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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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Hyperspectral image classification using Hyb-3D convolution neural network spectral partitioning Easala Ravi Kondal; Soubhagya Sankar Barpanda
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp295-303

Abstract

Hyperspectral image classification (HSIC) on remote sensing imaging has brought immersive achievement using artificial intelligence technology. In deep learning convolution neural networks (CNN), 2D-CNN, and 3D-CNN methods are widely used to classify the spectral-spatial bands of hyperspectral images (HSI). The proposed Hybrid 3D-CNN (H3D-CNN) model framework for deeper features extraction predicts classification accuracy in supervised learning. The model reduces the narrow gap between supervised and unsupervised learning and the complexity and cost of the previous models. The HSI classification analysis is carried out on real-world data sets of Indian pines Salinas datasets captured by Airborne visible, infrared imaging spectrometer (AVIRIS) sensors that performed superior classification accuracy results.
ISO/IEC 25010 based evaluation of rice seed analyzer: a machine vision application using image processing technique Ertie Abana; Benedict Sy
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp994-1001

Abstract

The traditional approach for quality assessment of rice is done by a human inspector manually which leads to inconsistencies and uncertainties in the assessment due to human error. To address this problem, researchers develop rice classification systems applying different methods. The development of these kinds of applications will contribute to the larger objective of maximizing the production of global food. This study introduced a new method of rice seed classification that applies hashing techniques pre-processing of image prediction and its precision rate is 93.06 percent, with a speed of 8.31 seconds per image. The developed application in this study was evaluated using ISO/IEC 25010 with total mean scores of 4.31 for functional suitability, 4.31 for performance efficiency, 4.58 for compatibility, 4.31 for usability, 4.58 for reliability, 4.51 for security, 4.28 for maintainability, and 4.42 for portability.
Design and realization of a dual-wavelength low level light therapy for acne and face rejuvenation treatment Napat Watjanatepin; Paiboon kiatsookkanatorn; Chaiyant Boonmee; Sarayoot Thongkullaphat; Tuanjai Archevapanich; Patcharanan Sritanauthaikorn; Khanittha Wannakam
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp147-160

Abstract

Low-level light therapy (LLLT) uses the light of wavelength between 400–700 nm to treat acne, reduce inflammation, stimulate collagen production, and rejuvenate the facial skin. This study designed and constructed a dual-wavelength LED LLLT device for the facial treatment. The light spectrum, power density, uniformity, stability, and safety of the device were analyzed. The proposed system consisted of an LED array with 415 and 633 nm wavelengths. Human machine interface with embedded system was used to control light intensity and treatment time. The phototherapy device is designed to be curvaceously sized to suit the face shape of Asian people. The results showed that the LLLT device emitted 633±5 nm red and 415±5 nm blue light with a linear adjustable light power density of 0-18.56 mW/cm2 and 0-3.70 mW/cm2, respectively. The spectrum distribution of the red and blue light was relatively constant over 30 minutes of operation. The uniformity and stability of red spectrum were about 89.9% and 95.08% and blue spectrum were 87.6% and 97.08%, respectively. The experimental face’s temperature was below 31.5 . For the future study, the LED phototherapy device will be applied for clinical research in collaboration with dermatologists.Low-level light therapy (LLLT) uses the light of wavelength between 400–700 nm to treat acne, reduce inflammation, stimulate collagen production, and rejuvenate the facial skin. This study designed and constructed a dual-wavelength LED LLLT device for the facial treatment. The light spectrum, power density, uniformity, stability, and safety of the device were analyzed. The proposed system consisted of an LED array with 415 and 633 nm wavelengths. Human machine interface with embedded system was used to control light intensity and treatment time. The phototherapy device is designed to be curvaceously sized to suit the face shape of Asian people. The results showed that the LLLT device emitted 633±5 nm red and 415±5 nm blue light with a linear adjustable light power density of 0-18.56 mW/cm2 and 0-3.70 mW/cm2, respectively. The spectrum distribution of the red and blue light was relatively constant over 30 minutes of operation. The uniformity and stability of red spectrum were about 89.9% and 95.08% and blue spectrum were 87.6% and 97.08%, respectively. The experimental face’s temperature was below 31.5 . For the future study, the LED phototherapy device will be applied for clinical research in collaboration with dermatologists.
Single current sensor based fault tolerant control of interior permanent magnet synchronous machine for drive applications Sankhadip Saha; Urmila Kar
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp674-685

Abstract

This paper presents an integrated method for current sensor fault detection and fault tolerant control (FTC) for traction interior permanent magnet synchronous motor (IPMSM). The proposed current sensor fault detection method is based on detecting changes in the d-q axis current. The FTC is based on d-q axis current estimation from the reference d-q axis current and the phase current measured by the surviving current sensor. The current estimation process is independent of machine parameters. Hence the estimation is robust and requires less computational cost. The effectiveness of the FTC method is verified by the transient analysis. Such FTC is suitable for electric vehicle traction applications to ensure non-stop control operation of the drive in the entire range of speed. The efficacy of the proposed FTC method is tested through extensive simulations in MATLAB/Simulink environment. The real-time applicability of the proposed FTC method using the cost-effective digital signal processor (DSP) is verified on Texas Instruments© TMSF28379D through the processor in loop (PIL) simulation model.
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.
Mobile application for care and health control of camelids Roberto Demmis Muñoz Villacorta; Carlos Manuel Oscco Aguero; Laberiano Andrade-Arenas
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1769-1779

Abstract

Due to the events caused by COVID-19, several activities were paralyzed, such as the export of camelids. In the present study, it was observed that many of the camelids that are located in the highest of the Andes, are exposed to diseases that originate from climatic changes or from the infrastructure in which they are inhabiting. For this reason, the veterinary mobile application for camelids was implemented, which will help care as well as sanitary control, this application was developed through the agile scrum methodology, since it adapts to the various modules used, which would be consulta of diseases, recommendations for breeding and contacts with veterinary experts. As a result, the optimal mobile application was obtained for the needs of the people who live in that sector. In addition, it made it easier for the farms, as well as for the people who are in the frozen areas, so that they have better care and control of this species of animals, since the camelids are part of the fauna of the Andes and above all all its fiber and its derivatives are exported, which generates great economic sustenance for that sector.
Near-field microwave focusing evaluation of dielectric lens antenna for human body model Amirah Abd Rahman; Kamilia Kamardin; Yoshihide Yamada; Masaharu Takahashi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp161-173

Abstract

Various small focus spot applicators are being investigated for hyperthermia therapy, which requires microwave concentration to heat tumors in the human body. Dielectric lens antenna is frequency independent and has strong focusing capability to achieve a very small focusing spot. In this paper, lenses with diameters of 30, 50 and 70 cm were designed to evaluate the size of the focal spot in the human body model. The electromagnetic simulator, FEKO was used to generate rays and near-field focusing data of dielectric lenses at a frequency of 2.45 GHz. The simulated focal spot sizes agreed well with the theoretical values. An analytical investigation into the power at the focal spot was conducted using the proposed power relations of the focused lens novel equation. The theoretical propagation loss is used to represent the power density degradation at the focal spot caused by microwave absorption by the human body. The simulation results of the focused lens in the human body indicated that the 30 cm lens achieved a larger focal spot with a greater focusing power, 0.714 mW compared to the 70 cm lens, which achieved a smaller focal spot but a lower focusing power, which was 0.393 mW.
Performance study of reactive routing protocol in wildfire detection using mobile ad-hoc network Nadia Al-Aboody; Muhsin Al-Amery
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp859-866

Abstract

The routing protocols play an important role in creating routes and sending packets between sensor nodes. There are many methods in the literature that presented and applied several protocols in various domains. However, there is a lack of using routing protocols in the detection of wildfire. Moreover, most methods have used a single number of sensor nodes, where there is a need to investigate the routing protocol based on different simulation parameters such as the number of sensor nodes. Therefore, in this paper, we propose a type of reactive routing protocol that is named Location Aided Routing (LAR). The simulation of LAR protocol has been conducted based on a various number of sensor nodes in order to deeply study and investigate the LAR protocol in the detection of wildfire. In addition, different performance metrics are used for evaluating the performance of the LAR protocol. In the simulation, the performance of LAR protocol shows promising results in the wildfire detection.
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.

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