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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 67 Documents
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Search results for , issue "Vol 21, No 2: February 2021" : 67 Documents clear
Current model predictive control for three-phase active power filter using cascaded h-bridge multilevel converter Abdelkader Yousfi; Youcef Bot; Fayçal Mehedi; Abdelkader Chaker
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Different technologies in particular in the medium and high-power conversion were implemented and taken into consideration in the last few years. These inverter topologies have been demonstrated to ensure the generation of high-quality voltage waveforms based on power half-conductor switches, which operate on the fundamental frequency. The multilevel inverter H-bridge is a promising alternative among the available multi-level inverter topologies. A predictional current control algorithm for multi-level converters and use on a three-phase cascaded inverter H-bridge. This article reports on a comparison of two check methods associated with a shunt active power filter based on the cascaded inverter of the three- Level type. The first approach is the traditional PI control unit and the second is the predictive current control unit. The reference current for the shunt active power filter is provided by the p-q control strategy for reactive power compensation and current harmonics. The cascade-type three-level inverter has more advantages over a two-leaved inverter; the simulation output of APF is checked by MATLAB/Simulink. The predictive controlled the APF associated with the three-level inverter shows more performances and efficiency compared to the conventional control algorithms.
Revealing and evaluating the influence of filters position in cascaded filter: application on the ECG de-noising performance disparity Abdenour Allali; Arres Bartil; Lahcene Ziet; Amar Hebibi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp829-838

Abstract

In this paper, a new optimization on windowing technique based on finite impulse response (FIR) filters is proposed for revealing and evaluating the Influence of filters position in cascaded filter tested on the ECG signal de-noising. baseline wander (BLW), power line interference (PLI) and electromyography (EMG) noises are getting removed. The performance of the adopted method is evaluated on the PTB diagnostic database. Subsequently, the comparisons are based on signal to noise ratio (SNR) improvement and mean square error (MSE) minimization. Where the Rectangular, and Kaiser windows have been used for the more potent performances. The disparity average (DA) of SNR values is detected; in both Kaiser and Rectangular windows are assessed by ±0.38046dB and ±0.70278dB respectively, while the MSE values were constant. The excellent configuration or filters position (H-B-L) of the filtration system is selected according to high measurements of SNR and low MSE too, to de-noise the ECG signals. First of all, this applied approach has led to 31.30 dB SNR improvement with MSE minimization of 26. 43%. This means that there is a significant contribution to improving the field of filtration.
Pythagorean fuzzy N-Soft groups M. Shazib Hameed; Salman Mukhtar; Haq Nawaz Khan; Shahbaz Ali; Muhammad Haris Mateen; Muhammad Gulzar
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1030-1038

Abstract

We elaborate in this paper a new structure pythagorean fuzzy $N$-soft groups which is the generalization of intuitionistic fuzzy soft group initiated by Karaaslan in 2013. In Pythagorean fuzzy N-soft sets concepts of fuzzy sets, soft sets, N-soft sets, fuzzy soft sets, intuitionistic fuzzy sets, intuitionistic fuzzy soft sets, Pythagorean fuzzy sets, Pythagorean fuzzy soft sets are generalized. We also talk about some elementary basic concepts and operations on Pythagorean fuzzy N-soft sets with the assistance of illusions. We additionally define three different sorts of complements for Pythagorean fuzzy N-soft sets and examined a few outcomes not hold in Pythagorean fuzzy N-soft sets complements as they hold in crisp set hypothesis with the assistance of counter examples. We further talked about {$(\alpha, \beta, \gamma)$-cut of Pythagorean fuzzy N-soft set and their properties}. We likewise talk about some essential properties of Pythagorean fuzzy N-soft groups like groupoid, normal group, left and right cosets, $(\alpha, \beta,\gamma)$-cut subgroups and some fundamental outcomes identified with these terms. Pythagorean fuzzy N-soft sets is increasingly efficient and adaptable model to manage uncertainties. The proposed models of Pythagorean fuzzy N-soft groups can defeat a few disadvantages of the existing statures.
Smart fire monitoring system with remote control usingZigBee network Jung kyu Park; Jaeho Kim
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1132-1139

Abstract

There are several differences between the two types of alarm systems, conventionalsystems and addressable systems.  It is important to carefully determine the introduc-tion of a fire alarm system according to the installation environment.  Talking aboutthe main difference relates to how the connected device communicates with the maincontrol panel by sending a signal.  Cost is another factor that can be a determinant ofyour chosen fire alarm system. In this paper, we proposed smart addressable fire detec-tion system.  In the proposed system, IoT was used and the network was constructedusing ZigBee module.  In the configured network, it consists of a local server and acontrol server. The local server controls the addressing sensor and sends the informa-tion obtained from the sensor to the control server.  The control server receives datatransmitted from the local server and enables quick fire action.  In the actual imple-mentation, the local server used the Lycra controller and ZigBee module. In addition,the control server used the Raspberry Pi and ZigBee modules and connected to theEthernet so that the administrator could monitor or control the local server.
Classification techniques’ performance evaluation for facial expression recognition Mayyadah R. Mahmood; Maiwan B. Abdulrazaq; Subhi R. M. Zeebaree; Abbas Kh. Ibrahim; Rizgar Ramadhan Zebari; Hivi Ismat Dino
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1176-1184

Abstract

Facial exprestion recognition as a recently developed method in computer vision is founded upon the idea of analazing the facial changes in which are witnessed due to emotional impacts on an individual. This paper provides a performance evaluation of a set of supervised classifiers used for facial expression recognition based on minimum features selected by chi-square. These features are the most iconic and influential ones that have tangible value for result dermination. The highest ranked six features are applied on six classifiers including multi-layer preceptron, support vector machine, decision tree, random forest, radial baised function, and k-nearest neioughbor to figure out the most accurate one when the minum number of features are utilized. This is done via analyzing and appraising the classifiers’ performance. CK+ is used as the research’s dataset. Random forest with the total accuracy ratio of 94.23 % is illustrated as the most accurate classifier amongst the rest. 
Optimisation of LEACH protocol based on a game theory clustering approach for wireless sensor networks Yassine Oukessou; Mohamed Baslam; Mohamed Oukessou
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp938-944

Abstract

The wireless sensor network clustering routing mechanism is the best multi-hop algorithm used to aggregate data from sensors to the base station. Therefore the elected nodes refuse to be a clusters heads CH and have a selfish and non cooperative behaviours in each group cluster. All that due to the high electric energy consumption, and especially that the most existing sensors are powered by batteries. In this paper, we will analyse the selfishness behaviour by using the most knowing mathematical model Game theory to improve the interaction decision making for the CH selection, and make a comparison with LEACH protocol.
Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules Md Abul Kalam Azad; Anup Majumder; Jugal Krishna Das; Md Imdadul Islam
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1140-1150

Abstract

The performance of a cognitive radio network (CRN) mainly depends on the faithful signal detection at fusion center (FC). In this paper, the concept of weighted Fuzzy rule in Iris data classification, as well as, four machine learning techniques named fuzzy inference system (FIS), fuzzy c-means clustering (FCMC), support vector machine (SVM) and convolutional neural network (CNN) are applied in signal detection at FC taking signal-to-interference plus noise ratio of secondary users as parameter. The weighted Fuzzy rule gave the detection accuracy of 86.6%, which resembles the energy detection model of majority rule of FC; however, CNN gave an accuracy of 91.3% at the expense of more decision time. The FIS, FCMC and SVM gave some intermediate results; however, the combined method gave the best result compared to that of any individual technique.
A new SDN-based load balancing algorithm for IoT devices Hind Sounni; Najib El kamoun; Fatima Lakrami
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1209-1217

Abstract

Nowadays, the emergence of the Internet of things devices has wholly revolutionized the customer's communication habits. The information can be collected at any time and anywhere. However, the mobility of communication devices in a dense network results inseveral problems, such as unbalanced network load and increased bandwidth demands, which decrease the network performance. To deal with these issues, this paper proposes a new load balancing algorithm based on the software-defined Network to enhance the performance of mobile devices communication over a Wi-Fi network. The use of the software-defined network automatizes the configuration of the network through a centralized controller; it provides programmability and an overall view of the network, along with optimizing resource allocation based on real-time network information, which facilitates the implementation of our algorithm. The proposed algorithm is implemented and evaluated through simulation using mininet-WiFi. The results indicate that our proposed method provides an efficient network load balancing and improves performancdevices' performance.
V2X communication system with non-orthogonal multiple access: outage performance perspective Tu-Trinh Nguyen; Dinh-Thuan Do
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp854-864

Abstract

To achieve low-latency and high-reliability (LLHR) for applications in the vehicle-toeverything (V2X) networks, the non-orthogonal multiple access (NOMA) based Long Term Evolution (LTE)-based is introduced a promising technology. NOMA-V2X provides higher spectrum efficiency compared with the orthogonal multiple access (OMA) based V2X. This study propose two-way relay assisted NOMA-V2X transmission by exploiting amplify-and-forward (AF) and full-duplex. We derive expressions of outage probability to evaluate performance of two vehicles and to improve the quality of service (QoS) for the device with the poor channel conditions. These expressions are further verified by Monte-Carlo simulations.
SQL injection attacks countermeasures assessments Mamdouh Alenezi; Muhammad Nadeem; Raja Asif
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1121-1131

Abstract

SQL injections attacks have been rated as the most dangerous vulnerability of web-based systems over more than a decade by OWASP top ten. Though different static, runtime and hybrid approaches have been proposed to counter SQL injection attacks, no single approach guarantees flawless prevention/ detection for these attacks. Hundreds of components of open source and commercial software products are reported to be vulnerable for SQL injection to CVE repository every year. In this mapping study, we identify different existing approaches in terms of the cost of computation and protection offered. We found that most of the existing techniques claim to offer protection based on the testing on a very small or limited scale. This study dissects each proposed approach and highlights their strengths and weaknesses and categorizes them based on the underlying technology used to detect or counter the injection attacks.

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