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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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Driver drowsiness monitoring system based on facial Landmark detection with convolutional neural network for prediction Roaa Albasrawi; Fajer F. Fadhil; Mohammed Talal Ghazal
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3966

Abstract

Several factors often contribute to car accidents, most of them caused by human error, and the most notable are drowsiness, fatigue, distracted driving, and alcohol. Although self-driving cars are the best solution to save human lives and avoid car accidents, they are expensive. The roads in many countries are not prepared for the movement of this type of car. Scare new technologies included in modern cars, such as backup cameras and sensors, contributed to keeping drivers safer in this paper. A driver monitoring system is based on determining the driver’s face’s main points, which provide the required vital information for face analysis. The EfficientNet convolutional neural network (ConvNet) model is used for facial landmarks prediction, which is employed to detect face drowsiness and fatigue in real-time. The system is trained to detect multiple traits, including facial expressions, yawning and head poses. The results show that employing facial landmarks will assist in efficiently producing eyes and mouth features, which can assist in appropriately creating models to analyze drowsiness. Due to this, the proposed safety features are applicable and available in future vehicles.
Stock market analysis with the usage of machine learning and deep learning algorithms Sarma, Seethiraju L. V. V. D.; Sekhar, Dorai Venkata; Murali, Gudipatu
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4305

Abstract

In this work we are focusing on listing out various works in the understanding of various parameters and context to get the overview of stock market analysis in the context of machine learning (ML) and deep learning (DL) models. The work focusses on the stock market analysis along with methodologies and algorithms used to understand the trends and the corresponding results as part of those studies. The importance of this work is to summarize and analyse the parameters which are highly influenced the understandingof the stock market trends. The outcome of the work is understanding the important factors which directly and indirectly influences the stock value raise and drop. The work highlights the methodologies and the algorithms used to stock market data analysis and efficient and effective recommendation of stable stocks to the customers. Further we are listing out the research gaps and future enhancements of the studies which are left over in the earlier works. The work pops up the limitations of some of the works in the existing works along with significance of hyper parameter techniques to clearly identify the features through which we can get more possibilities of better analysis of the data.
Analysis of instrumentation system for photovoltaic pyranometer used to measure solar irradiation level Prisma Megantoro; Muhammad Akbar Syahbani; Sigit Dani Perkasa; Ahmad Rahmad Muzadi; Yusrizal Afif; Agus Mukhlisin; Pandi Vigneshwaran
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4390

Abstract

A pyranometer is a device used to measure the level of solar irradiation. This device has a sensor that measures the density of the electromagnetic flux of solar radiation on a flat plane. The electromagnetic flux density parameter is converted into an electrical parameter in watts per square meter. Pyranometers are used in weather station devices to analyze and predict weather conditions. Solar power generation systems are usually also installed with this device. It is intended to monitor solar irradiation's condition to examine the generating system's performance. This article discusses the photovoltaic-based pyranometer characterization method. The characterization method is carried out to determine the measurement parameters such as accuracy, precision, and hysteresis. Knowing these parameters will make it possible to see the performance of measuring solar irradiation levels by a measuring instrument for solar irradiation levels, like a pyranometer. The characterization method is to compare the measurement results with standard instruments. The solar irradiance level monitoring is also optimal, accurate, and precise with a reliable measurement method.
Accurate license plate recognition system for different styles of Iraqi license plates Sukaina Sh Altyar; Samera Shams Hussein; Lubab Ahmed Tawfeeq
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.v12i2.4186

Abstract

Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recognize all these license plate types using the same algorithm. In this work, a new method has been proposed to efficiently recognize all these types of license plates. This has been done by utilizing a series of algorithms for preprocessing and recognition with new identification strategies. The results show that the system recognized license plate numbers with higher accuracy, reaching up to 97.85%. However, the method field to detect license plates when there are some high deformations in plate numbers or when they are partially covered with mud, which makes it difficult to distinguish numbers.
Reliability analysis of single phase quazi Z source inverter for standalone photovoltaic system Bharathi Rao; M. Satyendra Kumar
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4101

Abstract

Quazi Z source inverter has an advantage that it can boost or buck voltage to be given to an inverter. Operation of a QZSI is similar to a Z source inverter (ZSI). A conventional photovoltaic application uses a two-stage topology of boost converter and an inverter. A QZSI can be replaced for a two-stage topology to serve the purpose. A 3 KW single phase QZSI is designed and simulated for a standalone photovoltaic system in this paper. The results for total harmonic distortion (THD) of output voltage and mean time between failure (MTBF) of the overall system is compared with a conventional ZSI and two-stage topology for the same rating. MTBF of the overall system is computed using reliability block diagram method. Reliability curve is also plotted for all the three considered topologies.
Multi-feature stacking order impact on speech emotion recognition performance Yoga Tanoko; Amalia Zahra
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4287

Abstract

One of the biggest challenges in implementing SER is to produce a model that performs well and is lightweight. One of the ways is using one-dimensional convolutional neural network (1D CNN) and combining some handcrafted features. 1D CNN is mostly used for time series data. In time series data, the order of information plays an important role. In this case, the order of stacked features also plays an important role. In this work, the impact of changing the order is analyzed. This work proposes to brute force all possible combinations of feature orders from five features: Mel-frequency cepstral coefficient (MFCC), Mel-spectrogram, chromagram, spectral contrast, and tonnetz, then uses 1D CNN as the model architecture and benchmarking the model's performance on the Ryerson audio-visual database of emotional speech and song (RAVDESS) dataset. The results show that changing the order of features can impact overall classification accuracy, specific emotion accuracy, and model size. The best model has an accuracy of 79.17% for classifying 8 emotion classes with the following order: spectral contrast, tonnetz, chromagram, Mel-spectrogram, and MFCC. Finding a suitable order can increase the accuracy up to 16.05% and reduce the model size up to 96%.
Using sensorless direct torque with fuzzy proportional-integral controller to control three phase induction motor Yaser Nabeel Ibrahem Alothman; Wisam Essmat Abdul-Lateef; Sabah Abdul-Hassan Gitaffa
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.v12i2.3991

Abstract

Induction motors (IM) attracted many researchers in the last few decades. In this field, various applications are implemented, such as servo motor drives and electric vehicles. This work applies a sensorless direct torque controller (DTC) to control a three-phase IM. System dynamics of the IM were derived. A nonlinear dynamic model had introduced with white noise. Given the complexity of the dynamics, the Jacobean Linearization technique has been used to obtain the linear model for a control task. A DTC technique is employed to control the motor speed of the system with a combination of two controllers. The fuzzy proportional-integral (PI) controllers are applied to obtain the reference torque based on an optimization process against the speed error raise. The optimizer is called grey wolf optimizer (GWO) and is implemented to achieve the centre values of the two output memberships for the fuzzy PI controllers. Then the extended Kalman filter (EKF) is used to evaluate the direct and quadratic components of the rotor flux and rotor speed from the observation of stator voltages and currents. The system is tested employing MATLAB simulation software and determines the targeted results. The outcomes are evaluated to improve the control performance.
A novel approach for new architecture for green data centre Al-Fatlawi, Ahmed Abdulhassan; Al-Barazanchi, Israa
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4421

Abstract

The massive energy usage of data centers may be traced in part to the growing number of data centers and workstations because of economies of scale for cloud computing. It does, though, indicate wasteful power usage. Consequently, researching ways to improve the energy efficiency of datacenter equipment is now a crucial aspect in reducing datacenter power consumption. In this study, we describe methodologies and algorithms for flexible, energy-efficient, and effective load balancing in data centers, resulting in lower energy consumption by systems. Because of difficulties related with energy consumption, such as capital expenditure, operational costs, and environmental effect, renewable energy is becoming an increasing major consideration in data centers. With the rise in environmental consequences around the world, data centers must consider energy efficiency as one of the most critical factors. Cloud computing techniques have made a huge impact all over the world. Green DC is a concept that has been tested. We suggested an algorithm in this paper based on certain current algorithm limitations that will help to reduce environmental effect. We investigated the efficiency of our program further and used a load balancing method to improve its performance.
Comparison of photovoltaic nanogrid implementation: a simple reliability model for frontier, remote, and disadvantaged areas Ryandi Ryandi; Kevin Marojahan Banjar-Nahor; Nanang Hariyanto
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3814

Abstract

This paper aims to evaluate the photovoltaic (PV) nanogrid implementation and its risk for a project at a remote location. Unlike the normal approach, this approach is based on a discontinuity project. The main advantage of the model is the simplicity to compute the expected lifetime and display the reliability curve. The reliability is calculated using state space equation and a quantitative approach evaluates the risk of PV nanogrid scenarios based on costs. The MATLAB/Simulink simulates the scenarios including the basic scenario of a PV system that is a PV nanogrid consisting of a PV array and inverter, scenario 1 that is a PV nanogrid with a battery system, scenario 2 is an extension of scenario 1 with a battery repair, and scenario 3 is a PV nanogrid connected to the grid. The result indicates that adding a battery system increases the reliability and the expected lifetime of the system, and the battery system’s maintenance makes it higher. Scenario 3 shows high reliability and a longer expected lifetime. The risk matrix shows the position of reliability and its impact on each scenario. This work can be used in practice as an objective assessment to electrify frontier, remote, and disadvantaged (3T) areas beside levelized cost of energy (LCOE).
Multi-dimension SVPWM-based sensorless control of 7-phase PMSM drives Kamel Saleh; Mark Sumner
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.v12i2.4665

Abstract

A new control technique for the 7-phase permanent magnet synchronous machine (PMSM) when a failure in the speed sensor is introduced. This will make the whole drive system more robust and at the same time reduce the cost. The speed and the position of the shaft of the motor are obtained by tracking the saturation saliency of the 7-phase motor when a failure in speed sensor is occurred. The proposed saliency-tracking algorithm is based on measuring the derivative of the stator currents of the 7-phase motor after the switching of the insulated gate bipolar transistor (IGBT) of the 7-phase inverter due to the implementation of the multi-dimension space vector pulse width modulation (SVPWM). This modulation technique is used in the 7-phase drives to suppress the 3rd and 5th harmonics. Simulation results show that the 7-phase motor drive could track the reference speed at different load conditions when a failure in the speed sensor is occurred without compromising the performance.

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