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International Journal of Electrical and Computer Engineering
ISSN : 20888708     EISSN : 27222578     DOI : -
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.
Articles 6,301 Documents
Multi-kernel CNN block-based detection for COVID-19 with imbalance dataset Muhammad Khaerul Naim Mursalim; Ade Kurniawan
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2467-2476

Abstract

COVID-19, which originated from Wuhan, rapidly spread throughout the world and became a public health crisis. Recognizing the positive cases at the earliest stage was crucial in order to restrain the spread of this virus and to perform medical treatment quickly for patients affected. However, the limited supply of RT-PCR as a diagnosis tool caused greatly delay in obtaining examination results of the suspected patients. Previous research stated that using radiologic images could be utilized to detect COVID-19 before the symptoms appeared. With the rapid development of Artificial intelligence in medical imaging in recent years, deep learning as the core of this technology could achieve human-level-performance in diagnostic accuracy. In this paper, deep learning was implemented to detect COVID-19 using a chest X-ray dataset. The proposed model employed a multi-kernel convolution neural network (CNN) block combined with pre-trained ResNet-34 to overcome an imbalanced dataset. The model block adopted different kernel sizes as follows 1x1, 3x3, 5x5, and 7x7. The findings show that the proposed model is capable of performing binary and three class classification tasks with an accuracy of 100% and 93.51% in the validation phase and 95% and 83% in the test phase, respectively.
Implementation and evaluation of a 2.4 GHz multi-hop WSN: LoS, NLoS, different floors, and outdoor-to-indoor communications Vasin Chaoboworn; Yoschanin Sasiwat; Dujdow Buranapanichkit; Hiroshi Saito; Apidet Booranawong
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5170-5179

Abstract

In this paper, the communication reliability of a 2.4 GHz multi-hop wireless sensor network (WSN) in various test scenarios is evaluated through experiments. First, we implement an autonomous communication procedure for a multi-hop WSN on Tmote sky sensor nodes; 2.4 GHz, an IEEE 802.15.4 standard. Here, all nodes including a transmitter node (Tx), forwarder nodes (Fw), and a base station node (BS) can automatically work for transmitting and receiving data. The experiments have been tested in different scenarios including: i) in a room, ii) line-of-sight (LoS) communications on the 2nd floor of a building, iii) LoS and non-line-of-sight (NLoS) communications on the 1st floor to the 2nd floor, iv) LoS and NLoS communications from outdoor to the 1st and the 2nd floors of the building. The experimental results demonstrate that the communication reliability indicated by the packet delivery ratio (PDR) can vary from 99.89% in the case of i) to 14.40% in the case of iv), respectively. Here, the experiments reveal that multi-hop wireless commutations for outdoor to indoor with different floors and NLoS largely affect the PDR results, where the PDR more decreases from the best case (i.e., the case of a)) by 85.49%. Our research methodology and findings can be useful for users and researchers to carefully consider and deploy an efficient 2.4 GHz multi-hop WSN in their works, since different WSN applications require different communication reliability level.
Online instrument systems in reality for remote wiring and measurement of electronic in e-learning from LabVIEW+NI ELVIS II vs embedded system+web services Fahd Ouatik; Mustapha Raoufi; Farouk Ouatik; Mohammed Skouri
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1178-1185

Abstract

Recently The prestigious universities of the world strive and aim to computerize their distance education service and more specifically the remote practical work, which allows students to manipulate electronic experiments via the web, for to solve a set of problems: pedagogical, management, security, restriction by time and place and the problems the overcrowding of students in universities. This paper will describe the E@SLab system developed by the university Cadi Ayyad member of the e-live project funded by EU in the frame of ERASMUS+E@SLab is based on the latest technologies of development and respects educational and pedagogical standards. E@SLab offers 2 versions different of remote laboratory: first version (s1) is an embedded system its part software is node js+Ubuntu and the part hardware a card pcduino or raspebery. The second version (s2) is based on LABview and its hardware part is the NI ELVIS II pedagogical map. In this paper, we will compare and discuss the architecture, performance of the 2 versions of E@SLAB and review other famous approaches NetLab, VISIR, for comparing with E@SLab with the intention show its singularity.
Model reduction design for continuous systems with finite frequency specifications Miloud Koumir; Abderrahim El-Amrani; Ismail Boumhidi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3956-3963

Abstract

This paper is concerned with the problem of model reduction design for continuous systems in Takagi-Sugeno fuzzy model. Through the defined FF H∞ gain performance, sufficient conditions are derived to design model reduction and to assure the fuzzy error system to be asymptotically stable with a FF H∞ gain performance index. The explicit conditions of fuzzy model reduction are developed by solving linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
The impact of sentiment analysis from user on Facebook to enhanced the service quality Daniel D. Albesta; Michael L. Jonathan; Muhammad Jawad; Oktovianus Hardiawan; Derwin Suhartono
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3424-3433

Abstract

Facebook's influence on the modern social media platform is undoubtedly enormous. While it has gotten a backlash for its inability to control its influence over important affairs, there are still many questions regarding people's perception of Facebook and their sentiment over Facebook. This paper's role in this ongoing debate is to give a glimpse of people's sentiment and perception of Facebook in recent times. By collecting samples data from Facebook's Top Page, this paper hopes to represent a significant amount of people's aspirations towards this company. By processing the data with a processing tool to construct and model out the data and a sentiment analyzer tool helps determine the sentiment, this paper can deduce a 600-comment worth of processed data. The results from the 600 sampled comments concluded that the sentiments towards Facebook are 41.50% negative comments, 22.83% neutral comments, and 35.67% positive comments.
A new Li-ion battery charger with charge mode selection based on 0.18 um CMOS for phone applications Fouad Farah; Mustapha El Alaoui; Abdellali Elboutahiri; Mounir Ouremchi; Karim El Khadiri; Ahmed Tahiri; Hassan Qjidaa
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp1994-2002

Abstract

A new architecture of Li-Ion battery charger with charge mode selection is presented in this work. To ensure high efficiency, good accuracy and complete protection mode, we propose an architecture based on variable current source, temperature detector and power control. To avoid the risk of damage, the Li- Ion batteries charging process must change between three modes of current (trickle current (TC), constant current (CC), and constant voltage (CV)) in order to charge the battery with degrading current. However, the interest of this study is to develop a fast battery charger with high accuracy that is able to switch between charging modes without reducing its power efficiency, and to guarantee a complete protection mode. The proposed charger circuit is designed to control the charging process in three modes using the charging mode selection. The obtained results show that the Li-ion batteries can be successfully charged in a short time without reducing their efficiency. The proposed charger is implemented in 180 nm CMOS technology with a maximum charging current equal to 1 A and a maximum battery voltage equal to 4.22 V, (with input range 2.7-4.5 V). The chip area is 1.5 mm2 and the power efficiency is 90.09 %.
Robust recognition technique for handwritten Kannada character recognition using capsule networks N. Shobha Rani; Manohar N.; Hariprasad M.; Pushpa B. R.
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp383-391

Abstract

Automated reading of handwritten Kannada documents is highly challenging due to the presence of vowels, consonants and its modifiers. The variable nature of handwriting styles aggravates the complexity of machine based reading of handwritten vowels and consonants. In this paper, our investigation is inclined towards design of a deep convolution network with capsule and routing layers to efficiently recognize  Kannada handwritten characters.  Capsule network architecture is built of an input layer,  two convolution layers, primary capsule, routing capsule layers followed by tri-level dense convolution layer and an output layer.  For experimentation, datasets are collected from more than 100 users for creation of training data samples of about 7769 comprising of 49 classes. Test samples of all the 49 classes are again collected separately from 3 to 5 users creating a total of 245 samples for novel patterns. It is inferred from performance evaluation; a loss of 0.66% is obtained in the classification process and for 43 classes precision of 100% is achieved with an accuracy of 99%. An average accuracy of 95% is achieved for all remaining 6 classes with an average precision of 89%.
An ICA-ensemble learning approaches for prediction of RNA-seq malaria vector gene expression data classification Micheal Olaolu Arowolo; Marion O. Adebiyi; Ayodele A. Adebiyi; Charity Aremu
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1561-1569

Abstract

Malaria parasites introduce outstanding life-phase variations as they grow across multiple atmospheres of the mosquito vector. There are transcriptomes of several thousand different parasites. (RNA-seq) Ribonucleic acid sequencing is a prevalent gene expression tool leading to better understanding of genetic interrogations. RNA-seq measures transcriptions of expressions of genes. Data from RNA-seq necessitate procedural enhancements in machine learning techniques. Researchers have suggested various approached learning for the study of biological data. This study works on ICA feature extraction algorithm to realize dormant components from a huge dimensional RNA-seq vector dataset, and estimates its classification performance, Ensemble classification algorithm is used in carrying out the experiment. This study is tested on RNA-Seq mosquito anopheles gambiae dataset. The results of the experiment obtained an output metrics with a 93.3% classification accuracy.
Experimental study of the impact of dust on azimuth tracking solar PV in Sharjah Mohamed A. M. Abdelsalam; Fahad Faraz Ahmad; Abdul-Kadir Hamid; Chaouki Ghenai; Oussama Rejeb; Monadhel Alchadirchy; Waleed Obaid; Mamdouh El Haj Assad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3671-3681

Abstract

Dust is one of the significant constraints in utilizing solar photovoltaic systems under harsh weather conditions in the desert regions due to creating a shadow that blocks solar irradiance from reaching solar cells and consequently, significantly reducing their efficiency. In this research, experimental study was performed to comprehend the nature of dust particles and their impact on the electrical power output that is generated from azimuth tracking solar PV modules under Sharjah environmental conditions in winter season. According to laboratory experiments, the power losses are linearly related to the dust accumulated density on the surface of the solar panel with a slope of 1.27% per g/m2. The conducted Outdoor studies revealed that the absolute reduction in output power increased by 8.46% after 41 continuous days with one low-intensity rainy day. The linear relationship obtained from indoor experiments was applied later to estimate the dust deposited density on the outdoor setup. The results showed that a regular cleaning process every two weeks is recommended to maintain the performance and to avoid the soiling loss. This work will help engineers in the solar PV plants to forecast the dust impact and figure out the regularity of the cleaning process in case of single axis tracking systems.
Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine Aditi Agrawal; Rajeev Paulus
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3176-3185

Abstract

Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high.

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