Abstract The myth is a story that is passed on to the generations generation after generation, ridiculed by literary writers in their literary work; to convey an important idea to the recipient, and in legend many things useful to the creator, especially the novelist, from that ritual and harnesses to be symbols that reach the recipient what the creator thinks; The Arabic novel, I chose Sahel al-Nahr's novel of Sudanese novelist Buthaina Khader Makki, a well-known author in her country for her advocacy of women and their rights. She used legend and mythic symbols in a deliberate manner to convince the recipient that what he read was a real thing worth standing at Understand E, has reached a number of results, including Buthaina Khader Makki has made reality a myth and legend. : The novelist Buthaina Khodr Mekki narrated her story on the myth that was equivalent to the idea of differences between women and men, no matter how much she was a follower. The novelist resorted to the myth to try to give a convincing explanation for the strangeness of the reality presented in her life affected by it, and affected it; to have an eye different from the eye of others. The novel identified aspects of the use of myth in the novel are: Escape from the strength and pressure of current problems. And the explosion of literary connotations and transmitted to the mind of the recipient, to match the culture of the recipient and his knowledge of things, myth is a method of thrill. The myth was the idea of the novel and its characters; it was a collection of symbols and rituals that illustrated the message that the novelist wanted to convey. Finally, I hope that I have succeeded in trying to deliver an idea of Sudanese literature rich in creativity, thought and serious work to the recipients, perhaps to draw the attention of researchers to study more and more to explore the treasures.
In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
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Merging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering
... Show MoreIn the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn
... Show MoreRecently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural
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Idiomatic expressions in Russian journalism make one important borrowed means for making a dialogue with the receiver's intellect in so far as it has the distinct feature of having clarity and exactness of meaning. The meaning is seen as a shortcut for covering a series of concepts and details so as to arrive at the intended meaning. This is done by stimulating the reader by the use of certain clear idioms. The use of such idioms in a journalistic text is not for a linguistic purpose only, but it is a cultural and social phenomenon reflecting the type of current changes in the society and it aims at discoursing with the reader's mind. This paper is a practi
... Show MoreIn recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
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Field of translation is sampled with many types of translation, such as the literary, scientific, medical, etc. The translation of grammatical aspects has always been with difficulties.
Political translation is the focus here. There are many general problems faced by translators when translating political texts from Arabic into Spanish. The aim here is to clarify the definition of functions or terms within the text, and to arrive at the correct from of translation of such texts from Spanish into Arabic. It is worth mentioning that the paper is of two parts: the first exemplifies what is meant by translation, the prerequisites of a translator, along with mentioning the methods followed&nbs
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Translation is both a social and cultural phenomenon, it can neither exist outside a social community and it is within society, nor it can be viewed as a medium of cross-cultural fertilization. This paper aims to investigate the difficulties that a translator may face when dealing with legal texts such as marriage and divorce contracts. These difficulties can be classified according to the present paper into syntactic, semantic, and cultural. The syntactic difficulties include word order, syntactic arrangement, unusual sentence structure, the use of model verbs in English, and difference in legal system. As to the semantic difficulties, they involve lack of established terminology, finding functional and lexical equivalence, word for word t
... Show MoreText Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
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