Arabic language processing with artificial intelligence has evolved significantly in the past decades, from traditional rule- and dictionary-based techniques, through statistical models to modern deep and transformer models. This review intends to present an overview of the most well-known Arabic models as well as datasets used for its training, and the main practical applications such as sentiment analysis, machine translation, speech recognition, and smart assistant. AI-based Arabic NLP has had good progress in the previous decades, from rule and dictionary-based approaches to statistical methods and deep transformative learning models nowadays. In addition to it, the most popular state-of-the-art models that are fine-tuned for the Arabic language and their corpora of training data will be considered as well as major applications such as Sentiment Analysis, Machine Translation, Speech Recognition, and Virtual Assistant. This article review outlines the necessity for investment in language resources and advanced models to improve AI systems’ ability to accurately understand Arabic natural language, a contribution that will support real-life applications and smart services associated with its present formalized variant of AI model capabilities.
The present paper respects 'inversion' as a habit of arranging the language of modern English and Arabic poetry . Inversion is a significant phenomenon generally in modern literature and particularly in poetry that it treats poetic text as it is a violator to the ordinary text. The paper displays the common patterns and functions of inversion which are spotted in modern English and Arabic poetry in order to show aspects of similarities and differences in both languages. It concludes that inversion is most commonly used in English and Arabic poetry in which it may both satisfy the demands of sound correspondence and emphasis. English and Arabic poetic languages vary in extant to their manipulation of inverted styles as they show changeable f
... Show MoreThe probability is considered one of the grammatical cases in all languages of the world. Expressions of probability in Spanish language are expressed by various structures, expressions and some verb tenses. By this study explains the grammatical cases, the verbal periphrases, the impersonal expressions, the future tenses (simple and perfect) and the conditional mode of probability in Spanish language .We have explains these cases in detail with examples that have extracted from various spanish grammar books .The specific objective of this study is to know the resources and constructions of probability in Spanish language and their translation in Arabic language.
Assimilation is defined ,by many phoneticians like Schane ,Roach ,and many others, as a phonological process when there is a change of one sound into another because of neighboring sounds.This study investigates the phoneme assimilation as a phonological process in English and Arabic and it is concerned specifically with the differences and similarities in both languages. Actually ,this study reflects the different terms which are used in Arabic to refer to this phenomenon and in this way it shows whether the term 'assimilation ' can have the same meaning of 'idgham' in Arabic or not . Besides, in Arabic , this phenomenon is discussed from&nb
... Show MoreThe 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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Одной из активно развивающихся отраслей лексикологии является неология, объект её изучения - новое слово или неологизм. В задачу неологии входит выявление новых слов и новых значений у уже существующих в языке слов, анализ причин и способов их появления, описание факторов, влияющих на появление нового в лексической системе языка, разработка языковой политики в отношении новых номинаций. Лексикограф
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
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A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.
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This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa
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Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration process by de
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