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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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A human vision based system for biometric images recognition Boukhari, Wassila; Benyettou, Mohamed; Abderrahim, Belmadani
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.pp1508-1517

Abstract

In this paper, a universal biometric system based on human vision is proposed. From recent biological and physiological results, A human identification system that approximates the natural vision and recognition of individuals is conceived. Liquid state machine (LSM), as a recurrent spiking neural network, is highly inspired by the brain neural architecture with low training cost. However, input dimension of large scale images requires efficient processing at the cost of performance or resource overhead. This paper propose a new neural input coding for images based on frequency signals rather than pixels. Each image is filtered and fragmented then the LSM liquid (or reservoir) will receive, first, high frequency signals, then low frequency signals from each fragment. The two sets of output neurons states corresponding to each type of filter will be matched to the entire enrollment database. A weighted sum rule between the matching results will determine the right class of a biometric image. The system was tested on three different biometric datasets: face, palmprint and off-line signature, results show the reliability of the proposed approach.
Performance analysis of encryption and decryption algorithm Pronika Pronika; S. S. Tyagi
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.pp1030-1038

Abstract

In this tumultuous 21st century, we are surrounding by lots of applications such as social media websites all over the internet or this era can also define as digital era in which everything is accessible over the internet. There are billions of internet users all over the world and they share their information over the same and because of this lots of people intentionally trying to steal the confidential data of other people, so it is always advisable to share and store data in encrypted form. In this paper, we discuss different encryption and decryption algorithms and compare them with respect to time take by these algorithms for encrypting and decrypting different sizes of files.
Reconfigurable intelligent surfaces assisted wireless communication networks: ergodic capacity and symbol error rate Dinh-Thuan Do; Chi-Bao Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp358-364

Abstract

By enabling reconfigurable intelligent surfaces (RIS), we can deploy intelligent reflecting signals from the base station to destinations. Different from traditional relaying system, RIS relies on programmable metasurfaces and mirrors to improve system performance of destinations. We derive the formulas of main system performance metrics such as ergodic capacity and symbol error rate (SER). Based on types of modulation, we need to demonstrate other parameters which make influence to system performance. We show analytically that the number of reflecting elements along with the transmit power at the source can improve system performance. Moreover, we check the exactness of derived expressions by matching Monte-Carlo with analytical simulations. Finally, we find the best performance can be achieved at specific parameters and results are verified by explicit simulations.
Supervision and control by SCADA of an automated fire system Omar Chamorro-Atalaya; Dora Arce-Santillan; Teodoro Diaz-Leyva; Martin Diaz-Choque
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.pp92-100

Abstract

The purpose of this article is to describe the development of a prototype of a monitoring and control system for a fire-fighting system, implemented through SCADA (supervisory control and data acquisition) for which the OPC (OLE for process control) is known. Known KepServerEX6 (single data source connectivity platform), with which the integration of the PLC (programmable logic controller), the human-machine interface (HMI) and the computer will be controlled, with the application of monitoring the operating parameters of a fire fighting system. These parameters are the pressure and flow of the electric pump, the values of the parameters are regularly controlled automatically by means of a frequency variator, according to the sprinkler actuation, the variator varies its operating frequency until achieving the optimal pressure and flow values. The level of correlation between the indicators to be monitored by the SCADA system is highly significant, equal to 0.977, 0.983 and 0.997 respectively. In addition, the dispersion model of the indicators monitored by the SCADA system will be determined, is the quadratic, with a determination factor of 0.999.
Sentiment classification of user's reviews on drugs based on global vectors for word representation and bidirectional long short-term memory recurrent neural network Hadab Khalid Obayed; Firas Sabah Al-Turaihi; Khaldoon H. Alhussayni
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.pp345-353

Abstract

The process of product development in the health sector, especially pharmaceuticals, goes through a series of precise procedures due to its directrelevance to human life. The opinion of patients or users of a particular drugcan be relied upon in this development process, as the patients convey their experience with the drugs through their opinion. The social media field provides many datasets related to drugs through knowing the user's ratingand opinion on a drug after using it. In this work, a dataset is used that includes the user’s rating and review on the drug, for the purpose of classifying the user’s opinions (reviews) whether they are positive ornegative. The proposed method in this article includes two phases. The first phase is to use the Global vectors for word representation model for converting texts into the vector of embedded words. As for the second stage, the deep neural network (Bidirectional longshort-termmemory) is employedin the classification of reviews. The user's rating is used as a ground truth inevaluating the classification results. The proposed method present sencouraging results, as the classification results are evaluated through threecriteria, namely Precision, Recall and F-score, whose obtained values equal(0.9543, 0.9597and0.9558), respectively. The classification results of theproposed method are compared to a number of classifiers, and it was noticed that the results of the proposed method exceed those of the alternative classifiers.
Analysis the digital images by using morphology operators Hadeel Amjed Saeed; Sumaya Hamad; Azmi Tawfik Hussain
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.pp1654-1662

Abstract

In this paper, we deal with morphology images that try to improve the use of images. On the one hand, the process is used to obtain the histogram of the image then converted it into a non-color image (gray scale). The next step is to perform the erosion, dilation, open and close operations on the images, how these methods have important effects, and how can be used on a variable number of images, and found the differences between them. These operations were applied on four different images, check images, four basic operations (dilation, erosion, open and close) for each image were performed. Then, retrieving process to the original state of the image (the colored copy) was applied. The results found that retrieving the original images is difficult, and there is the occurrence of some noises on the image when it was retrieved. Finally, conclusions of the work are presented.
Autonomous path planning through application of rotated two-parameter overrelaxation 9-point Laplacian iteration technique W. K. Ling; A'Qilah Ahmad Dahalan; Azali Saudi
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.pp1116-1123

Abstract

Autonomous path navigation is one of the important studies in robotics since a robot’s ability to navigate through an environment brings about many advancements with it. This paper suggests the iteration technique called half-sweep two parameter overrelaxation 9-point laplacian (HSTOR-9P) to be applied on autonomous path navigation and aims to investigate its effectiveness in performing computation for path planning in an indoor static environment. This iteration technique is a harmonic function that solves the Laplace’s equation where the modelling of the environment is based on. The harmonic functions are an appropriate method to be used on autonomous path planning because it satisfies the min-max principle, therefore avoiding the occurrence of local minima which traps robot’s movements, and that it offers complete path planning algorithm. Its performance is tested against its predecessor iteration technique. Results shown that HSTOR-9P iteration technique enables path construction in a lower number of iterations, thus, performs better than its predecessors.
Predicting heart failure using a wrapper-based feature selection Minh Tuan Le; Minh Thanh Vo; Nhat Tan Pham; Son V.T Dao
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.pp1530-1539

Abstract

In the current health system, it is very difficult for medical practitioners/physicians to diagnose the effectiveness of heart contraction. In this research, we proposed a machine learning model to predict heart contraction using an artificial neural network (ANN). We also proposed a novel wrapper-based feature selection utilizing a grey wolf optimization (GWO) to reduce the number of required input attributes. In this work, we compared the results achieved using our method and several conventional machine learning algorithms approaches such as support vector machine, decision tree, K-nearest neighbor, naïve bayes, random forest, and logistic regression. Computational results show not only that much fewer features are needed, but also higher prediction accuracy can be achieved around 87%. This work has the potential to be applicable to clinical practice and become a supporting tool for doctors/physicians.
Modeling and real time digital simulation of microgrids for campuses Malta and Jordan based on multiple distributed energy resources Sidahmed Khiat; Abdelkader Chaker; Lazaros Zacharia; Ahmed Onen
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.pp657-672

Abstract

This paper presents the modeling and real-time digital simulation of two microgrids: the malta college of arts, science and technology (MCAST) and the german jordan university (GJU). The aim is to provide an overview of future microgrid situation and capabilities with the benefits of integrating renewable energy sources (RES), such as photovoltaic panels, diesel generators and energy storage systems for projects on both campuses. The significance of this work starts with the fact that real measurements were used from the two pilots, obtained by measuring the real physical systems. These measures were used to plan different solutions regarding RES and energy storage system (ESS) topologies and sizes. Also, the demand curves for the real microgrids of MCAST and GJU have been parameterized, which may serve as a test bed for other studies in this area. Based on actual data collected from the two pilots, a real-time digital simulation is performed using an RT-LAB platform. The results obtained by this tool allow the microgrid manager to have a very accurate vision of the facility operation, in terms of power flow and default responses.  Several scenarios are studied, extracting valuable insight for implementing both projects in the future. Eventually, the proposed models would be a blueprint for training and research purposes in the microgrid field.
Decentralised optimal deployment of mobile underwater sensors for covering layers of the ocean Valimohammad Nazarzehi; Rasoul Damani
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.pp840-846

Abstract

This paper presents the problem of sensing coverage of layers of the ocean in three dimensional underwater environments. We propose distributed control laws to drive mobile underwater sensors to optimally cover a given confined layer of the ocean. By applying this algorithm at first the mobile underwater sensors adjust their depth to the specified depth. Then, they make a triangular grid across a given area. Afterwards, they randomly move to spread across the given grid. These control laws only rely on local information also they are easily implemented and computationally effective as they use some easy consensus rules. The feature of exchanging information just among neighbouring mobile sensors keeps the information exchange minimum in the whole networks and makes this algorithm practicable option for undersea. The efficiency of the presented control laws is confirmed via mathematical proof and numerical simulations.

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