54) The researcher used the survey method as a main tool for collecting data and information as well as visits and structured interviews that took place during the period of application. The research reached a set of conclusions and recommendations among the conclusions that there is an art relationship There is a strong and moral impact between transformational lead

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
The role of Matrix metalloproteinase (MMP-9) and its tissue inhibitor (TIMP1) in Cutaneous Leishmaniasis patients and their role in prognosis
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Cutaneous leishmaniasis (CL) is a widespread, yet often overlooked, parasitic disease caused by the Leishmania protozoan, which is prevalent in numerous countries, including Iraq. This condition is marked by the appearance of skin lesions on various exposed areas of the body. In most old-world regions, sodium stibogluconate (SSG) is the classical widely used drug to treat CL. The progression of skin ulceration is controlled by different inflammatory modulators including cytokines and enzymes. In this study, the possible role of the enzyme Matrix metalloproteinase9 (MMP-9) and its inhibitor Metallopeptidase inhibitor-1 (TIMP-1) as immunological markers was evaluated in CL patients suffering from cutaneous leishmaniasis before and aft

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Thu Aug 01 2024
Journal Name
The American Journal Of Management And Economics Innovations
THE ROLE OF ECONOMIC DATA ANALYSIS IN MANAGING MEDIUM AND SMALL COMPANIES TO MAKE STRATEGIC DECISIONS AND IMPROVE PERFORMANCE: AN ANALYTICAL STUDY
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Economic analysis plays a pivotal role in managerial decision-making processes. This analysis is predicated on deeply understanding economic forces and market factors influencing corporate strategies and decisions. This paper delves into the role of economic data analysis in managing small and medium-sized enterprises (SMEs) to make strategic decisions and enhance performance. The study underscores the significance of this approach and its impact on corporate outcomes. The research analyzes annual reports from three companies: Al-Mahfaza for Mobile and Internet Financial Payment and Settlement Services Company Limited, Al-Arab for Electronic Payment Company, and Iraq Electronic Gateway for Financial Services Company. The paper concl

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