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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
 605   606   607   608   609 
Coplanar waveguide-fed ultra-wideband antenna with WLAN band Chaiyong Soemphol; Niwat Angkawisittpan
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.pp1523-1529

Abstract

A coplanar waveguidefed ultra-wideband antenna with extended transmission band to WLAN frequency is investigated. The proposed antenna consists of a modified semi-circular patch and staircase of ground plane. The prototype is fabricated on a low cost FR4 substrate with dielectric constant of 4.4 with thicknes of 0.8 mm. The overall dimensions of proposed UWB antenna are 34 mm x 40 mm. The simulation and experimental results have been shown that the proposed antenna archives low VSWR over transmission bandwidth from 2.10 - 12.7 GHz to cover both WLAN and UWB bands.  The average gain is 3.87 dBi. It depicts nearly omni-directional radiation pattern like dipole antenna. Moreover, the fabricated prototype antenna shows a good agreement between the simulated and measured results
The effectiveness of discrete hermite wavelet filters technique in digital image watermarking M. Abduldaim, Areej; Abdulrahman, Asma Abdulelah; Tahir, Fouad Shaker
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.pp1392-1399

Abstract

In this work, new discrete wavelets were derived Hermite polynomials for obtained discrete hermite wavelet transformation (DHWT), and their efficiency for use in image processing is demonstrated by proving the realization of important theorems. Moreover, the role of the new and proposed waveforms in their effective effect in placing the watermark with the color image is clarified, and a program was created using MATLAB software by creating a subprogram for constructing the new wavelet and proving its efficiency with an analytic image. The process is repeated using DHWT to analyze the image. The color image has been subjected to various attacks after which the watermark is retrieved from the image after comparing it with the proposed algorithm and it has proven its power faster and better than the previously suggested methods. The final conclusion shows that using new wavelets DHWT better peak signal of noise ratio (PSNR)s can be obtained and that the proposed algorithm fills in better the lack of awareness of the watermark and its strength under different attacks.
A smart management system of electric vehicles charging plans on the highway charging stations Ibrahim El-Fedany; Driss Kiouach; Rachid Alaoui
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.pp752-759

Abstract

Electric vehicles (EVs) are seen as one of the principal pillars of smart transportation to relieve the airborne pollution induced by fossil CO2 emissions. However, the battery limit, especially where the journey is with a long-distance road remains the most formidable obstacle to the large-scale use of EVs. To overcome the issue of prolonged waiting charging time due to the large number of EVs may have a charging plan at the same charging station (CS) along the highway, we propose a communication system to manage the EVs charging demands. The architecture system contains a smart scheduling algorithm to minimize trip time including waiting time, previous reservations and energyare needed to reach the destination. Moreover, an automatic mechanism for updating reservation is integrated to adjust the EVs charging plans. The results of the evaluation under the Moroccan highway scenario connecting Rabat and Agadir show the effectiveness of our proposal system. 
Automation of the burner of a pirotubular boiler to improve the efficiency in the generation of steam Omar Chamorro-Atalaya; Diego Goicochea-Vilela; Dora Arce Santillan; Martin Diaz-Choque; Teodoro Diaz-Leyva
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp101-109

Abstract

The purpose of this article is to describe the automation developed by means of a programmable logic controller for the burner of a fire tube boiler, in order to improve the efficiency in the process of generating steam quantified through the percentage of oxygen generated. The implementation was developed under a control strategy based on the use of servomotors that allow to gradually open or close the solenoid valves that dose the amount of air and fuel; Considering that there are multiple elements, I limited the analysis to one of its main components, called the burner. After developing this automation, it was possible to demonstrate the decrease in the variability of the oxygen percentage in relation to the optimal or desired value in the boiler. The experimentally obtained data of the oxygen percentage, were subjected to a statistical analysis of dispersion, in which the value of the Pearson's correlation coefficient was determined, whose value was equal to 0.298; This result allowed to conclude that the degree of variability of the indicator in analysis with respect to time is very low, which means that the variable maintains a constant value, equal to the desired value, after automating the fire tube boiler.
An enhanced framework for solving cold start problem in movie recommendation systems Salma Adel Elzeheiry; N. E. Mekky; A. Atwan; Noha A. Hikal
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.pp1628-1637

Abstract

Recommendation systems (RSs) are used to obtain advice regarding decision-making. RSs have the shortcoming that a system cannot draw inferences for users or items regarding which it has not yet gathered sufficient information. This issue is known as the cold start issue. Aiming to alleviate the user’s cold start issue, the proposed recommendation algorithm combined tag data and logistic regression classification to predict the probability of the movies for a new user. First using alternating least square to extract product feature, and then diminish the feature vector by combining principal component analysis with logistic regression to predict the probability of genres of the movies. Finally, combining the most relevant tags based on similarity score with probability and find top N movies with high scores to the user. The proposed model is assessed using the root mean square error (RMSE), the mean absolute error (MAE), recall@N and precision@N and it is applied to 1M, 10M and 20M MovieLens datasets, resulting in an accuracy of 0.8806, 0.8791 and 0.8739.
An android-based mobile educational game for disaster preparedness: an input to risk reduction management Gene Marck Bañares Catedrilla; Jefferson Llobit Lerios; Sherwin Banaag Sapin; Manuel C Lanuang; Chester Alexis C Buama
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.pp936-943

Abstract

The Philippines is one of the countries in the world who suffers in different disasters, particularly natural disasters. Every year, there are more than twenty incidents recorded in the country related to different disasters which involve numerous lives of its citizens. It is found that most Filipinos have lack of knowledge in terms of disaster preparation specially, teenagers. This paper intended to develop a mobile-based game that aims to spread awareness on what to do during disasters. Upon development, forty-five (45) respondents were chosen to test the reliability of the application which composed of elementary students, household owners, police officers, fire fighters and IT experts. Further, ISO 25010 was adapted and modified in assessing the project. The results showed that the application is strongly acceptable and gives appropriate output in terms of disaster preparation garnering a total mean of 3.83
Fault diagnosis of a squirrel cage induction motor fed by an inverter using lissajous curve of an auxiliary winding voltage Yakout Khadouj Jelbaoui; El Menzhi Lamiaà; Abdallah Saad
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.pp1299-1308

Abstract

The development of electronic power components has allowed the increase of the induction machine performance. Indeed, monitoring squirrel cage induction motors driven through rectifiers and inverters has been a major concern. This paper presents a new method to diagnose the combination inverter-machine faults. This technic considers an auxiliary winding which is a small coil inserted between two stator phases. It is based on Lissajous curve of this auxiliary winding voltage Park components. For this purpose, modeling the electromechanical conversion chain is necessary. The focus will particularly be on modeling both the squirrel cage induction machine and the inverter in a non-defected case which is a reference. Moreover, the explicit expressions developed for the inserted winding voltage and its Park components will be presented. The simulation results show the effectiveness of the proposed method.
Solving combined economic emission dispatch problem in wind integrated power systems Surender Reddy Salkuti
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.pp635-641

Abstract

A meta-heuristic based optimization method for solving combined economic emission dispatch (CEED) problem for the power system with thermal and wind energy generating units is proposed in this paper. Wind energy is environmentally friendly and abundantly available, but the intermittency and variability of wind power affects the system operation. Therefore, the system operator (SO) must aware of wind forecast uncertainty and dispatch the wind power accordingly. Here, the CEED problem is solved by including the nonlinear characteristics of thermal generators, and the stochastic behavior of wind generators. The stochastic nature of wind generators is handled by using probability distribution analysis. The purpose of this CEED problem is to optimize fuel cost and emission levels simultaneously. The proposed problem is changed into a single objective optimization problem by using weighted sum approach. The proposed problem is solved by using particle swarm optimization (PSO) algorithm. The feasibility of proposed methodology is demonstrated on six generator power system, and the obtained results using the PSO approach are compared with results obtained from genetic algorithm (GA) and enhanced genetic algorithms (EGA).
3D chaos graph deep learning method to encrypt and decrypt digital image Daniah Abdul Qahar Shakir; Ali Jbaeer Dawood
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.pp941-951

Abstract

We live in technological age development’s where many important data transmitted electronically from one device to another and in every place. Deep learning algorithms have facilitated the process of encoding and decoding digital images. Chaotic graph systems, on the other hand, are one of the most recent techniques utilized to encode image data based on the methods of cryptography. The chaos maps are divided into two main aspects, first one deals with the 1D map which requires fewer features and can be developed easily, the second one is the high dimensional map which is more complex than the 1D graph and it requires more features, more parameters, and it is relatively hard to develop. In this paper, we present a method for image encoding and decoding electronically using deep learning, the proposed algorithm was developed by using the hybrid technique of 3D chaos map generation, the best case of the proposed technique gave the following results: The average entropy calculation was (7.4838) before image encryption and (7.9896) after image encryption with average number of pixels change rate (NPCR) of (99.7085%) and the unified average changing intensity (UACI) of (33.2030%) which are the best outcomes when compared to other similar works.
Levenberg–Marquart logistic deep neural learning based energy efficient and load balanced routing in MANET A. Sangeetha; T. Rajendran
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.pp1002-1010

Abstract

As the advent of new technologies grows, the deployment of mobile ad hoc networks (MANET) becomes increasingly popular in many application areas. In addition, all the nodes in MANET are battery operated and the node mobility affects the path stability and creates excessive traffic leads to higher utilization of energy, data loss which degrades the performance of routing. So, in this paper we propose Levenberg–Marquardt logistic deep neural learning based energy efficient and load balanced routing (LLDNL-EELBR) which is a machine learning method to deeply analyze the mobile nodes to calculate residual load and energy and it also uses logistic activation function to select the mobile node having higher residual energy and residual load to route the data packet. Experimental evaluations of three methods (LLDNL-EELBR, multipath battery and mobility-aware routing scheme (MBMA-OLSR) and opportunistic routing with gradient forwarding for MANETs (ORGMA)) were done and the result reveals that LLDNL-EELBR method is able to increase the through put and minimizes the delay and energy consumption in MANET when compared to works under consideration. 

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