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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Salama A. Mostafa
Universiti Tun Hussein Onn Malaysia
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Analyzing bit error rate of relay sensors selection in wireless cooperative communication systems Ahmed Allawy Alawady; Ahmed Alkhayyat; Mohammed Ahmed Jubair; Mustafa Hamid Hassan; Salama A. Mostafa
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2492

Abstract

Cooperative communication systems, which make use of the intermediate relays between the transmitter and the receiver, have been employed as an effective technique to combat the channel fading and to enhance system performance. Cooperative systems have some drawbacks such as high latency and may diversity order not guaranteed. To alleviate the negative effects of these factors, the relay selection protocol is employed in cooperative communication systems to increase overall cooperative system performance. Relay selection in the cooperative systems enables the source to cooperate with the single relay node rather than multiple relay nodes which guaranteed the diversity order.
An accurate Alzheimer's disease detection using a developed convolutional neural network model Muhanad Tahrir Younis; Younus Tahreer Younus; Jamal Naser Hasoon; Ali Hussain Fadhil; Salama A. Mostafa
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3659

Abstract

Alzheimer's disease indicates one of the highest difficult to heal diseases, and it is acutely affecting the elderly normal lives and their households. Early, effective, and accurate detection represents an important blueprint for minimizing Alzheimer's progression risk. The modalities of brain imaging can assist in identifying the abnormalities associated with Alzheimer's disease. This research presents a developed deep learning scheme, which is designed and implemented to classify the brain images into multiclass, namely very mild, moderate, mild, and non-demented. The proposed convolutional neural network (CNN) based detection model attained a high performance with an accuracy of 99.92%, considerably enhancing the results achieved via the pre-trained 16 layers in the visual geometric group (VGG16) model and the other related learning models. Consequently, this developed model can assist medical personnel by providing a facilitating tool to identify Alzheimer's disease stage and establishing a suitable medical treatment platform.
A smart water grid network for water supply management systems Ali Adil Ali; Saadi Mohammed Saadi; Tameem Mohammed Mahmood; Salama A. Mostafa
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3227

Abstract

This paper proposes a smart water grids network (SWGN) architecture that combines the advantages of fog computing, internet of things (IoT), long range wide area network (LoRaWAN), and Software-defined networking (SDN). The main aims of the SWG architecture are to optimize data routing and monitor water supply and quality in real-time. SWGN handles a vast amount of data that is collected by IoT devices from different points related to water supply and quality. The data is processed in a distributed way by a number of fog servers that are located at the edge of the network. The fog controllers are deployed at the fog layer in order to take action locally for frequent events. The cloud layer has a cloud controller to take actions globally for infrequent events. The LoRaWAN provides communication technology that allows devices to operate regularly. The SDN technology decouples network traffic to control data routing decisions efficiently. A primitive evaluation under the Mininet emulator, focusing on SDN, shows the feasibility and efficiency of the architecture.
Co-Authors Abdullah Baz Ahmed Alkhayyat Ahmed Allawy Alawady Aida Mustapha Ali Adil Ali Ali Hashim Abbas Ali Hussain Fadhil Farooq Sijal Shaqwi Hairulnizam Mahdin Jamal Naser Hasoon Lukman Audah Luqman Hanif Audah Mohammad Faidzul Nasrudin Mohammed Ahmed Jubair Mohammed Ahmed Jubair Mohammed Salah Abood Muhanad Tahrir Younis Mustafa Hamid Hassan Mustafa Hamid Hassan Mustafa Maad Hamdi Noor Azah Samsudin Saadi Mohammed Saadi Sami Abduljabbar Rashid Shihab Hamad Khaleefah Tameem Mohammed Mahmood Younus Tahreer Younus