Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

This study aims to observe and analysis the propaganda discourse image for Daesh, and know how it marketing the fear due to symbols structure, and discover the straight meanings and hidden inspiration, with the ideology that the image presented.
The study is descriptive and qualitative, and the method is analytic survey used semiotic approach.
The most important results of the study refer to:
- Daesh functioning the image in fear manufacture in all it components: the symbol of savageness, body language, color, clothes uniform and professionally shot.
- The indicative meaning of fear promoted by Daesh based of the manufacturing «Holy», and that mean places non-touchable and non-insulted.
- Daesh used in its propagand

Many purposes require communicating audio files between the users using different applications of social media. The security level of these applications is limited; at the same time many audio files are secured and must be accessed by authorized persons only, while, most present works attempt to hide single audio file in certain cover media. In this paper, a new approach of hiding three audio signals with unequal sizes in single color digital image has been proposed using the frequencies transform of this image. In the proposed approach, the Fast Fourier Transform was adopted where each audio signal is embedded in specific region with high frequencies in the frequency spectrum of the cover image to sa

The present research aims at revealing the advertising image semiotics in the American printed poster by following the image's significance and its transformations through the poster design trends and indicating its nature whether it is an explicit or implicit image. The limits of the research were the American printed poster during 2016-2018 period. The theoretical side was determined by two sections, the first: (the advertising image semiotics) and the second (design trends in the printed poster). The research procedures were represented by the research method adopted in the analysis of the sample models identified in four models taken from the research community which contains (24) models. The selection was made according to the trend

Man was closely associated with nature in its various forms, as it represented the incubator for him in all areas of his life, so writers often made it a material for their literature and a fertile ground for their productions, so it appeared in its various forms and man’s need for it, its good and its bad in literature throughout history, and the Arabs are like Other nations, since the pre-Islamic era, nature was an important outlet and a refuge for poets in the production and creativity of literature and to this day, and when we talk about a poet from the Fatimid state, we find that nature - especially spring and its flowers - in that period took its take from literature and represented a phenomenon for many Among the

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye