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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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Backpropagation neural network based adaptive load scheduling method in an isolated power system Vijo M. Joy; Joseph John; Sukumarapillai Krishnakumar
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4511

Abstract

This work introduces an efficient load scheduling method for handling the day-to-day power supply needs. At peak load times, due to its instabilitythe power generation system fails and as a measure, the load shedding process is followed. The presented method overcomes this problem by scheduling the load based on necessity. For this load scheduling is handled with an artificial neural network (ANN). For the training purpose the backpropagation (BP) algorithm is used. The whole load essential is the input of the neural network (NN). The power generation of all resources and power losses at the instant of transmission is the NN output. The optimum scheduling of different power sources is important when considering all the available sources. Load scheduling shares the feasibility of entire load and losses. It is well-known as optimal scheduling if the constraints such as availability of power, load requirement, cost and power losses are considered. Training the system using a large number of parameters would be a difficult task. So, finest number of communally independent inputs is selected. The presented method aims to lower the power generation expenditure and formulate the power available on demand without alteration. The network is designed using MATLAB.
Robust attribute selection to improve the Parkinson's disease classification: a hybrid approach Al-Mashanji, Ameer K.; Alhasnawy, Laith Hamid; Hamza, Aseel Hamoud
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5247

Abstract

Parkinson’s disease (PD) is known to be a neurodegenerative syndrome that progresses chronically. As a result of the damage or death of brain neurons that generate dopamine patients tend to face difficulty when performing simple everyday tasks like walking, writing, or speaking. The main contribution of this work presents a hybrid method for improving predicting PD. This methodology has been obtained by means of testing a number of different combinations of classification algorithms and approaches for selecting attributes. A total of three attributes selection methods (correlation, information gain, and variance threshold) and three classifiers (decision trees (DT), naive bayes (NB), and support vector machine (SVM)) have been adopted. The speech data set provided by University of California-Irvine (UCI) machine learning (ML) repository is adopted to analyze the performance of different combinations. The combination of information gain and DT classifier achieved the best performance rather than other combination methods, reaching a classification accuracy of (97.43%). Finally, an additional comparison of the performance analysis with the results of previous studies was made and it was found that the proposed methodology proved to outperform the results of other studies conducted in this field.
A comparative study of classification techniques in data mining algorithms used for medical diagnosis based on DSS Ahmed Shihab Ahmed; Hussein Ali Salah
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4804

Abstract

A significant amount of data is gathered by the healthcare sector, but it is not appropriately mined and utilized. Finding these hidden links and patterns is frequently underutilized. Our study focuses on this element of medical diagnostics by identifying patterns in the information gathered about kidney illness, liver disease, and chronic pancreatitis (CP) and designing adaptive medical decision support systems (MDSS) to assist doctors. This research compares a variety of data mining (DM) techniques, knowledge extraction tools, and software platforms for usage in a DSS for analysis using the Waikato environment for knowledge analysis (WEKA) mining tool (decision tree (DT)). The objective is to determine the most significant risk factors based on the extraction of the categorization criteria. The datasets used for this work are illustrates how successfully DM and DSS are integrated. In this research, we suggest using the C4.5 DT algorithm, Naïve Bayes (NB) algorithm, and the logistic regression (LR) algorithm to categorize these diseases and evaluate their performance and accuracy rates. It inferred that the C4.5 algorithm accuracy is 0.873% which is better than the other two algorithms in terms of rule generation and accuracy.
Text-to-speech on health monitoring bracelet for the visually impaired Indrianto, Indrianto; Abdurrasyid, Abdurrasyid; Susanti, Meilia Nur Indah; Ramadhan, Arief
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5369

Abstract

Text-to-speech (TTS) is a technology that converts text into sound using a phonetization system and is especially useful to be applied to blind aids who need information in the form of sound because of their limitations. To help the visually impaired know their health conditions where the visually impaired feel limited to going out during the pandemic. For this reason, it is necessary to make an aid that can read text-based data such as body temperature, heart rate per minute, and oxygen levels into a voice that can be heard by the blind, the method used in this study is finite state automata (FSA) which is used to split Indonesian words into words according to its syllable patterns and facilitate the pronunciation process which is included in the blind aids so that it is expected to help the visually impaired to be able to find out their health condition. In this study, the test was carried out using the confusion matrix method and the results obtained were 100% accurate, 99.71% accuracy of temperature sensor, 98% accuracy of heart rate, and 95% accuracy of oxygen saturation.
Controlling the effectiveness of STATCOM using ANFIS based on PI controller Maha Abdulrhman Al-Flaiyeh; Nagham Hikmat Aziz; Saraa Ismaeel Khalel
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5089

Abstract

This research achieves two goals, the first is the modelling of the static synchronous compensator (STATCOM) and design of the control circuits for current, voltage and d.c capacitor voltage (Vd.c) to improve the power factor (PF) by preparing the reactive power by STATCOM so that its work is similar to the work of a synchronous condenser, and the second goal is to use smart techniques to control the Vd.c loop. For comparison, smart technical methods such as fuzzy logic type 1 (FL-T1), fuzzy logic type 2 (FL-T2), and adaptive neuro fuzzy inference system (ANFIS) were used to regulate the Vd.c on the capacitor instead of the traditional controller proportional integral (PI). Simulation was performed in MATLAB 2021 to determine the efficiency of the suggested method or approach controllers for STATCOM. The use of the proposed method improves the signal value of both the current and the voltage and the phase difference between them, which reaches almost zero. Proved that an ANFIS technique provides best Vd.c response in different values of balance and unbalance load compared with the other methods by obtaining the minimum peak overshoot (P-ov) and minimum settling time (ST).
Study of the thermal drifts on the piezoresistivity using mobility model and finite difference method of electric heater Abdelaziz Beddiaf; Fouad Kerrour
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5283

Abstract

In pressure sensors, four piezoresistors connected in a Wheatstone bridge are often provided with a voltage varying between 5 and 10 V. Unfortunately, this voltage is a source of drifts created by electric heating. This study focuses on the internal heating and piezoresistive effect of piezoresistors represented by the variation of their resistivity. To do this, we use the finite difference method (FDM) to solve the heat transfer equation, taking into account the conduction in Cartesian coordinates for the variable regime. We examine how the temperature affects the piezoresistivity in these sensors when the potential is applied. In this case, the variation of the temperature has been calculated as a function of applied voltage, as well as for the operating time of the sensor. Furthermore, the evolution of resistivity over time was determined for several geometric properties of the membrane using the mobility model. This was established for different doping levels. Additionally, the change in resistivity due to the application of voltage was evaluated. It was observed that resistivity is greatly affected by the temperature rise produced by the applied voltage when the device is actuated for a prolonged time. Consequently, this results in drifting in the output response of the sensor.
The performance of a multilevel multifunctional solar inverter under various control methods Darshni M. Shukla; Naimish Zaveri; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4097

Abstract

Photovoltaic (PV) inverters are now supposed to provide additional supporting services with more reliability and efficiency. This paper presents three different control methods for generating reference current in a multifunctional, multilevel grid-tied PV inverter for harmonic, reactive, and unbalance compensation. These methods are the synchronous reference frame (SRF) theory (d-q), the instantaneous reactive power (IRP) theory (p-q), and the conservative power theory (CPT). As a result, the primary goal is to propose a low-cost multifunctional solar invert for distributed generation, with an appropriate prototype developed in the laboratory for experimental validation of various modes of operation. Demonstrated results show that the presented inverter is capable of providing various ancillary services with all three types of control.
Tracking the GMPP of a solar photovoltaic water pumping system with an SMC controller in partial shading conditions Khadija, Sabri; Ouadia, El Maguiri; Abdelmajid, Farchi
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5504

Abstract

The focus of this paper will be on the development of a photovoltaic (PV) pumping system that employs a DC-DC boost converter as an intermediate power conditioning unit in a centrifugal water pump powered by a brushless DC (BLDC) motor supplied by a solar photovoltaic panel (SPV). This work describes a particle swarm optimization (PSO) maximum power point tracking (MPPT) method compared with the gray wolf optimizer (GWO) method that are closed-loop with a sliding mode controller (SMC) in order to control the operational point of a solar PV in partial shading conditions (PSC), the DC-DC boost converter provides a low starting current for the BLDC motor, and the voltage source inverter (VSI) is used to perform electronic commutation of the BLDC motor. Furthermore, the BLDC motor's speed is regulated by the changeable DC link voltage. The system under consideration, as well as the control approaches employed, were created in the MATLAB/Simulink environment.
Child tracking system using smartphone Taha A. Taha; Abadal-Salam T. Hussain; Hazry Desa; Faris Hassan Taha; Yasin Bektaş
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5161

Abstract

The number of missing children and kidnapping is on the rise in recent years. Every parent wills definitely going through an agonizing experience to have their children missing. Therefore, there are many safety measurements to prevent this incident from happening. The help of modern technologies is one of the ways to reduce children missing and kidnapping. A child can be tracked by using the global positioning system (GPS) and global system for mobile communication (GSM) technology. Advanced child monitoring systems are expensive. Not all families have the same living standards. For this purpose, a low-cost child tracking system is proposed in this study. The implementation of the proposed approach is reported in real-time.
An android application and speech recognition-based IoT-enabled deployment using NodeMCU for elderly individuals Arunav Mallik Avi; Md. Sohel Rana; Mustakim Billah Bedar; Md. Asif Talukder
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5062

Abstract

The internet of things (IoT) is the trendiest technology in the computing, Embedded and modern control systems industries. An efficient IoT-enabled home automation technique that allows users to remotely control home appliances and observe sensor data from a long distance via internet connectivity. This study identifies a smart approach to assisting any user, particularly elderly individuals, to control home appliances and monitor home weather conditions using an Android application and voice command using speech recognition. Multiple specialized microcontrollers, especially NodeMCU and other components like sensors, networks, relays, fans, lights and android devices are used to implement this proposed system. This IoT platform device is configured to recognize the instructions from the Android application to control appliances as well as compute real-time weather data from sensor and upload the sensor data stream to the IoT web server. The dedicated IoT web server, that is accessible by the Android application for further IoT operations. On the other hand, the Google Speech to Text (STS) service enables a facility to control home appliances through voice command. Mobility issues plague the elderly, complicating even the simplest tasks. From observation of this research, they can control this proposed system without ever touching any physical switches.

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