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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal 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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 98 Documents
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Search results for , issue "Vol 11, No 6: December 2021" : 98 Documents clear
Analysis of combined approaches of CBIR systems by clustering at varying precision levels S. M. Zakariya; Imtiaz A. Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5009-5018

Abstract

The image retrieving system is used to retrieve images from the image database. Two types of Image retrieval techniques are commonly used: content-based and text-based techniques. One of the well-known image retrieval techniques that extract the images in an unsupervised way, known as the cluster-based image retrieval technique. In this cluster-based image retrieval, all visual features of an image are combined to find a better retrieval rate and precisions. The objectives of the study were to develop a new model by combining the three traits i.e., color, shape, and texture of an image. The color-shape and color-texture models were compared to a threshold value with various precision levels. A union was formed of a newly developed model with a color-shape, and color-texture model to find the retrieval rate in terms of precisions of the image retrieval system. The results were experimented on on the COREL standard database and it was found that the union of three models gives better results than the image retrieval from the individual models. The newly developed model and the union of the given models also gives better results than the existing system named cluster-based retrieval of images by unsupervised learning (CLUE).
FPGA implementation of LDPC soft-decision decoders based DCSK for spread spectrum applications Fadhil S. Hasan; Mahmood F. Mosleh; Aya H. Abdulhameed
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4794-4809

Abstract

Spread spectrum (SS) communications have attracted interest because of their channel attenuation immunity and low intercept potential. Apart from some extra features such as basic transceiver structures, chaotic communication would be the analog alternative to digital SS systems. Differential chaos shift keying (DCSK) systems, non-periodic and random characteristics among chaos carriers as well as their interaction with soft data are designed based on low-density parity-check (LDPC) codes in this brief. Because of simple structure, and glorious ability to correct errors. Using the Xilinx kintex7 FPGA development kit, we investigate the hardware performance and resource requirement tendencies of the DCSK communication system based on LDPC decoding algorithms (Prob. Domain, Log Domain and Min-Sum) over AWGN channel. The results indicate that the proposed system model has substantial improvements in the performance of the bit error rate (BER) and the real-time process. The Min-Sum decoder has relatively fewer FPGA resources than the other decoders. The implemented system will achieve 10-4 BER efficiency with 5 dB associate Eb/No as a coding gain.
A MATLAB model for diagnosing sickle cells and other blood abnormalities using image processing Mohammed Al-Momin; Ammar Almomin
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5060-5065

Abstract

The conventional method for detecting blood abnormality is time consuming and lacks the high level of accuracy. In this paper a MATLAB based solution has been suggested to tackle the problem of time consumption and accuracy. Three types of blood abnormality have been covered here, namely, anemia which is characterized by low count of red blood cells (RBCs), Leukemia which is depicted by increasing the number of white blood cells (WBCs), and sickle cell blood disorder which is caused by a deformation in the shape of red cells. The algorithm has been tested on different images of blood smears and noticed to give an acceptable level of accuracy. Image processing techniques has been used here to detect the different types of blood constituents. Unlike many other researches, this research includes the blood sickling disorder which is epidemic in certain regions of the world, and offers a more accuracy than other algorithms through the use of detaching overlapped cells strategy.
A global system for mobile communications-based electrical power consumption for a non-contact smart billing system Ihsan Jabbar Hasan; Bushra Mahmoud Waheib; Nahla Abdul Jalil Salih; Nadhir Ibrahim Abdulkhaleq
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4659-4666

Abstract

This paper proposes a cheap solution to be a starting point for building smart electrical power billing systems. Electrical power has many challenges issues in Iraq, one of these challenges and the most important is the Billing system. The smart power meter uses an Arduino Uno as the core for controlling the sensed data and transmits it to the electrical power unit for billing services. The system is constructed with two parts: the transmitting unit measures the current, voltage, power and power factor through the compact new sensor PZEM-004T. The data sensed and processed by the microcontroller which displayed the KWh on (2*16 LCD) display. This data also transmitted to the electrical power company unit via the global system for mobile communications (GSM) module (SIM900A) which is a dual band GSM/GPRS-general packet radio service modem. The receiving part is mainly dedicated for collecting the required consumed power data via the same (SIM900A) module and also can display it using (2*16 LCD) display. For the sake of saving these data, the receiver part uses SD ram for such purposes. With such proposed system the electrical power company can control and collect their fees monthly without loss and with minimum cost.
Multiclassification of license plate based on deep convolution neural networks Masar Abed Uthaib; Muayad Sadik Croock
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5266-5276

Abstract

In the classification of license plate there are some challenges such that the different sizes of plate numbers, the plates' background, and the number of the dataset of the plates. In this paper, a multiclass classification model established using deep convolutional neural network (CNN) to classify the license plate for three countries (Armenia, Belarus, Hungary) with the dataset of 600 images as 200 images for each class (160 for training and 40 for validation sets). Because of the small numbers of datasets, a preprocessing on the dataset is performed using pixel normalization and image data augmentation techniques (rotation, horizontal flip, zoom range) to increase the number of datasets. After that, we feed the augmented images into the convolution layer model, which consists of four blocks of convolution layer. For calculating and optimizing the efficiency of the classification model, a categorical cross-entropy and Adam optimizer used with a learning rate was 0.0001. The model's performance showed 99.17% and 97.50% of the training and validation sets accuracies sequentially, with total accuracy of classification is 96.66%. The time of training is lasting for 12 minutes. An anaconda python 3.7 and Keras Tensor flow backend are used.
An approach to assess the quality of honey using partial least square method G. Rajalakshmi; A. Gopal; R. Pandian
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4991-4998

Abstract

The objective of the present study is to obtain the quantity of honey components such as moisture, glucose, fructose and sucrose in order to access the quality of honey. The tested honey samples are authenticated if the characteristics of a pure honey. The average ratio of 56% fructose to 44% glucose, but the ratios in the individual honeys ranged from a high of 64% fructose and 36% glucose to a low of 50% fructose and 50% glucose. The contents such as fructose and sucrose in honey is due to the presence of invertase enzymes. The organic acids present in the honey is responsible for the flavor and stability against the contamination of honey due to microorganisms. The natural food items are adulterated intentionally to increase the quantity and there by the quality gets affected. The main adulterants added in honey are sucrose, corn syrup, sugar syrup and jaggery syrup. The quantification deals in finding out the amount of basic constituents present in pure honey and adulterated honey using Fourier transform infrared (FTIR) spectrometer with the multivariate analysis and validating the same using chemical analysis method. The partial least square model is used in predicting the constituents of the samples.
Overall fuzzy logic control strategy of direct driven PMSG wind turbine connected to grid Mhamed Fannakh; Mohamed Larbi Elhafyani; Smail Zouggar; Hassan Zahboune
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5515-5529

Abstract

The fuzzy logic strategies reported in the literature about the control of direct drive permanent magnet synchronous generator (PMSG) connected to grid are limited in terms of inclusiveness and efficiency. So an overall control based on fuzzy logic and anti-windup compensation is proposed in this paper. Aiming at the inadequate of hill climb search (HCS) MPPT with fixed step size, the fuzzy logic is introduced in the stage of "generating rotor speed reference" to overcome the oscillations and slowness in traditional method. PI controllers are replaced by anti-windup fuzzy logic controllers in the "machine side control" stage and in "grid side control" stage to pertinently regulate the reference parameters. Then comparison tests with classical methods are implemented under varying climatic conditions. The results obtained demonstrate that the developed control is superior to other methods in response time (less than 4.528E-04 s), precision (an overshoot about 0.41%) and quality of produced energy (efficiency is 91%). The study verifying the feasibility and effectiveness of this algorithm in PMSG wind turbine connected to grid.
Performance analysis of massive multiple input multiple output for high speed railway Maharshi K. Bhatt; Bhavin S. Sedani; Komal Borisagar
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5180-5188

Abstract

This paper analytically reviews the performance of massive multiple input multiple output (MIMO) system for communication in highly mobility scenarios like high speed Railways. As popularity of high speed train increasing day by day, high data rate wireless communication system for high speed train is extremely required. 5G wireless communication systems must be designed to meet the requirement of high speed broadband services at speed of around 500 km/h, which is the expected speed achievable by HSR systems, at a data rate of 180 Mbps or higher. Significant challenges of high mobility communications are fast time-varying fading, channel estimation errors, doppler diversity, carrier frequency offset, inter carrier interference, high penetration loss and fast and frequent handovers. Therefore, crucial requirement to design high mobility communication channel models or systems prevails. Recently, massive MIMO techniques have been proposed to significantly improve the performance of wireless networks for upcoming 5G technology. Massive MIMO provide high throughput and high energy efficiency in wireless communication channel. In this paper, key findings, challenges and requirements to provide high speed wireless communication onboard the high speed train is pointed out after thorough literature review. In last, future research scope to bridge the research gap by designing efficient channel model by using massive MIMO and other optimization method is mentioned.
Analysis of WEKA data mining algorithms Bayes net, random forest, MLP and SMO for heart disease prediction system: A case study in Iraq Rana Riad K. AL-Taie; Basma Jumaa Saleh; Ahmed Yousif Falih Saedi; Lamees Abdalhasan Salman
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5229-5239

Abstract

Data mining is defined as a search through large amounts of data for valuable information. The association rules, grouping, clustering, prediction, sequence modeling is some essential and most general strategies for data extraction. The processing of data plays a major role in the healthcare industry's disease detection. A variety of disease evaluations should be required to diagnose the patient. However, using data mining strategies, the number of examinations should be decreased. This decreased examination plays a crucial role in terms of time and results. Heart disease is a death-provoking disorder. In this recent instance, health issues are immense because of the availability of health issues and the grouping of various situations. Today, secret information is important in the healthcare industry to make decisions. For the prediction of cardiovascular problems, (Weka 3.8.3) tools for this analysis are used for the prediction of data extraction algorithms like sequential minimal optimization (SMO), multilayer perceptron (MLP), random forest and Bayes net. The data collected combine the prediction accuracy results, the receiver operating characteristic (ROC) curve, and the PRC value. The performance of Bayes net (94.5%) and random forest (94%) technologies indicates optimum performance rather than the sequential minimal optimization (SMO) and multilayer perceptron (MLP) methods.
Coordinated planning in improving power quality considering the use of nonlinear load in radial distribution system Muhira Dzar Faraby; Ontoseno Penangsang; Rony Seto Wibowo; Andi Fitriati
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4610-4621

Abstract

Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.

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