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Deep stacked ensemble learning model for COVID-19 classification

COVID-19 is a growing problem worldwide with a high mortality rate. As a result, the World Health Organization (WHO) declared it a pandemic. In order to limit the spread of the disease, a fast and accurate diagnosis is required. A reverse transcript polymerase chain reaction (RT-PCR) test is often used to detect the disease. However, since this test is time-consuming, a chest computed tomography

Software and Communications

Automated detection and classification of galaxies based on their brightness patterns

Clues and traces of the universe's origin and its developmental process are deeply buried in galaxy shapes and formations. Automated galaxies classification from their images is complicated due to the faintness of the galaxy images, conflicting bright background stars, and image noise. For this purpose, the current work proposes a novel logically structured modular algorithm that analyses galaxy

Artificial Intelligence

A HYBRID RECOMMENDER FRAMEWORK FOR SELECTING A COURSE REFERENCE BOOKS

Recommender systems are receiving great attention these days, as various researchers and major companies are conducting continuous research in this field. Companies like Google and Amazon have provided different effective models for video recommendation systems, but the educational field is poorly studied as other researchers explained. Different researchers proposed various approaches showing the

Artificial Intelligence

Modeling of Soft Pneumatic Actuators with Different Orientation Angles Using Echo State Networks for Irregular Time Series Data

Modeling of soft robotics systems proves to be an extremely difficult task, due to the large deformation of the soft materials used to make such robots. Reliable and accurate models are necessary for the control task of these soft robots. In this paper, a data-driven approach using machine learning is presented to model the kinematics of Soft Pneumatic Actuators (SPAs). An Echo State Network (ESN)

Circuit Theory and Applications

Engineered magnetic oxides nanoparticles as efficient sorbents for wastewater remediation: a review

The rapid urbanization and industrialization is causing worldwide water pollution, calling for advanced cleaning methods. For instance, pollutant adsorption on magnetic oxides is efficient and very practical due to the easy separation from solutions by an magnetic field. Here we review the synthesis and performance of magnetic oxides such as iron oxides, spinel ferrites, and perovskite oxides for

Energy and Water

Recognizing Clothing Patterns and Colors for BVI People Using Different Techniques

For blind and visually impaired (BVI) people, it is an arduous task to recognize clothing patterns and colors. It is especially complex to recognize them automatically. This is a highly researched area in image processing. This paper provides BVI with the ability to detect patterns and colors without depending on personal assistance, leading to increasing their confidence. The user first captures

Artificial Intelligence
Software and Communications

An optimized ensemble model for prediction the bandwidth of metamaterial antenna

Metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their performance. Antenna size affects the quality factor and the radiation loss of the antenna. Metamaterial antennas can overcome the limitation of bandwidth for small antennas.Machine learning (ML)model is recently applied to predict antenna parameters.ML can be used as an alternative approach to the trial

Software and Communications
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Out of 331 organizations in 42 countries around the world, Design House, which is one of NilePreneurs’ initiatives by Nile University, has been selected by NASA as one of the few international companies who will have the license to manufacture its new pneumatic ventilator device “VITAL” for treating COVID-19 patients. Out of 331 organizations in 42 countries around the world, Design House, which