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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 15, No 2: April 2025" : 111 Documents clear
Modeling and enhancing inverse kinematics algorithms for real-time target tracking in inertial stabilization systems Kriouile, Abderahman; Hamida, Soufiane; Moussa, Abdoul Latif Abdou
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1544-1556

Abstract

This study develops a two-axis gimbal system designed to maintain a target within its field of view by compensating for motion of either the target or the platform. The focus is on inertial stabilization platforms (ISPs), where accurate, real-time tracking is essential for applications such as surveillance, navigation, and scientific observation. The research prioritizes the design and optimization of inverse kinematics algorithms to enhance system performance. A detailed analysis of mathematical models underpins the development, addressing challenges in real-time processing with advanced optimization techniques to minimize latency and maximize accuracy. The proposed algorithms achieve a mean tracking error of 0.002 m and a mean convergence time of 2.12 seconds, surpassing traditional methods in precision and efficiency. Performance is evaluated within a simulation framework using Simscape Multibody, testing the algorithms under various conditions. Validation extends to real-world scenarios to ensure robustness and practical applicability. The results demonstrate significant improvements in tracking accuracy and responsiveness, offering a reliable solution for dynamic environments. This work paves the way for more efficient gimbal systems, contributing to advancements in technologies requiring stable and precise tracking in dynamic and challenging settings.
Privacy-aware enhanced homomorphic mechanism for group data sharing Karemallaiah, Jayalakshmi; Revaiah, Prabha
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1805-1816

Abstract

Cloud-based group data sharing has gained huge popularity in recent years. Accomplishing the efficacy and security of the data in a cloud-computing framework is challenging. Sharing data in a cloud environment is quite challenging and needs to be resolved. Furthermore, while exchanging data on the cloud, it is challenging to achieve both anonymity and traceability. The main aim of this research work is to make it easier for the same group to share and store anonymous data on the cloud securely and effectively. This research work presents verifiable privacy-aware enhanced homomorphic (VPEH) encryption for multiple participants; moreover, the enhanced homomorphic encryption mechanism provides end-to-end encryption and allows the secure computation of data without revealing any data in the cloud. The proposed algorithm uses homomorphic multiplication to compute the hashes product of challenges blocks that makes it more efficient Furthermore, an additional security model is incorporated to verify the shared data integrity. The VPEH mechanism is evaluated considering parameters such as tag generation, proof generation, and verification; model efficiency is proved by observing the marginal improvisation over the other existing model by varying the number of blocks and several challenge blocks.
Customized dataset-based machine learning approach for black hole attack detection in mobile ad hoc networks Moudni, Houda; Er-rouidi, Mohamed; Lmkaiti, Mansour; Mouncif, Hicham
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp2138-2149

Abstract

This article explores the application of machine learning (ML) algorithms to classify the black hole attack in mobile ad hoc networks (MANETs). Black hole attacks threaten MANETs by disrupting communication and data transmission. The primary goal of this study is to develop an intrusion detection system (IDS) to detect and classify this attack. The research process involves feature selection, the creation of a custom dataset tailored to the characteristics of black hole attacks, and the evaluation of four machine learning models: random forest (RF), logistic regression (LR), k-nearest neighbors (k-NN), and decision tree (DT). The evaluation of these models demonstrates promising results, with significant improvements in accuracy, precision, F1-score, and recall metrics. The findings underscore the potential of machine learning in enhancing the security of MANETs by providing an effective means of attack classification.
System level optimization of series hybrid electric vehicle through plug-in charging feature using ADVISOR Hassan, Zain ul; Ahmad, Naseer; Sohaib, Muhammad
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1521-1531

Abstract

This research addresses the optimization of series hybrid electric vehicles (SHEVs) to enhance sustainable transportation by integrating a plug-in charging feature. The primary objective is to extend the range and improve battery management. Using MATLAB Simulink and the advanced vehicle simulator (ADVISOR), three SHEVs scenarios were simulated under the urban dynamometer driving system (UDDS) cycle. The study maintains constant parameters for the fuel converter and generator while optimizing the battery and motor controller. Compared to conventional hybrid electric vehicles (HEVs), this optimized SHEVs demonstrates a 17% improvement in battery thermal management and a 13.5% reduction in power losses. Additionally, the plug-in series hybrid electric vehicle (P-SHEVs) configuration shows a 5.26% increase in power output and a 35.71% improvement in the state of charge (SOC) over standard SHEVs configurations. The P-SHEVs design also achieves a 12.20% increase in the UDDS single-cycle range and an 11.5% reduction in fuel consumption. The integration of the electric vehicle (EV) charging feature further enhances the SHEVs, resulting in an 8.33% boost in motor power input and a 6.35% improvement in motor temperature profile, reaching a peak enhancement of 50% (18 kW). It contributes to the field by demonstrating the effectiveness of optimized configurations and the integration of a plug-in charging feature in SHEVs, thereby advancing the capacity of these vehicles to promote greener transportation solutions.
Object retrieval analysis on plastic bottle waste recycling-based image control using convex hull algorithm and autoregressive integrated moving average prediction method Marisa, Marisa; Azhar Ramli, Azizul; Fudzee, Mohd Farhan Md; Abdullah, Zubaile
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp2055-2069

Abstract

In Indonesia, plastic garbage bottles are the most common sort of waste. Given that waste is expected to grow annually, managing plastic waste is a major challenge. The results of the study were achieved by comparing the reference, which was a collection of manually created contour images, with 50 sets of vortex images with different forms and vortex areas as experimental objects. The results indicate that the suggested approach reports a mean error of 2.84%, a correlation coefficient of 0.9965, and a root mean square error of 0.2903 when compared to the manual extraction method. These findings imply that the extract area determined by the procedure outlined in this research is more accurate and nearer to the actual values. The proposed method can therefore be used in place of the traditional process for investigating cooling parameters through manual testing. With measurement values mean absolute percentage error (MAPE)=121,842, mean absolute deviation (MAD)=20,140, and mean squared deviation (MSD)=776,712, the trend analysis of plastic bottles for autoregressive integrated moving average (ARIMA) modeling leads to the conclusion that the waste from plastic bottles will continue to rise annually and that efforts must be made to address this trend with knowledge and waste recycling technology. Plastic that is advantageous to industry and society.
Application of machine learning methods to analysis and evaluation of distance education Mukhiyadin, Ainur; Mukasheva, Manargul; Makhazhanova, Ulzhan; Kassekeyeva, Aislu; Azieva, Gulmira; Kenzhebayeva, Zhanat; Abdrakhmanova, Alfiya
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp2172-2180

Abstract

In recent decades, distance learning has become an essential component of the modern educational system, providing students with flexibility and access to knowledge regardless of location. This paper discusses creating a hybrid machine-learning model for assessing the quality of distance learning based on survey data. The model combines two feature extraction methods: Term frequency-inverse document frequency (TF-IDF) and Word2Vec. Combining these methods allows for a more complete and accurate representation of text data, improving the quality of machine learning models. The study aims to develop and evaluate the effectiveness of the proposed hybrid model for analyzing survey data and assessing the quality of distance learning. The paper considers the tasks of collecting and preprocessing text data, experimentally comparing various feature extraction methods and their combinations, training and evaluating a machine learning model based on a combination of TF-IDF and Word2Vec features, as well as analyzing the results and assessing the effectiveness of the proposed model using various metrics. In conclusion, the prospects for further development and application of the proposed model in educational institutions to improve the quality of distance learning are discussed.
Design of low power complementary metal-oxide semiconductor static random-access memory cell for embedded memories at three different technology nodes Venkatesh, Seerapu; Sahukara, Krishna Veni
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1424-1433

Abstract

In this work, the complementary metal-oxide semiconductor (CMOS) static random-access memory (SRAM) cell is proposed using a hybrid model. It is designed by combining two different methods and simulated at different technologies which are 180, 90, and 45 nm. The proposed hybrid model SRAM cell has less power consumption. The power consumption results of the hybrid model SRAM cell are contrasted with the 6T CMOS SRAM, Stacked SRAM cell, and 8T SRAM cell at 180, 90, and 45 nm. Tanner tool was used for designing and simulating these different SRAM cell topologies at 180, 90, and 45 nm technology nodes. S-edit is used for designing circuit diagrams, T-edit is used for simulating spice net lists and W-edit is used for observing waveforms in Tanner tool. The hybrid SRAM cell at 45 nm got better power consumption results than other SRAM cell topologies at different technology nodes.
Buffers balancing of buffer-aided relays in 5G non-orthogonal multiple access transmission internet of things networks Alkhwatrah, Mohammad; Qasem, Nidal
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1774-1782

Abstract

Buffer-aided cooperative non-orthogonal multiple access (NOMA) enhances the efficiency of utilizing the spectral by allowing more users to share the same re- sources to establish massive connectivity. This is remarkably attractive in the fifth generation (5G) and beyond systems, where a massive number of links is essential like in the internet of things (IoT). However, the capability of buffer co-operation in reducing the outage is limited due to empty and full buffers, where empty buffers can not transmit and full buffers can not receive data packets. Therefore, in this paper, we propose balancing the buffer content of the inter-connected relays, so the buffers that are more full send packets to the emptier buffers, hence all buffers are more balanced and farther from being empty or full. The simulations show that the proposed balancing technique has improved the network outage probability. The results show that the impact of the balancing is more effective as the number of relays in the network is increased. Further- more, utilizing the balancing with a lower number of relays may lead to better performance than that of more relays without balancing. In addition, giving the balancing different levels of priorities gives different levels of enhancement.
The advances in natural language processing technology and its impact on modern society Borisova, Nadezhda; Karashtranova, Elena; Atanasova, Irena
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp2325-2333

Abstract

A wide range of information, such as books, news, reports, and other content, is constantly being produced, much of which is available online. Machine translation, spam detection, natural language interfaces, and question-answering applications have become increasingly popular. Natural language processing (NLP) is at the core of the automatic retrieval of information stored on computers. This article discusses NLP and its applications in daily activities. It covers the main stages of NLP and provides examples of its advances in various higher-level tasks. The objective is to highlight the significance of NLP in processing online content and in efficient interactions between humans and computers across various applications. As an essential element of artificial intelligence, NLP provides solutions for real-world problems and has the potential to transform the way companies operate.
Multi-robot architecture based on hybridized blockchain model Kumar, Rahul Harish; Subramanian, Gopalakrishnan Muthu; Bailuguttu, Sahana
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp1511-1520

Abstract

Multi-robot systems (MRS) are groups of robots that coordinate to complete a given task. In communication-based systems, the integrity of the information shared between robots becomes highly important as any security threat due to a malicious node in the system can cause a chain reaction to compromise the entire system. This paper proposes a hybridized blockchain model-based architecture (HBMA) built on robot operating system (ROS) which offers a semi-decentralized environment into which any communication-based algorithm can be plugged in. A security monitoring system is also provided with the architecture that identifies and shuts down malicious robots while also sending out alerts about the threat. This architecture is used to create secured, coupled approaches to localization of multi-robots and multi-robot path planning. This approach is validated on both physical robots and simulations run on ROS.

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