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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
A novel examination of limonene detection using plastic fiber optic sensors and the tapered approach Thanigai Anbalagan; Hazura Haroon; Hazli Rafis Abdul Rahim; Siti Halma Johari; Siti Khadijah Idris@ Othman; Hanim Abdul Razak; Maisara Othman
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.v12i2.4379

Abstract

A novel tapered plastic optic fiber (POF) biosensor is proposed and demonstrated for monitoring limonene in different concentrations. The mechanism of this device is based on an increase in the light transmission of a sensor submerged in a higher-concentration limonene solution, which also reflects an increase in the refractive index of the sensor. The tapered POF was fabricated using the chemical etching method to accomplish different waist diameters of 0.6 mm, 0.55 mm, and 0.5 mm, with a fiber length of 10 cm and a 2 cm sensing region. An Arduino integrated development environment (IDE) program was used to drive the voltage values from the photodetectors to obtain the measurements. As the limonene concentration solution varied from 20% to 100%, the output voltage of the sensor increased linearly, showing a sensitivity of 0.295 V/%, 0.33 V/%, and 0.46 V/% for tapered waist diameters of 0.6 mm, 0.55 mm, and 0.5 mm, respectively. The proposed sensor is a low-cost solution measurement option with high sensitivity, while it also involves a simple and easy fabrication technique.
Smart evaluation for deep learning model: churn prediction as a product case study Esam Mohamed Elgohary; Mohamed Galal; Ahmed Mosa; Ghada Atef Elshabrawy
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.v12i2.4180

Abstract

Customer churn prediction recently is one of the vital issues that confronts diverse business industries to sustain the customers base and profits. On the other hand, data scientists employ gigantic customer data to automate the data modelling process to offer these models as a generally portable service. This research has two main contributions: deep learning customer churn prediction model and smart evaluation prediction model service. So, this service harnesses any customer data to automate building, evaluation, and deployment of the churn prediction model. The research consists of three main parts. Firstly, it illustrates the dataset labelling which annotates customers data into churn or non-churn. Secondly, the deep learning churn prediction framework using convolutional neural network (CNN) algorithm. Finally, a case study is presented to show how churn prediction service is automatically trained and generated based on real customer data, where CNN parameters are adapted to achieve the most reliable performance in line with customers' behavior. The applied case study achieves accuracy 0.77, area under the curve (AUC) 0.84 and f1 score 0.83.
Metaheuristic based routing incorporated with energy harvesting for enhanced network lifetime in WBAN Ganeson Sathya; Daniel Jasmine Evanjaline
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.v12i2.4589

Abstract

Wireless body area networks (WBAN) have improved healthcare industries to a large extent by providing contactless measurements and remote data analysis. However, the challenges encountered are mostly in the form of energy depletion scenarios, which results in the reduction of network lifetime to a large extent. This work presents an effective model to provide energy-efficient routing and enhanced energy harvesting mechanisms to improve network lifetime. The ant colony optimization (ACO) method has been extended to include a fitness function that takes into account several factors, and this is the basis for the routing model. These processes ensure effective routing, which conserves energy and, in turn, results in enhanced network lifetime. Performance of the proposed model has been compared with the existing state-of-the-art models in the domain. Comparison with the metaheuristic-based model, cooperative energy efficient and priority based reliable routing protocol with network coding (CEPRAN), indicates the efficiency of the energy harvesting mechanism used in the proposed work. When compared with models using energy harvesting mechanisms, results exhibit higher network lifetime, depicting the efficiency of the proposed routing mechanism.
A comparison statement on DCPWM based conducted EMI noise mitigation process in DC-DC converters for EV Srinivasan Kalaiarasu; Sudhakar Natarajan
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.v12i2.4315

Abstract

Fast switching techniques at high frequencies are employed for quick charging and energy conversion in electric vehicle (EV) power converters. Electromagnetic interference (EMI) noise is produced due to the fast-switching process, which may result in malfunctioning and degraded EV performance. In this work, a digital chaotic pulse width modulation (DCPWM) technique-based EMI noise mitigation process has been applied to elementary positive output super lift Luo (EPOSLL), two-stage cascaded boost (TSCB), and ultra-lift Luo (ULL) converters, and a comparison study has been conducted with EMI reduction levels as per electromagnetic compatibility (EMC) standards. The duty cycle is varied from 0.5 to 0.67 to get the desired output voltage as an input of 10V to achieve the power ratings of 40 W to 80 W for various load conditions. A total of 4 dBV (3 V) to 15 dBV (10 V) of conducted EMI noise has been mitigated for the above-said converters. Simulation results based on power spectrum density and hardware results based on fast fourier transform (FFT) of output voltages are analyzed. According to the findings, the ULL converter is more acceptable for electromagnetic compatibility in EV applications than EPOSLL and TSCB DC-DC converters.
Data mining and analysis for predicting electrical energy consumption Inteasar Yaseen Khudhair; Sanaa Hammad Dhahi; Ohood Fadil Alwan; Zahraa A. Jaaz
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.v12i2.4593

Abstract

In this study paper, the feasibility of constructing a complete smart system for anticipating electrical power consumption is created, as electricity's market share is expected to expand over the future decades. Smart grids and smart meters will help utility companies and their customers soon. New services and businesses in energy management need software development and data analytics skills. New services and enterprises are competitive. The project's electricity consumers are categorized by their hourly power usage percentage. This classification was done using data mining (five algorithms in specific) and data analysis theory. This division aims to help each group minimize energy use and expenditures, encourage energy-saving activities, and promote consumer involvement by giving tailored guidance. The intended segmentation is done through an iterative process using a computer classification computation, post-analysis, and data mining with visualization and statistical methodologies.
Image preprocessing analysis in handwritten Javanese character recognition Fetty Tri Anggraeny; Yisti Vita Via; Retno Mumpuni
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.v12i2.4172

Abstract

The handwriting produced by each person is unique, so each person has a different stroke, even though they write the same letter. Handwritten Javanese is an exciting topic to study, in addition to scientific purposes and preserving Indonesian culture. The Javanese character image dataset is aksara Jawa: aksara Jawa custom dataset from the Kaggle database consists of 2,154 train data and 480 evaluation data. This research proposed to analyze the impact of some preprocessing methods in recognizing handwritten Javanese characters. The preprocessing methods are dilation, skeletonization, and noise reduction. The first process is segmentation for region of interest (ROI) extraction, then various preprocessing is used, and finally, the recognition step neural network (NN) to measure the effectiveness of the preprocessing method. The experiment shows that all preprocessing methods (dilation, skeletonization, and noise reduction) give excellent results, especially on the black background color, reaching 98% accuracy. Other experimental findings show that in any preprocessing combination, the black background accuracy is better than the white one.
Dissolved oxygen control system in polishing unit using logic solver Totok Soehartanto; I Putu Eka Widya Pratama; Safira Firdaus Mujiyanti; Dwi Nur Fitriyanah; Putri Yeni Aisyah; Rico Pardona Pardosi; Nabiilah Azizah Tjandra
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.v12i2.4445

Abstract

The research consists of two parts, the first one is to design the dynamic plant model of polishing unit using artificial neural network (ANN) type backpropagation, and the second one is to design a simulation of a close loop control system on Simulink consisting of logic solver, control valve and ANN polishing unit. The ANN polishing unit was trained and obtained the best model structure 4-24-3 with four inputs chemical oxygen demand (COD) influent, oil in water (OIW) influent, urea, and triple superphosphate (TSP), twenty-four hidden layer nodes, and three outputs (OIW effluent, COD effluent and dissolved oxygen (DO)). The mean square error (MSE) and root mean square error (RMSE) from ANN trained were 0.00485 and 0.06964, obtained by the second iteration. From the simulation results on Simulink by giving several scenarios in the logic solver condition table, the action is brought in the form of urea and TSP nutrition issued by the control valve. The values are used to achieve the DO setpoint (2 mg/L), among others: when COD and OIW influent exceed the quality standard, COD exceeds the quality standard, and OIW does not exceed the quality standard, and the DO error is below zero.
Human–machine interaction for motorized wheelchair based on single-channel electroencephalogram headband Yasir M. Abdal; Mohammed G. Ayoub; Mazin N. Farhan; Hasan A. Abdulla
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.v12i2.4163

Abstract

Human machine interaction (HMI) allows persons to control and interact with devices. Starting from elementary apparatus which acquires input bio-signals to controlling various applications. Medical applications are amongst the very important applications of HMI. One of these medical applications is assisting fully/partially paralyzed patients to restore movements or freely move using exoskeletons or motorized wheelchairs. Helping patients with spinal cord injury or serious neurological diseases to restore their movements is a key role objective for most researchers in this field. In this paper, an EEG-based HMI system is proposed to assist patients with tetraplegia/quadriplegia to mentally control a motorized wheelchair so they can move freely and independently. EEG power spectrum (α, β, δ, θ, and γ) from the frontal lobe of brain is recorded, filtered and wirelessly sent to the wheelchair to control directions and engine status. Four different experiments were conducted using the proposed system in order to validate the performance. Two different GUIs scenarios (cross-shaped and horizontal bar) were used with the experiments. Results showed that the horizontal bar scenario considered more user friendly while the cross-shaped is the more suitable for navigation. The implemented system can be equipped with modules and sensors such as GPS, ultrasound and accelerometer that improve the system performance and reliability.
Temperature and performance evaluation of multiprocessors chips by optimal control method Porya Soltani Hanafi Por; Abbas Ramazani; Mojtaba Hosseini Toodeshki
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.v12i2.4291

Abstract

Multi-core processors support all modern electronic devices nowadays. However, temperature and performance management are one of the most critical issues in the design of today’s microprocessors. In this paper, we propose a framework by using an optimal control method based on fan speed and frequency control of the multi-core processor. The goal is to optimize performance and at the same time avoid violating an expected temperature. Our proposed method uses a high-precision thermal and power model for multi-core processors. This method is validated on asymmetric ODROID-XU4 multi-core processor. The experimental results show the ability of the proposed method to achieve the adequate trade-off between performance and temperature control.
A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation Nursabillilah Mohd Ali; Rosli Besar; Nor Azlina Ab Aziz
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.v12i2.4838

Abstract

Breast cancer is one of the leading causes of death and most frequently diagnosed cancer amongst women. Annually, almost half a million women do not survive the disease and die from breast cancer. Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. In this work, simple machine learning methods are used to classify breast cancer microarray data to normal and relapse. The data is from the gene expression omnibus (GEO) website namely GSE45255 and GSE15852. These two datasets are integrated and combined to form a single dataset. The study involved three machine learning algorithms, random forest (RF), extra tree (ET), and support vector machine (SVM). Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. The result shows that the tuned SVM is best among the tested algorithms with accuracy of 97.78%. In the future it is recommended to include feature selection method to get the optimal features and better classification accuracies.

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