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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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Load frequency control of multi area system under deregulated environment using artificial gorilla troops optimization Sambugari Anil Kumar; M. Siva Sathya Narayana Varma; K. Jithendra Gowd
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.v11i6.4188

Abstract

The artificial gorilla troops method is utilized in the tilt integral derivative (TID) controller that is discussed in this paper in order to adorn the load frequency control (LFC) in the restructured thermal-hydal system. The controller is implemented in simulink. In this study, a mathematical definition of the social life of gorillas and innovative methods for exploring and exploiting gorilla habitats are presented. By applying step load perturbations and using integral square error as the evaluation method, the dynamic properties of the system can be determined. It is clear that the newly developed method of optimizing artificial gorilla troops performs better than the grey-wolf optimization technique (GTO). In this paper, the TID controller and the proportional integral derivative (PID) controller are contrasted with regard to a variety of optimization strategies inorder to compare different power transcations.
Traditional and hybrid solar photovoltaic array configurations for partial shading conditions: perspectives and challenges Dharani Kumar Narne; T. A. Ramesh Kumar; RamaKoteswara Rao Alla
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.v12i2.4520

Abstract

he role of photovoltaic (PV) array in converting solar energy to electrical energy is very much important to get maximum power. Current challenge in solar PV systems is to make them energy efficient. Partial shading conditions (PSCs) is one of the main causes for performance degradation of PV array. It not only effects the shaded region but also effect the overall output of the PV array. Proper selection of configuration is essential to overcome such type of challenges. There exist various types of traditional configurations such as series (S), parallel (P), series parallel (SP), total-cross-tied (TCT), bridge-link (BL), and honeycomb (HC). Hybrid configurations also available such as series-parallel-total-cross-tied (SPTCT), bridge-link-total-cross-tied (BL-TCT), honey-comb- total cross-tied (HC-TCT), and bridge-link-honey-comb (BL-HC). This paper presents an overview on various types of configurations available with their merits and demerits under various partial shading situations. This paper also insights recent advancements in PV array configurations with their future trends to benefit the researchers working in this domain.
Unmanned aerial vehicles and machine learning for detecting objects in real time Mustafa Fahem Al Baghdadi; Mehdi Ebady Manaa
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.v11i6.4185

Abstract

An unmanned aerial vehicle (UAV) image recognition system in real-time is proposed in this study. To begin, the you only look once (YOLO) detector has been retrained to better recognize objects in UAV photographs. The trained YOLO detector makes a trade-off between speed and precision in object recognition and localization to account for four typical moving entities caught by UAVs (cars, buses, trucks, and people). An additional 1500 UAV photographs captured by the embedded UAV camera are fed into the YOLO, which uses those probabilities to estimate the bounding box for the entire image. When it comes to object detection, the YOLO competes with other deep-learning frameworks such as the faster region convolutional neural network. The proposed system is tested on a wild test set of 1500 UAV photographs with graphics processing unit GPU acceleration, proving that it can distinguish objects in UAV images effectively and consistently in real-time at a detection speed of 60 frames per second.
Vehicular impact analysis of driving for accidents using on board diagnostic II Siddhanta Kumar Singh; Ajay Kumar Singh
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.v11i5.3864

Abstract

A large number of people meet with an accident everyday around the world. One of the leading causes of death is traffic accidents. The reasons behind India's rising number of road accidents contribute to bad driving behavior, poor road design and infrastructure, lack of enforcement of traffic laws. The post accidental investigation report is very important to know the actual reason of collision for the concerned parties and the insurance company and the police. The proposed work effectively extracts interpretable features describing complex driving patterns. It will provide analytical report of the accidents to various parties involved in process. This work analyzes the type and cause of accident. The experiment has been simulated using on board diagnostic II (OBD II) and smart phone accelerometer for post accidental analysis of collision. As the electronic control unit (ECU) does not provide accelerometer sensor, so the smart phone accelerometer has been utilized in conjunction with another parameter of OBD II device. The gravitational force (G-force) values observed from accelerometer sensor along the different axes and speed, acceleration, fuel consumption rate, and are retrieved from OBD II device. The result shows that the parameters recorded are very helpful in finding the actual accidental status of the vehicle.
Assessing the quality of social media data: a systematic literature review Oumaima Reda; Ahmed Zellou
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.v12i2.4588

Abstract

In recent years, social media have been at the heart of new communication technologies. They are no longer used only to facilitate interaction between family, friends, and professional relationships, but tend to become an increasingly used communication channel to address public opinion. Research involving data sources from social media are relatively a recent and expanding area of research, nevertheless, the literature remains limited regarding the complex issue of how to assess and ensure the quality of social media data significantly and adequately. Our goal in this study is to provide a clearer and deeper understanding and a comprehensive overview of the existing state of research pertaining to the assessment of data quality in social media context. We performed a systematic literature review (SLR) on the quality of social media data to collect, analyze, and discuss data on the accuracy and value of prior literature that has focused on this area, has addressed a variety of topics, and has been published between 2016 and 2021. We followed a predefined review process to cover all relevant research papers published during this period. Our results demonstrate and strengthen the significance and the importance of data quality especially in the context of social media.
Common human diseases prediction using machine learning based on survey data Jabir Al Nahian; Abu Kaisar Mohammad Masum; Sheikh Abujar; Md. Jueal Mia
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.v11i6.3405

Abstract

In this era, the moment has arrived to move away from disease as the primary emphasis of medical treatment. Although impressive, the multiple techniques that have been developed to detect the diseases. In this time, there are some types of diseases COVID-19, normal flue, migraine, lung disease, heart disease, kidney disease, diabetics, stomach disease, gastric, bone disease, autism are the very common diseases. In this analysis, we analyze disease symptoms and have done disease predictions based on their symptoms. We studied a range of symptoms and took a survey from people in order to complete the task. Several classification algorithms have been employed to train the model. Furthermore, performance evaluation matrices are used to measure the model's performance. Finally, we discovered that the part classifier surpasses the others.
Prediction measuring local coffee production and marketing relationships coffee with big data analysis support Anita Sindar Ros Maryana Sinaga; Ricky Eka Putra; Abba Suganda Girsang
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.v11i5.4082

Abstract

Following the increasing enthusiasm of the coffee market in Indonesia, a machine learning model is developed to study the relationship between coffee producers, consumers, production, and the market. Machine learning work flow is constructed in various stages; explore, develop, and validate the models. In this research, the building model predicts the production and market of late departure coffee based on labeled and unlabeled variables. The best predictions from the trained type of model algorithms of machine learning like tree accuracy of 85.7%, support vector machine (SVM) accuracy of 82.9%, and k-nearest neighbors, the accuracy of 82.9%, which produce three categories, namely, high production of 2 provinces, medium production of 21 provinces, and low production of 11 provinces. The accuracy classification is supported by the AUC value obtained for a high class, a medium class, and a low class. In addition, local coffee marketing modeling used in logistic regression was found with an accuracy of 88.9%, aiming to classify coffee interests between Arabica coffee and Robusta coffee. We found that the AUC value logistic regression for arabica coffee is about 0.94, while for Robusta is 0.92. The analysis of the classification modeling results shows a high level of accuracy of 93.0%.
Dual stage cascade controller for temperature control in greenhouse Abood, Layla H.; Kadhim, Nahida Naji; Mohammed, Yousra Abd
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.v12i1.4328

Abstract

In this paper, a dual stage cascade controller PI-(1+PD) is adopted to maintain and control temperature in greenhouse environment based on a smart and intelligent gorilla troops optimization (GTO) method for evaluating the controller gains to enhance the system response by reducing the error value and minimize the integral time absolute error (ITAE) fitness functions during simulation. The simulation results are obtained by using MATLAB 2019, then compared with two conventional controllers proportional integral derivative (PI and PID) based on evaluation parameters for all controllers in term of peak time, rise time, settling time and overshoot to show its efficient response if compared with other controllers used.
Comparison of different sparse dictionaries for compressive sampling Deepak M. Devendrappa; Karthik P.; Deepak N. Ananth; Aruna Kumar P.
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.v11i5.4014

Abstract

Compressive sampling/compressed sensing (CS) is building on the observation that most of the signals in nature are sparse or compressible concerning some transform domain. And by converse, the same can be reconstructed with high accuracy by making use of far fewer samples than what is required by violating Shannon-Nyquist theorem. Some of the transform techniques like discrete cosine transform, fast fourier transforms discrete wavelet transform, discrete fourier transforms. In this paper, novel CS techniques like FFTCoSAMP, DCTCoSaMP, and DWTCoSaMP are introduced and compared on different sparse transforms for CS in magnetic resonance (MR) images based on sparse signal sequences/dictionaries by means of transform techniques with respect to objective quality assessment algorithms like PSNR, SSIM and RMSE, where CoSaMP stands for compressive sampling matching pursuit. DWTCoSaMP is giving the PSNR values of 37.16 (DB4), 38.12 (Coif3), 38.5 (Sym8), for DCTCoSaMP and FFTCoSaMP, it’s 36.33 and 36.01 respectively. For DWTCoSaMP, SSIM value is 0.81, and for DCTCoSaMP and FFTCoSaMP, it’s 0.73 and 0.7 respectively. And finally, for DWTCoSaMP, RMSE value is 0.66, and for DCTCoSaMP and FFTCoSaMP, it’s 0.53 and 0.41 respectively. DWTCoSaMP reveals the best than rest of the methods and traditional CS techniques by the detailed comparison and analysis.
Finite element method based design and performance analysis of universal motor for agro applications Sharma, Sudhir Kumar; Manna, Manpreet Singh
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.v12i1.4204

Abstract

A universal motor is one that is capable of operating on either AC or DC power supply. The commutator is a component of the motor that has a significant impact on how efficiently the motor operates. It is essential to conduct an analysis of the pole structure of the universal motor in order to investigate the many aspects. The parametric study of a universal motor with a rating of 1 horsepower and 15,000 revolutions per minute that was designed with various combinations of brush angle and pole embrace factor for use in agricultural applications. The purpose of this study is to improve the effectiveness of the motor while preserving the ideal tolerance range for the model's other parameters as much as possible. The approach now allows for a greater degree of personalization for each distinct combination of factors. With the assistance of the finite element method (FEM), the transient solution is carried out so that the performance of the motor can be evaluated more accurately. The model that has been designed provides major design improvements, one of which is an improved average torque.

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