cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Tole Sutikno
Contact Email
ijece@iaesjournal.com
Phone
-
Journal Mail Official
ijece@iaesjournal.com
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
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 6,301 Documents
 597   598   599   600   601 
D-RAKE compression for enhanced internet of things data management in air quality monitoring Kartika Sari; Sari, Kartika; Hidayati, Rahmi
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.pp2468-2478

Abstract

This study addresses the issue of air pollution in Pontianak, marked by high levels of pollutant particles and chemical compounds that cause respiratory health risks. The research involves essential air quality monitoring using various sensors for temperature, humidity (DHT22), O2 (MQ-135), CO (MQ-7), CO2 (MG-811), and dust (GP2Y1010AU0F), collected real-time, leading to a notable increase in data volume. Due to limitations in internet of things (IoT) devices, there is a need for integration between cloud and IoT through data transmission to reduce the communication time and memory usage. The escalation in sensor data volume requires a lossless compression technique to ensure efficient storage without sacrificing crucial information. Compression plays a vital role in overcoming complex storage challenges, facilitating real-time data access for monitoring, and contributing to sustainable efforts to improve air quality in Pontianak. This research applies the D-RAKE compression method based on basic counting procedures with minimal memory requirements, cost-effective, low-speed microcontrollers commonly used in IoT devices. Despite its simplicity, simulation results indicate that the D-RAKE algorithm outperforms well-established compression methods such as gzip, bzip2, and rar, particularly for data sequences with sparse elements. Moreover, when applied to real- world data, D-RAKE achieves superior compression ratios compared to IoT-focused compression techniques.
Revisiting self-supervised contrastive learning for imbalanced classification Gao, Xiaoling; Ramli, Muhammad Izzad; Rosli, Marshima Mohd; Jamil, Nursuriati; Ariffin, Syed Mohd Zahid Syed Zainal
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.pp1949-1960

Abstract

Class imbalance remains a formidable challenge in machine learning, particularly affecting fields that depend on accurate classification across skewed datasets, such as medical imaging and software defect prediction. Traditional approaches often fail to adequately address the underrepresentation of minority classes, leading to models that exhibit high performance on majority classes but have poor performance on critical minority classes. Self-supervised contrastive learning has become an extremely encouraging method for this issue, enabling the utilization of unlabeled data to generate robust and generalizable models. This paper reviews the advancements in self-supervised contrastive learning for imbalanced classification, focusing on methodologies that enhance model performance through innovative contrastive loss functions and data augmentation strategies. By pulling similar instances closer and pushing dissimilar ones apart, these techniques help mitigate the biases inherent in imbalanced datasets. We critically analyze the effectiveness of these methods in diverse scenarios and propose future research directions aimed at refining these approaches for broader application in real-world settings. This review serves as a guide for researchers exploring the potential of contrastive learning to address class imbalances, highlighting recent successes and identifying crucial gaps that need addressing.
Ensemble of winning tickets: pruning bidirectional encoder from the transformers attention heads for enhanced model efficiency Smarts, Nyalalani; Selvaraj, Rajalakshmi; Kuthadi, Venu Madhav
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.pp2070-2080

Abstract

The advanced models of deep neural networks like bidirectional encoder from the transformers (BERT) and others, poses challenges in terms of computational resources and model size. In order to tackle these issues, techniques of model pruning have surfaced as the most useful methods in addressing the issues of model complexity. This research paper explores the concept of pruning BERT attention heads across the ensemble of winning tickets in order to enhance the efficiency of the model without sacrificing performance. Experimental evaluations show how effective the approach is, in achieving significant model compression while still maintaining competitive performance across different natural language processing tasks. The key findings of this study include model size that has been reduced by 36%, with our ensemble model reaching greater performance as compared to the baseline BERT model on both Stanford Sentiment Treebank v2 (SST-2) and Corpus of Linguistic Acceptability (CoLA) datasets. The results further show a F1-score of 94% and 96%, respectively, and accuracy scores of 95% and 96% on the two datasets. The findings of this research paper contribute to the ongoing efforts in enhancing the efficiency of large-scale language models.
Development and analysis of symmetric encryption algorithm Khompysh, Ardabek; Dyusenbayev, Dilmukhanbet; Maxmet, Muratkhan
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.pp1900-1911

Abstract

This paper introduces a new block encryption algorithm designed for the cryptographic protection of data. The paper introduces and explains a newly devised exponentiation modulo (EM) transform method, utilized to obtain the S-block, an essential element within the presented algorithm. A method of optimizing the choice of keys and increasing the efficiency of calculation was also used. It is proposed that incorporating characteristics of cryptographic primitives functioning within the Galois field into the algorithm can lead to favorable outcomes. To increase the encryption algorithm's speed, non-positional polynomial notation systems and a working base index table are used. The paper discusses the implementation of an encryption algorithm in C++ and examines the statistical characteristics of the resulting ciphertexts. For experimental testing of statistical safety, a set of statistical tests by National Institute of Standards and Technology (NIST) and D. Knuth was used. Furthermore, the resulting S-box was examined using linear, differential, and algebraic cryptanalysis techniques. In the future, this proposed S-box will be implemented in the encryption algorithm being developed for the preliminary encryption of confidential data.
Experimental study of performance and prototype of elliptical altitude detection based on global navigation satellite system Zulfikar, Dwi Aji; Nurkarya, Yoyok; Setiyadi, Johar; Kurniawan, Endro Sigit; Carudin, Carudin; Suhadi, Suhadi
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.pp1720-1734

Abstract

Global navigation satellite system (GNSS) is a multi-satellite-based navigation system, in the GNSS positioning process involves several navigation satellites such as global positioning system (GPS) which is a navigation system to bring up more observation data so that it is very useful when determining the desired parameters in a real-time data processing. In the research, an experimental study is used to determine land subsidence which is one of the vertical deformations of the earth's crust as a consequence of crustal dynamics. The result of the analysis is raw position data with the average method of detecting the height of the ellipsoid in the XYZ location area. Data collection is done by observation using the absolute method for one hour for position and fifteen days of observation for height. While the equipment used is u-blox Neo-7M, MCU TTL RS-485 module, ESP32-S Dev Kit V1 module, memory card module and real time clock (RTC). The results of the observation validation analysis are i) GPS-1 Easting 1.09 m and Northing 1.08 m, GPS-2 Easting 1.19 m and Northing 1.32 m, GPS-3 Easting 0.54 m and Northing 0.64 m while GPS-AVG GPS Easting 0.56 m and Northing of 0.64 m, ii) The results of the GPS-1 ellipsoid height analysis are 3.76 m, GPS-2 4.28 m, GPS-3 of 3.69 m, and iii) GPS AVG of 3.01 m.
Improved colored cubes teaching kit in representing and simplifying Boolean logic functions Elewah, Ibrahim; Jalaleddine, Sara; Tbeileh, Omar A.; Yainnakou, Stavros; Kamzoul, Azzam; El-Morhabi, Sara; Tabet, Maria Gergi; Hafez, Rania
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.pp1446-1454

Abstract

This work presents, explains, and discusses a colored variables cubes teaching kit. The cubes teaching kit is designed based on the cubes method that was developed to graphically simplify the Boolean logic functions with three, four, five, and six variables. This renewed method is developed to overcome the limitation of the conventional Karnaugh maps method in terms of simplifying Boolean functions with a maximum of four variables only. Students can use the teaching kit to place each cube in its right position. Based on the label of each cube, students will be able to figure out the function minterm number. After that, the students will sort the cubes to represent the function. Eventually, the students will develop the competency to check the cubes adjacency, and this will lead them to formulate simplified Boolean expressions. Students' engagement is expected to improve when theoretical knowledge is implemented using a three-dimensional physical cube teaching kit. The aim of this work is that both the educators and students, in engineering and engineering technology programs, can benefit from the adaptation and even more from the modification of the proposed approach to facilitate the achievement of their learning objectives.
Design and experimental validation of a single phase grid tied inverter for residential low power applications Mousmi, Ali; Schellmanns, Ambroise; Elghadhi, Salem; Desouches, Quentin
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.pp1372-1384

Abstract

This paper presents the design and control of a single phase grid tied inverter intended for low power applications in residential sector as part of smart grid environments or solar photovoltaic source integration. The total cost of the converters used in such applications involving low power rates, generally lower than 1 kW, cannot afford expensive components or complex techniques, so, the optimization of the power circuits as well as the simplification of the control algorithms are necessary to meet the specifications. In this purpose, this work presents the design steps of a single phase grid tied inverter including the structure choice, a synchronization algorithm based on the grid voltage zero crossing method, and the algorithm to control the injected power. Different experimental tests have been carried out and show the good performance of the converter which meets the requirements in terms of total harmonic distortion and efficiency.
A new trade-off approach to photovoltaic power smoothing Galarza, Jose; Condezo, David; Calcina, Armando; Saenz, Bartolome
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.pp1262-1273

Abstract

Renewable energy sources, such as grid-connected photovoltaic systems, present a challenge due to the intermittent nature of solar irradiance. In this research, the authors have suggested an approach for irradiance profile smoothing based on different sample sizes of measurements. The analysis has been performed using experimental measurements based on the irradiance and temperature of the series smart pyranometers (SMP3) pyranometer manufactured by Kipp & Zonen. The power smoothing uses a variable window size to compensate for a flat and intermittent profile. The moving standard deviation has been used to evaluate the window size in different ranges. The evaluation focuses on days with higher irradiance variability and the results for the suggested approach show better performance than the smoothing process with a large or small window. The suggested approach reaches an autocorrelation index of 0.988, which is more than 6% with respect to the constant window size. Furthermore, the analysis shows that more than 50% of the data have variability in the moving standard deviation within a range of 1% and 25%, as with this approach a flexible window size helps the smoothing process. An estimation of photovoltaic power between constant and variable window size has been evaluated and a difference of less than 1.5% has been obtained.
Control to compensate reactive power at medium voltage load nodes to improve performance and load voltage stabilization based on modular multilevel converter Cuong, Tran Hung; Tung, Nguyen Nhat; Anh, An Thi Hoai Thu
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.pp1463-1472

Abstract

This paper will present a reactive power control method for medium voltage power grids based on the modular multilevel converter (MMC) structure. In particular, the MMC converter applies control algorithms to operate as a D-STATCOM device. A proportional–integral (PI) controller combined with an improved nearest level modulation (NLM) method performs the system control process. The purpose is to create sinusoidal voltage levels on the alternating current (AC) side to generate or absorb reactive power according to load requirements. This will ensure that the amount of reactive power for the load node is always within the allowable value and improve voltage quality, increasing the power factor for the load. Verifying and evaluating results are performed on MATLAB/Simulink software.
Combined-adaptive image preprocessing method based on noise detection Shamshanovna, Razakhova Bibigul; Amangeldy, Nurzada; Kassymova, Akmaral; Kudubayeva, Saule; Kurmetbek, Bekbolat; Barlybayev, Alibek; Gazizova, Nazerke; Buribayeva, Aigerim
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.pp1584-1592

Abstract

The image processing method involves several critical steps, with image preprocessing being particularly significant. Segmentation and contour extraction on digital images are essential in fields ranging from image recognition to image enhancement in various recording devices, such as photo and video cameras. This research identifies and analyzes the main drawbacks of existing segmentation and contour extraction methods, focusing on object recognition. Not all filters effectively remove noise; some may clear areas of interest, affecting gesture recognition accuracy. Therefore, studying the impact of image preprocessing on gesture recognition outcomes is crucial for improving pattern recognition performance through more efficient preprocessing methods. This study seeks to find an optimal solution by detecting specific features during the preprocessing stage that directly influence gesture recognition accuracy. This research is a key component of the AP19175452 project, funded by the ministry of science and higher education. The project aims to create automated interpretation systems for Kazakh sign language, promoting inclusivity and technological innovation in communication aids. By addressing these challenges, the study contributes to the development of more robust and adaptive image preprocessing techniques for gesture recognition systems.

Page 599 of 631 | Total Record : 6301

 597   598   599   600   601 

Filter by Year

2011 2026


Reset
Filter By Issues
All Issue Vol 16, No 1: February 2026 Vol 15, No 6: December 2025 Vol 15, No 5: October 2025 Vol 15, No 4: August 2025 Vol 15, No 3: June 2025 Vol 15, No 2: April 2025 Vol 15, No 1: February 2025 Vol 14, No 6: December 2024 Vol 14, No 5: October 2024 Vol 14, No 4: August 2024 Vol 14, No 3: June 2024 Vol 14, No 2: April 2024 Vol 14, No 1: February 2024 Vol 13, No 6: December 2023 Vol 13, No 5: October 2023 Vol 13, No 4: August 2023 Vol 13, No 3: June 2023 Vol 13, No 2: April 2023 Vol 13, No 1: February 2023 Vol 12, No 6: December 2022 Vol 12, No 5: October 2022 Vol 12, No 4: August 2022 Vol 12, No 3: June 2022 Vol 12, No 2: April 2022 Vol 12, No 1: February 2022 Vol 11, No 6: December 2021 Vol 11, No 5: October 2021 Vol 11, No 4: August 2021 Vol 11, No 3: June 2021 Vol 11, No 2: April 2021 Vol 11, No 1: February 2021 Vol 10, No 6: December 2020 Vol 10, No 5: October 2020 Vol 10, No 4: August 2020 Vol 10, No 3: June 2020 Vol 10, No 2: April 2020 Vol 10, No 1: February 2020 Vol 9, No 6: December 2019 Vol 9, No 5: October 2019 Vol 9, No 4: August 2019 Vol 9, No 3: June 2019 Vol 9, No 2: April 2019 Vol 9, No 1: February 2019 Vol 8, No 6: December 2018 Vol 8, No 5: October 2018 Vol 8, No 4: August 2018 Vol 8, No 3: June 2018 Vol 8, No 2: April 2018 Vol 8, No 1: February 2018 Vol 7, No 6: December 2017 Vol 7, No 5: October 2017 Vol 7, No 4: August 2017 Vol 7, No 3: June 2017 Vol 7, No 2: April 2017 Vol 7, No 1: February 2017 Vol 6, No 6: December 2016 Vol 6, No 5: October 2016 Vol 6, No 4: August 2016 Vol 6, No 3: June 2016 Vol 6, No 2: April 2016 Vol 6, No 1: February 2016 Vol 5, No 6: December 2015 Vol 5, No 5: October 2015 Vol 5, No 4: August 2015 Vol 5, No 3: June 2015 Vol 5, No 2: April 2015 Vol 5, No 1: February 2015 Vol 4, No 6: December 2014 Vol 4, No 5: October 2014 Vol 4, No 4: August 2014 Vol 4, No 3: June 2014 Vol 4, No 2: April 2014 Vol 4, No 1: February 2014 Vol 3, No 6: December 2013 Vol 3, No 5: October 2013 Vol 3, No 4: August 2013 Vol 3, No 3: June 2013 Vol 3, No 2: April 2013 Vol 3, No 1: February 2013 Vol 2, No 6: December 2012 Vol 2, No 5: October 2012 Vol 2, No 4: August 2012 Vol 2, No 3: June 2012 Vol 2, No 2: April 2012 Vol 2, No 1: February 2012 Vol 1, No 2: December 2011 Vol 1, No 1: September 2011 More Issue