International Journal of Electrical and Computer 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.
Articles
6,301 Documents
Credal Fusion of Classifications for Noisy and Uncertain Data
Fatma Karem;
Mounir Dhibi;
Arnaud Martin;
Med Salim Bouhlel
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v7i2.pp1071-1087
This paper reports on an investigation in classification technique employed to classify noised and uncertain data. However, classification is not an easy task. It is a significant challenge to discover knowledge from uncertain data. In fact, we can find many problems. More time we don't have a good or a big learning database for supervised classification. Also, when training data contains noise or missing values, classification accuracy will be affected dramatically. So to extract groups from data is not easy to do. They are overlapped and not very separated from each other. Another problem which can be cited here is the uncertainty due to measuring devices. Consequentially classification model is not so robust and strong to classify new objects. In this work, we present a novel classification algorithm to cover these problems. We materialize our main idea by using belief function theory to do combination between classification and clustering. This theory treats very well imprecision and uncertainty linked to classification. Experimental results show that our approach has ability to significantly improve the quality of classification of generic database.
DC and RF characteristics of 20 nm gate length InAlAs/InGaAs/InP HEMTs for high frequency application
Amin Boursali;
Ahlam Guen-Bouazza;
Choukria Sayah
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i2.pp1248-1254
lnAlAs/lnGaAs/InP high electron mobility transistor (HEMT) offers excellent high frequency operation.In this work,the DC and RF performance of a 20 nm gate length enhancement mode InAlAs/InGaAs/InP high electron mobility transistor (HEMT) on InP substrate are presented.The SILVACO-TCAD simulations performed at room temperature using the appropriate model sshowed that the studied device exhibit excellent pinch-off characteristics, with a maximum transconductance of 1100ms/mm, a threshold voltage of 0,62V, and an Ion/Ioff ratio of 2.106. The cut-off frequency and maximum frequency of oscillation are 980 GHz and 1.3THz respectively. These promising results allow us to affirm that this device is intended to be used in high frequency applications.
Detection of Drug Interactions via Android Smartphone: Design and Implementation
Mourad Hadjila;
Rachid Merzougui;
Sidi Mohamed Hadj Irid
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i6.pp5371-5380
Despite the morbidity and cases of widespread drug poisoning, clinical guidelines are largely written by taking into account only one treatment at a time. The cumulative impact of multiple treatments is rarely considered. Drug treatment for people with several diseases produces a complex regimen called “polypharmacy” with a potential combination of harmful and even lethal drugs that can be prevented. This polypharmacy causes in many cases the death of some people due to drug interactions. The vast majority of these deaths can be prevented by detecting interactions before taking these medications. But the problem is that such information exists in a state that is difficult to access for the general public, much less for people with little knowledge in the field. Although the pharmacist is unmistakable and most viable source to avoid such a problem, he cannot know what the patient does not mention because he is not aware of what may affect his treatment. To remedy this, we aim in this paper to develop an ergonomic Android application that will inform the patient about the potential risks of such drug interactions. The application is optimized to handle various databases and operate automation of QR code.
Analysis of Ionospheric foF2 by Solar Activity over the Korean Peninsula
Min-Ho Jeon;
Chang-Heon Oh
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 1: February 2016
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v6i1.pp71-81
The F2 layer is the upper sector of the ionospheric F region, and it is ~250 km above sea level. It has a high electron density and thus plays an important role in shortwave communications. The variations of the critical frequency of the F2 layer (foF2) offer clues regarding the events happening within the entire F2 layer, and foF2 analysis is essential for stable shortwave communications. This study analyzes the seasonal and annual variations of the foF2 as well as the reactions of the F2 layer height at two locations in South Korea by employing the mean and standard deviation (SD) used in previous studies. To ensure a more elaborate analysis, the median and quartiles were used for analyzing the ionosphere. We thereby compensate for the limitations of the mean and SD in developing the SD, despite the convenience of the SD for probability analysis. The application of the median and quartiles for the analysis of ionospheric data led to analysis results with greater detail. This was achieved by determining the relative SD and concurrently displaying the outliers and range of variations
Analytical Model of Cage Induction Machine Dedicated to the Study of the Inner Race Bearing Fault
Marouane Hadjami;
Hubert Razik;
Mohamed El Kamel Oumaamar;
Abdelmamek Kezzar
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i1.pp458-471
This paper presents a new analytical model for inner bearing raceway defect. The model is based on the presentation of different machine inductances as Fourier series without any kind of reference frame transformation. The proposed approach shows that this model is able to give important features on the state of the motor. Simulation based on spectral analysis of stator current signal using Fast Fourier Transform (FFT) and experimental results are given to shed light on the usefulness of the proposed model.
A New Procedure to Detect Low Interaction Honeypots
Eleazar Aguirre-Anaya;
Gina Gallegos-Garcia;
Nicolás Solano Luna;
Luis Alfonso Villa Vargas
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 6: December 2014
Publisher : Institute of Advanced Engineering and Science
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Honeypots systems are an important piece of the network security infrastructure and can be deployed to accomplish different purposes such as: network sensing, capturing and learning about 0-day exploits, capturing and analyzing of black hat techniques, deterring black hats and data gathering for doing statistical analysis over the Internet traffic, among others. Nevertheless, all honeypots need to look like real systems, due to if a honeypot is unmasked, it loses its value. This paper presents a new procedure to detect low interaction honeypots, through HTTP request, regardless honeypot architecture. It is important to mention that Low Interaction Honeypots network services need to be improved in order to get trustworthy information. Otherwise, it should consider data obtained by low interaction honeypots like inaccurate and unreliable information.DOI:http://dx.doi.org/10.11591/ijece.v4i6.6885
Notice of Retraction Predicting Heart Ailment in Patients with Varying number of Features using Data Mining Techniques
T R Stella Mary;
Shoney Sebastian
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i4.pp2675-2681
Notice of Retraction-----------------------------------------------------------------------After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IAES's Publication Principles.We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.The presenting author of this paper has the option to appeal this decision by contacting ijece@iaesjournal.com.-----------------------------------------------------------------------Data mining can be defined as a process of extracting unknown, verifiable and possibly helpful data from information. Among the various ailments, heart ailment is one of the primary reason behind death of individuals around the globe, hence in order to curb this, a detailed analysis is done using Data Mining. Many a times we limit ourselves with minimal attributes that are required to predict a patient with heart disease. By doing so we are missing on a lot of important attributes that are main causes for heart diseases. Hence, this research aims at considering almost all the important features affecting heart disease and performs the analysis step by step with minimal to maximum set of attributes using Data Mining techniques to predict heart ailments. The various classification methods used are Naïve Bayes classifier, Random Forest and Random Tree which are applied on three datasets with different number of attributes but with a common class label. From the analysis performed, it shows that there is a gradual increase in prediction accuracies with the increase in the attributes irrespective of the classifiers used and Naïve Bayes and Random Forest algorithms comparatively outperforms with these sets of data.
The Development of an Application Conceived for the Design, Feasibility Study and Data Analysis of Photovoltaic Pumping Systems
B. Boukhris;
M. Mediouni;
L. Elmahni
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v7i2.pp713-719
Because of the rise in diesel and butane prices widely used for pumping, added to their negative impact on both Morocco's environment and trade balance, the use of renewable energies should sound obvious, practical and cost effective. This study offers the transformation of a traditional butane pumping system (BPS) and diesel pumping system (DPS), located on a farm nearby the city of Agadir, into an optimized solar pumping system (SPS). The suggested method is based on a techno-economic study according to the “Business-As-usual” scenario. As a first step, we have dimensioned our pumping system and chosen the elements that constitute it. As a second step, we carried out an economic analysis, based on the calculation of all costs, which makes it possible to ensure the viability of the components of our SPS over its life cycle and brought it to a discounted value. The processing of the different data is made possible thanks to the computer application “PVDesign” which we have developed. This application has allowed us to carry out a comparative study of several techniques of pumping systems. The result of the study is that the SPS beats the other systems at various levels, namely economic, environmental and technical.
CBIR of Batik Images using Micro Structure Descriptor on Android
Agus Eko Minarno;
Yuda Munarko;
Arrie Kurniawardhani
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i5.pp3778-3783
Batik is part of a culture that has long developed and known by the people of Indonesia and the world. However, the knowledge is only on the name of batik, not at a more detailed level, such as image characteristic and batik motifs. Batik motif is very diverse, different areas have their own motifs and patterns related to local customs and values. Therefore, it is important to introduce knowledge about batik motifs and patterns effectively and efficiently. So, we build CBIR batik using Micro-Structure Descriptor (MSD) method on Android platform. The data used consisted of 300 images with 50 classes with each class consists of six images. Performance test is held in three scenarios, which the data is divided as test data and data train, with the ratio of scenario 1 is 50%: 50%, scenario 2 is 70%, 30%, and scenario 3 is 80%: 20%. The best results are generated by scenario 3 with precision valur 65.67% and recall value 65.80%, which indicates that the use of MSD on the android platform for CBIR batik performs well.
Performance analysis of transformation and Bogdonov chaotic substitution based image cryptosystem
Prajwalasimha S. N.;
Basavaraj L
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i1.pp188-195
In this article, a combined Pseudo Hadamard transformation and modified Bogdonav chaotic generator based image encryption technique is proposed. Pixel position transformation is performed using Pseudo Hadamard transformation and pixel value variation is made using Bogdonav chaotic substitution. Bogdonav chaotic generator produces random sequences and it is observed that very less correlation between the adjacent elements in the sequence. The cipher image obtained from the transformation stage is subjected for substitution using Bogdonav chaotic sequence to break correlation between adjacent pixels. The cipher image is subjected for various security tests under noisy conditions and very high degree of similarity is observed after deciphering process between original and decrypted images.