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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 11, No 4: August 2022" : 64 Documents clear
Robust super-twisting sliding mode controller for the lateral and longitudinal dynamics of rack steering vehicle Norsharimie Mat Adam; Addie Irawan; Mohd Ashraf Ahmad
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3641

Abstract

Inertia phenomenon in steering vehicle is major factor that allow oversteering incident in which come from the insufficient steering and slip control over the vehicle itself. The efficient and robust control system is required to consider both precision and stability of the vehicle for better manuevering especially in cornering road. Therefore, this research has taken the initiative to contribute a better solution for vehicle control according to the mentioned problem and situation with a proposed robust super-twisting sliding mode control (ST-SMC) by simplified torque on wheel and steering angle input with decoupling lateral and longitudinal errors. This control technique approach to allow coping with the issue by reducing forces and inertia for optimum speed at the cornering period and with the almost precise steering positioning. The dynamic model of rack steering vehicle (RSV) is used as the model plant and the proposed control system is simulated for verification. The results shows that the proposed ST-SMC offers improved performance in terms of speed increase time and vehicle stability that gives impact to the RSV being skidded or collided to any obstacles during cornering period.
Provably curb man-in-the-middle attack-based ARP spoofing in a local network Hiba Imad Nasser; Mohammed Abdulridha Hussain
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3810

Abstract

Even today, internet users’ data security remains a significant concern. One problem is ARP poisoning, otherwise referred to as ARP spoofing. Such attacks are intended to exploit the identified ARP protocol vulnerability. Despite no straightforward remedy for ARP spoofing being apparent, certain actions may be taken to maintain one’s safety. The most basic and common defence against a poisoning attack is manually adding MAC and IP addresses to the static ARP cache table. However, this solution is ineffective for large networks where static entries require considerable time and effort to maintain, whether by human input or via special tools and settings for the static entries of network devices. Accordingly, this paper aimed to monitor network packet information and detect the behaviour of ARP poison attacks on operating systems, for instance Windows and Linux. The discovery and defence policy systematically and periodically check the MAC addresses in the ARP table, enabling alerts to be issued if a duplicate entry is detected. This enables the poison-IP address to be blocked before a reply is sent. Finally, the results showed that the superiority was successfully achieved in the detection, prevention and reporting mechanisms in the real-world environment.
An accurate Alzheimer's disease detection using a developed convolutional neural network model Muhanad Tahrir Younis; Younus Tahreer Younus; Jamal Naser Hasoon; Ali Hussain Fadhil; Salama A. Mostafa
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3659

Abstract

Alzheimer's disease indicates one of the highest difficult to heal diseases, and it is acutely affecting the elderly normal lives and their households. Early, effective, and accurate detection represents an important blueprint for minimizing Alzheimer's progression risk. The modalities of brain imaging can assist in identifying the abnormalities associated with Alzheimer's disease. This research presents a developed deep learning scheme, which is designed and implemented to classify the brain images into multiclass, namely very mild, moderate, mild, and non-demented. The proposed convolutional neural network (CNN) based detection model attained a high performance with an accuracy of 99.92%, considerably enhancing the results achieved via the pre-trained 16 layers in the visual geometric group (VGG16) model and the other related learning models. Consequently, this developed model can assist medical personnel by providing a facilitating tool to identify Alzheimer's disease stage and establishing a suitable medical treatment platform.
Electrocardiogram feature selection and performance improvement of sleep stages classification using grid search Lyra Vega Ugi; Fiky Yosef Suratman; Unang Sunarya
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3529

Abstract

Sleep analysis is often used to identify sleep-related human health. In many cases, sleep disorders could cause a particular disease. One of the approaches to detect sleep disorders is by investigating human sleep stages. However, the selection of the proper electrocardiogram (ECG) features is still considered challenging and becomes an issue to achieve the performance of the algorithm used. Therefore, it is necessary to investigate which ECG features are very significant to the performance of the algorithm. In this study, the support vector machine (SVM) method has been utilized to classify sleep stages into two classes namely awake and sleep. In order to improve the classification performances, an optimization method of grid search was used to find the best parameters of the SVM. Feature selection of information gain was then used to find the most significant ECG features. To validate the performance results, one leave-subject out cross-validation has been conducted during the implementation. There were ten subjects involved in this implementation. The ECG signals from those ten subjects were used to differentiate awake from sleep state. Based on the results, our method obtained an average accuracy of 85.46% a precision of 84.05% and a recall of 85.44% respectively.
Random early detection-quadratic linear: an enhanced active queue management algorithm Samuel Oluwatosin Hassan; Vivian Ogochukwu Nwaocha; Adewole Usman Rufai; Tola John Odule; Theophilus Aniemeka Enem; Lukman Adebayo Ogundele; Suleiman Abu Usman
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3875

Abstract

This paper identifies the lone linear drop function for computing the dropping probability between certain queue threshold values as a major weakness for the random early detection (RED) algorithm as it leads to large delay and queue instability. To address this concern, we propose an enhanced RED-based algorithm called random early detection-quadratic linear (referred to as “RED-QL”) active queue management (AQM) which leveraged the benefit of a quadratic packet drop function for a light-to moderate traffic load conditions together with a linear packet drop function for a heavy traffic load condition respectively. Results from ns-3 network simulator using different experimental scenarios clearly reveals that the proposed RED-QL algorithm yields a substantial reduction in delay performance and indeed a reduced average queue size than other three representative AQM algorithms. RED-QL is robust, easy to implement and deploy in routers (both in software and hardware) as no more than the packet drop probability profile of the classic RED’s algorithm implementation needs modest alteration.
Power quality assessment of novel multilevel and multistring inverters for electric vehicle applications Sri Krishna Kumar Sampathkumar; Dhal Pradyumna Kumar
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3512

Abstract

The requirement and demand of electric vehicles is extravagantly increasing in the current era for avoiding pollutions and as well to overcome the consumptions of liquid fuels. Under this scenario, for the production and applicability of electric vehicles, inverters play a major role to render appropriate battery power supply for the perfect operation of the electric vehicle. This research study devises a novel modified multilevel inverter and a new multistring inverter designed by reducing the number of switches and enabling the effective operation of the electric vehicle. Both the developed multilevel and multistring inverter is analyzed with respect to their switching states, their output voltage and the evaluated harmonic distortion. For comparison, a sinusoidal alternating current voltage is considered as reference and all the newly modeled configurations are compared with that of the existing inverter models to prove their superiority. The switched states of the designed inverters as applicable for electric vehicles are examined to attain a logical analysis with respect to the duty cycle of the individual switches. The power quality assessment of the designed inverter models are guaranteed based on the minimized total harmonic distortion and on comparison with the other inverter models from the earlier state-of-the-art techniques.
Fear of missing out during a pandemic: the driving factors of telemedicine application acceptance Muhammad Noor Fakhruzzaman; Ghea Sekar Palupi; Thinni Nurul Rochmah
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3848

Abstract

COVID-19 pandemic changed how society behaves. Travel and social restrictions, commonly associated with the term lockdown became popular and ubiquitous. Given the rise of gig economy and mobile app delivery in the past several years, combined with lockdowns during the pandemic, and the application of telemedicine becomes essential. Halodoc is one of the popular telemedicine applications in Indonesia, having several useful features such as text-based doctor consultation and prescription drug order-delivery, and Halodoc is easily preferred by many. This article explored the motivation behind using Halodoc as the preferred method of getting health service during the pandemic, behind the perceived usefulness and perceived ease of use of the application, we found that fear of missing out (FOMO) has an indirect role in the application adoption in society, especially during lockdowns, where social interaction is limited to social media and other internet-based platforms. The reason why FOMO can be an important factor in technology adoption and how advertisers should explore FOMO is further discussed.
Mobile development: learn du’a for early childhood learners Mohamed Imran Mohamed Ariff; Natasha Irina Khairul Annuar; Ahmad Farid Najmuddin; Ireen Munira Ibrahim; Noreen Izza Arshad; Samsiah Ahmad; Khairulliza Ahmad Salleh
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3860

Abstract

This project stands by acknowledging the use of mobile technology is progressively popular among early childhood learners in recent years. But, an extensive systematic literature search on educational mobile technology and touchscreen indicated that most of the applications are not suitable for early childhood learners as it lacks several multimedia features. Therefore, this project designates the development procedure of an educational mobile application for early childhood learners, who are very receptive to new knowledge and information. As a proof of concept, the development of this application utilizes the learning of the Islamic du’a recitation. This application was designed using the android studio and the flutter software combined with the java programming language. Upon the development of this application, several testings were done and analyzed. The result shows that users were satisfied with the applications as most of the testing scores were highly rated. Based on these results, the usage of this newly mobile application can be suggested to be adopted by early childhood learners.
Solar powered space vector pulse width modulation based induction motor drive for industry applications Muhammad Sohaib Choudhary; Muhammad Saqlain Saqi; Muhammad Rameez Javed; Hasan Erteza Gelani; Muhammad Akram; Muhammad Kashif Amjad; Sana Khan
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3023

Abstract

The new millennium has witnessed a rapid growth in the development of solar-powered electric systems as well as variable frequency drives (VFDs). Predominantly, pulse width modulation (PWM) based adjustable frequency drives are being employed in the industry for providing superior performance. The space vector pulse width modulation (SVPWM) has gained importance due to its improved harmonic profile. In the current effort, SVPWM based VFD for an induction motor is devised equipped with a push-pull converter for optimal performance. A feedback system is incorporated for motor controls. The SVPWM is implemented using FPGA based my-RIO controller because of its effective processing and power handling capabilities; whereas the feedback control is furnished using Lab-View. The performance of the proposed scheme is analyzed. The results confirm flexible control of the motor incorporated with the presented drive system which is supplied via solar power.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3877

Abstract

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.

Page 3 of 7 | Total Record : 64

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