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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Ihab A. Satam
Northern Technical University
Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Prediction of COVID-19 disease severity using machine learning techniques Alaa H. Ahmed; Mokhaled N. A. Al-Hamadani; Ihab A. Satam
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3272

Abstract

A terrifying spread of COVID-19 (which is also known as severe acute respiratory syndrome coronavirus 2 or SARS-COV-2) led scientists to conduct tremendous efforts to reduce the pandemic effects. COVID-19 has been announced pandemic discovered in 2019 and affected millions of people. Infected people may experience headache, body pain, and sometimes difficulty in breathing. For older people, the symptoms can get worse. Also, it can cause death because of the huge effect on some parts of the human body, particularly for those who have chronic diseases like diabetes. Machine learning algorithms are applied to patients diagnosed with Corona Virus to estimate the severity of the disease depending on their chronic diseases at an early stage. Chronic diseases could raise the severity of COVID-19 and that is what has been proved in this paper. This paper applies different machine learning techniques such as random forest, decision tree, linear regression, binary search, and k-nearest neighbor on Mexican patients’ dataset to find out the impact of lifelong illnesses on increasing the symptoms of the virus in the human body. Besides, the paper demonstrates that in some cases, especially for older people, the virus can cause inevitable death.
Arduino-based design and implementation of experimental rooms with a trombe wall for solar cells applications Raid W. Daoud; Obed Majeed Ali; Omer Khalil Ahmed; Ihab A. Satam
Bulletin of Electrical Engineering and Informatics Vol 12, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i3.4522

Abstract

The simplicity of design and construction following the researcher's or company's notion is the most typical description of solar panels. There will be a set of sensors in every design to derive information about the environment's shifting seasons and days. Two chambers of 1 m2 and 2 m in height were constructed for this study. A solar panel made from a unique exchangeable material has been installed instead of one of the walls, allowing a space between them for experimental reasons. Several temperature sensors were mounted inside and outside the chamber, as well as on the surface of the solar panel and within the air openings, in this work to record the temperature readings in various places. The used controller, an Arduino, is in charge of several operations, including controlling the solar panel's cooling device, reading and recording sensor data and storing it in RAM, controlling the orientation of the solar panel, controlling the vacuums, and regulating the on-off time of the motors. The findings show that by using sensor data, the system can keep the temperature constant when it is turned on. Additionally, the battery life will be preserved to the greatest extent feasible thanks to the well-balanced regulation of the loads.
Co-Authors Alaa H. Ahmed Haider A. Kamel Mokhaled N. A. Al-Hamadani Mokhaled N. Abdullah Obed Majeed Ali Omer Khalil Ahmed Raid W Daoud Raid W. Daoud Suhail N. Shihab