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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 2,901 Documents
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An improvement for CAST-128 encryption based on magic square and matrix inversion Kareem, Suhad Muhajer; Al-Adhami, Ayad; S. Rahma, Abdul Monem
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5340

Abstract

This paper presents two image encryption methods which aim to improve the CAST 128-bit algorithm by increasing the security level of encrypted images. The first improvement uses a magic square of order three, while the second improvement uses a 2×2 matrix over GF(P). Both modifications are used in each round of the CAST algorithm, in place of a standard algorithm which uses XOR to increase the correlation between the plaintext and ciphertext. Simulations are carried out in order to evaluate the image encryption system with regard to complexity, time consumption, histogram, information entropy, differential attacks, noise evaluation, adjacent pixels’ correlation index, National Institute of Standards and Technology (NIST) analyses, mean absolute error, and average difference. The experimental results demonstrate that the encryption and decryption time when using the proposed CAST 128-bit algorithm with magic square is less than the time required for the CAST 128-bit algorithm with the matrix. Conversely, the proposed CAST with the matrix is higher than the CAST with the magic square. Both theoretical analysis and experimental results confirm that the two proposed enhancements to CAST perform effectively with sufficient security levels.
Exploring COVID-19 vaccine sentiment: a Twitter-based analysis of text processing and machine learning approaches Khalaf, Ban Safir; Hamdan, Hazlina; Manshor, Noridayu
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7855

Abstract

In the wake of the 2020 coronavirus disease (COVID-19) pandemic, the swift development and deployment of vaccines marked a critical juncture, necessitating an understanding of public sentiments for effective health communication and policymaking. Social media platforms, especially Twitter, have emerged as rich sources for gauging public opinion. This study harnesses the power of natural language processing (NLP) and machine learning (ML) to delve into the sentiments and trends surrounding COVID-19 vaccination, utilizing a comprehensive Twitter dataset. Traditional research primarily focuses on ML algorithms, but this study brings to the forefront the underutilized potential of NLP in data preprocessing. By employing text frequency-inverse document frequency (TF-IDF) for text processing and long short-term memory (LSTM) for classification, the research evaluates six ML techniques K-nearest neighbors (KNN), decision trees (DT), random forest (RF), artificial neural networks (ANN), support vector machines (SVM), and LSTM. Our findings reveal that LSTM, particularly when combined with tweet text tokenization, stands out as the most effective approach. Furthermore, the study highlights the pivotal role of feature selection, showcasing how TF-IDF features significantly bolster the performance of SVM and LSTM, achieving an impressive accuracy exceeding 98%. These results underscore the potential of advanced NLP applications in real-world settings, paving the way for nuanced and effective analysis of public health discourse on social media.
Accident black spots identification based on association rule mining Mbarek, Abdelilah; Jiber, Mouna; Yahyaouy, Ali; Sabri, Abdelouahed
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6135

Abstract

This paper presents an analytical approach to identifying the important characteristics of accident black spots on Moroccan rural roads. An association rule mining method is applied to extract road spatial characteristics associated with fatal accidents. The weighted severity index was calculated for each section, which was then used to determine the severity levels of black spots. The apriori algorithm is applied to find the correlation between road characteristics and the severity levels of black spots. Then, a general rule selection method is proposed to identify the rules strongly associated with each severity level. The results show that the proposed approach is effective in identifying the most important factors contributing to accidents. Furthermore, it shows that the combination of several road characteristics, such as road width, road surface, and bridge presence, may contribute to fatal accidents. The general rule selection found that wet, bad surfaces, and narrow shoulders were significantly associated with accidents on rural roads. The findings of the present study can help develop effective strategies to reduce road accidents and thus improve road safety in the country.
Developing a secure voice recognition service on Raspberry Pi Le, Van-Hoan; Luc, Nhu-Quynh; Quach, Duc-Huy
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7655

Abstract

In this study, we present a novel voice recognition service developed on the Raspberry Pi 4 model B platform, leveraging the fast Fourier transform (FFT) for efficient speech-to-digital signal conversion. By integrating the hidden Markov model (HMM) and artificial neural network (ANN), our system accurately reconstructs speech input. We further fortify this service with dual-layer encryption using the Rivest–Shamir–Adleman (RSA) and advanced encryption standard (AES) methods, achieving encryption and decryption times well suited for real-time applications. Our results demonstrate the system's robustness and efficiency: speech processing within 1.2 to 1.9 seconds, RSA 2048-bit encryption in 2 to 6 milliseconds, RSA decryption in 6 to 10 milliseconds, and AES-GCM 256-bit encryption and decryption in approximately 2.6 to 3 seconds.
A review of deep learning models (U-Net architectures) for segmenting brain tumors Al-Murshidawy, Mawj Abdul-Ameer; Al-Shamma, Omran
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6015

Abstract

Highly accurate tumor segmentation and classification are required to treat the brain tumor appropriately. Brain tumor segmentation (BTS) approaches can be categorized into manual, semi-automated, and full-automated. The deep learning (DL) approach has been broadly deployed to automate tumor segmentation in therapy, treatment planning, and diagnosing evaluation. It is mainly based on the U-Net model that has recently attained state-of-the-art performances for multimodal BTS. This paper demonstrates a literature review for BTS using U-Net models. Additionally, it represents a common way to design a novel U-Net model for segmenting brain tumors. The steps of this DL way are described to obtain the required model. They include gathering the dataset, pre-processing, augmenting the images (optional), designing/selecting the model architecture, and applying transfer learning (optional). The model architecture and the performance accuracy are the two most important metrics used to review the works of literature. This review concluded that the model accuracy is proportional to its architectural complexity, and the future challenge is to obtain higher accuracy with low-complexity architecture. Challenges, alternatives, and future trends are also presented.
Reliability evaluation of non-isolated high gain interleaved DC-DC converter Ramamurthi, Subbulakshmy; Ramasamy, Palanisamy
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6585

Abstract

A high gain DC-DC converter is the crucial part in renewable energy systems (RES) and in electric vehicular systems. The reliability of those high-gain converters needs to be assessed for the long-term operation of renewable energy systems. This article presents the reliability analysis of non-isolated high gain interleaved DC-DC converter. The analysis primarily relies on calculating the mean time between failures (MTBF). Based on military handbook (MIL-HDBK-217) criteria, the reliability calculation is performed. Stress factors and predicted failure rate for each component of presented converter is evaluated and tabulated. Reliability evaluation is performed for 1.5 kW hardware prototype. Based on reliability evaluation results, a reliable converter with better operating life time has been introduced.
Accurate classification of forest fires in aerial images using ensemble model Madhuri, Ch Raga; Jandhyala, Sravya Sri; Ravuri, Deepthi Meenakshi; Babu, Vunnava Dinesh
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6527

Abstract

This paper proposes a method to identify forest fires in aerial images using three different convolutional neural networks (CNNs). Unlike general approaches that make use of a single CNN to classify the images, the proposed solution uses the outcomes of different CNNs and considers the most predicted class. This method overcomes the problems associated with using a single CNN, such as low accuracy due to the drawbacks associated with that model. The three different classifiers used here are InceptionV3, VGG-16, and ResNet50. Classification is carried out based on the presence of fire or smoke features in the images. The individual predictions are combined using max-ensembling. The performance is analyzed using metrics like precision, recall, accuracy and F1-score. From the work, it was found that the combined model resulted in an accuracy of 95.8%. The results confirm that the final model provides greater classification accuracy than the individual models. The proposed method can be used to predict forest fires from live aerial images more accurately and help reduce the damage caused.
Modified multicarrier sinusoidal pulse-width modulation for three-phase open-load five-level inverter Suroso, Suroso; Prasetijo, Hari; Susilawati, Hesti; Murdyantoro Am, Eko; Mubyarto, Agung
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7899

Abstract

Five-level voltage source inverter (VSI) is a power inverter topology generating a five-level output voltage waveform. This inverter topology can reduce harmonics distortion to be lower compared to a conventional two-level inverter. In practical, delay of gating signals is unavoidable during switching operation of power semiconductor switches. Adding dead time in the gating signals of VSI’s power switches is mandatory to avoid short circuit during switching operation. However, the dead time of the inverter’s switching signals causes low frequency harmonics and distortion of inverter’s output waveforms. In this paper, a different multicarrier sinusoidal pulse-width modulation (SPWM) method with harmonics suppression capability was proposed and applied in the three-phase open-connection load five-level inverter. The proposed modified SPWM was tested using computer simulation of Powersim (PSIM) software. The measured output waveforms of the five-level VSI at different power factor conditions are presented and analyzed. The total harmonics distortion (THD) values of inverter’s output current were suppressed using the proposed SPWM method to be less than 1%. The test results showed that the proposed modified SPWM method was able to reduce the distortion (THD) of alternating current (AC) waveform, and increase the quality of the inverter’s output power.
BER estimation for STBC-MC-DS-CDMA-4 antennas system by varied wavelet-carriers features via AWGN-flat channels Khadam, Nader Abdullah; Kadhim Jawad Alrubaie, Ali Jawad; Jumah Al-Thahab, Osama Qasim
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5371

Abstract

This paper improves the bit error rate (BER) of the modern communication system by taking into account the effect of the wavelet shape and the number of carriers on the performance of the space time block code multi-carrier direct sequence code division multiple access (STBC-MC-DS-CDMA). Here the transmitter is moved with speeds 2 km/hr, 45 km/hr and 100 km/hr via Rayleigh flat fading channel. Here, 2 antennas are employed at the receiver to mitigate the multipath signal influence. The system’s orthogonal frequencies are generated using Haar, Daubechies 4, Symlets 4, Cohen-Daubechies-Feauveau 1.1 with 9.7 and B-spline 3. The number of used carriers is 128, 512, and 1,024. Quadrature phase shift key (QPSK) is used with cyclic prefix 1/16 and a bandwidth of 20 MHz. traditional fast fourier transform (FFT) system is compared to the proposed discrete wavelet packet transform (DWPT) to show the BER enhancements. The space-time block coding (STBC) is used to enhance system cabability in error corection. The proposed system shows significant improvement in BER, so that, it reaches to the same BER when using FFT but with less signal to noise ratio (SNR), which interns reduce the power consumed within the system and the cost.
Printed circuit board and printed circuit board assembly methods for testing and visual inspection: a review Petkov, Nikolay; Ivanova, Malinka
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7601

Abstract

Testing and visual inspection of printed circuit boards (PCBs) and printed circuit board assemblies (PCBAs) are important procedures in the manufacturing process of electronic modules and devices related to locating and identifying possible defects and failures. Earlier defects detection leads to decreasing expenses, time and used resources to produce high quality electronics. In this paper an exploration and analysis about the current research regarding methods for PCB and PCBA testing, techniques for defects detection and vusial inspection is performed. The impact of machine and deep learning for testing and visual inspection procedures is also investigated. The used methodology comprises bibliometric approach and content analysis of papers, indexed in scientific database Scopus, considering the queries: “PCB and testing” and “PCB and testing”, “printed circuit board assembly and testing” and “PCBA and testing”, “PCB defect detection” and “PCBA defect detection”, “PCB and visual inspection”, and “PCBA and visual inspection”. The findings are presented in the form of a framework, which summarizes the contemporary landscape of methods for PCBs and PCBAs testing and visual inspection.

Page 237 of 291 | Total Record : 2901

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