Censure in poetry is a pattern of poetic construction, in which the poet evokes a voice other than his own voice or creates out of his own self another self and engages with him in dialogue in the traditional artistic style whose origin remains unknown. Example of the same may be found in the classical Arabic poets’ stopping over the ruins, crying over separation and departure and speaking with stones and andirons; all in the traditional technical mould. Censure confronting the poet usually emanates from the women as blaming, censure and cursing is closer to woman’s hearts than to the man’ hearts. Censure revolves around some social issues, such as the habit of over drinking wine and extravagant generosity taking risks, traveling,

Abstract of the research:

     This research sheds light on an important phenomenon in our Arabic language, which is linguistic sediments, and by which we mean a group of vocabulary that falls out of use and that native speakers no longer use it, and at the same time it happens that few individuals preserve the phenomenon and use it in their lives, and it is one of the most important phenomena that  It should be undertaken and studied by researchers;  Because it is at the heart of our huge linguistic heritage, as colloquial Arabic dialects retain a lot of linguistic sediments, and we usually find them at all levels of language: phonetic, banking, grammatical and semantic.  In the

Providing stress of poetry on the syllable-, the foot-, and the phonological word- levels is one of the essential objectives of Metrical Phonology Theory. The subsumed number and types of syllables, feet, and meters are steady in poetry compared to other literary texts that is why its analysis demonstrates one of the most outstanding and debatable metrical issues. The roots of Metrical Phonology Theory are derived from prosody which studies poetic meters and versification. In Arabic, the starting point of metrical analysis is prosodic analysis which can be attributed to يديهارفلا in the second half of the eighth century (A.D.). This study aims at pinpointing the values of two metrical parameters in modern Arabic poetry. To

Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject

The article provides a comparative analysis of comparisons in Russian and Arabic, aimed at identifying their structural, typological, and functional-pragmatic features. The study is based on a systematic approach to the analysis of linguistic means of expressing comparisons in two differ- ent linguistic cultures. The article analyzes the main structural components of comparisons, their classification, and their cognitive and aesthetic functions. The results of the study demonstrate the deep cultural conditioning of comparative constructions and their important role in representing the specific features of the respective linguistic cultures.

The concept of Cech fuzzy soft bi-closure space ( ˇ Cfs bi-csp) ( ˇ U, L1, L2, S) is initiated and studied by the authors in [6]. The notion of pairwise fuzzy soft separated sets in Cfs bi-csp is defined in this study, and various features of ˇ this notion are proved. Then, we introduce and investigate the concept of connectedness in both Cfs bi-csps and its ˇ associated fuzzy soft bitopological spaces utilizing the concept of pairwise fuzzy soft separated sets. Furthermore, the concept of pairwise feebly connected is introduced, and the relationship between pairwise connected and pairwise feebly connected is discussed. Finally, we provide various instances to further explain our findings.

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz