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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 9,174 Documents
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Dispersion compensation of optical systems utilizing fiber Bragg grating at 15 Gbits/s Alaa Hussein Ali; Saad Mutashar; Ali Mahdi Hammadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp369-378

Abstract

Nowadays the technological advancement of the information transmission is developing very rapidly and it becomes necessary to achieve a high speed in the transmission of data as well as higher data rate. Developments in optical communication systems address these needs. However, despite all the features and advantages of optical communication systems, the dispersion is still the main challenges. In this paper and to this end, fiber Bragg grating (FBG) is used in order to overcome the dispersion issue in the wavelength division multiplexing (WDM) transmission system. The WDM transmission system is simulated using the advanced tools of Optisystem 13. The simulation program was used at a speed of 15 Gbits/s with 50Km optical fiber length based on the different input design parameters such as input signal power, optical fiber length and attenuation coefficient. In addition, the output performance parameters are discussed in terms of quality factor (Q-factor) and eye diagram. Moreover, a comparison between the proposed design and previous related works is presented.
Uncertainty and sensitivity analysis applied to a voltage series operational amplifier Mohammad Nizam Ibrahim; Zainal Hisham Che Soh; Nor Shahanim Mohamad Hadis; Ali Othman
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1347-1355

Abstract

This paper investigates the applied uncertainty and sensitivity analysis to resistors used in voltage series operational amplifier circuit. Two resistors bands are considered which are the gold band (5% uncertainty) and the silver band (10% uncertainty). To generate resistors uncertainty sample points, the SIMLAB uncertainty and sensitivity tool is used. A total of  sample points based on Sobol’ technique has been created for each resistor band. The voltage series amplifier is modelled in MATLAB/Simulink. A MATLAB script has been written to execute Monte-Carlo simulations for reading the resistor sample points, updating and executing the voltage series model and finally calculating the voltage gain. The result of uncertainty analysis shows that the produced voltage gain is uncertain within the range of  for the gold band and  for the silver band with respect to a reference voltage gain. The result of sensitivity analysis shows that each resistor, although their values are different, contributes equally contribution to the uncertainty of voltage gain.
Alzheimer’s disease detection from optimal electroencephalogram channels and tunable Q-wavelet transform Puri, Digambar Vithhalbuwa; Nalbalwar, Sanjay; Nandgaonkar, Anil; Wagh, Abhay
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1420-1428

Abstract

Alzheimer’s disease (AD) is a non-curable neuro-degenerative disorder that has no cure to date. However, it can be delayed through daily activity assessment using a robust Electroencephalogram (EEG) based system at an early stage. A selection tech- nique using a Shannon entropy to signal energy ratio is proposed to select optimal EEG channels for AD detection. A threshold for channel selection is calculated using the best detection accuracy during backward elimination. The selected EEG channels are decomposed using Tunable Q-wavelet transform (TQWT) into nine different sub- bands (SBs). Four features: Katz’s fractal dimension, Tsallis entropy, Relyi’s entropy, and kurtosis are extracted for each SB. These features are used to train and test sup- port vector machine, k-nearest neighbor, Ensemble bagged tree (EBT), decision tree, and neural network for detecting AD patients from normal subjects. 16-channel EEG signals from 12 AD and 11 normal subjects recorded using the 10-20 electrode place- ment method are used for evaluation. Ten optimized channels are selected, resulting in 32.5% compression. The experimental results of the proposed method showed promis- ing classification accuracy of 96.20% with the seventh SB features and EBT classifier. The significance of these features was inspected by using the Kruskal-Wallis test.
Optimization of learning algorithms in multilayer perceptron for sheet resistance of reduced graphene oxide thin-film Noor Aiman bin Aminuddin; Nurlaila Ismail; Marianah Masrie; Siti Aishah Mohamad Badaruddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp686-693

Abstract

Multilayer perceptron (MLP) optimization is carried out to investigate the classifier's performance in discriminating the uniformity of reduced Graphene Oxide(rGO) thin-film sheet resistance. This study used three learning algorithms: resilient back propagation (RP), scaled conjugate gradient (SCG) and levenberg-marquardt (LM). The dataset used in this study is the sheet resistance of rGO thin films obtained from MIMOS Bhd. This work involved samples selection from a uniform and non-uniform rGO thin-film sheet resistance. The input and output data were under going data pre-processing: data normalization, data randomization and data splitting. The data were dividedin to three groups; training,  validation and testing with a ratio of 70%: 15%: 15%, respectively. A varying number of hidden neurons optimized the learning algorithms in MLP from 1 to 10. Their behavior helped establish the best learning algorithms in discriminating MLP for rGO sheet resistance uniformity. The performances measured were the accuracy of training, validation and testing dataset, mean squared errors (MSE) andepochs. All the analytical work in this study was achieved automatically via MATLAB software version R2018a. It was found that the LM is dominant inthe optimization of a learning algorithm in MLP forrGO sheet resistance.The MSE for LM is the most reduced amid SCG and RP. 
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.
Day-ahead solar irradiance forecast using sequence-to-sequence model with attention mechanism Sowkarthika Subramanian; Yasoda Kailasa Gounder; Sumathi Lingana
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 2: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i2.pp900-909

Abstract

The increasing integration of distributed energy resources (DERs) into power grid makes it significant to forecast solar irradiance for power system planning. With the advent of deep learning techniques, it is possible to forecast solar irradiance accurately for a longer time. In this paper, day-ahead solar irradiance is forecasted using encoder-decoder sequence-to-sequence models with attention mechanism. This study formulates the problem as structured multivariate forecasting and comprehensive experiments are made with the data collected from National Solar Radiation Database (NSRDB). Two error metrics are adopted to measure the errors of encoder-decoder sequence-to-sequence model and compared with smart persistence (SP), back propagation neural network (BPNN), recurrent neural network (RNN), long short term memory (LSTM) and encoder-decoder sequence-to-sequence LSTM with attention mechanism (Enc-Dec-LSTM). Compared with SP, BPNN and RNN, Enc-Dec-LSTM is more accurate and has reduced forecast error of 31.1%, 19.3% and 8.5% respectively for day-ahead solar irradiance forecast with 31.07% as forecast skill.
Password authentication scheme based on smart card and QR code Mushtaq Hasson; Ali A. Yassin; Abdulla J. Yassin; Abdullah Mohammed Rashid; Aqeel A. Yaseen; Hamid Alasadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp140-149

Abstract

As a hopeful computing paradigm, cloud services are obtainable to end users based on pay-as-you-go service. Security is represented one of the vital issues for the extended adoption of cloud computing, with the object of accessing several cloud service providers, applications, and services by using anonymity features to authenticate the user. We present a good authentication scheme based on quick response (QR) code and smart card. Furthermore, our proposed scheme has several crucial merits such as key management, mutual authentication, one-time password, user anonymity, freely chosen password, secure password changes, and revocation by using QR code. The security of proposed scheme depends on crypto-hash function, QR-code validation, and smart card. Moreover, we view that our proposed scheme can resist numerous malicious attacks and are more appropriate for practical applications than other previous works. The proposed scheme has proved as a strong mutual authentication based on burrows-abadi-needham (BAN) logic and security analysis. Furthermore, our proposed scheme has good results compared with related work.
An agent based model for assessing transmission dynamics and health systems burden for COVID-19 Narassima M. S.; Anbuudayasankar S. P.; Guru Rajesh Jammy; Rashmi Pant; Lincoln Choudhury; Aadharsh Ramakrishnan; Denny John
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1735-1743

Abstract

Coronavirus disease of 2019 (COVID-19) pandemic has caused over 230 million infections with more than 4 million deaths worldwide. Researches have been using various mathematical and simulation techniques to estimate the future trends of the pandemic to help the policymakers and healthcare fraternity. Agent-based models (ABM) could provide accurate projections than the compartmental models that have been largely used. The present study involves a simulation of ABM using a synthetic population from India to analyze the effects of interventions on the spread of the disease. A disease model with various states representing the possible progression of the disease was developed and simulated using AnyLogic. The results indicated that imposing stricter non-pharmaceutical interventions (NPI) lowered the peak values of infections, the proportion of critical patients, and the deceased. Stricter interventions offer a larger time window for the healthcare fraternity to enhance preparedness. The findings of this research could act as a start-point to understand the benefits of ABM-based models for projecting infectious diseases and analyzing the effects of NPI imposed.
Comparative study between fast terminal and second order sliding mode controls applied to a wind energy conversion system Touati Abdelwahed; Majdoul Radouane; Taouni Abderrahim; Mohamed Aboulfatah; Rabbah Nabila
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp765-779

Abstract

A he wind energy conversion system (WECS) consists of many subsystems, which present control difficulties due to the strong nonlinearities of the models and the effects of internal or external disturbances. In this work, the WECS is based on a doubly feed induction generator (DFIG) directly connected to the stator side network and interconnected via a power converter on the rotor side. The aim of the control strategy is to achieve regular regulation of the powers supplied by the generator and to produce energy of better quality. in order to improve the dynamic behavior of the doubly fed induction generator (DFIG); a comparative study is presented between two advanced control strategies; the second order sliding mode control and the FTSMC fast terminal sliding mode control. The proposed advanced tracking controller is synthesized based on the Lyapunov stability theory and guarantees the existence of the sliding mode around the sliding surface in a finite time. The analysis of the simulation results under the Matlab/Simulink environment confirms the effectiveness of the proposed methods through the performances obtained.
SMUPI-BIS: a synthesis model for users’ perceived impact of business intelligence systems Intedhar Shakir Nasir; Ayad Hameed Mousa; Ihab L. Hussein Alsammak
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i3.pp1856-1867

Abstract

Business intelligence is a collection of methodologies, methods, architectures, and technologies that convert raw data into significant and useful information used by organizations to enable more effective strategic, tactical, and operational insights and decision-making.  In spite of several studies have examined the critical success factors and development of business intelligence System, but few relevant studies have investigated perceptions of end-users Business Intelligence Systems. Furthermore, none of those studies was performed in a Higher Education Sector in Iraq. Consequently, the study aims to determine the business intelligence system features influencing perceived impact end users’ and of using business intelligence systems in Iraqi educational institutes. A technology acceptance model and technology organization environment framework were syntheses as a basis to develop a research model for business intelligence users' perceived impact and adopt of business intelligence systems named (SMUPI-BIS). Later, an online instrument (questionnaire) was designed to gather data from the business intelligence system users in five Iraqi universities. Twenty-one hypotheses were proposed and later tested. Then, for data analysis, the authors used several methods such as hierarchical regression, one-way ANOVA, descriptive statistics as well as structural equation modeling (SEM). The main outcomes of this study suggest that decision support, information quality, and real-time reporting are the most significant system characteristics influencing end users' perceived impact and their usage of business intelligence systems.

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