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.
This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
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The research aims to shed light on the ethics of information systems and their role in achieving banking excellence for a sample of private banks in the province of Baghdad. It is important to focus on studying the ethics of banking information systems, which has become one of the most important basic and strategic resources that banks rely on to achieve outstanding performance. Achieving banking leadership in the Iraqi banking market. The researchers adopted the descriptive analytical approach to the research, and the questionnaire was considered as a main tool for collecting information in addition to personal interviews. The research reached the most important results that there is an acceptable correlation relationship between the ethic
... Show MoreThe contemporary development applications on scientific areas of acyclic and cyclic Schiff bases and their complexes.
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Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.
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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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Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad
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The term "semantic exchange" was popularized in Arabic, especially in derivatives, grammatical structures, etc., but it came under different names or terms, including deviation, deviation, transition, displacement, tooth breach, replacement, attention, etc. In the rooting of this term through its study in language and terminology, and among linguists, grammar and others, we have reached a number of results, including The existence of a harmonization between the lexical and idiomatic meaning of the term exchange, and the phenomenon of semantic exchange is a form of expansion in language, and that the first language scientists They had turned to this And studied under Cairo for different names, as noted above.
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Translating the Qur’anic real meaning into other languages is considered to be a unique challenge as it is deeply rooted in Arabic culture and language. Thus, this operation often loses the rhetoric and poetic beauty of the Qur’anic text, hindering a deep understanding of its spiritual and moral significance. This study constitutes a part of a comparison study of certain kinship terms in Qur’anic Arabic' abawayn / wâlidayn, zawj / ba'al, and imra’a / zawj / ṣaẖiba and their equivalents in French and English versions. It is actually about providing some details on these Arabic terms and their equivalents by examining how they have been used in the Qur’anic context to indicate specific meaning. It is divided into two main parts
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