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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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Mobile agents assisted data collection in wireless sensor networks utilizing ZigBee technology Hoang Thuan Tran; Cuong V. Nguyen; Nghia Trung Phung; Minh T. Nguyen
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.v12i2.4541

Abstract

Wireless sensor networks (WSNs) are being utilized widely in many different industries, including agriculture, medicine, and the military. They contain many distributed sensors to monitor physical or environmental factors, such as temperature, humidity, pressure, etc. and use various communication technologies, including WiFi, radio frequency (RF), Bluetooth, and ZigBee. ZigBee is always a preferred choice for applications in WSNs. ZigBee has remarkable capabilities, such as saving energy and transmitting data over long distances. ZigBee end devices, as well as a ZigBee coordinator (ZC) and a ZigBee router (ZR), are crucial components of the WSNs. This article discusses the fundamentals of the ZigBee network, one of the most popular data transmission technologies in wireless sensor networks (WSNs). Additionally, we want to discuss the ZigBee communication technologies and their applications, particularly in the networks. Different scenarios for mobile agents including their routing protocols in WSNs are considered. Simulation results of different scenarios demonstrate how easily scalability can be achieved and provide a foundation for further ZigBee application development. At last, some conclusions and ideas are presented for considerations.
Speed control of hybrid energy sources fed BLDC motor drive with FOPID controllerusing various optimization techniques Sushita Kanagaraj; Shanmugasundaram Nithaiyan
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.v11i6.4095

Abstract

This article suggests the control of current and speed approach to reduce the torque ripple in BLDC motor. Initially, the renewable energy hybrid power system (REHPS) is composed of a generation system of PV, fuel cell (FC), and the storage system of battery bank. This REHPS uses solar power as their main source of electricity during the day. It uses the fuel cell as a secondary source for maintenance at night or during periods of shaded conditions. The novelty of the proposed method is to achieve torque ripple minimization and to control the speed of the BLDC motor. The speed and error torque of the BLDC motor is optimized by mayfly optimization algorithm (MOA). The MOA provides gain parameters of the fractional order proportional–integral–derivative (FOPID) controller. The advantage of the proposed method is to improve the level of dependability and provide flexibility in solving the system error. The proposed model is implemented in MATLAB/Simulink and experimental setup. The results of the proposed method are compared with the existing research techniques such as particle swarm optimization (PSO) and moth flame algorithm (MFA).
Bridgeless single stage AC/DC converter with power factor correction Anurag Sharma; Rajesh Gupta
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.v11i5.3607

Abstract

This research paper proposes a novel bridgeless single-stage isolated converter with power factor correction and load voltage control. The proposed converter reduces the input diode bridge requirement with reduced passive components and provides a unidirectional flow of power to the load. The single-stage design reduces the use of an electrolytic capacitor, which improves reliability and reduces the size of the converter. The proposed control method is based on a single proportional integral (PI) controller to achieve both power factor correction and input current control. The proposed bridgeless converter is suitable for electric vehicle (EV) charging. A simulation study is performed on the MATLAB/Simulink to verify the effectiveness of the proposed converter. The converter is implemented in the laboratory to obtain the experimental results using typhoon hardware in the loop (HIL) based real time simulator.
Automatic keyphrases extraction: an overview of deep learning approaches Ajallouda, Lahbib; Fagroud, Fatima Zahra; Zellou, Ahmed; Benlahmar, El habib
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.v12i1.4130

Abstract

Automatic keyphrases extraction (AKE) is a principal task in natural language processing (NLP). Several techniques have been exploited to improve the process of extracting keyphrases from documents. Deep learning (DL) algorithms are the latest techniques used in prediction and extraction of keyphrases. DL is one of the most complex types of machine learning, relying on the use of artificial neural networks to make the machine follow the same decision-making path as the human brain. In this paper, we present a review of deep learning-based methods for AKE from documents, to highlight their contribution to improving keyphrase extraction performance. This review will also provide researchers with a collection of data and information on the mechanisms of deep learning algorithms in the AKE domain. This will allow them to solve problems encountered by AKE approaches and propose new methods for improving key-extraction performance.
The effectiveness of big data classification control based on principal component analysis Mohammed, Mostafa Abdulghafoor; Akawee, Mostafa Mahmood; Saleh, Ziyad Hussien; Hasan, Raed Abdulkareem; Ali, Ahmed Hussein; Sutikno, Tole
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.v12i1.4405

Abstract

Large-scale datasets are becoming more common, yet they can be challenging to understand and interpret. When dealing with big datasets, principal component analysis (PCA) is used to minimize the dimensionality of the data while maintaining interpretability and avoiding information loss. It accomplishes this by producing new uncorrelated variables that gradually reduce the variance of the system. In the field of data analysis, PCA is a multivariate statistical technique commonly used to obtain rules explaining the separation of groups in a given situation. Classes are predicted using a classification algorithm, a supervised learning technique that indicates which type of data points will be presented. Creating a classification model using classification algorithms is required before any successful classification can be achieved. It is possible to predict the future using a variety of categorized strategies. It is necessary to reduce the dimensionality of data sets using the PCA approach. This article will begin by introducing the basic ideas of PCA and discussing what it can and cannot do. It will then describe some variants of PCA and their application and then shows how PCA improves the performance using a series of experiments.
Investigative uses of overmodulation techniques in modular multilevel cascaded converter Mohan P. Thakre; Jayesh A. Gangurde; Rakesh Shriwastava; Deepak P. Kadam; Sunil Somnath Kadlag; Haridarshan S. Sonawane
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.v11i6.3958

Abstract

Sinusoidal pulse width modulation (SPWM) is a method to generate the switching gate pulse of the converter. Overmodulation is a method where the modulation index exceeds the unity value and the system goes into the nonlinear region. To maintain the system in a linear region when operating in the overmodulation region, some techniques are developed. These techniques helped to operate the system in the linear range. Medium and high-power energy conversion systems mostly use a modular multilevel cascaded converter (MMCC), which has been an issue improving significantly in recent years. In this article, MMCC-based overmodulation techniques are compared with conventional PWM and analyzed on DC bus utilization (DBU), and total harmonic distortion (THD). MATLAB/Simulink digital platform used demonstrate overmodulation technique.
Long range and server inspired internet of smart street lights Singh, Rajesh; Krishna, Konda Hari; Kumar, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Chodhury, Sushabhan; Bisht, Yashwant Singh; Bisht, Kailash; Joshi, Kapil
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.v12i1.4044

Abstract

Currently, the integration of long-range (LoRa) and the internet of things (IoT) has been widely adopted in various applications for real-time monitoring with reliability. These technologies empower us to achieve the goal of the United Nations for the establishment of an inclusive, safe, resilient, and sustainable environment. The automation, monitoring, and controlling of streetlights is a necessary task for the development of smart infrastructure. With the motivation from the above, this study proposed a LoRa and IoT server-based architecture for automation and controlling of streetlights along with sensors. To implement the proposed architecture, the hardware of the sensor node and gateway based on ATMega 328P, 433 MHz LoRa module, and Wi-Fi module is realized. The realized hardware is deployed in the real-time environment and the sensor node can sense the motion of the object and also records the intensity value on the server through internet connectivity.
A novel classification and clustering algorithms for intrusion detection system on convolutional neural network Mathiyalagan Ramasamy; Pamela Vinitha Eric
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.v11i5.4145

Abstract

At present data transmission widely uses wireless network framework for transmitting large volume of data. It generates numerous security problems and privacy issues which laid a way for developing IDS. IDS act as preventive technique in securing computer networks. Previously there are numerous metaheuristic and deep learning algorithms used in IDS for detecting threats. Some are affected by dynamic growth of feature spaces and others are degraded in performance during detection of threats. One fine-grained model for intrusion detection can be developed by selecting accurate features and testing them with the intelligent algorithms. Based on these explorations, in this research IDS is implemented with intelligence from preprocessing to feature classification. At first stage, data preprocessing is done using binning concept to reduce noise. Secondly feature selection is done dynamically using dynamic tree growth algorithm with fire fly optimization techniques. Finally, these features are processed using DTB-FFNN for detecting anomalies perfectly. This DTB-FFNN is evaluated with popular KDD dataset. Our proposed model cable news network (CNN)-classification is compared with existing intelligent techniques: feed forward deep neural network, support vectors machines, decision tree, and CNN-clustering is compared with k-means, density-based spatial clustering of applications with noise (DBSCAN). The experimental outcome proves that dynamic tree based FFNN and CNN-clustering produce higher accuracy than the existing models.
Comparative analysis of influencing factors on pedestrian road accidents Hafeez, Farrukh; Sheikh, Usman Ullah; Al-Shammari, Saud; Hamid, Muhammad; Khakwani, Abdul Baqi Khan; Arfeen, Zeeshan Ahmad
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.v12i1.4312

Abstract

Road accident data includes detailed information about incidents that occurred, such as where they happened, the severity of the accident, and the number of people on the road at the time. Such information is useful in determining the causes of accidents and developing potential countermeasures. This research aims to determine the factors that contribute to pedestrian fatalities and injuries in traffic accidents. This study examined 150 pedestrian-vehicle accidents that took place between 1990 and 2021 in forty countries. Eleven factors have been identified as the major causes of accidents. The categorical principal component analysis (CATPCA) technique is used to reduce the number of dimensions and identify the elements that contribute to accidents. The eleven variables are classified into three groups: human factors, roadway environment, and vehicle attributes. The study found that car speed, weather, lighting, traffic conditions, area types, accident locations, and road conditions all had a significant impact on pedestrian accidents and fatalities. The findings show that a pedestrian's state (walking, running) and intention significantly increase the risk of serious injuries and death. The analysis of the driver's status suggests that the driver's intentions may also play a role in car accidents.
Proportional-integral-derivative controller design for time-delay systems via stability region centroid Aye Taiwo Ajiboye; Jayeola Femi Opadiji; Olusogo Joshua Popoola; Abdulrahman Olalekan Yusuf; Olalekan Femi Adebayo; Esther Toyin Olawole
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.v11i5.4309

Abstract

Design of proportional-integral-derivative (PID) controller with proportional, integral, and derivative gains given by ,  and  respectively, for time-delay systems is presented in this study. The centroid of the convex stability region (CCSR) method in the -  plane for fixed  is used. PID controller design for time-delay systems in the -  plane for a fixed  and -  plane for a fixed  have been extensively researched. Despite the amenability of CCSR method to design of PID controller in the -  plane for fixed , its application in this regard has not been given serious attention. The stability region in -  plane for fixed  was determined and the required controller gains in the region were determined using the CCSR method. Using the determined controller gains, the system closed loop unit step response for all the considered regions was plotted on same axes. Based on the obtained results, different combinations of controller gains can be implemented depending on the system time domain performance measures (TDPMs) requirements. However, selection of an appropriate controller gains combinations, requires compromise among any of the conflicting TDPMs.

Page 156 of 291 | Total Record : 2901

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