This research on women under the title (Empowerment of women…  From value education to the creation of human morality), includes a disclosure of the reasons that prevented women from performing their human role in the development of human societies and treatments that can provide to solve this big problem in the life These communities, especially the Eastern societies and the religious ones, believe that the woman has not received the care and care to raise her human values ​​in order to contribute to the required social contribution, for historical, economic, moral, religious, social and cultural reasons. And by shedding light on specific definitions of the most important rules on which the research relied

Care and attention to the structure in the sixties of the last century replaced the mark, and if the structure of Ms. pampered in research and studies, it has become the mark is also a spoiled lady .. But the relationship between the structure and the mark was not a break and break, but the relationship of integration, His themes are structural analysis, and these are intellectual themes that can not be surpassed in contemporary research, especially since semiotics have emerged from the linguistic inflection.

We have tried to distinguish between text and speech, which is a daunting task, as it seems that whenever the difference between them is clear and clear, we come back to wonder whether the text is the same discourse, and is

Wrong behavioral deviations among youth witnessed an obvious growing, some of these deviations are, robbery, drug and internet addiction, and smoking. Additionally, intellectual extremism and the disrespect of the traditions and genuine customs, In light of this issue, the research aims to shed light on the educational and preventative role of the woman in protecting and immunizing children from the wrong behavioral deviations. The woman has a significant and influential role in the society in general and in her family, in particular to the responsibility lies on her. The research shed light on the manifestations of behavioral deviation in children and the mechanisms of prevention and treatment. The research concluded with a set of recom

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

Witnessing human societies with the turn of the century atheist twenty huge revolution in information , the result of scientific and technological developments rapidly in space science and communications , and that made the whole world is like a small village not linked by road as it was in ancient times, through the rapid transportation as was the case a few years ago , thanks to the remote sensing devices that roam in space observant everything on the ground , that the information networks that overflowed the world a tremendous amount of information provided for each inhabitants of the earth , which made this information requirement for human life and human survival and well-being , as it has allowed that information to humans opportun

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed