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
 475   476   477   478   479 
Indexed-channel estimation under frequency and time-selective fading channels in high-mobility systems Ali Alqatawneh; Luae Al-Tarawneh; Ziyad Almajali
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.pp2865-2875

Abstract

Index modulation (IM) techniques have been employed in different communication systems to improve bandwidth efficiency by carrying additional information bits. In high-mobility communication systems and under both time-selective and frequency-selective fading channels with Doppler spread, channel variations can be tracked by employing pilot-aided channel estimation with minimum mean-squared error estimation. However, inserting pilot symbols among information symbols reduces the system's spectral efficiency in pilot-aided channel estimation schemes. We propose pilot-aided channel estimation with zero-pilot symbols and an energy detection scheme to tackle this issue. Part of the information bit-stream is conveyed by the indices of zero-pilot symbols leading to an increase in the system's spectral efficiency. We used an energy detector at the receiver to detect the transmitted zero-pilot symbols. This paper examines the impacts of diversity order on the zero-pilot symbol detection error probability and the mean-squared of error estimation. The impacts of pilot symbols number and the zero-pilot symbol number on the mean-squared error of the minimum mean-squared error (MMSE) estimator and the system error performance are also investigated in this paper.
Multimodal video abstraction into a static document using deep learning Muna Ghazi Abdulsahib; Matheel E. Abdulmunim
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.pp2752-2760

Abstract

Abstraction is a strategy that gives the essential points of a document in a short period of time. The video abstraction approach proposed in this research is based on multi-modal video data, which comprises both audio and visual data. Segmenting the input video into scenes and obtaining a textual and visual summary for each scene are the major video abstraction procedures to summarize the video events into a static document. To recognize the shot and scene boundary from a video sequence, a hybrid features method was employed, which improves detection shot performance by selecting strong and flexible features. The most informative keyframes from each scene are then incorporated into the visual summary. A hybrid deep learning model was used for abstractive text summarization. The BBC archive provided the testing videos, which comprised BBC Learning English and BBC News. In addition, a news summary dataset was used to train a deep model. The performance of the proposed approaches was assessed using metrics like Rouge for textual summary, which achieved a 40.49% accuracy rate. While precision, recall, and F-score used for visual summary have achieved (94.9%) accuracy, which performed better than the other methods, according to the findings of the experiments.
An optimized deep learning model for optical character recognition applications Sinan Q. Salih; Ahmed L. Khalaf; Nuha Sami Mohsin; Saadya Fahad Jabbar
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.pp3010-3018

Abstract

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recognition applications; the proposed method was evaluated for performance in terms of computational accuracy, convergence analysis, and cost.
Modelling and simulation for energy management of a hybrid microgrid with droop controller Khalil Saadaoui; Kaoutar Senhaji Rhazi; Youssef Mejdoub; Abderraouf Aboudou
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.pp2440-2448

Abstract

The most efficient and connected alternative for increasing the use of local renewable energy sources is a hybrid microgrid, these systems face additional challenges due to the integration of power electronics, energy storage technologies and traditional power plants. The hybrid alternating current-direct current (AC-DC) microgrid that is the subject of this research uses a primary-droop control system to regulate state variables and auxiliary services, thus, it is composed of batteries, solar panels and a miniature wind turbine (PDC) and controls how each energy source in a microgrid contributes to the final product. To achieve the given objectives, this paper will create appropriate models for each part of the microgrid design and define, among them, the energy storage batteries and power electronic converters required for each level of each of these systems. Finally, the dynamic nature of the system will be critically evaluated and characterized, to distribute the load and reduce imbalances, modify the primary drop of the resulting microgrid using MATLAB simulation.
African vulture optimizer algorithm based vector control induction motor drive system Reham H. Mohammed; Ahmed M. Ismaiel; Basem E. Elnaghi; Mohamed E. Dessouki
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.pp2396-2408

Abstract

This study describes a new optimization approach for three-phase induction motor speed drive to minimize the integral square error for speed controller and improve the dynamic speed performance. The new proposed algorithm, African vulture optimizer algorithm (AVOA) optimizes internal controller parameters of a fuzzy like proportional differential (PD) speed controller. The AVOA is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. This study compares fuzzy-like PD speed controllers optimized with AVOA to adaptive fuzzy logic speed regulators, fuzzy-like PD optimized with genetic algorithm (GA), and proportional integral (PI) speed regulators optimized with AVOA to provide speed control for an induction motor drive system. The drive system is simulated using MATLAB/Simulink and laboratory prototype is implemented using DSP-DS1104 board. The results demonstrate that the suggested fuzzy-like PD speed controller optimized with AVOA, with a speed steady state error performance of 0.5% compared to the adaptive fuzzy logic speed regulator’s 0.7%, is the optimum alternative for speed controller. The results clarify the effectiveness of the controllers based on fuzzy like PD speed controller optimized with AVOA for each performance index as it provides lower overshoot, lowers rising time, and high dynamic response.
Decentralized proportional-integral controller based on dynamic decoupling technique using Beckhoff TwinCAT-3.1 Nomzamo Tshemese-Mvandaba; Mkhululi Elvis Siyanda Mnguni
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.pp2721-2733

Abstract

An improved technique for the design of decentralized dynamic decoupled proportional-integral (PI) controllers to control many variables of column flotation was developed and implemented in this paper. This work was motivated by challenges when working with multiple inputs and multiple outputs (MIMO) systems that are not controllable by conventional linear feedback controllers. Conventional feedback control design consists of various drawbacks when it comes to complex industrial processes. The introduction of decentralization, decoupling, and many advanced controls design methods overcomes these drawbacks. Hence, the design and implementation of control systems that mitigate stability for MIMO systems are important. The developed closed-loop model of the flotation process is implemented in a real-time platform using TwinCAT 3.1 automation software and CX5020 Beckhoff programmable logic controllers (PLC) through the model transformation technique. The reasons for using the CX5020 as an implementation environment were motivated by the reliability, and is built according to new industry standards, allowing transformation, which makes it more advantageous to be used more than any other PLCs. This is done to validate the effectiveness of the recommended technique and prove its usability for any multivariable system. Comparable numerical results are presented, and they imply that industrial usage of this method is highly recommended.
Parkinson’s diagnosis hybrid system based on deep learning classification with imbalanced dataset Asmae Ouhmida; Abdelhadi Raihani; Bouchaib Cherradi; Sara Sandabad
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.pp3204-3216

Abstract

Brain degeneration involves several neurological troubles such as Parkinson’s disease (PD). Since this neurodegenerative disorder has no known cure, early detection has a paramount role in improving the patient’s life. Research has shown that voice disorder is one of the first symptoms detected. The application of deep learning techniques to data extracted from voice allows the production of a diagnostic support system for the Parkinson’s disease detection. In this work, we adopted the synthetic minority oversampling technique (SMOTE) technique to solve the imbalanced class problems. We performed feature selection, relying on the Chi-square feature technique to choose the most significant attributes. We opted for three deep learning classifiers, which are long-short term memory (LSTM), bidirectional LSTM (Bi-LSTM), and deep-LSTM (D-LSTM). After tuning the parameters by selecting different options, the experiment results show that the D-LSTM technique outperformed the LSTM and Bi-LSTM ones. It yielded the best score for both the imbalanced original dataset and for the balanced dataset with accuracy scores of 94.87% and 97.44%, respectively.
Medical image encryption techniques: a technical survey and potential challenges Ammar Odeh; Qasem Abu Al-Haija
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.pp3170-3177

Abstract

Among the most sensitive and important data in telemedicine systems are medical images. It is necessary to use a robust encryption method that is resistant to cryptographic assaults while transferring medical images over the internet. Confidentiality is the most crucial of the three security goals for protecting information systems, along with availability, integrity, and compliance. Encryption and watermarking of medical images address problems with confidentiality and integrity in telemedicine applications. The need to prioritize security issues in telemedicine applications makes the choice of a trustworthy and efficient strategy or framework all the more crucial. The paper examines various security issues and cutting-edge methods to secure medical images for use with telemedicine systems.
Priority based energy efficient hybrid cluster routing protocol for underwater wireless sensor network Tejaswini R Murgod; S. Meenakshi Sundaram; Sowmya Manchaiah; Santhosh Kumar
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.pp3161-3169

Abstract

A little change in the environment that goes unnoticed in an underwater communication network might lead to calamity. A little alteration in the environment must also be adequately analyzed in order to deal with a potential crisis. A priority-based routing protocol is required to ensure that the vital data perceived by the sensor about the environment changes. The priority-based routing system guarantees that vital data packets are delivered at a quicker pace to the destination or base station for further processing. In this work, we present a priority-based routing protocol based on the energy efficient hybrid cluster routing protocol (EEHRCP) algorithm. The suggested approach keeps two distinct queues for lower and higher priority data packets. In order to ensure that these packets get at their destination without any information loss and at a quicker rate, all of the crucial sensed data is passed through a higher priority queue. Test findings show that the suggested technique increases throughput, delivery percentage, and reduces latency for the crucial data packets.
Automatic food bio-hazard detection system Robinson Jimenez Moreno; Javier Eduardo Martinez Baquero
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.pp2652-2659

Abstract

This paper presents the design of a convolutional neural network architecture oriented to the detection of food waste, to generate a low, medium, or critical-level alarm. An architecture based on four convolution layers is used, for which a database of 100 samples is prepared. The database is used with the different hyperparameters that make up the final architecture, after the training process. By means of confusion matrix analysis, a 100% performance of the network is obtained, which delivers its output to a fuzzy system that, depending on the duration of the detection time, generates the different alarm levels associated with the risk.

Page 477 of 631 | Total Record : 6301

 475   476   477   478   479 

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