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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 113 Documents
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Search results for , issue "Vol 13, No 3: June 2023" : 113 Documents clear
Deep learning optimization for drug-target interaction prediction in COVID-19 using graphic processing unit Refianto Damai Darmawan; Wisnu Ananta Kusuma; Hendra Rahmawan
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp3111-3123

Abstract

The exponentially increasing bioinformatics data raised a new problem: the computation time length. The amount of data that needs to be processed is not matched by an increase in hardware performance, so it burdens researchers on computation time, especially on drug-target interaction prediction, where the computational complexity is exponential. One of the focuses of high-performance computing research is the utilization of the graphics processing unit (GPU) to perform multiple computations in parallel. This study aims to see how well the GPU performs when used for deep learning problems to predict drug-target interactions. This study used the gold-standard data in drug-target interaction (DTI) and the coronavirus disease (COVID-19) dataset. The stages of this research are data acquisition, data preprocessing, model building, hyperparameter tuning, performance evaluation and COVID-19 dataset testing. The results of this study indicate that the use of GPU in deep learning models can speed up the training process by 100 times. In addition, the hyperparameter tuning process is also greatly helped by the presence of the GPU because it can make the process up to 55 times faster. When tested using the COVID-19 dataset, the model showed good performance with 76% accuracy, 74% F-measure and a speed-up value of 179.
Simultaneous network reconfiguration and capacitor allocations using a novel dingo optimization algorithm Samson Oladayo Ayanlade; Abdulrasaq Jimoh; Emmanuel Idowu Ogunwole; Abdullahi Aremu; Abdulsamad Bolakale Jimoh; Dolapo Eniola Owolabi
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2384-2395

Abstract

Power loss and voltage magnitude fluctuations are two major issues in distribution networks that have drawn a lot of attention. Numerous strategies have been put forward to provide remedies to lessen the undesirable effects of these issues. Combining two of these approaches and dealing with them simultaneously to get more effective outcomes is essential. Therefore, this study hybridizes the network reconfiguration and capacitor allocation strategies using a novel dingo optimization algorithm (DOA) to solve the optimization problems. The optimization problems for simultaneous network reconfiguration and capacitor allocations were formulated and solved using a novel DOA. To demonstrate its effectiveness, DOA’s results were contrasted with those of the other optimization techniques. The methodology was validated on the IEEE 33-bus network and implemented in the MATLAB program. The results demonstrated that the best network reconfiguration was accomplished with switches 7, 11, 17, 27, and 34 open, and buses 8, 29, and 30 were the best places for capacitors with ideal sizes of 512, 714, and 495 kVAr, respectively. The voltage profile was significantly improved, and the power losses were significantly decreased. When compared to some of the different methods, DOA came out on top.
Optimized design of an extreme low power datalogger for photovoltaic panels Bilal Merabtane; Noureddine Benabadji
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2734-2742

Abstract

The paper focuses on the design and implementation of a low cost and compact data logger prototype using an extreme low power (XLP) and low pin count programmable interface controllers (PIC) microcontroller using its own flash memory for the periodic data acquisition storage, while many other works focus in the Arduino Eco-system. It is planned to pick four important analog measures from the photovoltaic system, and store them directly as 10-bit numerical counts, this yields to faster data acquisition and storage (no time consuming for mathematical computation to convert each numerical count of raw data to meaningful real-world data). Avoiding the use of any kind of display and keypad, and keeping the ratio run time over sleep time as low as possible, has a maximum impact on lowering the power consumption. This prototype can be serially linked to a personal computer (PC) to view the acquisition of measurements in real time, and to retrieve all collected data through a terminal application. The experimental results are stored in comma-separated values (CSV) files to ease post data analysis with any spread sheet software, for statistical calculations and graphs drawing, in order for instance, to find the faults of the photovoltaic system and optimize its management and its performance.
Power quality optimization using a novel backstepping control of a three-phase grid-connected photovoltaic systems Salwa Naddami; Najib Ababssi
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2517-2528

Abstract

A novel nonlinear backstepping controller based on direct current (DC) link voltage control is proposed in three-phase grid-connected solar photovoltaic (PV) systems to control the active and reactive power flow between the PV system and the grid with improved power quality in terms of pure sinusoidal current injection with lower total harmonic distortion (THD), as well as to ensure unity power factor, or to compensate for reactive power required by the load, i.e., the electrical grid. The output power of the PV array is supplied to the grid through a boost converter with maximum power point tracking (MPPT) control and an inverter. Simulation results of the proposed controller show good robustness under nominal conditions, parameter variations, and load disturbances, which presents the main advantage of this controller as compared to an existing controller. The performance of this work was evaluated using a MATLAB/Simulink environment.
Improving the error performance of offset pulse position modulation using Reed–Solomon error correction code and low-density parity Ahmed Hasan Salman; Basman Monther Al-Nedawe; Mohamed Ibrahim Shuja'a
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2847-2856

Abstract

An innovative performance study of an offset pulse-position modulation (OPPM) scheme is presented in this work with Reed–Solomon (RS) and low-density parity-checking (LDPC). The main aim is to resolve the errors of OPPM three using an RS or LDPC as a sporadic set of forward error correction (FEC). In this regard, the separate FEC has been utilized with coding that is based on multi-level, and waveform shaping based on the trellis. To systematically conduct this research, the greatest transmission efficiency that associated with the optimum RS code rates at different fiber normalization bandwidths is evaluated. Furthermore, the transmission efficiencies, channel extension, as well as the required number of photons per pulse of OPPM before and after the integration with RS or LDPC are compared. The results indicate an enhancement of mitigating the system's bit error rate and delivering more error-free data to the receiver in the occasion of applying the optimal settings of the RS or LDPC.
IEC 61850-9-2 based module for state estimation in co-simulated power grids David Celeita; Mario A. Rios; David M. Laverty; Jaime Forero; Andres F. Moreno-Jaramillo; Sean McLoone
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2555-2567

Abstract

This paper presents a research context on the virtualization of phasor measurement units (PMUs) and real-time power grids simulation with state estimation. In this research, real-time simulation is introduced to use powerful features for validating state estimation solutions with PMUs. Virtual and online measurement equipment are reviewed in this manuscript to develop an innovative integration of the OpenPMU incorporated with a real-time simulation power grid and additional virtualized PMUs. The implementation of the platform has useful features within the infrastructure that allows the user to reproduce a detailed modeled power grid with simulation software. The use of real-time simulation tools brings several possibilities for improving testing and prototype assessment with higher precision in different applications. In this case, 2 tests power systems are evaluated by realistic integration of IEC61850-9-2 data utilization to observe the performance of a customized state estimation approach. The study implements a versatile methodology for commissioning OpenPMU devices, interacting simultaneously with additional virtual PMUs within the same simulation through sampled values (SV) to validate the measurement frames and assess the estimation with the generated data. Finally, the proposed work identifies the potential of virtualizing PMUs and the features of the OpenPMU applied to state estimation in conjunction with real-time simulation data.
A comparison of various machine learning algorithms and execution of flask deployment on essay grading Udhika Meghana Kotha; Haveela Gaddam; Deepthi Reddy Siddenki; Sumalatha Saleti
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2990-2998

Abstract

Students’ performance can be assessed based on grading the answers written by the students during their examination. Currently, students are assessed manually by the teachers. This is a cumbersome task due to an increase in the student-teacher ratio. Moreover, due to coronavirus disease (COVID-19) pandemic, most of the educational institutions have adopted online teaching and assessment. To measure the learning ability of a student, we need to assess them. The current grading system works well for multiple choice questions, but there is no grading system for evaluating the essays. In this paper, we studied different machine learning and natural language processing techniques for automated essay scoring/grading (AES/G). Data imbalance is an issue which creates the problem in predicting the essay score due to uneven distribution of essay scores in the training data. We handled this issue using random over sampling technique which generates even distribution of essay scores. Also, we built a web application using flask and deployed the machine learning models. Subsequently, all the models have been evaluated using accuracy, precision, recall, and F1-score. It is found that random forest algorithm outperformed the other algorithms with an accuracy of 97.67%, precision of 97.62%, recall of 97.67%, and F1-score of 97.58%.
Sensor and internet of things based integrated inundation mitigation for smart city Berlian Al Kindhi; Umboro Lasminto; Masca Indra Triana; Satria Damarnegara; Sreenatha G. Anavatti
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2695-2703

Abstract

Flooding is a natural phenomenon that often occurs in tropical countries. Drainage design is one of the efforts to prevent floods, however, when the rainfall is high, there are still several inundation points that occur. This requires comprehensive handling to reduce the impact of these inundations, to get an adaptive solution, the use of internet of things based (IoT) tools is one of the alternatives proposed. This study proposes an IoT-based flood inundation monitoring system, which includes a water level reader, a web-based inundation monitoring system, a flood inundation area and depth reporting system as evaluation materials for the government city. The sensor module that we propose is a series of sensors in a hollow cylinder design to reduce water ripples. The server application is displayed in the form of an interactive area mapping which is divided into 4 layers for 4 different analyzes so that central officers can quickly coordinate with field officers to carry out mitigation actions in the affected area. The module requires a low cost and easy installation process compared to a liquid sensor, besides that the display in the form of a web makes it easier for officers to access monitoring applications anywhere compared to geographic information system based (GIS) applications. This research has been carried out and tested in one of the major cities in Indonesia.
Implementation design of energy trading monitoring application for blockchain technology-based wheeling cases Rezi Delfianti; Bima Mustaqim; Fauzan Nusyura; Ardyono Priyadi; Imam Abadi; Adi Soeprijanto
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2931-2941

Abstract

One obstacle to the energy industry’s tendency toward adopting renewable energy is the requirement for a monitoring system for energy transactions based on microgrids in the wheeling scheme (shared use of utility networks). The quantity of transaction expenses for each operational generator is not monitored in any case. In this project, a mobile phone application is developed and maintained to track the total amount of fees paid and received by all wheeling parties and the amount of electricity produced by the microgrid. In the wheeling case system research, the number of transaction costs, such as network rental fees, loss costs, and profit margins, must be pretty calculated for all wheeling participants. The approach created in this study uses a blockchain system to execute transactions, and transactions can only take place if the wheeling actor and the generator have an existing contract. The application of energy trading is the main contribution of this research. The created application may track energy transfers and track how many fees each wheeling actor is required to receive or pay. Using a security system to monitor wheeling transactions will make energy trades transparent.
Design of programmable hardware security modules for enhancing blockchain based security framework Devika Kalathil Nandalal; Ramesh Bhakthavatchalu
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp3178-3191

Abstract

Globalization of the chip design and manufacturing industry has imposed significant threats to the hardware security of integrated circuits (ICs). It has made ICs more susceptible to various hardware attacks. Blockchain provides a trustworthy and distributed platform to store immutable records related to the evidence of intellectual property (IP) creation, authentication of provenance, and confidential data storage. However, blockchain encounters major security challenges due to its decentralized nature of ledgers that contain sensitive data. The research objective is to design a dedicated programmable hardware security modules scheme to safeguard and maintain sensitive information contained in the blockchain networks in the context of the IC supply chain. Thus, the blockchain framework could rely on the proposed hardware security modules and separate the entire cryptographic operations within the system as stand-alone hardware units. This work put forth a novel approach that could be considered and utilized to enhance blockchain security in real-time. The critical cryptographic components in blockchain secure hash algorithm-256 (SHA-256) and the elliptic curve digital signature algorithm are designed as separate entities to enhance the security of the blockchain framework. Physical unclonable functions are adopted to perform authentication of transactions in the blockchain. Relative comparison of designed modules with existing works clearly depicts the upper hand of the former in terms of performance parameters.

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