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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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An approach based on deep learning that recommends fertilizers and pesticides for agriculture recommendation Nguyen Ha Huy Cuong; Trung Hai Trinh; Duc-Hien Nguyen; Thanh Khiet Bui; Tran Anh Kiet; Phan Hieu Ho; Nguyen Thanh Thuy
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5580-5588

Abstract

With the advancement of the internet, individuals are becoming more reliant on online applications to meet most of their needs. In the meantime, they have very little spare time to devote to the selection and decision-making process. As a result, the need for recommender systems to help tackle this problem is expanding. Recommender systems successfully provide consumers with individualized recommendations on a variety of goods, simplifying their duties. The goal of this research is to create a recommender system for farmers based on tree data structures. Recommender system has become interesting research by simplifying and saving time in the decision-making process of users. We conducted although a lot of research in various fields, there are insufficient in the agriculture sector. This issue is more necessary for farmers in Quangnam-Danang or all Vietnam countries by severe climate features. Storm from that, this research designs a system based on tree data structures. The proposed model combines the you only look once (YOLO) algorithm in a convolutional neural network (CNN) model with a similarity tree in computing similarity. By experiments on 400 samples and evaluating precision, accuracy, and the value of the predictive test as determined by its positive predictive value (PPV), the research proves that the proposed model is feasible and gain better results compared with other state-of-the-art models.
Single phase second order sliding mode controller for complex interconnected systems with extended disturbances and unknown time-varying delays Cong-Trang Nguyen; Chiem Trong Hien; Van-Duc Phan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4852-4860

Abstract

Novel results on complex interconnected time-delay systems with single phase second order sliding mode control is investigated. First, a reaching phase in traditional sliding mode control (TSMC) is removed by using a novel single phase switching manifold function. Next, a novel reduced order sliding mode observer (ROSMO) with lower dimension is suggested to estimate the unmeasurable variables of the plant. Then, a new single phase second order sliding mode controller (SPSOSMC) is established based on ROSMO tool to drive the state variables into the specified switching manifold from beginning of the motion and reduce the chattering in control input. Then, a stability condition is suggested based on the well-known linear matrix inequality (LMI) method to ensure the asymptotical stability of the whole plant. Finally, an illustrated example is simulated to validate the feasible application of the suggested technique.
Security and privacy recommendation of mobile app for Arabic speaking Hameed Almubarak; Mohamed Khairallah Khouja; Ahmed Jedidi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5191-5203

Abstract

There is an enormous number of mobile apps, leading users to be concerned about the security and privacy of their data. But few users are aware of what is meant by app permissions, which sometimes do not illustrate what kind of data is gathered. Therefore, users are still concerned about security risks and privacy, with little knowledge and experience of what security and privacy awareness. Users depend on ratings, which may be fake, or keep track of their sense to install an app, and an enormous number of users do not like to read reviews. To solve this issue, we propose a recommender system that reads users' reviews, and which exposes flaws, violations and third-party policies or the quality of a user's experience. In order to design and implement our recommender, we conduct a survey which supports two significant points: to detect the level of security and privacy awareness between users, and to gather new words into a dictionary of a recommender system, which assists to classify each review on the correct level, which can indeed reveal the scale of security and privacy in an app.
Realistic image synthesis of COVID-19 chest X-rays using depthwise boundary equilibrium generative adversarial networks Zendi Iklima; Trie Maya Kadarina; Eko Ihsanto
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5444-5454

Abstract

Researchers in various related fields research preventing and controlling the spread of the coronavirus disease (COVID-19) virus. The spread of the COVID-19 is increasing exponentially and infecting humans massively. Preliminary detection can be observed by looking at abnormal conditions in the airways, thus allowing the entry of the virus into the patient's respiratory tract, which can be represented using computer tomography (CT) scan and chest X-ray (CXR) imaging. Particular deep learning approaches have been developed to classify COVID-19 CT or CXR images such as convolutional neural network (CNN), and deep convolutional neural network (DCNN). However, COVID-19 CXR dataset was measly opened and accessed. Particular deep learning method performance can be improved by augmenting the dataset amount. Therefore, the COVID-19 CXR dataset was possibly augmented by generating the synthetic image. This study discusses a fast and real-like image synthesis approach, namely depthwise boundary equilibrium generative adversarial network (DepthwiseBEGAN). DepthwiseBEGAN was reduced memory load 70.11% in training processes compared to the conventional BEGAN. DepthwiseBEGAN synthetic images were inspected by measuring the Fréchet inception distance (FID) score with the real-to-real score equal to 4.3866 and real-to-fake score equal to 4.4674. Moreover, generated DepthwiseBEGAN synthetic images improve 22.59% accuracy of conventional CNN models.
A digital game for preserving food cultural heritage: design and evaluation of ThaiFoodAdventure game Kannattha Chaisriya; Lester Gilbert; Ratchada Suwangerd; Sasithorn Rattanarungrot
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5272-5278

Abstract

Digital games are a powerful tool for the presentation of food cultural heritage. A digital game was designed and developed to raise and enhance young people’s interest in and knowledge of Thai food cultural heritage, currently an under-researched field. The platform game was played on a mobile device and required the collection of food ingredients appropriate to popular cuisine in four Thai regions while overcoming obstacles. A sample (N=61) of young people (mean age=19 years) played the game, and the differences in their pre and post-test knowledge of and interest in Thai food and its cultural heritage were analyzed. The findings showed a highly significant increase in interest in and knowledge of Thai food cultural heritage, and did so despite the opinion of some participants that learning games were less interesting than conventional games, or that games were not a good way of raising interest in cultural heritage.
Design of miniaturized patch crossover based on superformula slot shapes Mutaz Akram Banat; Nihad Ibrahim Dib
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5145-5152

Abstract

In this paper, miniaturized microstrip crossover circuits are proposed using slots shapes obtained using the superformula. The design starts by using a conventional half-wavelength square patch crossover. For miniaturization purposes, different superformula slot shapes are introduced on the square patch. The proposed crossovers are designed to operate at 2.4 GHz using a 0.8 mm thick FR-4 substrate with a relative permittivity of 4.4. The designs are simulated using the high frequency structure simulator (HFSS). One of the miniaturized designs is fabricated and its scattering parameters are measured using a vector network analyzer. Simulated and measured results agree very well. At the design frequency, the measured input port matching is better than ˗19 dB, while ????12, ????13 and ????14 have the values of ˗12 dB, ˗2.2 dB and ˗10 dB, respectively. Furthermore, a 71% size reduction is achieved as compared to the conventional crossover area.
Parameter estimation and control design of solar maximum power point tracking Mashhood Hasan; Waleed Hassan Alhazmi; Waleed Zakri; Anwar Ulla Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4586-4598

Abstract

Parameters evaluation, design, and intelligent control of the solar photovoltaic model are presented in this work. The parameters of zeta converters such as a rating of an inductor, capacitor, and switches for a particular load are evaluated its values to compare the trade of the existing model and promoted to research in the proposed area. The zeta converter is pulsed through intelligent controller-based maximum power point tracking (intelligent-MPPT). The intelligent controller is a fuzzy logic controller (FLC) which extracts maximum power from the solar panel using the zeta converter. The performance of evaluated parameters based on the solar system and zeta converter is seen by an intelligent control algorithm. Moreover, evaluated parameters of solar photovoltaic (PV) and zeta converter can be examined the performance of fuzzy based intelligent MPPT under transient and steady-state conditions with different solar insolation. The brushless direct current motor-based water pump is used as the direct control (DC) load of the proposed model. The proposed model can enhance the research and assist to develop a new configuration of the present system.
Combinational load shedding using load frequency control and voltage stability indicator Hussein Hadi Abdul-Wahid Al-Sadooni; Rashid Hamid Al-Rubayi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4661-4671

Abstract

This paper proposes a load shedding program for evaluating and distributing the minimum load power to be curtailed required to bring the frequency and voltage, after the system was subjected to a heavy disturbance, to the allowable range for each load bus. The quantity of load shedding was estimated to restore the power system's frequency, taking into account the turbine governor's primary control and the generators' reserve power for secondary control. Calculation and review of the load bus's voltage stability indicator (Li) to prioritize the load shedding quantity at these locations. The lower the voltage stability indicator on the load bus, the less load shedding can occur, and vice versa. The frequency and voltage values are still within allowable ranges with this approach, and a significant amount of load shedding can be prevented, resulting in a reduction in customer service interruption. The proposed method's efficacy was demonstrated when it was checked against the IEEE 30 bus 6 generators power system standard simulated in MATLAB environment and it minimize the power to be shed by around 20% of the conventional load shedding schemes.
Optimized servo-speed control of wind turbine coupled to doubly fed induction generator Abdelhamid Mansouri; Fateh Krim
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4688-4699

Abstract

Optimal control of any variable speed wind turbine needs maximum power point tracking (MPPT) coupled to doubly fed induction generator (DFIG) for better power generation. This paper offers a novel direct power servo-speed control of wind turbine. This latter is based on DFIG optimal hysteresis MPPT inverter current control combined with space voltage modulation (SVM) inverter voltage technique, thus providing a stable and continuous energy flow to power grid. In this design, the asynchronous machine stator is directly connected to the grid. Bidirectional power converter, acting as frequency converter, is rotor circuit located. Rectifier supplies rotor windings with voltages and reference frequency resulting from control procedure of the power exchange between the stator and grid. Inverter is directly controlled by means of SVM technique to maintain direct current (DC) bus voltage constant. Simulation results show that the proposed configuration improves power converters efficiency due that rotor circuit needs less power than stator circuit which is injected into the grid.
Statistical features learning to predict the crop yield in regional areas Pinaka Pani Ramanahalli; Hemanth Kollegal Siddamallu; Ravi Kumar Yelwala Basavaraju
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5321-5329

Abstract

The plethora of information presented in the form of benchmark dataset plays a significant role in analyzing and understanding the crop yield in certain regions of regional territory. The information may be presented in the form of attributes makes a prediction of crop yield in various regions of machine learning. The information considered for processing involves data cleaning initially followed by binning to reduce the missing data. The information collected is subjected to clustering of data items based on patterns of similarity, The data items that are similar in nature is fed to the system with similarity measure, which involves understanding the distance of data items from its related data item leading to hyper parameters for analyzing of information while calculating the crop yield. The information may be used to ascertain the patterns of data that exhibit similarity with nearest neighbor represented by another attribute. Thus, the research method has yielded an accuracy of 89.62% of classification for predicting the crop yield in agricultural areas of Karnataka region.

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