Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Emad A. Mohammed
Northern Technical University
Computer Science & IT

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Design and implementation of single bit error correction linear block code system based on FPGA Abdullah Mohammed A. Hamdoon; Zaid Ghanim Mohammed; Emad A. Mohammed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.12033

Abstract

Linear block code (LBC) is an error detection and correction code that is widely used in communication systems. In this paper a special type of LBC called Hamming code was implemented and debugged using FPGA kit with integrated software environments ISE for simulation and tests the results of the hardware system. The implemented system has the ability to correct single bit error and detect two bits error. The data segments length was considered to give high reliability to the system and make an aggregation between the speed of processing and the hardware ability to be implemented. An adaptive length of input data has been consider, up to 248 bits of information can be handled using Spartan 3E500 with 43% as a maximum slices utilization. Input/output data buses in FPGA have been customized to meet the requirements where 34% of input/output resources have been used as maximum ratio. The overall hardware design can be considerable to give an optimum hardware size for the suitable information rate.
Internet of things based real-time electric vehicle and charging stations monitoring system Emad A. Mohammed; Mahmood Hameed Qahtan; Ahmed J. Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1661-1669

Abstract

Due to a shortage of fuel sources and the increment in environmental pollution, efficient techniques should be introduced. The best solution is to move to the use of electric vehicles. The article aims to develop a solution for electric vehicle (EV) charging station locations that utilize the internet of things (IoT) technology. The IoT is a paradigm that uses sensors and transmitting networks to provide current facilities with a real-time global communication perspective of the physical world. This paper proposes a real-time system to provide a real-time update to EV location and charging stations (CSs) location to reduce time lost by users searching CSs, and provides real-time charging station (CS) recommendations for EV users by displaying the nearest CS, provide estimation arrival time to the nearest CS, display distance between nearest CS and EV real-time updated. The work of the proposed system was tested, and the most significant error rate (17 meters) is represented by the difference in the distance obtained from the system and the distance obtained from Google Map. The total accuracy of the design for the tested case is (98.014%).
Citrus leaves disease diagnosis Emad A. Mohammed; Ghasaq Hashim Mohammed
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i2.pp925-932

Abstract

Agriculture is the most important sector in developing countries, so the main source of concern for farmers is plant diseases that lead to a lack of production and a waste of money and crops. In this paper, a system using computer-assisted convolutional neural networks (CNN) with camera is developed to characterize diseases of citrus trees. This proposed system can help farmers to increase and improve the quality of their agricultural productivity. In addition to reducing the spread of the disease through early detection. Citrus leaf dataset was created to train and test the model because citrus is one of the main crops in Iraq. The results of the experiment shown that the implemented CNN achieved high classification accuracy of (92%) with fewer parameters, making it flawless and promising outcomes.
Co-Authors Abdullah Mohammed A. Hamdoon Ahmed J. Ali Ghasaq Hashim Mohammed Mahmood Hameed Qahtan Zaid Ghanim Mohammed