Bulletin of Electrical Engineering and Informatics
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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2,901 Documents
Performance evaluation of precoding system for massive multiple-input multiple-output
Sarmad Khaleel Ibrahim;
Saif A. Abdulhussien
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.3877
Low latency, high data speeds, and a higher degree of perceived service quality for consumers and base station capacity are only some of the advantages of fifth generation (5G) mobile communications. This paper focuses on the design of a precoding system for downlink transmission of multi-user multiple-input multiple-output (MU-MIMO). For MU-MIMO systems, the traditional precoding techniques investigated are difficult since the transmitter precoding matrices created by singular value decomposition (SVD) are calculated twice. This paper implements different techniques of precoding with channel coding. Two advanced precoding, zero forcing (ZF) and maximum ratio transmitter (MRT) systems will be evaluated to find the best between them. Three different coding channels (turbo, low-density parity-check (LDPC), and polar) are used in this paper. The results indicate that the ZF-MU-MIMO with turbo coding outperforms MRT precoding, and more spatial diversity gain may be gained, in terms of throughput, number of users supported, and lower error rate in downlink and uplink massive MIMO.
Distributed big data analysis using spark parallel data processing
Hoger Khayrolla Omar;
Alaa Khalil Jumaa
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i3.3187
Nowadays, the big data marketplace is rising rapidly. The big challenge is finding a system that can store and handle a huge size of data and then processing that huge data for mining the hidden knowledge. This paper proposed a comprehensive system that is used for improving big data analysis performance. It contains a fast big data processing engine using Apache Spark and a big data storage environment using Apache Hadoop. The system tests about 11 Gigabytes of text data which are collected from multiple sources for sentiment analysis. Three different machine learning (ML) algorithms are used in this system which is already supported by the Spark ML package. The system programs were written in Java and Scala programming languages and the constructed model consists of the classification algorithms as well as the pre-processing steps in a figure of ML pipeline. The proposed system was implemented in both central and distributed data processing. Moreover, some datasets manipulation manners have been applied in the system tests to check which manner provides the best accuracy and time performance. The results showed that the system works efficiently for treating big data, it gains excellent accuracy with fast execution time especially in the distributed data nodes.
Evaluating multi-state systems reliability with a new improved method
Yasser Lamalem;
Soufiane Hamida;
Yassine Tazouti;
Oussama El Gannour;
Khalid Housni;
Bouchaib Cherradi
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i3.3509
The computation of network reliability for a system with many states is an NP-hard issue. Finding all the minimum path vectors (d-MPs) lower boundary points for each level d is one of the few approaches for computing such dependability. This research proposed enhancements to the technique described in Chen's "Searching for d-MPs with rapid enumeration" paper. We propose additional adjustments to the method that creates the flow vector F in this enhancement. This decreases the number of required steps and the temporal complexity of the method. Comparing the newly suggested approach to the old algorithm reveals that the adjustment has increased the enumeration's efficiency and degree of complexity.
Ca7Si2P2O16:Eu2+ green phosphor for optic enhancement of the WLEDs dual-layer remote structure
Van Liem Bui;
Guo Feng Luo;
Tam Nguyen Kieu
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.4066
To enhance the dual-layer remote phosphorus configuration’s color standard help spread its application in the LED devices, the new green-emitting phosphor of Ca7Si2P2O16:Eu2+ is proposed. The sol-gel method is used to dope the Eu2+ ions with Ca7Si2P2O16. Increasing the ion Eu2+ concentration can lead to high thermal stability, color-tunable ability, stronger green emission band, and higher photoluminescence extraction. The dual-layer structure’s color standards, as well as the luminous flux, are examined with different concentrations of Ca7Si2P2O16:Eu2+ in the phosphor layer. Owing to the improved features, the green phosphor Ca7Si2P2O16:Eu2+ has enhanced the emission intensity in the blue and green wavelengths, resulting in better color mixing and distribution. The luminescence shows the enhancement when increasing the concentration of Ca7Si2P2O16:Eu2+. However, the color rendering feature can present a reduction with more than 10% wt. green phosphor within the double-layer phosphorus remote configuration, due to color balance’s loss.
Recent development of planar microwave sensor for material characterization of solid, liquid, and powder: a review
Harry Sucitra Roslan;
Maizatul Alice Meor Said;
Zahriladha Zakaria;
Mohamad Harris Misran
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.4120
Microwave is the most popular sensor in industrial applications for detecting material characterization. Over the past decade, microwave sensor is high demand, especially in medical for detecting cancer in the human body, agriculture for detecting moisture of soil, and freshness in the food industry. The previous study has shown that the high demands of the microwave sensor in industrial applications make researchers always think of new ideas to design microwave sensors to improves accuracy and sensitivity. This paper reviews an investigation of material characterization of recent developments of a planar sensor for various contaminants and parameter value of solid, liquid, and powder as material under test (MUT). Planar resonator sensor enhances the weakness of conventional sensors in bulky size, required a large volume of samples, and high cost. This planar sensor will differentiate MUT properties based on scattering parameters at various operating frequencies. The framework presented in this review paper includes new developments in resonator structure as well as advanced design of potential future research work. Previous studies will be objectively analysed and compared in order to gain a better understanding of microwave resonant sensors and to develop innovative concepts to further enhance application research involving material characterization.
Design of a closed-loop autotune PID controller for three-phase for power factor corrector with Vienna rectifier
Nawres Ali Almamoori;
Bogdan Dziadak;
Ahmad H. Sabry
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.3728
A closed-loop auto-tuner proportional integral derivative (PID) controller for tuning the DC-link voltage, voltage neutral controllers, and DQ axis current for a power factor corrector with Vienna rectifier is developed and discussed in this study. In traditional tuning of these control loops, it is needed to tune one loop at a time manually, which tends to be a difficult and time-consuming process. In this work, we add a closed-loop PID auto-tuner in the control design will help to simplify and speed up this process by tuning all the 4 PID controllers in a single simulation running in a closed loop. Essentially, it runs auto-tuning experiments for the DQ axis -current, output voltage, and neutral point voltage loops by injecting perturbations; recording the output; estimating the plant frequency response, and tuning the PI controller parameters. In DQ-axis control, projections are used to convert time-based3-phase currents into a time invariant 2-coordinate vector. The results after adding the auto-tuner show that the response time improved considerably when the balanced load was introduced with the individual loads being connected. The results show that the neutral point voltage controller did a good job of keeping the voltage neutral point stable compared to the older controller gains.
Multi categorical of common eye disease detect using convolutional neural network: a transfer learning approach
Abu Kowshir Bitto;
Imran Mahmud
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.3834
Among the most important systems in the body is the eyes. Although their small stature, humans are unable to imagine existence without it. The human optic is safe against dust particles by a narrow layer called the conjunctiva. It prevents friction during the opening and shutting of the eye by acting as a lubricant. A cataract is an opacification of the eye's lens. There are various forms of eye problems. Because the visual system is the most important of the four sensory organs, external eye abnormalities must be detected early. The classification technique can be used in a variety of situations. A few of these uses are in the healthcare profession. We use visual geometry group (VGG-16), ResNet-50, and Inception-v3 architectures of convolutional neural networks (CNNs) to distinguish between normal eyes, conjunctivitis eyes, and cataract eyes throughout this paper. With a detection time of 485 seconds, Inception-v3 is the most accurate at detecting eye disease, with a 97.08% accuracy, ResNet-50 performs the second-highest accuracy with 95.68% with 1090 seconds and lastly, VGG-16 performs 95.48% accuracy taking the highest time of 2510 seconds to detect eye diseases.
An optimized algorithm for peak detection in noisy periodic and quasi-periodic signals
Luc Tri Tuyen;
Pham Quoc Vuong;
Thach Thi Ninh
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.3655
This paper represents a modified version (called T-AMPD) of automatic multiscale-based peak detection (AMPD) algorithm, which was previously proposed by Scholkmann et al for peak detection of noisy periodic and quasi-periodic signals, in order to optimize the algorithm and reduce the computational cost while still maintaining the accuracy. By introducing a new parameter , the number of expected peaks, to the algorithm and some other adjustments, the T-AMPD outperforms the original algorithm in processing time. Experiments in some real-world signals show that the modified algorithm is greatly better than the original one in runtime performance. Specifically, our T-AMPD was compared to the newest version of AMPD which is available in an R programming package. As a result, our T-AMPD is 2 to 25 times faster than the original AMPD in computational time, while the accuracy remains unchanged.
Techniques of medical image encryption taxonomy
Mustafa A. Al-Fayoumi;
Ammar Odeh;
Ismail Keshta;
Ashraf Ahmad
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.3850
Medical images are one of the most significant and sensitive data types in computer systems. Sending medical images over the internet necessitates using a robust encryption scheme that is resistant to cryptographic attacks. Confidentiality is the most critical part of the three security objectives for information systems security, namely confidentiality, integrity, and availability. Confidentiality is the most critical aspect for the secure storage and transfer of medical images. In this study, we attempt to classify various encryption methods in order to assist researchers in selecting the optimal strategy for protecting sensitive patient information while transferring medical images without alteration and outline the measures that should be adopted to address challenges and concerns relevant to techniques of medical image encryption.
Trajectory tracking control for mecanum wheel mobile robot by time-varying parameter PID controller
Nguyen Hong Thai;
Trinh Thi Khanh Ly;
Le Quoc Dzung
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/eei.v11i4.3712
This paper presents the design method a proportional integral derivative (PID) controller with time-varying parameters for trajectory tracking of a mecanum-wheeled robot with a minor error. First, a nonlinear kinematic error model of the robot is established and linearized around the working point. Then a PID controller with time-varying parameters is designed based on this linear model. The coefficients of KP, KI, and KD control parameters are determined by trial and error technique to ensure that the robot moves along the desired trajectory with minimal error. A platform mecanum-wheeled mobile robot has been designed and manufactured to demonstrate the proposed controller. Simulation and experimental results are presented to verify the effective and accuracy of the proposed controller. It shows that can apply this research to control of a four mecanum-wheeled mobile robot in logistics services in practice.