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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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Determination of optimized sleep interval for 10 gigabit-passive optical network using learning intelligence Affida M. Zin; Sevia Mahdaliza Idrus; Nur Asfahani Ismail; Arnidza Ramli; Fadila Mohd Atan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2663-2671

Abstract

The overall aim of this project is to investigate the application of a machine learning method in finding the optimized length of asleep time interval (TAS) in a cyclic sleep mechanism (CSM). Since past decade, the implementations of CSM in the optical network unit (ONU) to reduce the energy consumption in 10 gigabit-passive optical network (XG-PON) were extensively researched. However, the newest era sees the emergence of various network traffic with stringent demands that require further improvements on the TAS selection. Since conventional methods utilize complex algorithm, this paper presents the employment of an artificial neural network (ANN) to facilitate ONU to determine the optimized TAS values using learning from past experiences. Prior to simulation, theoretical analysis was done using the M/G/1 queueing system. The ANN was than trained and tested for the XG-PON network for optimal TAS decisions. Results have shown that towards higher network load, a decreasing TAS trend was observed from both methods. A wider TAS range was recorded from the ANN network as compared to the theoretical values. Therefore, these findings will benefit the network operators to have a flexibility measure in determining the optimal TAS values at current network conditions.
Ensemble-based face expression recognition approach for image sentiment analysis Gubin Moung, Ervin; Chuan Wooi, Chai; Mohd Sufian, Maisarah; Kim On, Chin; Ahmad Dargham, Jamal
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2588-2600

Abstract

Sentiment analysis based on images is an evolving area of study. Developing a reliable facial expression recognition (FER) device remains a difficult challenge as recognizing emotional feelings reflected in an image is dependent on a diverse set of factors. This paper presented an ensemble-based model for FER that incorporates multiple classification models: i) customized convolutional neural network (CNN), ii) ResNet50, and iii) InceptionV3. The model averaging ensemble classifier method is used to ensemble the predictions from the three models. Subsequently, the proposed FER model is trained and tested on a dataset with an uncontrolled environment (FER-2013 dataset). The experiment demonstrated that ensembling multiple classifiers outperformed all single classifiers in classifying positive and neutral expressions (91.7%, 81.7% and 76.5% accuracy rate for happy, surprise, and neutral, respectively). However, when classifying disgust, anger, and sadness, the ResNet50 model alone is the better choice. Although the Custom CNN performs the best in classifying fear expression (55.7% accuracy), the proposed FER model can still classify fear expression with comparable performance (52.8% accuracy). This paper demonstrated the potential of using the ensemble-based method to enhance the performance of FER. As a result, the proposed FER model has shown a 72.3% accuracy rate.
Automatic recognition of Arabic alphabets sign language using deep learning Rehab Mustafa Duwairi; Zain Abdullah Halloush
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2996-3004

Abstract

Technological advancements are helping people with special needs overcome many communications’ obstacles. Deep learning and computer vision models are innovative leaps nowadays in facilitating unprecedented tasks in human interactions. The Arabic language is always a rich research area. In this paper, different deep learning models were applied to test the accuracy and efficiency obtained in automatic Arabic sign language recognition. In this paper, we provide a novel framework for the automatic detection of Arabic sign language, based on transfer learning applied on popular deep learning models for image processing. Specifically, by training AlexNet, VGGNet and GoogleNet/Inception models, along with testing the efficiency of shallow learning approaches based on support vector machine (SVM) and nearest neighbors algorithms as baselines. As a result, we propose a novel approach for the automatic recognition of Arabic alphabets in sign language based on VGGNet architecture which outperformed the other trained models. The proposed model is set to present promising results in recognizing Arabic sign language with an accuracy score of 97%. The suggested models are tested against a recent fully-labeled dataset of Arabic sign language images. The dataset contains 54,049 images, which is considered the first large and comprehensive real dataset of Arabic sign language to the furthest we know.
Virtual reality technology to support the independent living of children with autism Laiali Almazaydeh; Reham Al-Mohtadi; Mohammed Abuhelaleh; Arar Al Tawil
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp4111-4117

Abstract

Many designed systems have shown the potential of virtual reality (VR) to greatly transform autism treatment studies. Indeed, the literature shows that treatment via VR is appropriate for effective and repeatable training, without the intense anxiety, allowing trainees to recognize and modulate errors as they occur. This study evaluates the effectiveness of a new VR-based learning environment designed to safely practice and rehearse the daily activities related to the school world in children affected with autism. A total of nine children with autism actively enrolled in the study to learn and test their street crossing skills and social attention. Incremental change of difficulty levels has been added to the designed environment to generalize real-world situations, this includes overlaid distraction audio and increased vehicles intensity and speed. In order to enhance the learning experience, the real-time feedback is given according to the participant’s behavior, additionally, post processing profile is given for analysis purpose, where the participant’s behavior can be reviewed by parents and therapist to determine whether the participant’s mistakes are in decision making or focusing attention. The Wilcoxon signed-rank test for a single sample was used to test the change in the skills of participants with autism after using the educationally and therapeutically VR technology compared to a baseline. As a result, significant effects were found on the behavioral measures indicating that the VR-based learning environment is promoting a positive and informative learning environment.
Dominating set based arbitrary oriented bilingual scene text localization Mirle Jayanth, Roopa; Kapanaiah, Mahantesh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3730-3738

Abstract

Localizing and recognizing arbitrarily oriented text in natural scene images is the biggest challenge. It is because scene texts are often erratic in shapes. This paper presents a simple and effective graph representational algorithm for detecting arbitrary-oriented text location to smoothen the text recognition process because of its high impact and simplicity of representation. An arbitrarily oriented text can be horizontal, vertical, perspective, curved (diagonal/off-diagonal), or even a combination. As a pre-processing step, image enhancement is performed in the frequency domain to improve the representation of images that are invariant to intensity. It is necessary to draw bounding boxes for each candidate character in the scene images to extract text regions. This step is carried out by utilizing the advantage of the region-based approach called maximally stable extremal regions. A typical problem with curved text localization is that non-text objects may occur within localized text regions. Our method is the first in the literature that searches for dominating sets to solve this problem. This dominating set method outperforms several traditional methods, including deep learning methods used for arbitrary text localization, on challenging datasets like 13th international conference on document analysis and recognition (ICDAR 2015), multi-script robust reading competition (MRRC), CurvedText 80 (CUTE80), and arbitrary text (ArT).
Design of field programmable gate array-based data processing system for multi global positioning system receiver Zainul Abidin; Nauval Aryawiratama; Adharul Muttaqin; Ryoichi Miyauchi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3466-3476

Abstract

A global positioning system (GPS) sensor is needed for a ballistic/moving object to do position tracking. In previous study, a multi GPS processing system was made using several microcontrollers and data processing cannot be done simultaneously. Therefore, it was considered as ineffective system. In this research, field programmable gate array (FPGA)-based data processing system for multi-GPS receiver was proposed. The proposed system was designed to reduce root mean square error (RMSE). There are two main processes in the proposed system which work in parallel, i.e. data parsing and data processing. Raw data from GPS receiver was collected and calculated to get average value, then sent it through serial communication to show result. Experimental results confirm the RMSE value of the proposed system is smaller than the conventional one. The RMSE for latitude, longitude, and altitude decrease by 38.46%, 58.28%, and 24.80%, respectively.
Improved noisy gradient descent bit-flipping algorithm over Rayleigh fading channel Reza Biazaran; Hermann Joseph Helgert
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2699-2710

Abstract

Gradient descent bit flipping (GDBF) and its many variants have offered remarkable improvements over legacy, or modified, bit flipping decoding techniques in case of decoding low density parity check (LDPC) codes. GDBF method and its many variants, such as noisy gradient descent bit flipping (NGDBF) have been extensively studied and their performances have been assessed over multiple channels such as binary symmetric channel (BSC), binary erasure channel (BEC) and additive white Gaussian noise (AWGN) channel. However, performance of the said decoders in more realistic channels or channel conditions have not been equally studied. An improved noisy gradient descent bit flipping algorithm is proposed in this paper that optimally decodes LDPC encoded codewords over Rayleigh fading channel and under various fade rates. Comparing to NGDBF method, our proposed decoder provides substantial improvements in both error performance of the code, and in the number of iterations required to achieve the said error performance. It subsequently reduces the end-to-end latency in applications with low or ultra-low latency requirements.
Robust control of aircraft flight in conditions of disturbances Satybaldina Dana Karimtaevna; Amirzhanova Zinara Bekbolatovna; Mashtayeva Aida Assilkhanovna
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3572-3582

Abstract

One of the most dangerous parts of the flight is the landing phase, as most accidents occur at this stage. In order to reduce the effect of the low-level wind shear on the longitudinal motion of the aircraft in the glide path landing mode (task) a robust H- control is proposed. Dynamic models of the plane and wind shear are built. H2 and H∞ synthesis methods are investigated for the task of aircraft flight control in a vertical plane during landing under conditions of undefined disturbances. Both control methods allow to reduce height deviation significantly. However, suboptimal control H∞ provides better quality of transition processes both in height and speed than optimal control H2. The results of simulation of the synthesized system confirm the effectiveness of H∞ - control for increasing robust stability to uncertainties caused by wind disturbances.
An efficient cloudlet scheduling via bin packing in cloud computing Amine Chraibi; Said Ben Alla; Abdellah Ezzati
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp3226-3237

Abstract

In this ever-developing technological world, one way to manage and deliver services is through cloud computing, a massive web of heterogenous autonomous systems that comprise adaptable computational design. Cloud computing can be improved through task scheduling, albeit it being the most challenging aspect to be improved. Better task scheduling can improve response time, reduce power consumption and processing time, enhance makespan and throughput, and increase profit by reducing operating costs and raising the system reliability. This study aims to improve job scheduling by transferring the job scheduling problem into a bin packing problem. Three modifies implementations of bin packing algorithms were proposed to be used for task scheduling (MBPTS) based on the minimisation of makespan. The results, which were based on the open-source simulator CloudSim, demonstrated that the proposed MBPTS was adequate to optimise balance results, reduce waiting time and makespan, and improve the utilisation of the resource in comparison to the current scheduling algorithms such as the particle swarm optimisation (PSO) and first come first serve (FCFS).
Novel asymmetric space vector pulse width modulation for dead-time processing in three-phase power converters Indriarto Yuniantoro; Mochammad Haldi Widianto
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2346-2352

Abstract

This research analyzes the asymmetric control strategies in multilevel inverters, including asymmetric techniques in space vector modulation of power converters. Modulation parameters such as reference voltage vector (Vref), switching time, and duty cycle are derived in the three-dimensional spatial vector geometry formulation. Asymmetric space vector pulse width modulation (SVPWM) is unique in specifying modulation parameters, has unequal tetrahedron patterns, accompanied by application examples for the upper and lower sector pairs of a tetrahedron. The combination of the switch in the form of an inclined cylinder produces twelve pairs of asymmetric tetrahedrons where the voltage vector positions are in the other twenty-four tetrahedrons. The calculation shows processing dead-time in switching, which is used for current compensation in three-phase power converters.

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