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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 112 Documents
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Search results for , issue "Vol 13, No 1: February 2023" : 112 Documents clear
Forecasting smoked rubber sheets price based on a deep learning model with long short-term memory Kornkanok Phoksawat; Eakkarat Phoksawat; Benjamin Chanakot
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp688-696

Abstract

This research aimed to create suitable forecasting models with long-short term memory (LSTM) from time series data, the price of rubber smoked sheets (RSS3) using 2,631 data from the Rubber Authority of Thailand for the past 10 years. The data was divided into two sets: first series 2,105 data points were used to create the LSTM prediction model; second series 526 data points were used to estimate forecasting performance using the root mean square error (RMSE), the mean absolute percentage error (MAPE), and accuracy rate of the model. The results showed that the most suitable forecasting model for time series data, with a total of 9 LSTM layers comprised of 3 primary LSTMs. Each LSTM layer has the number of neurons 100, 150, and 200 to obtain an optimal neural network of the LSTM technique. The number of epochs and iteration was 30, 40, and 50. Dropout layers between each LSTM layer have a probability of 30%. The results of the test to measure the performance of the time series forecasting data showed that the 9-layer model with the LSTM model architecture of LSTM 3 layers gave the best forecast, with RMSE of 2.4121, MAPE of 0.0413 and 95.88% accuracy rate.
A genetic algorithm for shortest path with real constraints in computer networks Fahad. A. Alghamdi; Ahmed Younes Hamed; Abdullah M. Alghamdi; Abderrazak Ben Salah; Tamer Hashem Farag; Walaa Hassan
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp435-442

Abstract

The shortest path problem has many different versions. In this manuscript, we proposed a muti-constrained optimization method to find the shortest path in a computer network. In general, a genetic algorithm is one of the common heuristic algorithms. In this paper, we employed the genetic algorithm to find the solution of the shortest path multi-constrained problem. The proposed algorithm finds the best route for network packets with minimum total cost, delay, and hop count constrained with limited bandwidth. The new algorithm was implemented on four different capacity networks with random network parameters, the results showed that the shortest path under constraints can be found in a reasonable time. The experimental results showed that the algorithm always found the shortest path with minimal constraints.
A reconfigurable dual port antenna system for underlay/interweave cognitive radio Laith Wajeeh Abdullah; Adheed H. Sallomi; Ali Khalid Jassim
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp443-453

Abstract

An antenna system that is reconfigurable in frequency is presented in this paper as a novel dual port design that serves both undelay and interweave cognitive radio. This 25×40×0.8 mm3 system is composed of two wide slot antennas: the first is designed as an ultra-wideband (UWB) antenna with controllable band rejection capabilities, while the second antenna is reconfigurable for communication purposes. Three slots are etched into the patch of the UWB antenna to obtain band notching in wireless local area network/Xband/International Telecommunication Union bands (WLAN/Xband/ITU) bands which can be controlled by a positive-intrinsic-negative (PIN) diode across each slot. The configuration states of these three diodes are all useable that produces seven band rejection modes plus the UWB operation mode. The second antenna is configured by five PIN diodes to operate either in Cband, WLAN or Xband regions which results in three interweave modes when setting the first antenna for UWB sensing. The design is simulated by computer simulation technology (CST) v.10. S21 results shows good isolation while input reflection coefficient and realized gain results prove system’s scanning, filtering and communication capabilities. This system is new that it gathers the undelay/interweave operation in a single design and when considering its large number of operation modes it looks adequate for many cognitive radio applications.
Machine learning for prediction models to mitigate the voltage deviation in photovoltaic-rich distributed network Mohammed Baniyounis; Samer Z. Salah; Jasim A. Ghaeb
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp55-68

Abstract

The voltage deviation is one of the most crucial power quality issues that occur in electrical power systems. Renewable energy plays a vital role in electrical distribution networks due to the high economic returns. However, the presence of photovoltaic systems changes the nature of the energy flow in the grid and causes many problems such as voltage deviation. In this work, several predictive models are examined for voltage regulation in the Jordanian Sabha distribution network equipped with photovoltaic farms. The augmented grey wolf optimizer is used to train the different predictive models. To evaluate the performance of models, a value of one for regression factor and a low value for root mean square error, mean square error, and mean absolute error are used as standards. In addition, a comparison between nineteen predictive models has been made. The results have proved the capability of linear regression and the gaussian process to restore the bus voltages in the distribution network accurately and quickly and to solve the shortening in the voltage dynamic response caused by the iterative nature of the heuristic algorithm.  
The effect of changing the formation of multiple input multiple output antennas on the gain Majed Omar Dwairi; Mohamed Salaheldeen Soliman; Amjad Yousef Hendi; Ziad AL-Qadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp531-548

Abstract

In this paper, different 2×1 and 2×2 multiple input multiple output (MIMO) antennas were investigated with changing substrate shapes and changing the placing of the patches on the substrate, all the investigated antennas based on FR-4 substrate are characterized by , and loss , with a partial ground. The original antenna covered 3.4 to 13.5 GHz. The best simulation results of the proposed 2×1 MIMO antenna received for 2×1 inverted with high ultra-wideband (UWB) with bandwidth up to 40 GHz, the received maximum gain was up to 6.51 dB, with an average gain of more than the original single antenna at about +1.27 dB. The best of eight 2×2 MIMO antennas configurations that give good results were shown. The best-received gain compared with a single antenna gain were at 4.2 GHz about +2.73, +1.17, and +0.92 dB for plus-shaped, loop, and chair-shaped respectively. A comparison between the proposed MIMO antennas and other reported works were done. The proposed MIMO antennas give a good maximum gain and are suitable for different narrow bands within the UWB such as wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), aeronautical radio navigation (ARN), International Telecommunication Union 8-GHz (ITU-8), and X-Band applications with the ability to give high gain without the need to increase the radiated power of the transmitter antenna.
Predicting reaction based on customer's transaction using machine learning approaches Israa M. Hayder; Ghazwan Abdul Nabi Al Ali; Hussain A. Younis
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp1086-1096

Abstract

Banking advertisements are important because they help target specific customers on subscribing to their packages or other deals by giving their current customers more fixed-term deposit offers. This is done through promotional advertisements on the Internet or media pages, and this task is the responsibility of the shopping department. In order to build a relationship with them, offer them the best deals, and be appropriate for the client with the company's assurance to recover these deposits, many banks or telecommunications firms store the data of their customers. The Portuguese bank increases its sales by establishing a relationship with its customers. This study proposes creating a prediction model using machine learning algorithms, to see how the customer reacts to subscribe to those fixed-term deposits or offers made with the aid of their past record. This classification is binary, i.e., the prediction of whether or not a customer will embrace these offers. Four classifiers that include k-nearest neighbor (k-NN) algorithm, decision tree, naive Bayes, and support vector machines (SVM) were used, and the best result was obtained from the classifier decision tree with an accuracy of 91% and the other classifier SVM with an accuracy of 89%.
Early coronavirus disease detection using internet of things smart system Tabarak Ali Abdulhussein; Hamid A. Al-Falahi; Drai Ahmed Smait; Sameer Alani; Sarmad Nozad Mahmood; Mohammed Sulaiman Mustafa
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp1161-1168

Abstract

The internet of things (IoT) is quickly evolving, allowing for the connecting of a wide range of smart devices in a variety of applications including industry, military, education, and health. Coronavirus has recently expanded fast across the world, and there are no particular therapies available at this moment. As a result, it is critical to avoid infection and watch signs like fever and shortness of breath. This research work proposes a smart and robust system that assists patients with influenza symptoms in determining whether or not they are infected with the coronavirus disease (COVID-19). In addition to the diagnostic capabilities of the system, the system aids these patients in obtaining medical care quickly by informing medical authorities via Blynk IoT. Moreover, the global positioning system (GPS) module is used to track patient mobility in order to locate contaminated regions and analyze suspected patient behaviors. Finally, this idea might be useful in medical institutions, quarantine units, airports, and other relevant fields.
Design of an axial mode helical antenna with buffer layer for underwater applications Afiza Nur Jaafar; Hajar Ja’afar; Yoshihide Yamada; Fatemeh Sadeghikia; Idnin Pasya Ibrahim; Mohd Khairil Adzhar Mahmood
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp473-482

Abstract

Recently, there is an increasing demand for high-speed wireless communication network for short-range underwater communication. From previous research, most underwater antennas produced omnidirectional radiation pattern which has lower antenna gain. There are a few considerations that need to be taken if the antenna is designed to operate in water environment. This paper discusses the electromagnetic properties which affect the underwater antenna design. Physical properties such as electrical permittivity and conductivity of water contribute significant effect to the size of the antenna as it influences the behavior of electromagnetic signal that propagates in water. In this study, an axial mode helical antenna with waterproof container is presented which operates at 433 MHz. The axial mode helical antenna has circular polarization and is suitable to support wireless application which is surrounded by some obstruction. The proposed antenna produces a bidirectional radiation pattern by placing it into a waterproof casing. Good agreement between the simulation and measurement results validates the concept. However, a little discrepancy between the simulated and measured results may be attributed to the noise originated from the equipment and the environment.
Ameliorate the performance using soft computing approaches in wireless networks Chandrika Dadhirao; Ravi Sankar Sangam
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp502-510

Abstract

Wireless sensor networks are an innovative and rapidly advanced network occupying the broad spectrum of wireless networks. It works on the principle of “use with less expense, effort and with more comfort.” In these networks, routing provides efficient and effective data transmission between different sources to access points using the clustering technique. This work addresses the low-energy adaptive clustering hierarchy (LEACH) protocol’s main backdrop of choosing head nodes based on a random value. In this, the soft computing methods are used, namely the fuzzy approach, to overcome this barrier in LEACH. Our approach’s primary goal is to extend the network lifetime with efficient energy consumption and by choosing the appropriate head node in each cluster based on the fuzzy parameters. The proposed clustering algorithm focused on two fuzzy inference structures, namely Mamdani and Sugeno fuzzy logic models in two scenarios, respectively. We compared our approach with four existing works, the conventional LEACH, LEACH using the fuzzy method, multicriteria cluster head delegation, and fuzzy-based energy efficient clustering approach (FEECA) in wireless sensor network. The proposed scenario based fuzzy LEACH protocol approaches are better than the four existing methods regarding stability, network survivability, and energy consumption.
Developing a trust model using graph and ranking trust of social messaging system Mostafa Heidarzadeh Kalahroudy; Kheirollah Rahsepar Fard; Yaghoob Farjami
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp997-1007

Abstract

Trust is an important issue in social interactions, especially in using cyberspace services. In this paper, a trust and evaluation model are proposed based on which the government can provide reliable services to users. The model is a distributed and hierarchical model. First, the number 12 trust criteria and the weight of these criteria were extracted using the analytical hierarchy process (AHP) and analytic network process (ANP) techniques. Second, to obtain the trust in the service examined, for each criterion, a graph of trusted entities is proposed. Then, a weighted graph with the number of trusted entities called trust pathways measure will be obtained. To test the model, the effect of the 12 criteria on three important evaluation factors over seven widely used social services was rated by three experts. The trust of each service was obtained, which was satisfactory as compared to a valid organizational evaluation. Finally, the correlation coefficient of this comparison was 70.37%, indicating that the results from this model were appropriate.

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