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,

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

This research shows the problem of the economic development of underdeveloped countries in an unconventional way, as these papers explain the problems of the economic development. This research not only reviews the problems, but it illustrates them in a philosophical way, basis of the data of modernity, this mean it is a process of connecting between the absence of the modernity values and the failure of development in underdeveloped countries. The Search follows the descriptive approach to get to the goal of search by four main axes. The first axis includes clarifying  modernity and its principles, the second axis includes clarifying the economic development , the third axis includes the features of the mod

Worldwide, there is an increased reliance on COVID-19-related health messages to curb the COVID-19 outbreak. Therefore, it is vital to provide a well-prepared and authentic translation of English-language messages to reach culturally and linguistically diverse audiences. However, few studies, if any, focus on how non-English-speaking readers receive and linguistically accept the lexical choices in the messages translated into their language. The present study tested a sample of translated Arabic COVID-19-related texts that were obtained from the World Health Organization and Australian New South Wales Health websites. This study investigated to that extent Arabic readers would receive translated COVID-19 health messages and whether the t

The reality of teaching the Arabic language rules is not satisfactory, as the pedagogical methods used do not help students develop their mental skills, especially critical thinking skills. They are often traditional in terms of teaching students, who are passive, passive, often passive, active, and often active, their listening task, and the teacher's task of narrating facts and judgments. It is a blind simulation student, a dependency on others, and a weak spirit of creativity, innovation, and opinion. The opinions of educators and teachers almost agree on the reasons for students' weakness in learning the rules of Arabic, and that the reason lies in the way of teaching. The difficulty or the ease of the rules of Arabic does not lie in th

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

The study aimed to achieve the following: Developing comprehensive quality standards for evaluating the curricula of Arabic Language Departments in Colleges of Education at Iraqi universities. Evaluating the curricula of Arabic Language Departments in light of comprehensive quality standards. The study was delimited to: The Arabic language curricula—namely (grammar, morphology, literature, rhetoric, criticism, and prosody)—taught in Arabic Language Departments across their four academic years for the academic year (2010/2011). Arabic Language Departments in Colleges of Education at Iraqi universities (Baghdad, Diyala, Mosul, Basra, and Babylon). Faculty members of Arabic Language Departments in Colleges of Education at Iraqi universitie

Considering the expanding frequency of breast cancer and high incidence of vitamin D3 [25(OH)D3] insufficiently, this investigate pointed to explain a relation between serum [25(OH)D3] (the sunshine vitamin) level and breast cancer hazard. The current study aimed to see how serum levels of each [25(OH)D3], HbA1c%, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were affected a woman’s risk of getting breast cancer. In 40 healthy volunteers and 69 untreated breast cancer patients with clinical and histological evidence which include outpatients and hospitalized admissions patients at the Oncology Center, Medical City / Baghdad - Iraq. Venous blood samp