Departments and offices of public relations and media in any institution or company is the most important departments that reflect the results of their work negatively or positively on their reputation. This goes beyond the trust and credibility that its internal and external audiences will give it. Where such matter requires the staff, working in these departments and offices, to have communication skills that qualify them to do the role of marketing the communication message. Yet, the communication skills of public relations and media staff vary from person to person depending on the communication position. This skill has two criteria: Achieving the communication goal and the speed in achieving it as a number of skills

The present study deals with prepositions in the patterns of analytical unite of modern Russian language out of the functional -semantic aspects, which enhances the lexical semantics.  The study, also, sheds light on the prepositions of semantic derivation that adds value to the meaning of the unites, promotes the appearance of new forms that match the more important diverse complex analytical unit.

В статье рассмотрены отыменные предлоги в системе литических единиц русского языка с позиций функционального и семантического аспектов. Репрезентирована специфика функциониров

Traditionally, style is defined as the expressive, emotive or aesthetic emphasis added linguistically to the discourse with its meaning is the same. In the current study, however, style is defined as the linguistic choice that the language users can make for specific purposes.

    This study, thus, aims at analyzing political Arabic and English speeches to find out whether there are differences of style between English and Arabic and whether the choices the language users make  can show any traits of their psychological status.

    To fulfill the above aims, the study hypothesizes that English and Arabic  speeches can be analyzed stylistically and that there are stylistic difference

Arabic calligraphy has great importance in the printing designs that are often on the written character-based to perform functional goals and to achieve some of the aesthetic values ​​in design work, has led major developments in the field of computer manufacturing and design software for the design and layout to increase to deal with the programmed character for the purposes of typesetting has confronted this Find the Arab character programmed for the purposes of typesetting for the detection of the most important design interventions that underwent the Arabic letter written to turn it into a programmed image intended for the purposes of the printing and typesetting has been addressed in the context of which the theoretical types of

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

The evaluation and efficiency and effectiveness of account system for the department of delegation and cultural Relationships in the center of ministry of higher Education and Scientific research Considered as a very important and active subjects in the modification of accounting system in this department and to develop it and make it able to make available important and accurate information for the planning requirements and monetary and evaluation performance and to make decisions, besides to develop the performance of Iraqi Cultural departments working abroad and to render its role effective to serve the students of higher education in the progressive Countries to facility its growing in scientific and professional and technica

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