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 translation would affect their preparedness to easily accept and their ability to fully comprehend the messages in terms of the used lexical items. The survey-based research also explored the translation process and methods that would best ensure the messages would reach the target audience with the least loss of meaning. The study concluded that some acceptability issues and comprehensibility failure were detected in the available translated versions as a result of improper word selection, which could be attributed to adopting a literal translation method and uncommon collocations of certain medical terminologies. Therefore, this study recommends that effective translation of COVID-19-related health messages will be achieved by adopting a two-tier translation process, preferably involving a medical specialised translator.
جاء هذا البحث في اربع مباحث تناول المبحث الاول الاطار العام للبحث ،وتناول المبحث الثاني (الدراسة النظرية) بيان تاريخ المعجمات اللغوية والتعريف بها وباهدافها ووظائفها وانواعها والمادة التي تناولتها وتنظيمها وترتيبها ،وتناول المبحث الثالث(الدراسة العملية) التعريف بالمعجمات اللغوية الورقية والمحوسبة المتوافرة في مكتبات عينة البحث وبيان مدى استعمالها من طلبة الدراسات العليا ، وتناول المبحث الرابع الاستنتاج
... Show MoreCorona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)
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Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.
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Vaccine hesitancy poses a significant risk to global recovery from COVID-19. To date however, there is little research exploring the psychological factors associated with vaccine acceptability and hesitancy in Iraq.
To explore attitudes towards COVID-19 vaccination in Iraq. To establish the predictors of vaccine uptake and vaccine hesitancy in an Iraqi population.
Using a cross-sectional design, 7,778 participants completed an online questionnaire exploring their vaccination status, likelihood of infection, perc
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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
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This research examines aspects of Imam Al-Qurtubi's efforts in matters related to the topics of faith that he dealt with in his interpretation (the provisions of the provisions of the Qur’an); and it has been shown that Imam Al-Qurtubi in most of the doctrinal issues dealt with in his interpretation approximates the doctrine of the Sunnis of Ash'aris, Maturids and people of impact. He had responses to some of the teams, such as stereoscopic, karami, and Mu'tazilite, reinforcing the responses with transfer and mental evidence.
It was found that Imam Al-Qurtubi says that there is an increase in faith and a decrease in it, that the increase is through actions (so obedience increases and decreases in sin) and that the
Arabic prose poem and the antithesis of contrast: poetry _ prose and West _ East
Abstract
The research aims to examine the effect of Hawkins' strategy on students in the fourth grade of primary school in the General Directorate of Education in Baghdad / Karkh 3 for the academic year (2020-2021). The research was limited to the topics of the Arabic language grammar book for the fourth grade of primary school. The researcher developed the research hypothesis, which is: that there is no statistically significant difference at the significance level (0.05) between the average scores of the experimental group students who study using the Hawkins strategy and the average scores of the control group students who study in the traditional method in the achievement test. The researcher set a number of
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