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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 66 Documents
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Search results for , issue "Vol 24, No 2: November 2021" : 66 Documents clear
An efficient data masking method for encrypted 3D mesh model Manikamma Malipatil; D. C. Shubhangi
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp957-964

Abstract

The industrial 3D mesh model (3DMM) plays a significant part in engineering and computer aided designing field. Thus, protecting copyright of 3DMM is one of the major research problems that require significant attention. Further, the industries started outsourcing its 3DMM to cloud computing (CC) environment. For preserving privacy, the 3DMM are encrypted and stored on cloud computing environment. Thus, building efficient data masking of encrypted 3DMM is considered to be efficient solution for masking information of 3DMM. First, using the secret key, the original 3DMM is encrypted. Second without procuring any prior information of original 3DMM it is conceivable mask information on encrypted 3D mesh models. Third, the original 3DMM are reconstructed by extracting masked information. The existing masking methods are not efficient in providing high information masking capacity in reversible manner and are not robust. For overcoming research issues, this work models an efficient data masking (EDM) method that is reversible nature. Experiment outcome shows the EDM for 3DMM attain better performance in terms of peak signal-to-noise ratio (PSNR) and root mean squared error (RMSE) over existing data masking methods. Thus, the EDM model brings good tradeoffs between achieving high data masking capacity with good reconstruction quality of 3DMM.
A low-cost development of automatic weather station based on Arduino for monitoring precipitable water vapor Wayan Suparta; Aris Warsita; Ircham Ircham
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp744-753

Abstract

Water vapor is the engine of the weather system. Continuous monitoring of its variability on spatial and temporal scales is essential to help improve weather forecasts. This research aims to develop an automatic weather station at low cost using an Arduino microcontroller to monitor precipitable water vapor (PWV) on a micro-scale. The surface meteorological data measured from the BME280 sensor is used to determine the PWV. Our low-cost systems also consisted of a DS3231 real-time clock (RTC) module, a 16×2 liquid crystal display (LCD) module with an I2C, and a micro-secure digital (micro-SD) card. The core of the system employed the Arduino Uno surface mount device (SMD) R3 board. The measurement results for long-term monitoring at the tested sites (ITNY and GUWO) found that the daily mean error of temperature and humidity values were 1.30% and 3.16%, respectively. While the error of air pressure and PWV were 0.092% and 2.61%, respectively. The PWV value is higher when the sun is very active or during a thunderstorm. The developed weather system is also capable of measuring altitude on pressure measurements and automatically stores daily data. With a total cost below 50 dollars, all major and support systems developed are fully functional and stable for long-term measurements.
Energy‑harvesting and energy aware routing algorithm for heterogeneous energy WSNs Mohammed Mehdi Saleh; Ruslan Saad Abdulrahman; Aymen Jaber Salman
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp910-920

Abstract

Wireless sensor networks are regarded as the most essential components of contemporary technologies since they are in charge of sensing and monitoring processes, which are the primary functions of these technologies. Because these nodes rely on an unchangeable battery and are randomly deployed in the environment, node energy management is the most essential issue to consider when designing algorithms to enhance the network's life. Clustering is a wireless sensor network (WSN) routing technique that has been implemented in order to extend network lifetime. Also, it is trendy to increase the energy levels of the node battery by utilizing various energy harvesting techniques in order to extend the network lifetime. In this paper, a new energy-aware clustering algorithm (EHEARA) has been proposed. The proposed algorithm is based on a dynamic clustering function and adopts a solar energy harvesting scheme in order to improve network lifetime. Furthermore, the active-sleep mechanism was used to distribute node activity and balance communication among nodes within clusters and cluster heads with the base station. The proposed algorithm is simulated using matrix laboratory (MATLAB), and the results show that it outperforms the low energy adaptive clustering hierarchy (LEACH), distributed energy efficient clustering (DEEC), and stable election protocol (SEP) algorithms in terms of network lifetime, energy consumption, and network throughput.
Magnetic sensitivity modeling of dual gate MOS transistor Mohamed Kessi; Arezki Benfdila
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1238-1248

Abstract

In this paper, the magnetic field effect on the carrier transport phenomenon in the double gate metal-oxide-semiconductor field-effect transistor (MOSFET) has been investigated. This is done by exploring the Lorentz force and the behavior of a semiconductor subjected to a constant magnetic field. The magnetic field modulates the electrons position and density as well as the potential distribution in the case of silicon tunnel tunneling field-effects (FETs). This modulation impacts the device electrical characteristics such as ON current (ION), subthreshold leakage current (IOF), threshold voltage (VT), magneto-transconductance (gmm) and output magneto-conductance (gmDS). In addition, a hall voltage (VH) is induced and modulated by the magnetic field. It has been observed that this voltage influences the effective applied gate voltage. It has been observed that the threshold voltage variations induced by the magnetic field is of paramount importance and affects the device switching properties both speed and power dissipation, noted that the threshold voltage VT and (Ion/Iof) ratio are reduced by 10-3V and 102 for a magnetic field of ±6 and ±5.5 Tesla, respectively. We have simulated the different behavior in the channel, mainly doping concentration, potential distribution, conduction and valence bands, total current density, total charge density, electric field, electron mobility, and electron velocity.
Diagnosis of rotor faults by fast Fourier transform using an auxiliary winding voltage Yakout Khadouj Jelbaoui; Lamiaa El Menzhi; Abdallah Saad
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp680-688

Abstract

Condition monitoring and on-line detection have attracted several researchers in order to carry out an efficient diagnosis of machine failures. Therefore, the detection in early stage avoids system breakdown and reduce the maintenance cost. This paper presents a new diagnosic approach to detect the broken bars and broken end ring faults for a squirrel cage induction machine based on the fast Fourier transform analysis applied on a new signature as the voltage of an auxiliary winding. The auxiliary winding is a small coil inserted between two of the stator phases, the explicit expression of its voltage is presented. The signal is monitored in six faults cases under a different load level, the emergence of the fault frequencies changes for each kind of failure. The successfully simulation results obtained show the effectiveness of this approach.
Performance analysis of power beacon-assisted D2D communication networks in the presence of eavesdropper and co-channel interference Bui Vu Minh; Van-Duc Phan
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp888-895

Abstract

Performance analysis of power beacon-assisted D2D communication networks in the presence of eavesdropper and co-channel interference is presented is investigated. The outage probability and the intercept probability of the proposed system are analyzed and derived. The impact of the main system parameters on the system performance is investigated. The Monte Carlo simulation is used for verifying the correctness of the analytical section.
Machine learning approach on road accidents analysis in Calabarzon, Philippines: an input to road safety management Kristelle Anne R. Torres; Jonardo R. Asor
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp993-1000

Abstract

This research was conducted to help the traffic policy makers and general public in preventing road incidents using the collected traffic accident dataset between the years 2016 and 2019. Data mining using classification algorithm was utilized to develop a predictive model for predicting occurrences of traffic accidents. Classification algorithms such as decision tree, k-nn, naïve bayes and neural network have been compared in identifying better classification capability in classifying stage of felony. Neural network shows a very promising result in classifying road accident with a total accuracy result of 87.63%. Nonetheless, k-nn and naïve bayes both acquired a higher than 80% accuracy which shows that this classification algorithms were also good in predicting road accidents. Moreover, public vehicle is more prone in accident rather than private vehicle in both stage of felony and accident may occur between or on 3:00pm and 6:00pm.
Morphological characteristics of X-ray thorax images of COVID-19 patients using the Bradley thresholding segmentation Retno Supriyanti; Muhammad Alqaaf; Yogi Ramadhani; Haris B. Widodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1074-1083

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has made test screening much needed. Currently, the most commonly used is the swab type. Although in fact, there is also a screening method with chest radiology. The purpose of this study is to develop a COVID-19 early detection system based on X-ray images of the patient's thorax in the form of a computer-aided diagnosis. This case is based on the fact that X-ray modalities are available in several health care centers in Indonesia, compared to other modalities such as computed tomography (CT) scan or magnetic resonance imaging (MRI). In this paper, we emphasize the X-ray thorax image segmentation process to explore the morphological information of the thorax. We use the Bradley thresholding segmentation method. The results obtained are promising to be further developed with a performance percentage of 73.33% for the thorax for COVID-19 patients and 54% for the thorax for normal patients.
Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system K. Ibrahim Ata; A. Che Soh; A. J. Ishak; H. Jaafar
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1173-1182

Abstract

A common algorithm to solve the single-source shortest path (SSSP) is the Dijkstra algorithm. However, the traditional Dijkstra’s is not accurate and need more time to perform the path in order it should visit all the nodes in the graph. In this paper, the Dijkstra-ant colony algorithm (ACO) with binary search tree (BST) has been proposed. Dijkstra and ACO are integrated to produce the smart guidance algorithm for the indoor parking system. Dijkstra algorithm initials the paths to finding the shortest path while ACO optimizes the paths. BST has been used to store the paths that Dijkstra algorithm initialled. The proposed algorithm is aimed to control the shortest path as well as guide the driver towards the nearest vacant available space near the entrance. This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. Moreover, the reason behind using the BST is to make the generation of the path by Dijkstra’s algorithm more accurate and less time performance. The results show a range of 8.3% to 26.8% improvement in the proposed path compared to the traditional Dijkstra’s algorithm.
Electromagnetic nonlinear parametric study of the SynRM using FEM method Benessalah Djamel; Houassine Hamza; Nadir Kabache; Moussaoui Djeloul
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp637-648

Abstract

The interest in synchronous reluctance machine (SynRM) does not stop increasing in recent decades; this is encouraged by their numerous advantages. This paper presents a nonlinear parametric study of the SynRM using finite element method (FEM) method. After a brief introduction and a description of the basic principles of SynRM an investigation and an evaluation of the effects of some influential parameters’ variables of the machine on the torque and magnetic losses is highlighted. The SynRM is created using ANSYS Maxwell software, using 2D FEM. The analyses are performed in the ANSYS Maxwell. The influence of the thickness of the air gap, the opening angle of the rotor, the width and the height of the stator tooth are listed and discussed. The obtained results reveals that the opening angle of the rotor and the air gap produces a large effect over the torque of the SynRM. In order to validate, the finite element model of the studied machine, experimental tests were carried out on designed machine such as the measurement of the synchronous inductance, the torque and the different losses. The experimental results are in agreement with those obtained by FEM.

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