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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 9,138 Documents
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Fuzzy controlled modified reduced switch converter for switched reluctance motor under dynamic loading Ritika Asati; Deepak S. Bankar; Aishwarya Apte; Amit L. Nehete; Yogesh Mandake
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp50-58

Abstract

In this paper, modified reduced switch converter topology is used to drive 8/6 pole, 7500 W switched reluctance motor (SRM) with an electric vehicle (EV) load. Fuzzy logic control (FLC) is developed for the modified converter topology and its performance is compared with the proportional integral (PI) controller. Analytical equations, switching pulses and different mode of operation are presented for modified reduced switch converter using double phase magnetization scheme. The converter topology adopts a modified switching sequence i.e., magnetization then freewheeling before demagnetization. It offers lesser torque ripples, reduced phase current and need only four switches for a 4-phase SRM drive. Modified reduced switch converter is simulated in MATLAB-simulation to investigate and compare the steady state waveforms and transient speed response of the PI and FLC. Torque ripple in modified converter is 50% less than the classical converter. Peak overshoot and settling time performance of FLC is superior as compared to PI, when applied to modified converter with EV loading.
AMSVT: audio Mel-spectrogram vision transformer for spoken Arabic digit recognition Mahmoudi, Omayma; El Allali, Naoufal; Bouami, Mouncef Filali
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp1013-1021

Abstract

This work presents a novel model to recognize spoken digits in the Arabic language. Due to the transformer-based models' tremendous success in natural language processing (NLP), several attempts have been made to extend transformer-based designs to other domains, such as vision and audio. However, our approach consists of extracting and inputting Mel-spectrogram features into our model of the proposed audio Mel-spectrogram vision transformer (AMSVT) for training. The signal processing community has been interested in these models due to the successful use of vision transformers (ViT) in several computer vision applications. This is because signals are frequently recorded as spectrograms (using the Mel-spectrogram, for example), which may be given directly as input to vision transformers. Our model outperformed a group of models in terms of accuracy and time, such as convolutional neural network (CNN)-based and recurrent neural network (RNN)-based.
Dynamic line rating for grid transfer capability optimization in Malaysia Nurul Husniyah Abas; Mohd Zainal Abidin Ab Kadir; Norhafiz Azis; Jasronita Jasni; Nur Fadilah Ab Aziz
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp696-706

Abstract

This paper details a case study on the implementation of dynamic line rating (DLR) to enhance the ampacity rating of Malaysia’s grid. Utilizing heat balance equations endorsed by the Institute of Electrical and Electronics Engineering (IEEE 738) and the International Council on Large Electric Systems (CIGRE technical brochure 601), the ampacity rating of a Zebra-type aluminum cable steel reinforced (ACSR) conductor on a 275 kV transmission line has been assessed. Real-time weather conditions and conductor temperatures, measured hourly by the DLR sensor over the course of a year, were incorporated into the ampacity calculation to determine the available margin. The weather parameters were analyzed based on the monsoon seasons. A comparative analysis between various methods outlined in the standards and the estimated ampacity rating derived from both standards is presented. According to both standards, the findings indicate that DLR surpasses static line rating (SLR), highlighting the presence of untapped ampacity for grid optimization. Remarkably, CIGRE TB 601 exhibits a higher ampacity rating margin than the IEEE 738 standard, with a percentage difference of 16.20%. The study concludes that the conductor is underutilized and proposes optimization through the integration of real-time weather conditions data into the heat balance equations.
Mathematical models for resolving the nonlinear formula for solar cell Mohammed Rasheed; Iqbal Alshalal; Arshad Abdula Ashed; Mohammed Abdelhadi Sarhan; Ahmed Shawki Jaber
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp653-660

Abstract

Accurate representation of a photovoltaic solar cell requires a comprehensive assessment of modeling factors that are unique to the individual device being studied. In the context of the single diode model, it is necessary to ascertain five distinct parameters, namely Rs, Rsh, Iph, Io, and n. In general, analytical or numerical methods may be used to calculate these values. In this paper, two alternative iterative approaches to solving nonlinear problems in solar cells without temperature are described and analyzed. The new iterative approach has several instances that have been quantitatively tested. This novel approach can be seen as a potential option for solving nonlinear equations. Additionally, a comparison between the suggested method, classic chord formula (CCM), and predictor-corrector type reveals that it is better and has the lowest evaluation. This is supported by an examination of accuracy and efficiency (as evaluated by function evaluations) false position method (FPM).
Optical sensor to improve the accuracy of non-invasive blood sugar monitoring Aliya Zilgarayeva; Nurzhigit Smailov; Sergii Pavlov; Sharafat Mirzakulova; Madina Alimova; Bakhytzhan Kulambayev; Dinara Nurpeissova
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1489-1498

Abstract

Optical sensors offer a painless method of monitoring blood glucose levels using various light technologies to analyze blood characteristics without penetrating the skin. The literature review part reflects the progress in optical sensor technology evaluates its potential in blood glucose monitoring by overcoming the limitations of conventional methods and recognizes the challenges and future prospects in this rapidly developing area of research. The results of empirical studies are then presented. The methodology is presented as a non-invasive method of blood glucose monitoring based on near-infrared spectroscopy. To precisely evaluate blood glucose concentrations, spectroscopy techniques involving absorption and reflection are employed at wavelengths 450, 900, 1350, and 1800 nm. After absorption and reflection of glucose molecules, light is generated. An experimental study of different samples revealed a linear relationship between the final output voltage and sugar concentration. The results demonstrate a correlation between blood glucose level and signal intensity after transmission.
Adaptive fuzzy weighted median filter for microcalcifications detection in digital breast tomosynthesis images Syafiqah Aqilah Saifudin; Siti Noraini Sulaiman; Muhammad Khusairi Osman; Iza Sazanita Isa; Noor Khairiah A Karim; Nur Athiqah Harron
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp197-209

Abstract

Breast cancer is a global leading cause of female mortality. Digital breast tomosynthesis (DBT) is pivotal for early breast cancer detection, with microcalcifications serving as crucial indicators. However, the movement of the DBT machine introduces blurry artefacts, potentially impacting accurate diagnosis. This study addresses this challenge by proposing an adaptive fuzzy weighted median filter (AFWMF) to enhance DBT images and aid microcalcification diagnosis. AFWMF automatically determines optimal parameters based on input images, outperforming conventional methods with a threshold range (C) from peak to end of switching. Quantitative assessment reveals peak signal to noise ratio (PSNR), and mean absolute error (MAE) values of 96.2267 and 0.0000636, respectively, demonstrating a significant improvement in microcalcification detection. This study contributes an effective and adaptive enhancement technique for DBT images, promising better breast cancer diagnosis, particularly in microcalcification scenarios.
Stereo object matching for mobile robot path planning using artificial fish algorithms Andi Besse Firdausiah Mansur
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp661-670

Abstract

The popularity of robots is on the rise, not only in industrial settings but increasingly in daily venues such as airports. Recently, some organizations have carried out experiments utilizing robots specifically created to improve airport hygiene, security, and passengers’ overall satisfaction. Furthermore, the utilization of the artificial fish (AFs) algorithm in path planning for mobile robots yielded exceptional outcomes. The robot can replicate the prey behavior of the AFs algorithm, as evidenced by the prevalence of pos one in the simulation. The robot exhibits another behavior, which is the subsequent behavior. The behavior of the AFs algorithm is influenced by the available food sources. Simultaneously, mobile robots are influenced by the stimulation of their neighboring responses. Afterwards, the three primary classifiers are employed to perform stereo-object matching on different objects. The recognition rate achieved by the AdaBoost classifier is promising, with an accuracy rate of 92.4%. This result shows excellent potential for improving the path planning of mobile robots equipped with visual surveillance systems for their surroundings.
A hybrid spectral-spatial fusion technique for hyperspectral object classification Radhakrishna Mani; Manjunatha Raguttapalli Chowdareddy
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp361-369

Abstract

In the field of object classification, hyperspectral imaging (HSI) has been widely used, due to its spectral-spatial, and temporal resolution of larger areas. The HSI is generally used to identify the objects physical properties in accurate manner and as well as to identify similar object with acceptable spectral signatures. Thus, the HSI has been widely used for object identification applications in different fields such as precision agriculture, environmental study, crop monitoring, and surveillance. However, the object classification is time consuming due to extremely large size; thus, the feature fusion of both spectral and spatial have been done. The current feature fusion method fails to retain semantic object intrinsic feature; further, current classification technique induces higher misclassification. In addressing the research issues this paper introduces a hybrid spectral-spatial fusion (HSSF) technique to reduce feature size and retains object intrinsic properties. Finally, in reducing misclassification a soft-margins kernel is introduced in support vector machine (SVM). Experiment is conducted on standard Indian Pines dataset; the result shows the HSSF-SVM model attain much higher accuracy and Kappa coefficient performance.
Pole placement tuning of proportional integral derivative feedback controller for knee extension model Saharul Arof; Emilia Noorsal; Saiful Zaimy Yahaya; Zakaria Hussain; Rosfariza Radzali; Faridah Abdul Razak; Harith Firdaus Mustapha
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1566-1581

Abstract

Functional electrical stimulation (FES) has shown potential in rehabilitative exercises for patients recovering from spinal cord injuries. In recent developments, conventional open-loop FES control techniques have evolved into closed-loop systems that employ feedback controllers for automation. However, closed-loop FES systems often face challenges due to muscle non-linear effects, such as fatigue, time delays, stiffness, and spasticity. Therefore, an accurate non-linear knee model is required during the design stage, and precise tuning of the feedback controller parameters is vital. A proportional– integral–derivative (PID) controller is commonly used as a feedback controller due to its simplicity and ease of implementation. However, most PID tuning methods are complex and time consuming. This paper investigates the viability of employing the pole placement technique for tuning a PID controller that regulates the non-linear knee extension model. The pole placement method aims to improve the control and adaptability of the PID controller in closed-loop FES systems, specifically by facilitating knee extension exercises. MATLAB Simulink was used to assess the effectiveness of this tuning approach. Results showed that the PID controller performed satisfactorily without non-linearities, but performance varied with the inclusion of specific non-linearities. The pole placement tuning method facilitated preliminary assessments of PID controller performance, preceding highly advanced optimization.
DeepCOVID: a deep learning approach for accurate COVID-19 detection in point-of-care lung ultrasound Uma Narayanan; Renjini Pappadiyil Sukumri
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1063-1071

Abstract

Sickness still continued to spread through several countries when it first appeared in China. The number of COVID-19 cases is rising daily worldwide, posing a severe threat to the government and the populace. As a result of the virus’s rapid spread, doctors are having trouble recognizing positive cases. It is obvious that computer-based diagnosis must be developed to get results at a reasonable cost. The classic convolutional neural network (CNN) is used for this, utilizing the CT dataset, and the upgraded CNN model is used with the lung ultrasound (LUS) dataset. The CT and LUS COVID imaging datasets are compared in the model. The accuracy of both deep learning models is higher. We customized ResNet50, a pre-trained deep learning architecture, for a web application paradigm. First, we suggest a method for normalizing data that addresses its variability because it is collected in hospitals using various CT scanners and ultrasound machines. Second, we identify COVID-19 patients using U-Net segmentation and classification. The CNN architecture is added for deep learning purposes, and Res-Net 50 offers incredible accuracy.

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