Abstract: In this research review paper, we have introduced our work with a comprehensive study on data warehousing, regarding to its novelty; depending on that, there was an intensive research work, because of its importance and need nowadays, we have reviewed and studied big amount of researches available in the Information Systems research centers around the globe. We have focused on optimization in our comprehensive studies and also on the processes of data warehousing with respect to its updated optimized queries approaches and its vast utilization in the Market. We found that ,the most useful information extracted by using both approaches which have used within new optimized techniques for query-driven approaches, has got potentially effected on the strategies of most successful data warehousing integration models. arabic 9 English 68
Mohamed Abdeldaiem Abdelhadi Mahboub(10-2019)

Abstract:- Our research paper has presented a new developed model for secured search into a big data of document collections. The developed model has investigated the importance of secured search and also the need for its practices in the real world. We have actually, studied both side of encryption in practical techniques issues and theoretical issues to improve the integration of information retrieval and cryptographic methods used for secured searching. We have chosen 3DES encryption technique to encrypt document data collections. Our new developed secured model has provided an efficient secured searching and/or security and authenticity over all. arabic 9 English 58
Mohamed Abdeldaiem Abdelhadi Mahboub, , (9-2019)

The manual detection and classification finding correct location and identifying type of tumor becomes a rigorous and hectic task for the radiologists. Medical diagnosis via image processing and machine learning is considered one of the most important issues of artificial intelligence systems. Deep learning has been used successfully in supervised classification tasks in order to learn complex patterns. The main contributions of this paper are as create a more generalized method for brain tumor classification using deep learning a variety of neural networks were constructed based on the preprocessing of image data., analyze the application of tumorless brain images on brain tumor classification and empirically evaluate neural networks on the given datasets with per image accuracy and per patient accuracy. And also presents an efficient image segmentation using machine learning algorithm with some optimization techniques to detect brain tumors. arabic 19 English 128
Mohamed Abdeldaiem Abdelhadi Mahboub(3-2019)