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The search of the things that accused him of Imam Hassan (peace be upon him) by Almstherquan (Lammens and Ntnj) as a personal spineless, he went to the pleasures and desires and then died of Asrafh them, and we studied their stories without any intolerance and spasm, and turned out to be marked by prejudice on Imam Hassan ( peace be upon him), but it is a matter of research diagnosis of the reasons that pushed Palmstcherqan to follow this approach, and can these reasons be classified into two categories: the first regards the Muslims themselves and the second is due to the Orientalists and were carrying the ideas may be pre-Islam or that it resulted from a misunderstanding or malice, or their return to the Umayyad novels. Imam Hassan did not have (peace be upon him) droopy, but the problems he faced at the beginning of his successor, at a time when Sid had dominated the Levant for many years at a time and reached Imam Hassan conditions (peace be upon him) to the extent dared some army commanders and escape to Sid, others dared to led the attack on his tent and pulled the place where he prayed beneath him, and dragged him from his shirt and injured him in such circumstances were not the Imam Hassan (peace be upon him) any way but to accept the Magistrate, however it was the conditions if carried out by Mu'awiya was a victory of Imam Hassan (AS peace), and was able to Imam Hassan (peace be upon him), this policy and measure Alaklaia In such sensitive circumstances to keep the egg Islam, and the failure of those who they want to demolish Islam by attacking Imam Hassan policy (peace be upon him) the wise, and God knows where he makes his message.

This study revisits the process of vowel lowering in the Arabic dialect known as Qeltu, which is spoken in parts of northern Iraq and neighboring Syria and Turkey. It aims to uncover hitherto unreported patterns of vowel lowering and re-examines a frequently held axiom that attributes a categorical impact of specific linguistic units on the behavior of this phonological process (e.g. Al-Ani, 1970; Thelwall, 1990; Rose, 1996). The analysis of spoken data from 30 speakers considers various linguistic and social constraints that may or may not influence the process of vowel lowering. The data was collected through sociolinguistic interviews (Tagliamonte, 2006). It is generally acknowledged that the main allophones of Iraqi Arabic [i], [iː], [uː] (Al-Khalesi, 2006) are respectively realized as [a], [ɛː], and [ɔː] in Qeltu (Jastrow, 1994 & 2006). This is especially noticeable when these vowels are adjacent to guttural sounds, as exemplified in the words: /miʃhuːr/ famous, /sˤtˤuːħ/ roof and /daqiːq/ flour, which are pronounced as [maʃhɔːr], [sˤtˤɔ:ħ] and [daqɛ:q], respectively (Jastrow, 1994; Muhammad, 2018). Results indicate that the relationship between guttural sounds and the lowering of vowels in Qeltu cannot be solely predicted by their proximity to each other, and that additional social factors are involved in determining this phenomenon.

Editorial Article

Significant scholarly interest has been focused on the use of AI in English as a Foreign Language (EFL) instruction because it presents novel opportunities for improving language learning contexts and pedagogical approaches. This study provides an in-depth investigation into how AI is revolutionizing English as a foreign language (EFL) instruction, with special focus on the ways in which this technology can help students acquire a language in a fun, engaging, and one-on-one setting. This research examines the ethical and sociological implications of the broad integration of AI technology into language learning environments, highlighting major trends and identifying critical gaps through a thorough literature assessment and bibliometric analysis. In order to advance the conversation and promote responsible AI integration in EFL classrooms, the findings stress the importance of addressing long-term efficacy and sustainability concerns, offering extensive pedagogical training for educators, and developing interdisciplinary collaborations. This study aids the expanding body of knowledge by clarifying the complex role that AI plays in EFL classrooms, providing direction for future studies, and paving the way for the creation of solid frameworks for the responsible application of AI in educational settings.

Abstract With the rapid growth of online content written in the Kurdish language, there is an increasing need to make it machine-readable and processable. Part of speech (POS) tagging is a critical aspect of natural language processing (NLP), playing a significant role in applications such as speech recognition, natural language parsing, information retrieval, and multiword term extraction. This study details the creation of the DASTAN corpus, the first POS-annotated corpus for the Sorani Kurdish dialect. The corpus, containing 74,258 words and thirty-eight tags, employs a hybrid approach utilizing the bigram hidden Markov model in combination with the Kurdish rule-based approach to POS tagging. This approach addresses two key problems that arise with rule-based approaches, namely misclassified words and ambiguity-related unanalyzed words. The proposed approach’s accuracy was assessed by training and testing it on the DASTAN corpus, yielding a 96% accuracy rate. Overall, this study’s findings demonstrate the effectiveness of the proposed hybrid approach and its potential to enhance NLP applications for Sorani Kurdish.

During the COVID-19 pandemic, medical imaging techniques like computed tomography (CT) scans have demonstrated effectiveness in combating the rapid spread of the virus. Therefore, it is crucial to conduct research on computerized models for the detection of COVID-19 using CT imaging. A novel processing method has been developed, utilizing radiomic features, to assist in the CT-based diagnosis of COVID-19. Given the lower specificity of traditional features in distinguishing between different causes of pulmonary diseases, the objective of this study is to develop a CT-based radiomics framework for the differentiation of COVID-19 from other lung diseases. The model is designed to focus on outlining COVID-19 lesions, as traditional features often lack specificity in this aspect. The model categorizes images into three classes: COVID-19, non-COVID-19, or normal. It employs enhancement auto-segmentation principles using intensity dark channel prior (IDCP) and deep neural networks (ALS-IDCP-DNN) within a defined range of analysis thresholds. A publicly available dataset comprising COVID-19, normal, and non-COVID-19 classes was utilized to validate the proposed model's effectiveness. The best performing classification model, Residual Neural Network with 50 layers (Resnet-50), attained an average accuracy, precision, recall, and F1-score of 98.8%, 99%, 98%, and 98% respectively. These results demonstrate the capability of our model to accurately classify COVID-19 images, which could aid radiologists in diagnosing suspected COVID-19 patients. Furthermore, our model's performance surpasses that of more than 10 current state-of-the-art studies conducted on the same dataset. 8 pages, 2 figures, The 1st International Conference on Electronic and Computer Engineering, Universiti Teknologi Malaysia, "accept"

Previous research has shown that both input quantity and quality play a role in dual language learning. However, it is unclear whether input quantity factors (e.g., school input) and input quality factors (e.g., home media input) work similarly in the language development of bilinguals while other potential internal and external factors are controlled for. This paper addressed this issue through investigating the influence of input quantity and input quality factors, both at the individual and group levels, on morphosyntax, vocabulary size, and lexical access ability in the Kurdish-L1 and English-L2 of Kurdish–English bilingual adolescents. Data were collected via a battery of standardized and researcher-developed measures and a detailed questionnaire. The results from backward regressions revealed that higher parental Kurdish proficiency and more exposure to Kurdish input through siblings and reading activities were associated with better Kurdish morphosyntactic skill, while a larger Kurdish vocabulary size was predicted by more exposure to native-speaker input in Kurdish. Both more Kurdish input received in preschool/school and through Kurdish media were related to better lexical access ability in Kurdish. Further, more exposure to English input in preschool/school predicted better English morphosyntactic skill and a larger vocabulary size, whereas higher paternal English proficiency was associated with better lexical access ability in English. Hierarchical regression analyses showed that input quality was more important in explaining Kurdish morphosyntactic and vocabulary size skills and lexical access ability in both languages, while input quantity explained more variance in English morphosyntactic and vocabulary size skills. Out-of-class Kurdish input outweighed instructional input to a certain extent in relation to Kurdish skills and lexical access ability in English, while instructional English input was more important for English morphosyntax and vocabulary size.

Abstract The area northeast of Mosul, a collection of villages with varying topography and terrain, is known for being a mosaic of ethnic and religious minorities. The village of Mērgī, the focus of interest in this paper, is one of the historical Christian settlements in the area, located on the southern foot of the Mount Maqlūb. Based on a fieldwork carried out in 2022 in Mērgī, this article investigates the linguistic situation in this village and carries out comparisons with the other well-documented related dialects in the vicinity.