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Hanan Abed Alwally Abed Allah
Mustansiriya University

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Secure and smart system for monitoring patients with critical cases Hanan Abed Alwally Abed Allah; Rawsam Abduladheem Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1800-1807

Abstract

Recently, heat-related diseases like COVID19, Chickenpox, Typhoid, and others are increasing significantly; therefore, the need for portable devices to measures the heat of the human body accurately, quickly, easily with low cost has become very necessary to preserve the life of patients. For this reason, a smart system has been developed to monitor the patient's heat, in addition to temperature and humidity of the critical environment such as surgical operating rooms, patients’ isolation rooms and pharmacies, because it can help propagate infectious agents like viruses and bacteria. The proposed system divided into four parts: transmitted part (arduino, heat sensor, and hygrometer sensor), alarm part consists of lights and alarm bell, emergency part (doctors and nurses), and the medical application has been used as the last part. The application can be used only by authorized persons and through the accounts which are granted to them, in order to protect the data from sabotage and maintain the privacy and confidentiality of it.
Live to learn: learning rules-based artificial neural network Aseel Shakir I. Hilaiwah; Hanan Abed Alwally Abed Allah; Basim Akhudir Abbas; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp558-565

Abstract

An extensive review of the artificial neural network (ANN) is presented in this paper. Previous studies review the artificial neural network (ANN) based on the approaches (algorithms) used or based on the types of the artificial neural network (ANN). The presented paper reviews the ANN based on the goal of the ANN (methods, and layers), which become the main objective of this paper. As a famous artificial intelligent model, ANN mimics the human nervous system in handling the information transmited by different nodes (also known as neurons) in this model. These nodes are stacked in layers and work collectively to bring about solution to complex problems. Numerous structures exist for ANN and each of these structures is designed to addressa a specific task. Basically, the ANN architecture is comprised of 3 different layers wherein the first layer rpresents the input layer that consist of several input nodes that represent the input parameterfor the model. The hidden layer is te second layer and consists of a hidden layer of neurons. The neurons in this layer are directly connected to the neurons in the output layer. The third layer is the output layer which is the models’ response layer. The output layer neurons have the activation functions for the calculation of the ANN final output. The connection between the nodes in the ANN model is mediated by synaptic weights. This paper is a comprehensive study of ANN models and their layers.
Co-Authors Aseel Shakir I. Hilaiwah Basim Akhudir Abbas Rawsam Abduladheem Hasan Tole Sutikno