International Journal of Electrical and Computer 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.
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Performance evaluation of hierarchical clustering protocols with fuzzy C-means
Hamid Barkouk;
El Mokhtar En-Naimi;
Aziz Mahboub
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3212-3221
The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.
Two-step artificial neural network to estimate the solar radiation at Java Island
Adi Kurniawan;
Eiji Shintaku
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3559-3566
The availability of information about solar radiation characteristics, particularly solar radiation predictions, is important for efficiently designing solar energy systems. Solar radiation information is not available in Indonesia because official measurements have not been conducted by the Indonesian Meteorological, Climatology, and Geophysical Agency (BMKG). In this study, a new two-step artificial neural network (ANN) is proposed to estimate both the daily average and hourly solar radiation at Java Island, Indonesia. The input parameters for the daily average solar radiation estimation are the location and time required, along with five selected monthly meteorological parameters that BMKG predicts for the subsequent month. The selected meteorological parameters are temperatures, relative humidity, and precipitation. The estimated daily average solar radiation is then used as the input parameter of the hourly solar radiation estimation along with the local time and location. The ANN training was conducted using two years of data, 2018 and 2019, from Surabaya and Jakarta, while the validation was performed in the same cities for January through July 2020. The accuracy of the proposed method is comparable to previous studies with an average R2 of 98.70% for the daily average solar radiation estimate and 97.44% for the hourly solar radiation estimate.
The impact of sentiment analysis from user on Facebook to enhanced the service quality
Daniel D. Albesta;
Michael L. Jonathan;
Muhammad Jawad;
Oktovianus Hardiawan;
Derwin Suhartono
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3424-3433
Facebook's influence on the modern social media platform is undoubtedly enormous. While it has gotten a backlash for its inability to control its influence over important affairs, there are still many questions regarding people's perception of Facebook and their sentiment over Facebook. This paper's role in this ongoing debate is to give a glimpse of people's sentiment and perception of Facebook in recent times. By collecting samples data from Facebook's Top Page, this paper hopes to represent a significant amount of people's aspirations towards this company. By processing the data with a processing tool to construct and model out the data and a sentiment analyzer tool helps determine the sentiment, this paper can deduce a 600-comment worth of processed data. The results from the 600 sampled comments concluded that the sentiments towards Facebook are 41.50% negative comments, 22.83% neutral comments, and 35.67% positive comments.
Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine
Aditi Agrawal;
Rajeev Paulus
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3176-3185
Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high.
Solar/wind pumping system with forecasting in Sharjah, United Arab Emirates
Waleed Obaid;
Abdul-Kadir Hamid;
Chaouki Ghenai
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp2752-2759
This paper demonstrates a water pumping hybrid power system design. The proposed system was designed for water related applications in Sharjah (Latitude 25.29 °N and Longitude 55 °E), United Arab Emirates. The proposed water hybrid system has two primary renewable power systems: solar PV panels and wind turbines. The proposed hybrid system considers the changes in weather conditions (humidity, wind speed, and temperature) since wind speed affects the performance of the wind turbines and solar panels are affected by solar irradiance. The following components are involved in the proposed design: battery (to store the power from solar panels), voltage regulator circuit (for getting stable DC voltage), three-phase rectifier (to convert the reduced AC voltage to DC), three-phase transformer (for reducing the obtained AC voltage), and DC electric motor (the main output of the proposed water pumping system). The proposed water pumping system relies on neural network blocks to achieve weather forecasting by obtaining solar irradiance values from the input temperature, wind speed, and humidity in a span of five years. Both MATLAB and Simulink are used simulate the performance of the proposed system under different weather conditions by changing the values according to the measured weather conditions values over five years.
Association rule hiding using integer linear programming
Suma B.;
Shobha G.
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3451-3458
Privacy preserving data mining has become the focus of attention of government statistical agencies and database security research community who are concerned with preventing privacy disclosure during data mining. Repositories of large datasets include sensitive rules that need to be concealed from unauthorized access. Hence, association rule hiding emerged as one of the powerful techniques for hiding sensitive knowledge that exists in data before it is published. In this paper, we present a constraint-based optimization approach for hiding a set of sensitive association rules, using a well-structured integer linear program formulation. The proposed approach reduces the database sanitization problem to an instance of the integer linear programming problem. The solution of the integer linear program determines the transactions that need to be sanitized in order to conceal the sensitive rules while minimizing the impact of sanitization on the non-sensitive rules. We also present a heuristic sanitization algorithm that performs hiding by reducing the support or the confidence of the sensitive rules. The results of the experimental evaluation of the proposed approach on real-life datasets indicate the promising performance of the approach in terms of side effects on the original database.
Optimization techniques on fuzzy inference systems to detect Xanthomonas campestris disease
Julio Barón Velandia;
Camilo Enrique Rocha Calderón;
Daniel David Leal Lara
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3510-3518
This paper shows the outcomes for four optimization models based on fuzzy inference systems, intervened using Quasi-Newton and genetic algorithms, to early assess bean plants’ leaves for Xanthomonas campestris disease. The assessment on the status of the plant (sane or ill) is defined through the intensity of the color in the RGB scale for the data-sets and images to analyze the implementation of the models. The best model performance is 99.68% when compared with the training data and a 94% effectiveness rate on the detection of Xanthomonas campestris in a bean leave image. Therefore, these results would allow farmers to take early measures to reduce the impact of the disease on the look and performance of green bean crops.
Four-leg active power filter control with SUI-PI controller
Mohamed M. El-sotouhy;
Ahmed A. Mansour;
Mostafa I. Marei;
Aziza M. Zaki;
Ahmed A. EL-Sattar
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp2768-2778
Four-leg active power filter is considered one of the greatest vital active filters that are frequently used in industrial applications, especially those that need to be controlled in each individual phase. Also, to control the neutral current that created because of a lot of unbalanced and non-linear loads. In this paper, the used active filter was controlled by a proposed control method which can achieve simplicity and intelligence at the same time. The novelty of this paper is using the proposed controller with Four-leg active power filter. This controller relies on instantaneous reactive power theory, which used to create the required currents that are injected into the network via the used active filter to remove the problems created by unbalanced and non-linear loads. It is also maintained that the current source a pure sinusoidal wave. The system is implemented on MATLAB/Simulink. The simulation results proved the preference of the proposed controller than the conventional proportional-integration controller, where it reduced the percentage of total harmonic distortion for the current source.
Potential key challenges for terahertz communication systems
Ahmad A. A. Solyman;
Ismail A. Elhaty
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp3403-3409
The vision of 6G communications is an improved performance of the data rate and latency limitations and permit ubiquitous connectivity. In addition, 6G communications will adopt a novel strategy. Terahertz (THz) waves will characterize 6G networks, due to 6G will integrate terrestrial wireless mobile communication, geostationary and medium and low orbit satellite communication and short distance direct communication technologies, as well as integrate communication, computing, and navigation. This study discusses the key challenges of THz waves, including path losses which is considered the main challenge; transceiver architectures and THz signal generators; environment of THz with network architecture and 3D communications; finally, Safety and health issues.
Intelligent control of battery energy storage for microgrid energy management using ANN
Younes Boujoudar;
Mohamed Azeroual;
Hassan Elmoussaoui;
Tijani Lamhamdi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v11i4.pp2760-2767
In this paper, an intelligent control strategy for a microgrid system consisting of Photovoltaic panels, grid-connected, and li-ion battery energy storage systems proposed. The energy management based on the managing of battery charging and discharging by integration of a smart controller for DC/DC bidirectional converter. The main novelty of this solution are the integration of artificial neural network (ANN) for the estimation of the battery state of charge (SOC) and for the control of bidirectional converter. The simulation results obtained in the MATLAB/Simulink environment explain the performance and the robust of the proposed control technique.