Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

Linguistic research according to modern curricula:
   It is one of the important matters that occupy the ideas of those concerned with linguistic studies, whether Arabic or otherwise. Recent years have witnessed the advancement of this methodological approach, and books and studies in Arabic have been written on important, multifaceted issues, of grammatical and linguistic origins, and their balance with new developments and ideas attracted mostly from Western studies.
    The comparative approach - as they call it - is one of the modern approaches that is based on balancing a language with other sisters belonging to its family, to reach similarities and differences between them, and to know the c

The paper aims at initiating and exploring the concept of extended metric known as the Strong Altering JS-metric, a stronger version of the Altering JS-metric. The interrelation of Strong Altering JS-metric with the b-metric and dislocated metric has been analyzed and some examples have been provided. Certain theorems on fixed points for expansive self-mappings in the setting of complete Strong Altering JS-metric space have also been discussed.

        Of the importance of the concept of ownership of real estate as the basic basis from which various projects are launched in various economic, tourism, and urban areas .... The need to research the diagnosis of real estate reality went astray in the difficulties, which played a decisive role in the process of urban development.

 This leads us to the research problem of the difficulty of implementing urban development plans in many cases due to the absence of a clear methodology for organizing and modernizing the ownership of real estate and its coordination with the management of urban land and to achieve the objective

The aim of this work is to design an algorithm which combines between steganography andcryptography that can hide a text in an image in a way that prevents, as much as possible, anysuspicion of the hidden textThe proposed system depends upon preparing the image data for the next step (DCT Quantization)through steganographic process and using two levels of security: the RSA algorithm and the digitalsignature, then storing the image in a JPEG format. In this case, the secret message will be looked asplaintext with digital signature while the cover is a coloured image. Then, the results of the algorithmare submitted to many criteria in order to be evaluated that prove the sufficiency of the algorithm andits activity. Thus, the proposed algorit

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet