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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.
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 12, No 2: April 2023" : 64 Documents clear
Optimization-based pseudo random key generation for fast encryption scheme Shihab A. Shawkat; Najiba Tagougui; Monji Kherallah
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4953

Abstract

Data encryption is being widely employed to secure data in order to provide confidentiality, authenticity and data privacy. In proposed method a novel method for (encryption, decryption) message through optimization using genetic algorithm (GA) is presented which aims to maintain the security of the message via increasing the complexity of the key used in the encryption. The proposed method is named stream cipher randomization using GA (SCRGA). It is characterized by its secrecy by hiding the statistical properties for the input message. The GA increases the key diffusion in order to eliminate the likelihood of using the statistical analysis and cryptanalysis techniques to obtain the original text. A key (k) will be supplied as input to pseudorandom bit generator and then it produces a random 8-bit output, The SCRGA evaluates the candidate keys and it would select the one that achieves the best value of the fitness function by maximization three criteria considered in matching the input message and the key. The test results were based on the comparison of the proposed method with two other state-of-the-art methods, that the SCRGA outperformed the other two methods in terms of the execution time (encryption, decryption) and encryption rounds key size.
Alzheimer’s disease classification and detection by using AD-3D DCNN model Afiya Parveen Begum; Prabha Selvaraj
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4446

Abstract

Deep learning techniques had achieved notability in the healthcare domain and are more specialized in medical imaging. Alzheimer’s disease (AD) enduring nervous system disorder affects elderly senior people with loss of cognitive processes and loss of memory. Early and précised detection of AD is essential for patient medical assistance and potential treatment. Since deep learning algorithms are adequate to analyze the enormous dataset and extract higher-level features from it, unlike traditional machine learning algorithms. This work presents a system-based deep convolutional neural network (DCNN) algorithm to detect AD and its stages. A DCNN and 3D densely connected convolutional neural networks (3D-DCNN) are used to perform the feature analysis and classification task. Finally, the features learned from the DCNN and 3D-DCNN are concatenated to classify disease. Alzheimer's disease neuroimaging initiative (ADNI) dataset is used for experimental analysis. The proposed AD-3DCNN model is compared to existing pre-trained models like Xception, inception V3, mobile Net, and dense Net and has recorded a highest accuracy for predicting different stages of AD. Apart from accuracy, various performance measures are used for evaluating system performance as precision, recall, and F1 score accuracy.
Real-time multiple face mask and fever detection using YOLOv3 and TensorFlow lite platforms Ali A. Abed; Alaa Al-Ibadi; Issa Ahmed Abed
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4227

Abstract

COVID-19 has caused disruptions to many aspects of everyday life. To reduce the impact of this pandemic, its spreading must be controlled via face mask wearing. Manually mask-checking for everybody is embarrassing and uncontrollable. Hence, the proposed technique is used to help for automatic mask-checking based on deep learning platforms with real-time surveillance live infra-red (IR) camera. In this paper, two recent object detection platforms, named, you only look once version 3 (YOLOv3) and TensorFlow lite are adopted to accomplish this task. The two models are trained with a dataset consisting of images of persons with/without masks. This work is simulated with Google Colab then tested in real-time on an embedded device mated with fast GPU called Raspberry Pi 4 model B, 8 GB RAM. A comparison is made between the two models to verify their performance in relation to their precision rate and processing time. The work of this paper is also succeeded to realize multiple face masks real-time detection up to 10 facemasks in a single scene with high inference speed. Temperature is also measured using IR touchless sensor for each person with sound alarming to alert fever. The presented detector is cheap, light, small, and fast, with 99% accuracy rate during training and testing.
Apply three metaheuristic algorithms for energy storage-based integrated power system to reduce generation cost Dao Trong Tran; Phu Trieu Ha; Hung Duc Nguyen; Thang Trung Nguyen
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4544

Abstract

This research applies new computing methods to optimize the operation of a typical hydrothermal system for one day. The system consists of one thermal power plant (TPP) and one pumped storage hydropower plant (PSHP). The main target of the research is to determine the amount of water that must be discharged or pumped back to the reservoir to reduce the total electricity production cost (TEPC) of TTP. The volumes of water storage in the reservoir at the beginning and end points of the schedule must be the same. Three meta-heuristic algorithms are applied, including Coot optimizer (COOT), aquila optimizer (AO), and particle swarm optimizations (PSO) in which COOT and AO were proposed at early 2021. The results show that the effectiveness of COOT is better than AO, PSO and several methods in previous studies. Hence, COOT is considered a powerful computing tool for the problem.
Normal operation and reverse action of on-load tap changing transformer with its effect on voltage stability Sinan Moayad A. Alkahdely; Ahmed Nasser B. Alsammak
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4556

Abstract

As electrical grids have expanded significantly, so too has the load on network buses. This, however, causes voltage drops to occur at the load side of the grid. A voltage drop causes a system to become unstable, increases its power loss, and reduces the amount of power that it transfers before finally leading to a collapse. An on-load tap changing (OLTC) transformer can be used to prevent the negative effects of an increased load by restoring the load voltage to its base value when sudden disturbances occur in the source. However, incorrect OLTC placement can cause the system to become unstable and cause collapse. This is referred to as the reverse action phenomenon of an OLTC. Therefore, this present study examined improving the ability of an OLTC to increase system stability and prevent collapse. A simple radial power distribution system was modelled in MATLAB. The results indicate that the proposed model can increase system stability and prevent collapse.
Use of scanning devices for object 3D reconstruction by photogrammetry and visualization in virtual reality Irena Drofova; Wei Guo; Haozhou Wang; Milan Adamek
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4584

Abstract

This article aims to compare two different scanning devices (360 camera and digital single lens reflex (DSLR) camera) and their properties in the three-dimensional (3D) reconstruction of the object by the photogrammetry method. The article first describes the various stages of the process of 3D modeling and reconstruction of the object. A point cloud generated to the 3D model of the object, including textures, is created in the following steps. The scanning devices are compared under the same conditions and time from capturing the image of a real object to its 3D reconstruction. The attributes of the scanned image of the recon-structed 3D model, which is a mandarin tree in a citrus greenhouse in a daylight environment, are also compared. Both created models are also compared visually. That visual comparison reveals the possibilities in the application of both scanning devices can be found in the process of 3D reconstruction of the object by photogrammetry. The results of this research can be applied in the field of 3D modeling of a real object using 3D models in virtual reality, 3D printing, 3D visualization, image analysis, and 3D online presentation.
Accurate license plate recognition system for different styles of Iraqi license plates Sukaina Sh Altyar; Samera Shams Hussein; Lubab Ahmed Tawfeeq
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4186

Abstract

Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recognize all these license plate types using the same algorithm. In this work, a new method has been proposed to efficiently recognize all these types of license plates. This has been done by utilizing a series of algorithms for preprocessing and recognition with new identification strategies. The results show that the system recognized license plate numbers with higher accuracy, reaching up to 97.85%. However, the method field to detect license plates when there are some high deformations in plate numbers or when they are partially covered with mud, which makes it difficult to distinguish numbers.
Using sensorless direct torque with fuzzy proportional-integral controller to control three phase induction motor Yaser Nabeel Ibrahem Alothman; Wisam Essmat Abdul-Lateef; Sabah Abdul-Hassan Gitaffa
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.3991

Abstract

Induction motors (IM) attracted many researchers in the last few decades. In this field, various applications are implemented, such as servo motor drives and electric vehicles. This work applies a sensorless direct torque controller (DTC) to control a three-phase IM. System dynamics of the IM were derived. A nonlinear dynamic model had introduced with white noise. Given the complexity of the dynamics, the Jacobean Linearization technique has been used to obtain the linear model for a control task. A DTC technique is employed to control the motor speed of the system with a combination of two controllers. The fuzzy proportional-integral (PI) controllers are applied to obtain the reference torque based on an optimization process against the speed error raise. The optimizer is called grey wolf optimizer (GWO) and is implemented to achieve the centre values of the two output memberships for the fuzzy PI controllers. Then the extended Kalman filter (EKF) is used to evaluate the direct and quadratic components of the rotor flux and rotor speed from the observation of stator voltages and currents. The system is tested employing MATLAB simulation software and determines the targeted results. The outcomes are evaluated to improve the control performance.
Multi-dimension SVPWM-based sensorless control of 7-phase PMSM drives Kamel Saleh; Mark Sumner
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4665

Abstract

A new control technique for the 7-phase permanent magnet synchronous machine (PMSM) when a failure in the speed sensor is introduced. This will make the whole drive system more robust and at the same time reduce the cost. The speed and the position of the shaft of the motor are obtained by tracking the saturation saliency of the 7-phase motor when a failure in speed sensor is occurred. The proposed saliency-tracking algorithm is based on measuring the derivative of the stator currents of the 7-phase motor after the switching of the insulated gate bipolar transistor (IGBT) of the 7-phase inverter due to the implementation of the multi-dimension space vector pulse width modulation (SVPWM). This modulation technique is used in the 7-phase drives to suppress the 3rd and 5th harmonics. Simulation results show that the 7-phase motor drive could track the reference speed at different load conditions when a failure in the speed sensor is occurred without compromising the performance.
Bluetooth beacons based indoor positioning in a shopping malls using machine learning Kamel Maaloul; Brahim Lejdel; Eliseo Clementini; Nedioui Med Abdelhamid
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4200

Abstract

The adoption of Bluetooth beacon technology demonstrates a broad interest in indoor positioning technology because of its low cost and ease of use. Bluetooth beacons usually have an accuracy of fewer than 4 meters. The use of machine learning (ML) leads to results with greater accuracy compared to using traditional filtering methods. In this paper, we provide indoor localization based on Bluetooth beacons using several different ML techniques. We used ML algorithms to locate customers' devices in shopping malls. The extra-trees classifier and k-neighbors classifier found the device with greater than 90% accuracy. Other algorithms were able to determine the location with less accuracy. The results also showed that Bluetooth technology is a valid solution to find the data used to analyze the spatial-temporal behavior of individuals.

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