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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6,301 Documents
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A novel improved elephant herding optimization for path planning of a mobile robot Oultiligh, Ahmed; Ayad, Hassan; El Kari, Abdeljalil; Mjahed, Mostafa; El Gmili, Nada
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp206-217

Abstract

Swarm intelligence algorithms have been in recent years one of the most used tools for planning the trajectory of a mobile robot. Researchers are applying those algorithms to find the optimal path, which reduces the time required to perform a task by the mobile robot. In this paper, we propose a new method based on the grey wolf optimizer algorithm (GWO) and the improved elephant herding optimization algorithm (IEHO) for planning the optimal trajectory of a mobile robot. The proposed solution consists of developing an IEHO algorithm by improving the basic EHO algorithm and then hybridizing it with the GWO algorithm to take advantage of the exploration and exploitation capabilities of both algorithms. The comparison of the IEHO-GWO hybrid proposed in this work with the GWO, EHO, and cuckoo-search (CS) algorithms via simulation shows its effectiveness in finding an optimal trajectory by avoiding obstacles around the mobile robot.
Real time implementation of downlink orthogonal frequency division multiplexing based non-orthogonal multiple access transceiver using NI USRP platform Kaba, Vanita; Patil, Rajendra; Chandrashekar, Shyamala
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4138-4146

Abstract

The growing fame and utilization of wireless multimedia approaches have led to the advancement of the wireless system. The fifth generation (5G) of wireless communication was developed to serve users with enhanced proficiency, low latency, reliable communication, and lesser battery exhausts. The non-orthogonal multiple access (NOMA) scheme is a proficient multiple access scheme to fulfil the requirement of a 5G mobile system. NOMA enables a remarkable enhancement in the systems throughput and ability to connect devices. NOMA distinguishes each user by allocating a distinct power level, superimposing all the user’s signals utilizing superposition coding while transmitting and at the reception, each user’s signals are decoded by employing successive interference cancellation (SIC). This study builds a real time downlink orthogonal frequency division multiplexing based NOMA (OFDM-NOMA) transceiver system using the NI USRP 2944R and 2901 platforms. The performance evaluation of the proposed OFDM-NOMA system is carried out in terms of signal to noise ratio by adjusting transmitting gain and the distance of users from the base station system. Experimental results show that the signal-to-noise ratio (SNR) of each user relies on the power allocation factor and proximity of users from the base station, and SIC output is compared with constellation variations.
Enhancing privacy-preserving in vehicular cloud through an incentive-based strategy Mistareehi, Hassan; Tennyson, Matthew; Bany Salameh, Haythem
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4078-4087

Abstract

The literature has extensively explored vehicle ad hoc networks (VANETs) and vehicular clouds, with a common assumption in these studies being incorporating onboard units (OBUs) in vehicles. OBUs are used to collect and disseminate information between vehicles. Furthermore, numerous studies assume the presence of road infrastructure for communication. Implementing a vehicular cloud can play a vital role in aggregating data on events such as weather conditions, traffic information and accidents. This information is distributed to other vehicles, allowing drivers to make informed decisions and ensure safe driving practices. To protect privacy within the vehicular cloud, pseudonyms serve as a means of communication between vehicles and roadside units (RSU). Numerous existing approaches suggest more frequent updates to vehicle pseudonyms to reduce the likelihood of linking transmitted messages by vehicles. However, some of these strategies overlook situations where vehicle density is low, and vehicles have limited willingness to engage in the pseudonym-changing process. This article introduces an architecture that encourages vehicles to participate in the pseudonym-changing process to enhance vehicle privacy. This is achieved by issuing rewards to vehicles that can be used to access cloud services.
A classification model for predicting course outcomes using ensemble methods Al-Momani, Emad; Shatnawi, Ala'a; Almomani, Mohammad; Almomani, Ammar; Alauthman, Mohammad
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp7090-7102

Abstract

Educational data mining has sparked a lot of attention in latest years. Many machine learning methods have been suggested to discover hidden information from educational data. The extracted knowledge assists institutions in enhancing the effectiveness of teaching tactics and the quality of education. As a result, it improves students' performance and educational outputs overall. In this paper, a classification model was built to classify students' grades in a specific course into different categories (binary and multi-level classification tasks). The dataset contains features related to academic and non-academic information. The models were built using a variety of machine learning algorithms: decision tree (J48), support vector machine (SVM), and k-nearest neighbor (K-NN). Furthermore, ensemble methods (bagging, boosting, random subspace, and random forest) which combined multiple decision tree classifiers were implemented to improve the models' performance. The data set was modified under two stages: features selection method and data augmentation using a method called synthetic minority over sampling technique (SMOTE). Based on the results of the experiments, it is possible to predict the students' performance successfully by using machine learning algorithms and ensemble methods. Random subspace obtained the best accuracy at two-level classification task with modified data with 91.20%. At the three-level classification task, the best accuracy was obtained by random forest with 87.18%.
Hotspot temperature analysis of distribution transformer under unbalanced harmonic loads using finite element method Mohd Wazir, Muhammad Haziq; Mat Said, Dalila; Mohd Yassin, Zaris Izzati; Abd Wahid, Siti Aisyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1287-1298

Abstract

In an electrical power distribution system, harmonic distortion is the most prominent power quality problem that causes long-term adverse effects such as failure of distribution transformers. Considering that most transformer problems are caused by heat losses due to the presence of harmonics, it was decided to use a numerical method with the highest accuracy, finite element method (FEM) to analyze the hot spot temperature (HST) of the thermal distribution transformer model. Through the use of COMSOL Multiphysics software, three phases of unbalanced harmonic loads are considered, which contribute to three different total harmonic distortion current (THDI) levels and five different insulation temperature classes. Using the IEEE C57.110-2018 guidance, the simulation outputs are then verified with HST results from the HST mathematical model. The findings indicated that with the increased loadings, the unbalanced harmonic currents have impacted the HST increment and distinguished the HST values between the phases.
An efficient approximate method for solving Bratu’s boundary value problem Al-Khaled, Kamel; Ajeel, Mahmood Shareef; Abu-Irwaq, Issam; Al-Khalid, Hala
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5738-5743

Abstract

We compute the numerical solution of Bratu’s boundary value problem (BVP). To achieve this, we apply a new and useful approach to solve Bratu’s boundary value problem by using Green’s function and a new integral operator, along with a modified version of the Adomian decomposition method. This process produces solutions that call for the boundary conditions to be applied explicitly. Statistical results demonstrating the robustness and efficiency of the proposed scheme are included. An exact and approximate solution comparison is made with known results. The quantitative outcomes showcase our novel approach’s high numerical precision and consistency across a range of parameter configurations.
Smart city: an advanced framework for analyzing public sentiment orientation toward recycled water Bahra, Mohamed; Fennan, Abdelhadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp1015-1026

Abstract

The coronavirus pandemic of the past several years has had a profound impact on all aspects of life, including resource utilization. One notable example is the increased demand for freshwater, a lifeblood of our planet, on the other hand, the smart city vision aims to attain a smart water management goal by investing in innovative solutions such as recycled water systems. However, the problem lies in the public’s sentiment and willingness to use this new resource which discourages investors and hinders the development of this field. Therefore, in our work, we applied sentiment analysis using an extended version of the fuzzy logic and neural network model from our previous work, to find out the general public opinion regarding recycled water and to assess the effects of sentiments on the public’s readiness to use this resource. Our analysis was based on a dataset of over 1 million text content from 2013 to 2022. The results show, from spatio-temporal perspectives, that sentiment orientation and acceptance-behavior towards using recycled water have increased positively. Additionally, the public is more concerned in areas driven by the smart city vision than in areas of medium and low economic development, where investment in sensibilization campaigns is needed.
Improving the efficiency of food supplies for a trading company based on an artificial neural network Bisenovna, Kassekeyeva Aislu; Arman Ashatuly, Sadvakassov; Zhanar Beibutovna, Lamasheva; Yesilbayuly, Kerimkhulle Seyit; Zagievna, Abdrakhmanova Alfiya; Galymbekovna, Makpal Zhartybayeva; Oralkhanuly, Oralkhanov Berdibek
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4407-4417

Abstract

This article presents the proper organization of the supply chain to meet consumer demand, which is crucial for modern commercial enterprises involved in the sale of various products. Studies indicate that a company's success is linked to the satisfaction of its customers. To optimize the supply chain, this study will consider the use of artificial neural network models. The results of this model will seek a balance between demand and supply, helping determine the necessary quantity of goods to satisfy demand and prevent overproduction. By using this model, the company can fully meet the needs of its customers. Additionally, the company saves its resources and labor costs and reallocates them to other tasks. The model demonstrates the optimization of production and supply business processes, as well as an increase in efficiency.
Improved Vigenere approach incorporating pseudorandom affine functions for encrypting color images El Bourakkadi, Hamid; Chemlal, Abdelhakim; Tabti, Hassan; Kattass, Mourad; Jarjar, Abdellatif; Benazzi, Abdelhamid
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2684-2694

Abstract

This article presents an improvement to the traditional Vigenere encryption method, specifically adapted for the encryption of color images. This enhancement relies on the use of two chaotic maps widely employed in the field of cryptography. After vectorizing the original image and calculating the initialization value, which alters the seeding pixel to trigger the encryption process, our approach integrates two new large substitution tables. These tables are linked to confusion and diffusion functions, incorporating multiple reversible pseudo-random affine functions at the pixel level. Finally, a global permutation is applied to the entire resulting vector to increase the temporal complexity of potential attacks on our system. Simulations conducted on a diverse set of images of various sizes and formats demonstrate the resilience of our approach against any unexpected attacks.
Smart monitoring technique for solar cell systems using internet of things based on NodeMCU ESP8266 microcontroller Ali, Ahmed H.; El-Kammar, Raafat A.; Hamed, Hesham F. Ali; Elbaset, Adel A.; Hossam, Aya
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp2322-2329

Abstract

Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.

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