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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 111 Documents
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Search results for , issue "Vol 13, No 4: August 2023" : 111 Documents clear
Internet of things-blockchain lightweight cryptography to data security and integrity for intelligent application Martin Parmar; Parth Shah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4422-4431

Abstract

The industrial internet of things (IoT) plays a major role in the growth of automation and increasing digital connectivity for machine-to-machine communication. The research community has extensively investigated the possibility of IoT and blockchain integration for the last couple of years. The major research is focused on the benefits of integrating blockchain with IoT. In this work, we first focus on the issue of integrating IoT nodes with blockchain networks, especially for non-real-time IoT nodes that do not have an in-built clock mechanism. As a result, they cannot establish communication with real-time blockchain networks. Another critical security issue is protecting data coming from IoT devices to blockchain networks. Blockchain is enough mature to protect the data in its ecosystem. However, information coming from outside of the world does not have any guarantee of data integrity and security. This paper first addresses the clock synchronization issue of IoT nodes with blockchain using a network time protocol and then proposes an IoT-blockchain light-weight cryptographic (IBLWC) approach to secure the entire IoT-blockchain ecosystem. This paper also presents the performance analysis of IBLWC as a suitable and cost-effective solution that incurs less processing overhead for IoT-blockchain-based applications.
Risk management framework in Agile software development methodology Mohammad Hadi Zahedi; Alireza Rabiei Kashanaki; Elham Farahani
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4379-4387

Abstract

In software projects that use the Agile methodology, the focus is on development in small iterations to allow both frequent changes and client involvement. This methodology affects the risks that may happen in Agile software projects. Hence, these projects need a clear risk management process to reduce risks and address the problems before they arise. Most software production methodologies must use a framework for risk management, but currently, there is no such framework for the Agile methodology. Therefore, we present a risk management framework for projects that use the Agile methodology to help the software development process and increase the likelihood of the project’s success. The proposed framework states the necessary measures for risk management according to the ISO31000 standard at each stage of the Agile methodology. We evaluated the proposed framework in two running software projects with an Agile methodology by a number of expert experts. The results show that using our proposed framework increases the average positive risk reaction score by 49%.
Direct torque control and dynamic performance of induction motor using fractional order fuzzy logic controller Geeta Kamalapur; Mruttanjaya S. Aspalli
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp3805-3816

Abstract

Conventional direct torque control (DTC) is one of the best control systems for regulating the torque of an induction motor (IM). However, the DTC’s enormous waves in flux and torque cause acoustic noise that degrades control performance, especially at low speeds due to the DTC’s low switching frequency. Direct torque control systems, which focus just on torque and flux, have been proposed as a solution to these problems. In order to improve DTC control performance, this work introduces a fractional-order fuzzy logic controller method. The objective is to analyze this technique critically with regard to its efficacy in reducing ripple, its tracking speed, its switching loss, its algorithm complexity, and its sensitivity to its parameters. Simulation in MATLAB/Simulink verifies the anticipated control approach’s performance.
Accurate fashion and accessories detection for mobile application based on deep learning Yamin Thwe; Nipat Jongsawat; Anucha Tungkasthan
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4347-4356

Abstract

Detection and classification have an essential role in the world of e-commerce applications. The recommendation method that is commonly used is based on information text attached to a product. This results in several recommendation errors caused by invalid text information. In this study, we propose the development of a fashion category (FC-YOLOv4) model in providing category recommendations to sellers based on fashion accessory images. The resulting model was then compared to YOLOv3 and YOLOv4 on mobile devices. The dataset we use is a collection of 13,689, which consists of five fashion categories and five accessories' categories. Accuracy and speed analysis were performed by looking at mean average precision (mAP) values, intersection over union (IoU), model size, loading time, average RAM usage, and maximum RAM usage. From the experimental results, an increase in mAP was obtained by 99.84% and an IoU of 88.49 when compared to YOLOv3 and YOLOv4. Based on these results, it can be seen that the models we propose can accurately identify fashion and accessories categories. The main advantage of this paper lies in i) providing a model with a high level of accuracy and ii) the experimental results presented on a smartphone.
Uncertainty model for rate of change of frequency analysis with high renewable energy participation Tomas Rubiano; Mario A. Rios
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp3660-3671

Abstract

Large-scale integration of inverter-based renewables is displacing synchronous machine generation, causing a reduction in the inertia of electrical power systems. This reduction is reflected in an increase in the rate of change of frequency (RoCoF). Additionally, the variation of the RoCoF will depend on the uncertainty associated with the generation of non-conventional renewable energy sources. For the planning of the operation of the system, it is essential to know the range of variation of the RoCoF when there are disturbances in the system and uncertainties in the generation of non-conventional sources of renewable energy. This paper proposes to establish the calculation of a confidence interval of the RoCoF variation that considers these uncertainties. So, this paper proposes a method to consider these uncertainties based on the probabilistic point estimate method (PEM); considering multiple renewable non-conventional sources with correlated or uncorrelated behavior in their powers injected into the system. On the other hand, as there are different proposals to calculate the RoCoF, this paper presents the application of the uncertainty model with three different RoCoF proposed calculation methods.
Power transfer control within the framework of vehicle-to-house technology Hicham Ben Sassi; Yahia Mazzi; Fatima Errahimi; Najia Es-Sbai
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp3817-3828

Abstract

The emerging vehicle-to-grid (V2G) technology has gained a lot of praise in the last few years, following its experimental validation in several countries. As a result, this technology is being investigated for standalone houses under the name of vehicle-to-house (V2H). This latter proposes a two-way power transfer between the electric vehicles and isolated houses relying on renewable sources for power supply. In this paper an implementation of the V2H technology is investigated, using the adaptive backstepping control approach for the bidirectional half-bridge and the integral sliding mode control for the DC-DC converter. The robustness of the controller and its capability to respond to the desired performances were tested using different realistic scenarios. The obtained results yielded, a perfect sinusoidal output voltage with a voltage level of 220 V and a frequency of 50 Hz. This is further been validated by a frequency analysis resulting in a THD of 0.25%.
Drone’s node placement algorithm with routing protocols to enhance surveillance Emmanuel Kasai Akut; Aliyu Danjuma Usman; Kabir Ahmad Abubilal; Habeeb Bello; Ahmed Tijani Salawudeen; Abdulmalik Shehu Yaro
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4194-4203

Abstract

Flying ad-hoc network (FANET) is characterized by key component features such as communication scheme, energy awareness, and task distribution. In this research, a surveillance space considering standard petroleum pipe was created with three drones viz: drone 1 (D1), master drone (DM), and drone 2 (D2) to survey as FANET. DM aggregate packets from D1, D2 and communicate with the static ground control station (SGCS). The starting point of the three drones and their trajectories during deployment were calculated and simulated. Selection of DM, D1, and D2 was done using battery level before take-off. Simulation results show take-off time difference which depends on the distance of each drone to the SGCS during deployment. D1 take-off first, while DM and D2 followed after 0.0704 and 0.1314 ms respectively. The position-oriented routing protocols results indicated variation of information flow within time notch due to variation in the density of the transmitted packets. Packets delivery periods are 0.00136×103 sec, 0.00110×103 sec, and 0.00246×103 sec for time notch 1, 2, and aggregating time notch respectively. From the results obtained, two algorithms were used successfully in deploying the drones
Reconstructing 3D model of accident scene using drone image processing Mohamad Norsyafiq Iman Norahim; Khairul Nizam Tahar; Gyanu Raja Maharjan; Jose C. Matos
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4087-4100

Abstract

At the current stage, an investigation technique on the accident takes a longer time and this causes longer traffic congestion. The aim of this study is to reconstruct a 3D model of an accident scene using an unmanned aerial vehicle (UAV). The flight parameters that have been chosen are the circular method, the double grid method, and the single grid method. All these designs can produce a good 3D model to achieve the study’s objective. The methodology in this study is divided into 4 phases which are preliminary work, data acquisition, data processing, and data analysis. The main results of this study are the 3D model of the accident scene, an orthophoto map layout, and an accuracy assessment of a 3D model of reconstructed accident scene. All these parameters will be tested on accuracy based on the root mean square error (RMSE) value, comparing the UAV data and site measurement data. This objective has been tested for 10 different types of processing and different types of flight parameters. The best result among all the methods is the circular method 5 meters with ground control point (GCP) since this method has the least RMSE value which is 0.047 m. UAVs can replace the site measurement to reconstruct the accident scene.
Server virtualization in higher educational institutions: a case study Sreelakshmi Koratagere; Ravi Kumar Chandrashekarappa Koppal; Iyyanahalli Math Umesh
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4477-4487

Abstract

Virtualization is a concept in which multiple guest operating systems share a single piece of hardware. Server virtualization is the widely used type of virtualization in which each operating system believes that it has sole control of the underlying hardware. Server virtualization has already got its place in companies. Higher education institutes have also started to migrate to virtualized servers. The motivation for higher education institutes to adopt server virtualization is to reduce the maintenance of the complex information technology (IT) infrastructure. Data security is also one of the parameters considered by higher education institutes to move to virtualization. Virtualization enables organizations to reduce expenditure by avoiding building out more data center space. Server consolidation benefits the educational institutes by reducing energy costs, easing maintenance, optimizing the use of hardware, provisioning the resources for research. As the hybrid mode of learning is gaining momentum, the online mode of teaching and working from home options can be enabled with a strengthened infrastructure. The paper presents activities conducted during server virtualization implementation at RV College of Engineering, Bengaluru, one of the reputed engineering institutes in India. The activities carried out include study of the current scenario, evaluation of new proposals and post-implementation review.
Wearable sensor-based human activity recognition with ensemble learning: a comparison study Yee Jia Luwe; Chin Poo Lee; Kian Ming Lim
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4029-4040

Abstract

The spectacular growth of wearable sensors has provided a key contribution to the field of human activity recognition. Due to its effective and versatile usage and application in various fields such as smart homes and medical areas, human activity recognition has always been an appealing research topic in artificial intelligence. From this perspective, there are a lot of existing works that make use of accelerometer and gyroscope sensor data for recognizing human activities. This paper presents a comparative study of ensemble learning methods for human activity recognition. The methods include random forest, adaptive boosting, gradient boosting, extreme gradient boosting, and light gradient boosting machine (LightGBM). Among the ensemble learning methods in comparison, light gradient boosting machine and random forest demonstrate the best performance. The experimental results revealed that light gradient boosting machine yields the highest accuracy of 94.50% on UCI-HAR dataset and 100% on single accelerometer dataset while random forest records the highest accuracy of 93.41% on motion sense dataset.

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