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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
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Articles 70 Documents
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Search results for , issue "Vol 12, No 5: October 2023" : 70 Documents clear
The contribution of image processing in the evaluation of guided bone regeneration Hamid El Byad; Manal Ezzahmouly; Mohammed Ed-Dhahraouy; Abdelmajid El Moutaouakkil; Zineb Hatim
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5795

Abstract

One of the most ambitious goals of modern bone surgery is to predict the shape of the bone defect, monitor the progress of bone regeneration, and assess the quantity and quality of newly formed bone. Calcium phosphate biomaterials such as hydroxyapatite and tricalcium phosphate are commonly used as bone substitutes in maxillofacial and dental surgery. The objective of this work is to use cone-beam computed tomography (CBCT) and image processing to assess the spatial (architectural) layout, rate of bone generation and osseointegration of implanted commercial granules (PAH 40%, β-TCP 60%, size 0.5 to 1 mm) in the bone defect generated after tooth extraction. CBCT measurements were performed at 48 hours and 12 months. The analysis of 3D images and the application of appropriate morphological mathematical operations allowed us to evaluate the volume of the cavity to be filled, the volume occupied by the granules and the volume of porosity generated by the random stacking of the granules. The result shows that the bone generation rate reaches a value of 89% after one year of implantation. This study shows that by using 3D image processing techniques CBCT, the same results as classical anatomical and histological studies can be obtained.
Multi-objective metaheuristic optimization algorithms for wrapper-based feature selection: a literature survey Anitha Gopalakrishnan; Vinodhini Vadivel
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4757

Abstract

In the data mining and machine learning (ML) discipline, feature selection problem is considered among many researchers in the recent times. Feature selection process targets to minimize feature set number and maximize performance accuracy by identifying optimal features. Multiple objectives are considered while identifying the optimal feature hence multi-objective metaheuristic optimization algorithms (MOMOAs) are applied. In this study, literature review is performed MOMOAs-for solving wrapper feature selection problem (WFS). The literature review for solving WFS problem and discuss the challenges faced by the researchers in solving the feature selection problem. The literature review is performed on all relevant studies published in the last 12 years [2009-2022]. A detailed overview of the feature selection preliminaries, MOMOAs-WFS, role of the classifier in feature selection problem are presented. The outcome of this literature review is to highlight the existing works related to WFS problem using MOMOAs. Finally, the research areas for improvement are identified and emphasized for the scientists to survey in the field of MOMOAs.
Accelerated thermal aging of Kraft papers impregnated with dielectric liquids Imran Sutan Chairul; Norazhar Abu Bakar; Sharin Ab Ghani; Mohd Shahril Ahmad Khiar; Nor Hidayah Rahim; Syahrun Nizam Md Arshad@Hashim
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4336

Abstract

Accelerated thermal aging was conducted on Kraft papers impregnated with mineral insulating oil (MO) and palm insulating oil (PO), and the effect of aging time on the oils and Kraft papers was observed. Each sample consisted of insulating oil, dried Kraft paper, and weighed metal catalysts (copper, iron, zinc, and aluminum) in a bottle. Prior to aging, the bottles were left for 24 h at room temperature for impregnation to take place. The thermal aging experiments were carried out at 130 °C for 250, 500, and 750 h. The properties of the MO and PO (moisture content, acidity, and ultraviolet-visible absorption spectra) and the properties of the Kraft papers (tensile strength and colour) were determined. Results showed that the aged PO had higher moisture content compared with the aged MO. However, the Kraft papers impregnated with PO had better tensile strength after 750 h of aging, which may be attributed to the affinity of PO to moisture. This slows down the hydrolytic degradation mechanism. In terms of colour, the Kraft papers were darker than their original colour as the tensile strength decreased. To conclude, the Kraft paper impregnated with PO had higher tensile strength compared with those impregnated with MO.
On the design of trust and mobility based evaluation for intelligent collaborative UAVs assisted VANETs Sami Abduljabbar Rashid; Ahmed Shamil Mustafa; Abdulkareem Dawah Abbas; Hamza Qasim Abdullah; Mohammed Jassim Mohammed
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5223

Abstract

In recent days, vehicles usage and speed are highly increased that leads to an increase in energy consumption, delay, and overhead in the network. In this paper, a novel trajectory is introduced to achieve maximum reliability namely trust and mobility-based evaluation for intelligent collaborative (TMIC)-UAVs assisted VANETs. Reactive multipath greedy routing protocol (RMGR) is the hybrid routing protocol and it is the combination of ad hoc on-demand multipath distance vector (AOMDV) with greedy geographic forwarding (GGF) which is used for routing in frequently changeable network topology. To protect the network from malfunctions, effective trust evaluation (ETE) is performed by calculating the direct trust and indirect trust. Finally, to achieve effective communication among the UAVs, hybrid optimization is performed which is the combination of the genetic algorithm (GA) and the crow swarm optimization (CSO) algorithm. For validation network simulator (NS3) is used and the results show that this approach achieves high energy efficiency, delivery ratio, and reduction in delay when compared with the earlier research.
Improve power quality of charging station unit using African vulture optimization algorithm Saleh Masoud Abdallah Altbawi; Saifulnizam Abdul Khalid; Ahmad Safawi Mokhtar; Rayan Hamza Alsisi; Zeeshan Ahmad Arfeen; Hussain Shareef; Mehreen Kausar Azam
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5717

Abstract

In recent years, there is growth in acceptance to consume fewer fossil fuels globally and the manufacturing of electric vehicles (EVs) has become more popular. However, the increase in the number of systems connected to the grid that contain EVs with a huge power capacity leads to unstable working in the power system. To assess the stability of the electric charging station several control approaches in AC part and DC parts during charging mode and discharging modes are tested. African vulture optimization algorithm (AVOA) has been utilized to tune the system controllers (proportional integral derivative (PID)/tilt integral derivative (TID) controllers). The superiority of AVOA is confirmed by comparing the performance with the genetic algorithm (GA). Two objective functions have been used i.e. integral time absolute error (ITAE) and integral square time error (ISTE). AVOA-tuned TID controllers using ISTE were found to be the best to contain the frequency deviations. The results have shown of the AC part and DC part is within an acceptable limit recommended by IEEE standard. Further, maximum peak overshoot, undershoot, and settle time obtained by AVOA-tuned PID and TID controllers are found the best. Finally, the improvement of the performance index obtained by AVOA over its counterpart GA is confirmed.
Limits of reactive power compensation of a doubly fed induction generator based wind turbine system Abdulabbas, Ali Kadhim; Alawan, Mazin Abdulelah; Shary, Diyah Kammel
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4968

Abstract

The doubly fed induction generator (DFIG) systems feature a significant amount of free power capacity that may be used for reactive power adjustment when they are put into practical use. This change, which is occasionally overlooked, is a significant one. Using DFIG systems for wind turbines (WT), this paper explored strategies for reducing and using reactive power. In order to investigate the power characteristic and how it is regulated in DFIG systems, a mathematical model for the steady-state performance of DFIG WT has been developed and presented. Here is a detailed derivation of the limiting range of DFIG's reactive power capacity as well as the physical constraints on reactive power output. The distribution of the DFIG WT at a distribution network's end is demonstrated by a simulation example. Within this simulation, reactive power management strategy, load fluctuation, and the change in wind speed are all taken into consideration. Due to the possibility of a rise in the voltage at the access point, can concluded that both acceptable and efficient to use DFIG WT's reactive power capabilities as an additional continuous reactive power source for effectiveness.
Betel leaf classification using color-texture features and machine learning approach Novianti Puspitasari; Anindita Septiarini; Ummul Hairah; Andi Tejawati; Heni Sulastri
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5101

Abstract

The existence of machine learning has been exploited to solve difficulties in various fields, including the classification of leaf species in agriculture. Betel leaf is one of the plants that provide health advantages. The objective of using a machine learning approach is to classify the betel leaf species. This study involved several processes: image acquisition, region of interest (ROI) detection, pre-processing, feature extraction, and classification. The feature extraction used the combination features of color and texture. Furthermore, the classification applied four classifiers, including artificial neural network (ANN), K-nearest neighbors (KNN), Naive Bayes, and support vector machine (SVM). The evaluation in this study implemented cross-validation with a K-fold value of 5. The method performance produced the highest accuracy value of 100% using the color and texture features with the SVM classifier.
Novel annular seven tooth antenna compare its gain and return loss with circular patch antenna for mobile navigation Raja Meganathan; Saravanakumar Rengaraj
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5325

Abstract

The aim of the study involves the design of a novel annular seven tooth antenna and comparing its gain, return loss with a circular patch. Totally 38 samples are considered for the analysis which is obtained using the G power tool by fixing the pretrained power and the error rate as 0.811 and 0.051 respectively. The total 38 samples are grouped into two namely novel annular seven tooth antenna with 19 samples and circular patch with 19 samples. The performance of the antennas is analyzed using return loss and gain. The design of novel annular seven tooth antenna produced a high gain of 7.7 dB which is more significant than the gain of circular patch antennas (CPA) for navigation application. It is found that the gain, return loss of the designed novel annular seven tooth antenna is 7.7 dB, -18.1 dB. The gain and return loss of the novel annular seven tooth antenna is improved and it is compared with circular patch. It is more significant as it has a p value less than 0.05.
A PSO optimized RBFNN and STSMC scheme for path tracking of robot manipulator Atheel K. Abdul Zahra; Turki Y. Abdalla
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5018

Abstract

This article presents the design of super twisting sliding mode control (STSMC) based on radial basis function neural network (RBFNN) for path tracking of two link robot manipulator. The proposed controller is utilized to guarantee and achieve that the surface of sliding can be in equilibrium point within a short time and avoid the problem of chattering at the output. The Lyapunov theory is used in presenting a new convergence proof. Also, the particle swarm optimization (PSO) algorithm is employed to give the optimal parameter values of the proposed controller. Simulation results explain the goodness of the proposed control method for trajectory tracking of 2-link robot manipulator when compared with SMC strategy. Results demonstrate that the the percentage improvement in mean square error (MSE) of using STSMC when compared with the standard SMC are 15.36%, 16.94% and 12.92%, for three different cases respectively.
Stacking ensemble learning for optical music recognition Francisco Calvin Arnel Ferano; Amalia Zahra; Gede Putra Kusuma
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5129

Abstract

The development of music culture has resulted in a problem called optical music recognition (OMR). OMR is a task in computer vision that explores the algorithms and models to recognize musical notation. This study proposed the stacking ensemble learning model to complete the OMR task using the common western musical notation (CWMN) musical notation. The ensemble learning model used four deep convolutional neural networks (DCNNs) models, namely ResNeXt50, Inception-V3, RegNetY-400MF, and EfficientNet-V2-S as the base classifier. This study also analysed the most appropriate technique to be used as the ensemble learning model’s meta-classifier. Therefore, several machine learning techniques are determined to be evaluated, namely support vector machine (SVM), logistic regression (LR), random forest (RF), K-nearest neighbor (KNN), decision tree (DT), and Naïve Bayes (NB). Six publicly available OMR datasets are combined, down sampled, and used to test the proposed model. The dataset consists of the HOMUS_V2, Rebelo1, Rebelo2, Fornes, OpenOMR, and PrintedMusicSymbols datasets. The proposed ensemble learning model managed to outperform the model built in the previous study and succeeded in achieving outstanding accuracy and F1-scores with the best value of 97.51% and 97.52%, respectively; both of which were achieved by the LR meta-classifier.

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