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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 6,301 Documents
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Sliding-mode controller for a step up-down battery charger with a single current sensor Juan Pablo Villegas Ceballos; Carlos Andres Ramos-Paja; Elkin Edilberto Henao-Bravo
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1251-1264

Abstract

This paper proposes a battery charger solution based on the Zeta DC/DC converter to provide a general interface between batteries and microgrid direct current (DC) buses. This solution enables to interface batteries and DC buses with voltage conversion ratios lower, equal, and higher than one using the same components and without redesigning the control system, thus ensuring global stability. The converter controller is designed to require only the measurement of a single inductor current, instead of both inductors currents, without reducing the system flexibility and stability. The controller stability is demonstrated using the sliding-mode theory, and a design procedure for the parameters is developed to ensure a desired bus performance. Finally, simulations and experiments validate the performance of the proposed solution under realistic operation conditions.
Incentive mechanism design for citizen reporting application using Stackelberg game I Made Ariya Sanjaya; Suhono Harso Supangkat; Jaka Sembiring; Widya Liana Aji
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp2147-2157

Abstract

The growing utilization of smartphones equipped with various sensors to collect and analyze information around us highlights a paradigm called mobile crowdsensing. To motivate citizens’ participation in crowdsensing and compensate them for their resources, it is necessary to incentivize the participants for their sensing service. There are several studies that used the Stackelberg game to model the incentive mechanism, however, those studies did not include a budget constraint for limited budget case. Another challenge is to optimize crowdsourcer (government) profit in conducting crowdsensing under the limited budget then allocates the budget to several regional working units that are responsible for the specific city problems. We propose an incentive mechanism for mobile crowdsensing based on several identified incentive parameters using the Stackelberg game model and applied the MOOP (multi-objective optimization problem) to the incentive model in which the participant reputation is taken into account. The evaluation of the proposed incentive model is performed through simulations. The simulation indicated that the result appropriately corresponds to the theoretical properties of the model.
A hybrid approach to medical decision-making: diagnosis of heart disease with machine-learning model Tamilarasi Suresh; Tsehay Admassu Assegie; Subhashni Rajkumar; Napa Komal Kumar
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1831-1838

Abstract

Heart disease is one of the most widely spreading and deadliest diseases across the world. In this study, we have proposed hybrid model for heart disease prediction by employing random forest and support vector machine. With random forest, iterative feature elimination is carried out to select heart disease features that improves predictive outcome of support vector machine for heart disease prediction. Experiment is conducted on the proposed model using test set and the experimental result evidently appears to prove that the performance of the proposed hybrid model is better as compared to an individual random forest and support vector machine. Overall, we have developed more accurate and computationally efficient model for heart disease prediction with accuracy of 98.3%. Moreover, experiment is conducted to analyze the effect of regularization parameter (C) and gamma on the performance of support vector machine. The experimental result evidently reveals that support vector machine is very sensitive to C and gamma.
Super-linear speedup for real-time condition monitoring using image processing and drones Moath Alsafasfeh; Bradely Bazuin; Ikhlas Abdel-Qader
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1548-1557

Abstract

Real-time inspections for the large-scale solar system may take a long time to get the hazard situations for any failures that may take place in the solar panels normal operations, where prior hazards detection is important. Reducing the execution time and improving the system’s performance are the ultimate goals of multiprocessing or multicore systems. Real-time video processing and analysis from two camcorders, thermal and charge-coupling devices (CCD), mounted on a drone compose the embedded system being proposed for solar panels inspection. The inspection method needs more time for capturing and processing the frames and detecting the faulty panels. The system can determine the longitude and latitude of the defect position information in real-time. In this work, we investigate parallel processing for the image processing operations which reduces the processing time for the inspection systems. The results show a super-linear speedup for real-time condition monitoring in large-scale solar systems. Using the multiprocessing module in Python, we execute fault detection algorithms using streamed frames from both video cameras. The experimental results show a super-linear speedup for thermal and CCD video processing, the execution time is efficiently reduced with an average of 3.1 times and 6.3 times using 2 processes and 4 processes respectively.
On the applicability of numerical tools for simulating wave-ports close to the cutoff frequency Eman Mohamed Eldesouki; Khalid Mustafa Ibrahim; Ahmed Mohmed Attiya
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1724-1731

Abstract

This paper focuses on a common drawback in electromagnetic numerical computer aided design computer aided design (CAD) tools: high frequency structure simulator (HFSS), computer simulation technology (CST) and FEKO, where the excitation by using a wave-port below and close to the cutoff frequency has unreliable values for the reflection coefficient. An example for such problem is presented in the design of a dual horn antenna fed by two different waveguide sections. To overcome this numerical error in the results of these CAD tools, a tapered waveguide section is used in the simulation as an excitation mechanism to the feeding waveguide. The cross section of the input port at this tapered waveguide section is designed to have a cutoff frequency smaller than the lowest frequency under investigation for the original problem. Then, by extracting the effect of the tapered section from the obtained reflection coefficient, it would be possible to obtain the reflection coefficient of the original problem.
Automatic text summarization of konkani texts using pre-trained word embeddings and deep learning Jovi D’Silva; Uzzal Sharma
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1990-2000

Abstract

Automatic text summarization has gained immense popularity in research. Previously, several methods have been explored for obtaining effective text summarization outcomes. However, most of the work pertains to the most popular languages spoken in the world. Through this paper, we explore the area of extractive automatic text summarization using deep learning approach and apply it to Konkani language, which is a low-resource language as there are limited resources, such as data, tools, speakers and/or experts in Konkani. In the proposed technique, Facebook’s fastText pre-trained word embeddings are used to get a vector representation for sentences. Thereafter, deep multi-layer perceptron technique is employed, as a supervised binary classification task for auto-generating summaries using the feature vectors. Using pre-trained fastText word embeddings eliminated the requirement of a large training set and reduced training time. The system generated summaries were evaluated against the ‘gold-standard’ human generated summaries with recall-oriented understudy for gisting evaluation (ROUGE) toolkit. The results thus obtained showed that performance of the proposed system matched closely to the performance of the human annotators in generating summaries.
Determining customer limits by data mining methods in credit allocation process Tuğçe Ayhan; Tamer Uçar
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1910-1915

Abstract

The demand for credit is increasing constantly. Banks are looking for various methods of credit evaluation that provide the most accurate results in a shorter period in order to minimize their rising risks. This study focuses on various methods that enable the banks to increase their asset quality without market loss regarding the credit allocation process. These methods enable the automatic evaluation of loan applications in line with the sector practices, and enable determination of credit policies/strategies based on actual needs. Within the scope of this study, the relationship between the predetermined attributes and the credit limit outputs are analyzed by using a sample data set of consumer loans. Random forest (RF), sequential minimal optimization (SMO), PART, decision table (DT), J48, multilayer perceptron(MP), JRip, naïve Bayes (NB), one rule (OneR) and zero rule (ZeroR) algorithms were used in this process. As a result of this analysis, SMO, PART and random forest algorithms are the top three approaches for determining customer credit limits.
Discrete interferences optimum beamformer in correlated signal and interfering noise Satyanand Singh; Sajai Vir Singh; Dinesh Yadav; Sanjay Kumar Suman; Bhagyalakshmi Lakshminarayanan; Ghanshyam Singh
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1732-1743

Abstract

This paper introduces a significant special situation where the noise is a collection of D-plane interference signals and the correlated noise of D+1 is less than the number of array components. An optimal beamforming processor based on the minimum variance distortionless response (MVDR) generates and combines appropriate statistics for the D+1 model. Instead of the original space of the N-dimensional problem, the interference signal subspace is reduced to D+1. Typical antenna arrays in many modern communication networks absorb waves generated from multiple point sources. An analytical formula was derived to improve the signal to interference and noise ratio (SINR) obtained from the steering errors of the two beamformers. The proposed MVDR processor-based beamforming does not enforce general constraints. Therefore, it can also be used in systems where the steering vector is compromised by gain. Simulation results show that the output of the proposed beamformer based on the MVDR processor is usually close to the ideal state within a wide range of signal-to-noise ratio and signal-to-interference ratio. The MVDR processor-based beamformer has been experimentally evaluated. The proposed processor-based MVDR system significantly improves performance for large interference white noise ratio (INR) in the sidelobe region and provide an appropriate beam pattern.
Bandwidth enhancement of dual-band bi-directional microstrip antenna using complementary split ring resonator with defected structure for 3/5 GHz applications Charernkiat Pochaiya; Srawouth Chandhaket; Prapan Leekul; Jhirat Mearnchu; Tanawut Tantisopharak; Thunyawat Limpiti
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1683-1694

Abstract

This paper presents a bandwidth enhancement of a dual-band bi-directional rectangular microstrip patch antenna. The novelty of this work lies in the modification of conventional rectangular microstip patch antenna by using the combination of two techniques: a complementary split ring resonator (CSRR) and a defected patch structure (DPS). The structure of antenna was studied and investigated via computer simulation technology (CST). The dimension and position of CSRR on the ground plane was optimized to achieve dual bandwidth and bi-directional radiation pattern characteristics. In addition, the bandwidths were enhanced by defecting suitable shape incorporated in the microstrip patch. A prototype with overall dimension of 70.45×63.73 mm2 has been fabricated on FR-4 substrate. To verify the proposed design, the impedance bandwidth, gain, and radiation patterns were carried out in measurements. The measured impedance bandwidths were respectively 560 MHz (3.08-3.64 GHz) and 950 GHz (4.64-5.59 GHz) while the measured gains of each bandwidth were respectively 4.28 dBi and 4.63 dBi. The measured radiation patterns were in good agreement with simulated ones. The proposed antenna achieves wide dual bandwidth and bi-directional radiation patterns performances. Consequently, it is a promising candidate for Wi-Fi or 5G communications in specific areas such as tunnel, corridor, or transit and rail.
An analysis between exact and approximate algorithms for the k-center problem in graphs Velin Kralev; Radoslava Kraleva; Viktor Ankov; Dimitar Chakalov
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp2058-2065

Abstract

This research focuses on the k-center problem and its applications. Different methods for solving this problem are analyzed. The implementations of an exact algorithm and of an approximate algorithm are presented. The source code and the computation complexity of these algorithms are presented and analyzed. The multitasking mode of the operating system is taken into account considering the execution time of the algorithms. The results show that the approximate algorithm finds solutions that are not worse than two times optimal. In some case these solutions are very close to the optimal solutions, but this is true only for graphs with a smaller number of nodes. As the number of nodes in the graph increases (respectively the number of edges increases), the approximate solutions deviate from the optimal ones, but remain acceptable. These results give reason to conclude that for graphs with a small number of nodes the approximate algorithm finds comparable solutions with those founds by the exact algorithm.

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