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Bulletin of Electrical Engineering and Informatics
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Core Subject : 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.
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Articles 64 Documents
Search results for , issue "Vol 11, No 3: June 2022" : 64 Documents clear
Design hybrid filter technique for mixed noise reduction from synthetic aperture radar imagery Ekbal Hussain Ali; Ahmed Hameed Reja; Layla H. Abood
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3708

Abstract

For military and civilian applications, synthetic aperture radar (SAR) imaging is an essential instrument for obtaining images of the Earth's surface. Speckle noise, a form of noise that is multiplicative, generated by conflicting echoes returned from each pixel, has a significant impact on the SAR picture. On SAR pictures, a hybrid filter for mixed noise reduction is used to remove the mixed noises that are present in the data during capture and transmission. Specifically, speckle noise and salt and pepper noises from SAR images. Both are being worked on at the same time to minimize mixed noise in SAR pictures without revealing edges or other features. This study proposes a technique that combines a hybrid filter derived from a statistics filters with nonlinear functions (SFNF). When comparing to mean, median as no adaptive filters, and frost filter, a lee filter, and fuzzy filters as adaptive filters, this hybrid filter produces good results. MATLAB was used to carry out the simulation. To illustrate the filtering technique's performance, quantitative measurements like signal to noise ratio (SNR) procedure, the mean square error (MSE) method, and edge measurement (β) mechanization are used.
Two-layer remote phosphor package as a solution to promote color quality scale and lumen in WLEDs Phuc Dang Huu; Dieu An Nguyen Thi
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3766

Abstract

This article demonstrates the influence of the red-light LaAsO4:Eu3+ phosphorus on the optical features of the two structures: one-layer remote phosphorus scheme (SRPS) and two-layer remote phosphorus scheme (DRPS). As a result, the Mie hypothesis is used to demonstrate and prove the comparison between color quality and luminosity (LF) between these two factors. The SRPS is a phosphor layer that consists of LaAsO4:Eu3+ particles combined with the YAG:Ce3+ mixture. Meanwhile, DRPS is two phosphor layers of red and yellow separated from each other. To improve the dispersing property, 5% of SiO2 is combined with the phosphorous films. The difference between the structures influences the optical features of WLEDs. The obtained outcomes show that the color rendering index (CRI) rises along with the concentrations of both structures while these values are nearly identical to each other. Meanwhile, at ACCTs (5600 K - 8500 K), the color quality scale (CQS) in DRPS reaches 74, which is higher than SRPS's 71 at 8500 K. Besides, the lumen in DRPS is considerably greater than that in SRPS at 2%-14% LaAsO4:Eu3+. In short, DRPS brings considerable benefits to the color quality and lumen when compared to SRPS. In addition, choosing a suitable concentration also becomes highly vital to achieve desirable CQS and LF.
Convolutional neural network for color images classification Nora Ahmed Mohammed; Mohammed Hamzah Abed; Alaa Taima Albu-Salih
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3730

Abstract

Artificial intelligent and application of computer vision are an exciting topic in last few years, and its key for many real time applications like video summarization, image retrieval and image classifications. One of the most trend method in deep learning is a convolutional neural network, used for many applications of image processing and computer vision. In this work convolutional neural networks CNN model proposed for color image classification, the proposed model build using MATLAB tools of deep learning. In addition, the suggested model tested on three different datasets, with different size. The proposed model achieved highest result of accuracy, precision and sensitivity with the largest dataset and it was as following: accuracy is 0.9924, precision is 0.9947 and sensitivity is 0.9931, compare with other models.
Multi-input interleaved DC-DC converter for hybrid renewable energy applications Ibrahim Alhamrouni; Mohamed Salem; Younes Zahraoui; Basilah Ismail; Awang Jusoh; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3779

Abstract

The increasing demand for hybrid energy systems based on renewable energy sources has enabled the new dimension for multi-input converter (MIC). Various topologies have been introduced over the last decade. However, most of these topologies have several drawbacks in terms of design complexity or efficiency. Therefore, this research aims to introduce a multi-input DC-DC converter for hybrid renewable energy applications. The proposed multi-input converter is able to hybridize different sources such as solar PV array and PEMFC. Analysis and simulation have been carried out for the double input two-phase interleaved converter in operating the boost mode. The proposed converter is designed in matlab simulink by using interleaved boost converter method to achieve a boosted and smoothened output. The proposed topology has shown a remarkable performance in terms of output voltage boosting, voltage ripple reduction as well as enhanced efficiency through interleaved boosting technique. From the simulation results, it can be observed that the proposed converter can gain high efficiency which is higher than 97%. The obtained results have been validated with previously published works and the proposed technique has been proven to yield compatible and improved outcomes.
A novel optimizing PI control of shunt active power filter for power quality enhancement Ayad Mahmood Hadi; Ekhlas M. Thajeel; Ali K. Nahar
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3225

Abstract

In this paper, shunt active power filter (SAPF) is designed to address the problem of current harmonics in the source current arising from a nonlinear load and improve the quality of electric power. That will be by compensating reactive power and harmonic currents. The PI controller responsible for DC-link energy storage tuning was developed using the Lévy flight distribution algorithm (LFA). It is a novel, previously unused optimization approach to suggest relative gain Kp and integration gain Ki gain values for the PI controller. This approach aims to get the best dynamic performance of SAPF, speed up the convergence rate, get the fastest best stability and bypass constant voltage advancement for DC-link. The model was tested and implemented in MATLAB simulation software. The result of total harmonic distortion THD showed the efficiency of this method compared with the results of traditional PI. The design of the model in the current reference frame was based on instantaneous reactive power (pq) theory.
Intelligent multiperiod wind power forecast model using statistical and machine learning model Manisha Galphade; Valmik Nikam; Biplab Banerjee; Arvind Kiwelekar
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3756

Abstract

With the rapidly increasing integration of wind energy into the modern energy grid system, wind energy prediction (WPP) is playing an important role in the planning and operation of an electrical distribution system. However, the time series data of wind energy always has nonlinear and non-stationary characteristics, which is still a great challenge to be accurately predicted. This paper proposes the intelligent wind power forecast model and evaluates to forecast long term, short term and medium term wind power. It uses statistical and machine learning approach for finding the best model for multiperiod forecasting. The model has been tested on Sotavento wind farm historical data, located in Galicia, Spain. The experimental results show that random forest has better accuracy than other models for long term, short term and medium term forecasting. The power prediction accuracy of the proposed model has been evaluated on RMSE, and MAE metrics. The proposed model has shown better accuracy for medium term and long term forecast. The accuracy is improved by 72.12% in case of medium term and 50.49% in case of long term.
Advanced content-based retrieval for digital correspondence documents with ontology classification Rifiana Arief; Suryarini Widodo; Ary Bima Kurniawan; Hustinawaty Hustinawaty; Faisal Arkan
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3376

Abstract

The growth of digital correspondence documents with various types, different naming rules, and no sufficient search system complicates the search process with certain content, especially if there are unclassified documents, the search becomes inaccurate and takes a long time. This research proposed archiving method with automatic hierarchical classification and the content-based search method which displays ontology classification information as the solution to the content-based search problems. The method consists of preprocessing (creation of automatic hierarchical classification model using a combination of convolutional neural network (CNN) and regular expression method), archiving (document archiving with automatic classification), and retrieval (content-based search by displaying ontology relationships from the document classification). The archiving of 100 documents using the automatic hierarchical classification was found to be 79% accurate as indicated by the 99% accuracy for CNN and 80% for Regex. Moreover, the search results for classified content-based documents through the display of ontology relationships were discovered to be 100% accurate. This research succeeded in improving the quality of search results for digital correspondence documents as indicated by its higher specificity, accuracy, and speed compared to conventional methods based on file names, annotations, and unclassified content.
A comparative study of multiband mamdani fuzzy classification methods for west of Iraq satellite image Nezar Ismat Seno; Muntaser Abdul Wahed Salman; Rabah Nory Farhan
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3561

Abstract

In our paper, performance of four fuzzy membership function generation methods was studied. These methods were studied in the context of implementing Mamdani fuzzy classification on a set of satellite images for western Iraqi territory. The first method generate triangulate membership functions using mean, minimum (min) and maximum (max) of histogram attribute values (AV), while peak and standard deviation (STD) of these AV were used in the second. On the other hand, in the third and fourth methods, Gaussian membership functions are generated using same mentioned values in the first and second method respectively. The goal was to generate a Mamdani type fuzzy inference system the membership function (MF) of each fuzzy set and implementing the AV of western Iraqi territory training data sets. A pixel-by-pixel comparison of each method with traditional maximum likelihood method (ML) was made on data sets comprising six bands of satellite imagery of the western Iraqi region taken by the Landsat-5 satellite. Simulation results of these performance comparisons singled out that the method using Gaussian MFs together with peak and STD of the AV as the best achiever with a similarity of 83.16 percent for band (3) of the studied area.
Performance of circular patch microstrip antenna for adaptive modulation and coding applications Hiba A. Alsawaf; Bushra Muhammed Ahmad
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3402

Abstract

The thickness of the substrate is one factor influencing antenna performance. In this paper, the circular patch antenna was designed using rogers RT5880 with dielectric constant of 2.20, loss kept 0.0009 and FR-epoxy with dielectric constant of 4.4, loss kept 0.02. The thickness of the substrate was varied to see how it affected antenna performance, such as return loss. The thickness of the checked substrate is 1.58 mm, which is the standard thickness for rogers RT5880 as well as 2.08 mm, 2.58 mm and 2.85 mm. The simulation work is carried out by ANSYS HFSS software. In this paper, the thicknesses of different substrates are checked while other parameters stay constant and the circular patch radius of the antennas is optimized to achieve a resonant frequency of 3.5 GHz based on the thickness of the above-mentioned substrates used. Return loss, VSWR, gain and half power beam width were found, and the results showed that with the increase in the thickness of the substrate, the gain increases and the value of half power beam width (HPBW) and better results were obtained in the case of RTduroid 5880 and for thicknesses h=2.85 mm
Face detection and global positioning system on a walking aid for blind people Abdurrasyid Abdurrasyid; Indrianto Indrianto; Meilia Nur Indah Susanti
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3429

Abstract

Blindness is a general term used for the condition of someone who experiences a disturbance or obstacle in their sense of sight. In general, blind people walk with special canes to help them walk and increase their safety. However, there are problems that arise when blind people walk home or go from a path that they are used to or to a place where they have never traveled. There is the possibility that blind people get lost and find it difficult to determine their way home because they don't know where they are going. For this reason, it is necessary to create a system that can monitor their whereabouts in real time and provide directions, provide information on the steps to their destination and they can also notify their families and related foundations if they are in trouble. For this reason, it is necessary to make an integrated tool with the haar cascade method to detect faces to find out whether there are humans or other obstacles that can shows 94% accuracy, in addition a global positioning system (GPS) can help blind people to show the direction of the destination.