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.
With the emergence of globalization, international and diplomatic relations have developed among countries and led to the creation of new words, concepts and diplomatic terminology. The purpose of this thesis is to study and analyze the types of written, oral and nonverbal diplomatic language and to shed light on the types of diplomatic translation/interpretation. In addition to that, the thesis investigates the role of translator/interpreter when translating diplomatic texts and interpreting diplomatic speeches in international conferences, organizations, etc. It also tackles the difficulties faced during translation/interpretation and how to overcome these problems and find appropriate solutions for them. The main purpose of this thesi
... Show MoreIn our research, we dealt with one of the most important issues of linguistic studies of the Holy Qur’an, which is the words that are close in meaning, which some believe are synonyms, but in the Arabic language they are not considered synonyms because there are subtle differences between them. Synonyms in the Arabic language are very few, rather rare, and in the Holy Qur’an they are completely non-existent. And how were these words, close in meaning, translated in the translation of the Holy Qur’an by Almir Kuliev into the Russian language.
The synthesis of nanoparticles (GNPs) from the reduction of HAuCl4 .3H2O by aluminum metal was obtained in aqueous solution with the use of Arabic gum as a stabilizing agent. The GNPs were characterized by TEM, AFM and Zeta potential spectroscopy. The reduction process was monitored over time by measuring ultraviolet spectra at a range of λ 520-525 nm. Also the color changes from yellow to ruby red, shape and size of GNP was studied by TEM. Shape was spherical and the size of particles was (12-17.5) nm. The best results were obtained at pH 6.
Abstract The study aimed at reviewing translation theories proposed to address problems in translation studies. To the end, translation theories and their applications were reviewed in different studies with a focus on issues such as critical discourse analysis, cultural specific items and collocation translation.
There are numbers of automatic translation services that internet users can choose to automatically translate a certain text, and Google translate is one of these automatic services that proposes over 51 Languages. The present paper sheds light on the nature of the translation process offered by Google, and analyze the most prominent problems faced when Google translate is used. Direct translation is common with Google Translate and often results in nonsensical literal translations, particularly with long compound sentences. This is due to the fact that Google translation system uses a method based on language pair frequency that does not take into account grammatical rules which, in turn, affects the quality of the translation. The
... Show MoreThis study investigates the phonotactics of English obstruent clusters in the word-final position from a markedness theory perspective among Iraqi EFL College Students whose native language, Arabic, prefers only two-member word-final obstruent cluster as a maximum. The markedness of clusters is measured depending on Iraqi EFL College Students’ utilization of the simplification strategies. This study tries to answer whether or not word-final obstruent clusters are marked or unmarked for Iraqi EFL College Students, and whether or not the markedness of the obstruent cluster increases as to its length. In order to answer these questions, a test has been distributed among 60 Iraqi EFL Fourth-Year College students, Department of English, Colleg
... Show MoreThe current study aimed to measure the attitudes of female teachers towards the use of digital learning and the degree of possessing their digital education skills. The study sample consisted of (180) workers with disabilities (mental disability، auditory impairment، visual disability، hyperactivity and distraction. To achieve the goals of the study, the transformation measure was used towards digital education for people with disabilities. The study reached the following results: the availability of digital learning skills among workers with disabilities. The study concluded with a series of recommendations including holding Training courses to keep up with the challenges of educational trends and modern technology in this area.
Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
... Show MoreAutomatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recogn
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