Corpus linguistics is a methodology in studying language through corpus-based research. It differs from a traditional approach in studying a language (prescriptive approach) in its insistence on the systematic study of authentic examples of language in use (descriptive approach).A “corpus” is a large body of machine-readable structurally collected naturally occurring linguistic data, either written texts or a transcription of recorded speech, which can be used as a starting-point of linguistic description or as a means of verifying hypotheses about a language. In the past decade, interest has grown tremendously in the use of language corpora for language education. The ways in which corpora have been employed in language pedagogy can be divided into two main categories: indirect and direct application. In the former corpora are used in designing and developing the syllabuses, dictionaries, tests, and teaching materials, while later, corpus data are used for data-driven learning and what is known as grammar safari. So this research aims at employing corpus data in teaching Arabic grammar. Functional syntactic analysis of corpus is a must for this purpose, so Quranic corpus is the most appropriate one. In this paper,I examined the specification phenomenon (التمييز) in Quranic corpus and compared the descriptive and prescriptive approaches in teaching causative object as a grammatical phenomenon in Arabic.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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This paper presents a study of the application of gas lift (GL) to improve oil production in a Middle East field. The field has been experiencing a rapid decline in production due to a drop in reservoir pressure. GL is a widely used artificial lift technique that can be used to increase oil production by reducing the hydrostatic pressure in the wellbore. The study used a full field model to simulate the effects of GL on production. The model was run under different production scenarios, including different water cut and reservoir pressure values. The results showed that GL can significantly increase oil production under all scenarios. The study also found that most wells in the field will soon be closed due to high water cuts. Howev
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В статье рассматривается вопрос об использовании мультимедийных средств для оптимизации процесса формирования коммуникативной компетенции в иракской аудитории с привлечением компьютерных технологий. Статья посвящена использованию мультимедийных технологий и различных приемов формирования интереса к русскому языку. Включение в процесс обучения коммуникативно-значимого, аутентичн
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This paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with
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After its 35-year occupation of Japan and the US occupation, Korea has set its sights on a long-term goal of building its country and establishing its foundations, unobtrusive and unchecked by the problems and wars that have stood in the way of its goal, surpassing all odds and achieving the best results. The most powerful Asian and global economies, which gained the respect of the world and its appreciation of the experience has become referred to as boys