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Bulletin of Electrical Engineering and Informatics
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Core Subject : 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 65 Documents
Search results for , issue "Vol 12, No 4: August 2023" : 65 Documents clear
License plate recognition in slow motion vehicles Qudes Mb Aljelawy; Tariq M. Salman
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4990

Abstract

The recognition of license plate numbers represents one of the most efficient techniques to identify any individual vehicle. The principle of the system is that the detection of the license plate will be done with two techniques first you only look once (YOLO) and cascade classifier. Then after achive correct detection, the system will send the result (the image of the license plate) to Easy optical character recognition (OCR) library to read it and transform the image into text. In this paper, an analytical study of the surveillance system which affects by parallax due to camera movement has been done, by merging the OCR technique with the attached camera using python aided Raspberry Pi. The hardware system has been designed and implemented.
Segmenting the eating behaviour of university students using the K-means algorithm Lenin Quiñones Huatangari; María Alina Cueva Ríos; Rafaela Teodosia Huerta Camones
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4543

Abstract

Universities that teach arts education do not only teach how to play an instrument or conduct musical ensembles; they are agents of change in eating behaviour for the praxis of teaching and dissemination of healthy education. The objective of the research was to segment the eating behaviour of students of the artistic education-music speciality of the National University of Education "Enrique Guzmán y Valle" by applying the K-means algorithm. To do this, the methodology consisted of understanding the problem, understanding the data collected, preparing the data, modelling and evaluating the model. For modelling, the free software Weka was used through the K-means clustering technique on a data matrix of 148 instances with forty-three nominal variables collected online based on an instrument designed and validated to assess eating behaviour in university students. Two was determined to be the optimal clustering for eating behaviour in university students, using the elbow method, with a distribution of 49% for the first cluster and 51% for the second cluster. The results of the study population showed that the eating behaviour of university students is adequate.
Experimental and simulation investigation for rotor bar fault diagnosis in closed-loop induction motors drives Seddik Tabet; Adel Ghoggal; Hubert Razik; Ishaq Amrani; Salah Eddine Zouzou
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4833

Abstract

This research presents a comparative analysis of two broken rotor bar (BRB) fault identification techniques for closed-loop induction motors (IMs). Both motor current signal analysis and Hilbert transform (HT) rely on spectrum analysis by means of fast fourier transform (FFT). Both approaches have shown their ability to identify BRBs under varying loads. In contrast, the HT is deemed more efficient than the motor current signature analysis (MCSA) approach when the motor is working without load. To maintain a high-performance speed control and to compensate for BRBs effect on the mechanical speed, the approach of control used is direct torque control (DTC). Utilizing a real-time implementation in MATLAB/Simulink with the real-time interface (RTI) based on the dSPACE 1104 board, the efficacy of the two techniques was evaluated.
Design of CRC circuit for 5G system using VHDL Adham Hadi Saleh; Hayder Khaleel AL-Qaysi; Khalid Awaad Humood; Tahreer Mahmood
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4598

Abstract

In this document, we focus on how to design cyclic redundancy check (CRC) circuits with different 5G polynomial divisor using very high-speed integrated circuit (VHSIC) hardware description language (VHDL) to integrate in field-programmable gate array (FPGA) suitable kit using a suitable design code. The different between designed circuits came from the different of data size according to polynomials requirements conditions since there are huge data size in 5G system that required divide it with suitable method and then implemented the required circuit. CRC code as a polar code and short low density parity check (LDPC) is proposed in 5G new radio (NR) systems, CRC properties to divided data and CRC cod make it particularly very useful for codes with higher data rate and longer lengths, and for codes with low data rates and small length as an error detection method. The CRC encoder circuit (transmitter side) and CRC decoder circuit (receiver side) with different polynomial and data size have been designed using VHDL. Xilinx ISE 14.3 simulator, where the test bench simulation results give the expected simulator results of proposed decoding circuit scheme so to integrated using ZYNQ FPGA kit.
Influence of natural clouds on the performance of solar cell systems in Iraq Hiba Nadhim Ameen Al-Kaoaz; Omar Sharaf Al-deen Yehya Al-Yozbaky
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4703

Abstract

Solar energy generated by photovoltaic (PV) technology can be supplied to standalone systems, as it combines efficiency and cost-effectiveness. However, this combination is achieved only after considering the effects of shading, which can significantly influence electrical output. The primary factor that influences the use of solar energy in electricity generation is irradiation. PV cells are significantly impacted by shading, where the output of the PV cell reduces in the presence of a shadow. In this study, the researchers have presented an experimental analysis of how shading affects two PV cells, using the series and parallel configurations. The experimental work is installed at the University of Mosul, Department of Electrical Engineering, Renewable Lab (Iraq). MATLAB was used to simulate, evaluate, and compared the results to understand the effects of shading on PV cell output. This research offers an analytical technique to determine the probable effects of Partial shadowing conditions on PV power generation. The results provide the effects of partial shadowing in an annual performance loss of ≥10–30%. The orientation of the PV panels' tilt angle has an impact on their output power. When the tilt angle deviates from its ideal value, the PV panel's output drops off substantially.
Federated learning security mechanisms for protecting sensitive data Asraa A. Abd Al-Ameer; Wesam Sameer Bhaya
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4751

Abstract

One of the new trends in the field of artificial intelligence is federated learning (FL), which will have promising roles in many real-world applications due to the work characteristics of its architecture. The learning mechanism for this technique is based on making training in a distributed manner on the local data for each client using decentralized data, then collecting parameters for each local training and uploading it to the server, which in turn will send model updates to all clients to give the final learning result. To provide a broad study on FL from security and privacy aspects, this research paper introduces a general view of FL and its categories, most attacks that can befall it, the safety mechanisms used by existing works in attacks defense, enhancing the safety and privacy of FL whether in the transmission or collecting of data. Then, the usage of FL in network security by many research papers has been presented, and how good results were achieved, and finally a comparison has been made between these papers.
Bandwidth enhancement of millimeter-wave microstrip patch antenna array for 5G mobile communication networks Umar Musa; Suleiman Babani; Suleiman Aliyu Babale; Abubakar Sani Ali; Zainab Yunusa; Sani Halliru Lawan
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4680

Abstract

This paper proposed enhancing the bandwidth of a millimeter wave microstrip patch antenna (MPA) and its array for a 5G mobile communication network. The proposed antenna is designed and fabricated on a Rogers RT Duroid 5,880 substrate with a standard thickness of 0.5 mm, a relative dielectric constant of 2.2, and a tangent loss of 0.0009. With a center frequency of 28 GHz, a measured return loss of -21.37 dB, a bandwidth of 1.14 GHz, and a gain of 6.27 dBi, the proposed single element operates in the local multipoint distribution service band. The proposed antenna is designed and manufactured as an array of 1×2 and 1×4 elements. The 2-element MPA array has a measured bandwidth of 1.207 GHz and a gain of 7.76 dBi, higher than that of a single element. The 4-element MPA array achieved a measured bandwidth of 2.685 GHz and a gain of 9.87 dBi, which is higher than the 2-element and single-element arrays at 28 GHz. This demonstrates that the array of antennas improves gain and bandwidth significantly. Hence, the proposed antenna and array are suitable for 5G mobile communication networks due to their small size.
Interleaved boost converter voltage regulation using hybrid ANFIS-PID controller for off-grid microgrid Linus Alwal Aloo; Peter Kamita Kihato; Stanley Irungu Kamau; Roy Sam Orenge
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4906

Abstract

The utilization of a microgrid with a photovoltaic (PV) and wind generation system presents a challenge due to their voltage and power output variations. This problem is majorly addressed within the converter section of the microgrid using maximum power point tracking (MPPT) algorithms and voltage regulation strategies. This paper presents an interleaved boost converter (IBC) modeling and voltage control using a hybrid adaptive neuro-fuzzy inference system-proportional plus integral plus derivative (ANFIS-PID) controller for an off-grid microgrid. The modeling used the interleaving technique to obtain the microgrid’s transfer function (TF) and case study simulation models within MATLAB and Simulink environments. The performance of the ANFIS-PID controller, which regulates voltage in the microgrid, was compared to that of the traditional proportional integral (PI) controller. Results indicated that the hybrid ANFIS-PID controller performed better than the PI controller in terms of reduced settling time, overshoot, rise time, and the ability to address the nonlinear dynamics of the microgrid.
New efficient fractal models for MapReduce in OpenMP parallel environment Muslim Mohsin Khudhair; Furkan Rabee; Adil AL_Rammahi
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4977

Abstract

Parallel data processing is one of the specific infrastructure applications categorized as a service provided by cloud computing. In cloud computing environments, data-intensive applications increasingly use the parallel processing paradigm known as MapReduce. MapReduce is based on a strategy called "divide and conquer," which uses ordinary computers, also called "nodes," to do processing in parallel. This paper looks at how open multiprocessing (OpenMP), the best shared-memory parallel programming model for high-performance computing, can be used in the MapReduce application using proposed fractal network models. Two fractal network models are offered, and their work is compared with a well-known network model, the hypercube. The first fractal network model achieved an average speedup of 3.239 times while an efficiency ranged from 73-95%. In the second model of the network, the speedup got to 3.236 times while keeping an efficiency of 70-92%. Furthermore, the path-finding algorithm employed in the recommended fractal network models remarkably identified all paths and calculated the shortest and longest routes.
Machine learning techniques for accurate classification and detection of intrusions in computer network Mutyalaiah Paricherla; Mahyudin Ritonga; Sandip R. Shinde; Smita M. Chaudhari; Rahmat Linur; Abhishek Raghuvanshi
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4708

Abstract

An incursion into the computer network or system in issue occurs whenever there is an attempt made to circumvent the defences that are in place. Training and examination are the two basic components that make up the intrusion detection system (IDS) and each one may be analysed separately. During training, a number of distinct models are built, each of which is able to distinguish between normal and abnormal behaviours that are included within the dataset. This article proposes a combination of ant colony optimization (ACO) and the firefly approach for feature selection. The final outcome of giving careful thought to the selection of features will eventually result in greater accuracy of categorisation. When classifying various sorts of features, we make use of a wide variety of machine learning (ML) algorithms, including AdaBoost, gradient boost, and Bayesian network (BN), amongst others. The tests and assessments made use of data obtained from three distinct datasets, namely NSL-KDD, UNSW-NB15, and CICIDS 2017. The degree of performance of an individual may be broken down into its component parts, which include the F1 score, accuracy, precision, and recall. Gradient boost performs far better when it comes to recognising and classifying incursions.

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