Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

Writing in English is one of the essential factors for successful                      EFL learning .Iraqi students at the preparatory schools encounter problems when using their background knowledge in handling subskills                                  of writing(Burhan,2013:164).Therefore, this study aims to investigate the 4^thyear preparatory school students’ problems in English composition writing, and find solutions to these pro

The scientific studies that deal with Herminutia (interpretation) as the art of reading the interpretation practiced by the recipient after his understanding of the literary texts and works of art that he sees or read them so that these readings to make the act of reading and allow him the opportunity to mature and rational reflection of each text or artistic work.

Based on this, the researchers considered the establishment of the problem of their research through the search for the problematic overlap of concepts in the interpretive practices of the literary text?

The second chapter dealt with the definition of the term interpretation as well as interpretation as a theory and concept, and then the indicators reached by t

       The current research aims to build a training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students. To achieve the objectives of the research, the following hypothesis was formulated:

   There is no statistically significant difference at (0.05) level of significance between the average grades of the students participating in the training program according to the knowledge economy and the average grades of the students who did not participate in the training program in the test of productive thinking. The study sample consisted of (288) second intermediate grade students divided into (152) for the control group

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model

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

        The current research aims to investigate the skills of the intended meaning beyond the context when reading poetry among fifth literary students. To achieve the aim of the research, the researcher has followed the descriptive approach and used two tools: an open questionnaire that includes an inquiry about the skills of the intended meaning beyond the poetic context, and a closed questionnaire that were examined by the juries, and modified accordingly. Besides, its validity and stability were examined by applying the study on an exploratory sample of (15) teachers to reach its final version and determine the time required to answer it. Then, the researcher applied it on the research sample of (9