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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 26, No 3: June 2022" : 64 Documents clear
Investigating low order harmonics of sinusoidal pulse width modulation with voltage closed loop control Ali Hussein Al-Omari; Saif Al-Zubaidi
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1258-1265

Abstract

This paper investigates the low order harmonics of a simplified approach to generate high quality sinusoidal pulse width modulation (SPWM) waveform produced by voltage source inverter (VSI). Programmable interface controllers (PIC) microcontroller was chosen to produce the signals in Real time with voltage feedback to control the puls width during direct current (DC) link voltage reduction. The research considered simplicity, durability, and reliability as conditions. The proposed technique was successfully passed one of the biggest challenges which is time criteria presence due to execution time of the feedback loop and the transient time required for power electronics switches to turn fully off and on, known as dead time. The proposed technique can be considered as practical, high feasibility according to economic point of view and its accuracy to the input variables. The pseudocode, algorithm, and flowchart for closed loop real time voltage control to produce SPWM system using microcontroller was explained, illustrated and verified. The desired objectives were accomplished to achieve system that is able to generate high quality real-time SPWM with closed loop control.
Output power control of nuclear reactor using ant lion optimization-based controller Tarek A. Boghdady; Mostafa Mahmoud Ibrahim; Essam Aboul Zahab; Mahmoud Sayed
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1299-1305

Abstract

Power level control is a critical issue in nuclear power stations due to its nonlinear dynamics. One of the most commonly used controllers is fractional order proportional–integral–derivative (FOPID). The FOPID is an enhanced and modern controlling system that has two additional added parameters. In this paper, comparison between particle swarm, gray wolf and ant lion optimization techniques is performed to determine the FOPID controller parameters. The nuclear reactor is a pressurized water reactor which is a fifth order nonlinear reactor model and is simulated using MATLAB software based on the point kinetic model. The integral square error (ISE) performance index is used to evaluate the performance of the three optimization techniques. The simulation results show that ant lion optimization for tuning the FOPID controller parameters gives the best performance and integral square error index better than the two other optimization techniques.
Cancerous brain tumor detection using hybrid deep learning framework Sonali Kothari; Shwetambari Chiwhane; Shruti Jain; Malti Baghel
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1651-1661

Abstract

Computational models based on deep learning (DL) algorithms have multiple processing layers representing data at multiple levels of abstraction. Deep learning has exploded in popularity in recent years, particularly in medical image processing, medical image analysis, and bioinformatics. As a result, deep learning has effectively modified and strengthened the means of identification, prediction, and diagnosis in several healthcare fields, including pathology, brain tumours, lung cancer, the abdomen, cardiac, and retina. In general, brain tumours are among the most common and aggressive malignant tumour diseases, with a limited life span if diagnosed at a higher grade. After identifying the tumour, brain tumour grading is a crucial step in evaluating a successful treatment strategy. This research aims to propose a cancerous brain tumor detection and classification using deep learning. In this paper, numerous soft computing techniques and a deep learning model to summarise the pathophysiology of brain cancer, imaging modalities for brain cancer, and automated computer-assisted methods for brain cancer characterization is used. In the sense of machine learning and the deep learning model, paper has highlighted the association between brain cancer and other brain disorders such as epilepsy, stroke, Alzheimer's, Parkinson's, and Wilson's disease, leukoaraiosis, and other neurological disorders.
Performance comparison of TOPAS chirped fiber Bragg grating sensor with Tanh and Gaussian apodization Dedi Irawan; Khaikal Ramadhan; Saktioto Saktioto; Azwir Marwin
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1477-1485

Abstract

In this work we carried out a numerical simulation with software Optigrating for Apodization chirped fiber Bragg grating (CFBG) with TOPAS material to improve sensitivity sensor, it was found that CFBG with a grating length of 50 mm has advantages in terms of ripple factor, side lobe left (SLL), and side lobe right (SLR) with values of -0,998 and -10,5264 dB, respectively. While the 10 mm CFBG has a narrower full-width half maximum (FWHM) with a value of 0.4528 nm. Tanh and Gaussian apodization were arranged in the CFBG design, it was found that the Tanh linear-CFBG had a narrow FWHM but for the ripple factor and the main lobe and side lobes were not good enough compared to the Tanh Cubicroot-CFBG, and the same pattern was also obtained in the Gaussian apodization. The narrow FWHM indicates the accuracy in detecting temperature, as well as the suppression of SLL and SLR. for the effect of apodization on CFBG it was found that The Tanh Linear-CFBG design with TOPAS material has the highest sensitivity which is -51.76 pm/oC compared to other designs.

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