Euphemisms are advantageous in people’s social life by turning sensitive into a more acceptable ones so that resentful feelings and embarrassment can be avoided. This study investigates the ability of Iraqi English learners in using euphemistic expressions, meanwhile, raising their awareness and the faculty members in English teaching faculties regarding the relevance of discussing the topics that demand euphemisation. This study comprised three stages: initial test, explicit instruction with activities, and a final test for the students’ development in this domain. A test has been distributed among 50 respondents, who are at the fourth year of their undergraduate study at the University of Babylon/ College of Basic Education. The low rate of producing and recognising euphemisms in the first stage of the study, it is concluded that Iraqi students that the course design in the foreign context is inadequate. After consistent training during the second stage, students have shown significant development in mastering these expressions.
تلخصت مشکلة هذا البحث في التعرف على الدوافع التي تقف وراء تعرض الطلبة الدارسين في أقسام اللُّغة الإنکليزية للقنوات الفضائية الناطقة باللُّغة الإنکليزية والإشباعات المتحققة عن هذا التعرض في هذا المجتمع الخاص الذي يشکل بيئة اجتماعية علمية محددة، عن طريق تطبيق نظرية الإستخدامات والإشباعات في إطار المجتمعات الخاصة، وسعى هذا البحث إلى تحقيق ثلاثة أهداف هي، قياس استخدامات لطلبة الدارسين في أقسام اللُّغة الإنک
... Show Moreبسمة الأوقاتي/ أكاديمية وباحثة في العلاقات الدولية تولي الرئيس الأمريكي دونالد ترامب منصبه لولاية ثانية في العشرين من كانون الثاني / يناير من هذا العام (2025) وهو أكثر تمسكاً بعقيدته السياسية التي كان عنوانها في ولايته الأولى (أمريكا أولا / America First) وحاملا لتوجهات جيوسياسية جديدة ومثيرة للجدل
Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreAn oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification
... Show MoreDeep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec
... Show Morethis research aims it measure the technical efficiency of the branches of the General Company for Land Transport, That scattered geographically at country level, by Data Envelopment analysis (DEA) technique, as this technique relies on measuring the efficiency of a set of asymmetric Decision making units, which is one of the nonparametric mathematical methods for and application related to Linear Programming, and this is what helps the General Company for Land Transport to diagnose its branches performance by benchmarking with each other and determine the performance gap. The research found that there is variation in the level of efficiency in the company's branches
اتجهت دول العالم الى تسخير جميع الإمكانيات والخبرات والعلوم من اجل الوصول الى مستويات متقدمة في الرياضات المختلفة ويهدف التدريب الرياضي إلى إعداد اللاعبين إعدادا جيدا تكمن مشكلة البحث من خلال خبرة الباحثتان الميدانية ومتابعة تدريبات لاعبي المدرسة التخصصية كرة اليد فقد لوحظ هناك ضعف واضح في الأداء المهاري ولابد من تطوير أوجه الضعف لتحقيق مستوى انجاز افضل . ويهدف البحث اعداد تمرينات خاصة بأستخدام جهاز ا
... Show MoreThis research work dealt with the problem of layout the production line of engine of fan roof at the General Company for Electrical Industries (GCEI). It was observed that the assembly line of engine was unstable and subject to severe fluctuations. In addition the execution of tasks at some stations was observed to be very fast while at other stations was slow. This phenomenon resulted into bottlenecks between workstations, idle time, and work in process. The system design was used to assign tasks to work stations according to different heuristics (Ranked Positional weight techniques, longest Task Time, Most following tasks, Shortest tasks time, Least number of following task).
The study revealed that th
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