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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 64 Documents
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Search results for , issue "Vol 27, No 3: September 2022" : 64 Documents clear
A secure communication protocol for civil drones Ayad Al-Adhami; Rajaa K. Hasoun; Ekhlas K. Gbashi; Soukaena Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1490-1501

Abstract

This paper introduces a secure communication protocol that provides secured communication pathways to manipulate drones through unsecured communication. The deployment of the proposed protocol works through providing two secured communication paths; drones to the drone’s controller path and controller to data centre path. The first secured communication path has achieved a high level of security and privacy by using a modification of SHA-1 method and an advanced encryption method. The modification of the SHA-1 is called 83SHA-1. These modifications can increase rounds in the first stage up to 83 rounds, inject each round with expansion and S-Boxes procedures that are used in DES to extend length from 160 to 240 bits then reduce it from 240 to 160 bits. After hash data from the drone then use the advanced encryption method which is called Geffe-Genetic (GG) Encryption algorithm where three types of keys will be used for deception attackers. The second accomplishment is to ensure providing secure communication between the drone’s controller and datacentre by using RNA-RADG-CBC (RRCBC) encryption algorithm where will generate an initialization vector (IV) for cipher block chaining (CBC) randomly, generate keys, and propose an encryption/decryption method. The security analysis shows a promising high security level of drones’s data.
Controller placement problem in software defined networks Hassan Hadi Saleh; Israa Adnan Mishkal; Dheyab Salman Ibrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1704-1711

Abstract

The requirements for the network are increasing by the expanding and spreading the Internet. The Previous techniques of the network do not meet the modern needs, thus, a new technical presents software-defined networking (SDN). SDN recognizes as a promising new model that separates the control plane (traffic routing and network topology) from the data plane (network architecture layers). The architecture of SDN has some features that find in a single controller or many controllers instance of programmable, flexible, and scalable. In the current SDN, multiple controllers are essential. Therefore, the optimal number of the controllers and their locations is the most significant challenge, known as the controller placement problem (CPP). It deploys the optimal number of controllers within the network while meeting presentations requirements considered conflicting in nature example: credibility, load balancing, latency, energy efficiency, and computation time. Many studies researched the ways to develop solutions for improving scalability, place selection for SDN. This paper presents the CPP and gives a comprehensive review of SDN issues based on the recent well-known research to extract available solution strategies. Finally, it discusses the limitations and future study directions that can support researchers in this field.
Autoregressive prediction analysis using machine deep learning Mohammad S. Khrisat; Anwar Alabadi; Saleh Khawatreh; Majed Omar Al-Dwairi; Ziad A. Alqadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1509-1516

Abstract

Regression analysis, in statistic a modelling, is a set of statical processes that can be used to estimate the relationship between a dependent variable, commonly known as the outcome or response, and more independent variables generally called predictors of covariant. On the other hand, autoregression, which is based on regression equations, is a sequential model that uses time to predict the next step data from the previous step. Given the importance of accurate modelling and reliable predictions. in this paper we have analyzed the most popular methods used for data prediction. Nonlinear autoregressive methods were introduced, and then the machine deep learning approach was used to apply prediction based on a selected input data set. The mean square error was calculated for various artificial neural networks architecture to reach the optimal architecture, which minimized the error. Different artificial neural network (ANN) architectures were trained, tested, and validated using various regressive models, a recommendation was raised according to the obtained and analyzed experimental results. It was shown that using the concepts of machine deep learning will enhance the response of the prediction model.
Specific absorption rate distribution evaluation in a different substrate for hyperthermia treatment Bibi Sarpinah Sh Naimullah; Kasumawati Lias; Norlida Buniyamin; Ahmad Tirmizi Jobli; Mazlina Mansor Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1311-1319

Abstract

Hyperthermia treatment procedure (HTP) isatreatment that uses high heatgenerated from electromagnetic (EM) waves, which is about 42 °C to 45 °C within a particular duration. However, poor focus position distance on the treated tissue has become a significant concern among the researchers since it may contribute to a wide area of unwanted hot spots, which lead to severe adverse health effects on healthy tissue.This paper presents a specific absorption rate (SAR) distribution evaluation of different microstrip antenna substrates with different electrical permittivities, contributing to different sizes of microstrip antenna patches, which then provide different attainment of the SAR distribution on the treated tissue. Operating frequencies of 434MHz, 915 MHz, and 2,450 MHz with 10 W operating powerare utilized. ASEMCAD X is used to conduct a simulation in obtaining the SAR distribution, which determines the focus position distance on different tumour (malignant tissue) sizes. Based on the results, the suitable substrate for frequency 915 MHz and 2,450MHz is RT5880, and RT5870, while RO3210 and RT6010 performed their best at 434MHz and 2,450MHz. The finding of this study can be used for further research in optimizing microstrip antenna development for HTP.
Computational phantoms for investigating impact of noise magnitude on modulation transfer function Choirul Anam; Ariij Naufal; Heri Sutanto; Geoff Dougherty
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1428-1437

Abstract

Accurate measurement of spatial resolution in terms of modulation transfer function (MTF) is essential in computed tomography (CT) images. The purpose of this study was to developed a computational phantom that can be used to evaluate the effect of noise on the MTF in CT images. Our computational phantoms for measuring MTF in CT were developed with MATLAB software. The phantom image was blurred by a point spread function of a certain standard deviation. Subsequently, different noise levels were added to the phantoms. Next, an automatic MTF calculation was implemented. The first step of the MTF calculation was to determine the region of interest (ROI). Profile was generated from the ROI, and a line spread function (LSF) curve was formed. The LSF curve was Fourier transformed to produce a MTF curve. Greater noise added to phantom image, it yields greater effect of standard deviation on the measured MTF. The greater noise makes the MTF curve increases differently than MTF with 0 HU noise. The 10% MTF values at the 25% noise reach more than 2.0 cycle/mm. By the developed computational phantoms, the spatial resolution and the amount of noise can be determined independently.
Towards an approach based on particle swarm optimization for Arabic named entity recognition on social media Brahim Ait Ben Ali; Soukaina Mihi; Ismail El Bazi; Nabil Laachfoubi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1589-1600

Abstract

Named entity recognition is an essential task for various applications related to natural language processing (NLP). It aims to retrieve a variety of named entities (NEs) from text and categorize them according to predetermined target categories. In many cases, using the entire feature set can be time-consuming and negatively impact the performance. Moreover, it is challenging to find the relevant subsets of features for a particular task due to the high number. The feature selection technique is an unsupervised process for selecting informative features by creating a new subset of informative features. This technique is used to enhance the underlying algorithm's performance. This article implements an effective feature selection algorithm using particle swarm optimization (PSO) to identify and classify the Arabic NEs in the text from social media. PSO is a search algorithm that utilizes a population of particles in a multidimensional space. The proposed method is evaluated using two publicly available Arabic Dialect social media datasets. It is demonstrated through comparisons with both baselines and previous models that the new approach achieves significant accuracy with considerably reduced feature sets in all parameters.
Enhancement of motor speed identification using artificial neural networks Arshad B. Salih; Zuhair Shakor Mahmood; Ardm Haseeb Mohammed Ali; Ali Najdet Nasret
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1388-1396

Abstract

In this study have been utilized a modified version of ant colony optimization to improve the thresholds of neural networks and weights by including therank-weight approach. Furthermore, this technique easily overcome the drawbacks speed up convergence into the minimum while training the backpropagation neural network. The improved ant colony optimization-backpropagation neural.not only has the capacity to map extensively, but it also enhances operating efficiency noticeably, according to the simulation findings. The simulation results revealed that the speed sensor replaced with the ant colony optimization rw-optimized back propagation neural network-speed identification and motor’s speed determined using this approach the result is satisfactory.
Comparative evaluation of optical amplifiers in passive optical access networks Bimogo Joseph Armel; Essiben Dikoundou Jean-Francois; Ihonock Eyembe Luc
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1452-1461

Abstract

In this paper, the parameters of optical amplifiers are evaluated using numerical methods with the Optisystem software. The main objective of this evaluation is the implementation of an optical telecommunication architecture, able to push back the current limits, due to a more and more restricted bandwidth following a demand which does not stop growing. We start from a study of the classical architecture of an optical telecommunication network with an external modulation provided by the mach zehnder modulator, the non return to zero (NRZ) coding, a pseudo random bit generator and a continuous wave (CW) laser diode of frequency 193.1 THz. The results obtained show a transmission possibility at 30.8 dBm and an output power of 25 dBm (316 mW) with an electrical rate signal to noise (SNR) and optical rate signal to noise (OSNR) beyond 34 dBm. The successive integration of the different amplifiers will improve these results with a gain of more than 10 dBm and also provide a better signal quality.
The application of phosphor Sr4La(PO4)3O:Ce3+,Tb3+,Mn2+ on white light-emitting diodes My Hanh Nguyen Thi; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1251-1257

Abstract

Using a high temperature solid-state technique, various phosphors Sr4La(PO4)3O:Ce3+, Tb3+,Mn2+ (SLPO:Ce,Tb,Mn) were produced. In Sr4La(PO4)3O, the luminescence characteristics, thermal stability, and energy conversion between Ce3+ and Tb3+-Mn2+ have been thoroughly studied. The sensitizer Ce3+ particles inclusion could considerably improve the feeble Tb3+ green radiation and Mn2+ red radiation via energy transfer. By adjusting the scale of Ce3+/Tb3+ over Ce3+/Mn2+ atoms, the color of the emission may be changed. White light was produced in the Sr4La(PO4)3O:0.12Ce3+,0.3Mn2+ specimen with chromatism coordinates of (0.3326, 0.3298), showing that the phosphors SLPO:Ce,Tb,Mn possess promising application on WLEDs. The conclusion is supported by Mie-scattering theory and Lambert-Beer's law.
Design, fabrication and performance analysis of floodlight shaped microstrip antenna for Wi-Fi/IoT applications John Colaco; Jillian Cotta
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1462-1469

Abstract

This paper proposes a design and fabrication of a floodlight-shaped microstrip patch antenna using flame-retardant (FR)-4 substrate within the frequency band of 1-6 GHz. The proposed antenna resonating at a multi-frequency band (2.01-2.2 GHz, 3.7-3.8 GHz, 4.82-4.96 GHz, and 5.61-6 GHz) is suitable for Wi-Fi and IoT applications. The proposed antenna has a size of 50×60×1.6 mm 3. The design was implemented using CADFEKO software, and the same was fabricated and measured using a vector network analyzer. Further, the performance analysis of the structure is carried out using the CADFEKO software, firstly by shifting the location of the microstrip feed line along the width of the patch and secondly by amending the structure. The verdicts show that the proposed antenna provides high impedance matching at multi-frequency bands and shows a very good agreement between simulated and fabricated results. The changed feed-line location and modified structure provide improved performance, which can be utilized for various other wireless communication channels.

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