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.
The study aims to build a model that revolves around the main question of the role of strategic agility (SA) in enhancing organizational excellence (OE). For the purpose of achieving OE and to determine the extent of interest and knowledge of managers at the Midwest Refineries Company (MRC) on the theoretical and practical implications, and on the performance foundations of these two vital variables with the aim of continuous improvement. A questionnaire was used and distributed to a random sample of 54 managers in this important energy production company. The study followed the descriptive analytical approach to answer the questions raised. The study model and dimensions were built according to reference models, most notably the mo
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The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p
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The research problem arose from the researchers’ sense of the importance of Digital Intelligence (DI), as it is a basic requirement to help students engage in the digital world and be disciplined in using technology and digital techniques, as students’ ideas are sufficiently susceptible to influence at this stage in light of modern technology. The research aims to determine the level of DI among university students using Artificial Intelligence (AI) techniques. To verify this, the researchers built a measure of DI. The measure in its final form consisted of (24) items distributed among (8) main skills, and the validity and reliability of the tool were confirmed. It was applied to a sample of 139 male and female students who were chosen
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In spite of the disappearing of a clear uniform textbook for teaching ESP at different departments and different colleges in both scientific and humanistic studies, the practitioners at those departments and colleges have to teach translation as one of the important requirements to pass the English language exam. The lack of defined translation activities is a noticeable problem therefore; the problem of teaching translation is diagnosed in that the students lack the ability to comprehend the text in English language and other translation knowledge and skills.
The study aims to suggest a translation strategy and then find out the effect of the translation strategy on ESP learners’ achievement in translation. A sample of 50 stud
... Show MoreThis study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin
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The primary goal of root canal treatment (RCT) is to expel the presence of any necrotic or vital tissue, microbes and their byproducts from the canal space before press forward with the following steps of the RCT procedures. Although this is difficult to attain, various strives had been practiced by employing chemical and mechanical methods to eliminate as much microorganisms as possible and make the canal space valid for the obturation materials to be received. The aim of this review is to demonstrate some of what new remedies that could be used as root canal disinfectant by summarizing the recent studies regarding the efficacy of different natural products against the most persistence microbiota that could be responsible for most
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This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b
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