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Shehata, Naglaa Saeed
- Big Data with Column Oriented NOSQL Database to Overcome the Drawbacks of Relational Databases
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Authors
Affiliations
1 Helwan University, Cairo, EG
2 Egyptian Organization for Standardisation & Quality, Cairo, EG
1 Helwan University, Cairo, EG
2 Egyptian Organization for Standardisation & Quality, Cairo, EG
Source
International Journal of Advanced Networking and Applications, Vol 11, No 5 (2020), Pagination: 4423-4428Abstract
Due to the Era of Big Data with the large amount of distributed databases in the web and the rapid growth in the smart systems a rapid growth happening in database models and the relational database fails to dealing with such a big amount of data and have many limitations the need to new technologies comes up, which makes DBMS developers move towards column oriented NOSQL database. The main goal of this paper is to provide a survey on NOSQL Model especiallya column oriented NOSQL database, providing the user with the benefit of using NOSQL database, Instead of using the (row database) relational to overcome the drawbacks of the relational database Model.Keywords
Relational Databases, NoSQL, Columnar Database, BASE Properties.- Algorithms of Deep Learning:Convolutional Neural Network Role with Colon Cancer Disease
Abstract Views :146 |
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Authors
Affiliations
1 Information Systems Department ,Faculty of Computers and Artificial Intelligence, Helwan University, EG
2 Information Systems Department, Faculty of Computers and Artificial Intelligence, Helwan University, EG
1 Information Systems Department ,Faculty of Computers and Artificial Intelligence, Helwan University, EG
2 Information Systems Department, Faculty of Computers and Artificial Intelligence, Helwan University, EG
Source
International Journal of Advanced Networking and Applications, Vol 13, No 1 (2021), Pagination: 4827-4832Abstract
The world's third most serious and lethal cancer rankings are colon cancer. Like cancer, the most important stage of early diagnosis is. Deep learning has become a leading learning tool for object detection and its successes in advancing the analysis of medical images have attracted attention. Convolutionary neural networks (CNNs), which play an indispensable role in the detection and potential early diagnose of colon cancer, are the most popular method of deep learning algorithms for this purpose. In this article we hope to take a look at the progress of colonic cancer analysis by studying profound learning practices. This study provides an overview of popular profound study algorithms used in analysis of colon cancer. All studies in the fields of colon cancer, including detection, classification as well as segmentation and survival prediction, will then be collected. Finally, we will conclude the work by summarizing the latest deep learning practices in analysis of colon cancer, a critical examination of the challenges and proposals for future research.Keywords
Deep Learning, Colon Cancer, Medical Image Analysis, Convolutional Neural Networks.References
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- M. Abdellatif, M. Salah, and N. Saeed, “ScienceDirect Overcoming business process reengineering obstacles using ontology-based knowledge map methodology,” Futur. Comput. Informatics J., vol. 3, no. 1, pp. 7–28, 2018.
- N.Shehata and A.Abed, “Big Data with Column Oriented NOSQL Database to Overcome the Drawbacks of Relational Databases,” Int. J. Adv. Netw. Appl., vol. 4428, pp. 4423–4428, 2020.
- Deep Neural Networks for Weather Forecasting
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Authors
Affiliations
1 Faculty of Computers & Artificial Intelligence, Helwan University, Cairo, EG
2 Faculty of engineering, Banha university, EG
1 Faculty of Computers & Artificial Intelligence, Helwan University, Cairo, EG
2 Faculty of engineering, Banha university, EG
Source
International Journal of Advanced Networking and Applications, Vol 15, No 2 (2023), Pagination: 5915-5923Abstract
Numerical Weather Prediction focuses on taking current observations of weather and processing these data with computer models to forecast the future state of weather and is used to produce shortand medium-range weather forecasts from 10-15 days of the state of the atmosphere. A weather satellite is a type of satellite that is primarily used to monitor the weather and climate of the Earth. Electromagnetic radiation is energy emitted by all matter above absolute zero temperature ex., visible light, infrared light, heat, microwaves, and radio and television waves and Electromagnetic radiation is absorbed mainly by several gases in the Earth's atmosphere, among the most important being water vapor, carbon dioxide, and ozone. The paper proposed methodology involves training deep neural networks to take reanalysis weather data at a given point in time as input, and then produce reanalysis weather data at a future point in time as output. We used a single point in time for both input and outputKeywords
weather prediction, computer models ,Electromagnetic radiationReferences
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