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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 6,301 Documents
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Passive magnetic coil design for electromagnetic interference evaluation of axle counters Yoppy, Yoppy; Yudhistira, Yudhistira; Nugroho, Hutomo Wahyu; Trivida, Elvina; Wahyu Wijanarko, Tyas Ari; Bakti, Aditia Nur; Mandaris, Dwi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp166-174

Abstract

Measurement of magnetic fields near the railway tracks is crucial to ensure compatibility with the operation of axle counters. According to EN 50592 standard, the magnetic field is detected with a passive magnetic coil and an oscilloscope. From previous studies, in general, there has been no in-depth analysis of how the choice of coil winding parameters could affect the coil output voltage, which then affect the measurement sensitivity, in particular the coil design based on the standard and it is applicability for electromagnetic interference (EMI) evaluation of axle counters. Therefore, this paper will explore the design of a passive magnetic coil to obtain the optimum coil output voltage within the frequency range. Simulations showed that for 10-100 kHz and 100 kHz–1.3 MHz range, the optimum number of turns happened at 60-100 and 15-60 turns, respectively. Based on that, two example coils had been built. Simulations and measurements of their frequency response were in good agreement, with a deviation less than 1.0 dB.
Performance analysis of deep unified model for facial expression recognition using convolution neural network Kavita, Kavita; Chhillar, Rajender Singh
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4046-4054

Abstract

Facial expression recognition has gathered substantial attention in computer vision applications, with the need for robust and accurate models that can decipher human emotions from facial images. Performance analysis of a novel hybrid model combines the strengths of residual network (ResNet) and dense network (DenseNet) architectures after applying preprocessing for facial expression recognition. The proposed hybrid model capitalizes on the complementary characteristics of ResNet's and DenseNet's densely connected blocks to enhance the model's capacity to extract discriminative features from facial images. This research evaluates the hybrid model performance and conducts a comprehensive benchmark against established facial expression recognition convolution neural network (CNN) models. The analysis encompasses key aspects of model performance, including classification accuracy, and adaptability with the LFW dataset for facial expressions such as Anger, Fear, Happy, Disgust, Sad, Surprise, along Neutral. The research observes that the proposed hybrid model is more accurate and efficient computationally than existing models consistently. This performance analysis eliminates information on the hybrid model's perspective to further facial expression recognition research.
MSAPersonality: a modern standard Arabic dataset for personality recognition Chraibi, Khaoula; Chaker, Ilham; Dhassi, Younes; Zahi, Azeddine
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4498-4507

Abstract

Automatic personality recognition is a task that attempts to automatically infer personality traits from a variety of data sources, including Text. Our words, whether spoken or written, reveal a lot about who we are. As people speak different languages, each with its own set of characteristics and level of complexity, identifying their personalities automatically might be language-dependent. This task requires an annotated text corpus with personality traits. However, the lack of corpora for languages other than English makes the task extremely challenging. We concentrated our efforts in this paper on the Arabic language in particular because it is understudied and lacks a corpus, despite being one of the most widely spoken languages in the world. Our primary goal was constructing our “MSAPersonality” dataset, which consists of 267 texts in modern standard Arabic that have been annotated with the Big Five personality traits. To evaluate the dataset and its potential for classification and regression, we used text preprocessing techniques, feature extraction, and machine learning algorithms. We obtained promising experimental results. Therefore, further research into predicting personality from Arabic text can be conducted.
Collusion-resistant multiparty data sharing in social networks Shetty, Nisha P.; Muniyal, Balachandra; Proothi, Nandini; Gopal, Bhavya
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1996-2013

Abstract

The number of users on online social networks (OSNs) has grown tremendously over the past few years, with sites like Facebook amassing over a billion users. With the popularity of OSNs, the increase in privacy risk from the large volume of sensitive and private data is inevitable. While there are many features for access control for an individual user, most OSNs still need concrete mechanisms to preserve the privacy of data shared between multiple users. The proposed method uses metrics such as identity leakage (IL) and strength of interaction (SoI) to fine-tune the scenarios that use privacy risk and sharing loss to identify and resolve conflicts. In addition to conflict resolution, bot detection is also done to mitigate collusion attacks. The final decision to share the data item is then ascertained based on whether it passes the threshold condition for the above metrics.
Traffic signs detection and prohibitor signs recognition in Morocco road scene Taouqi, Imane; Klilou, Abdessamad; Chaji, Kebir; Arsalane, Assia
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6313-6321

Abstract

Traffic sign detection is a crucial aspect of advanced driver assistance systems (ADAS) for academic research and the automotive industry. seeing that accurate and timely detection of traffic signs (TS) is essential for ensuring the safety of driving. However, TS detection methods encounter challenges like slow detection speed and a lack of robustness in complex environments. This paper suggests addressing these limitations by proposing the use of the you only look one version 7 (YOLOv7) network to detect and recognize TS in road scenes. Furthermore, the k-means++ algorithm is used to acquire anchor boxes. Additionally, a tiny version of YOLOv7 is used to take advantage of its real-time and low model size, which are required for real-time hardware implementation. So, we conducted an experiment using our proprietary Morocco dataset. According to the experimental results, YOLOv7 achieves 85% in terms of mean average precision (mAP) at 0.5 for all classes. And YOLOv7-tiny obtains 90% in the same term. Afterward, a recognition system for the prohibitive class using the convolutional neural network (CNN) is trained and integrated inside the YOLOv7 algorithm; its model achieves an accuracy of 99%, which leads to a good specification of the prohibitive sign meaning.
Ambient intelligent framework for modelling critical medical events based on context awareness Subramanyam, Manjunath; Parthasarathy, Srirangapatna Sampathkumararan
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3106-3115

Abstract

With the rapid pace of communication technology, the modern communication system still encounters challenges in meeting the dynamic requirements of users. Facilitating emergency services for patients without a caretaker side by is quite challenging. This work contributes a solution towards state-of-the-art research problems by introducing a novel architecture using collaboration, coordination and user activity detection using contextual information. A prototype is built and experiment is carried out to emphasize the importance of real-time activity-based context awareness in ambient intelligence (AmI) applications. The primary contributions of this work are introduction of novel architecture and usage of both static and dynamic activity-based contextual parameters. The secondary contribution of this model is to integrate ambient intelligence with context awareness to offer higher accuracy in determining the critical condition of a patient. Initially, analytical models are built using the context-based attributes that consider both clinical and non-clinical entities based on the minimal and essential vital information of patient. This paper further discusses the experimental model, which is highly cost-efficient both from an operational and usage viewpoint. Different assessment environments have been used for assessing the performance of the model.
Enhancing the accuracy of low-cost thermocouple devices through deep-wavelet neural network calibration Julian, James; Wahyuni, Fitri; Dewantara, Annastya Bagas; Winarta, Adi; Putra, Nandy
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2625-2633

Abstract

Data collection using thermocouple sensors in low-cost data acquisition is prone to noise interference, which could reduce the data quality. Noise sources such as cold junction compensators, electromagnetic interference, and Johnson noise can significantly affect the reliability and accuracy of conventional measurements. This study aims to improve the quality of thermocouple sensor readings on low-cost data acquisition using calibration method based on deep learning and the denoising process using a wavelet transform. This taken approach successfully increase the accuracy value of 97.67% with a mean absolute error (MAE) of 0.2. The precision also increases of 262.7% as indicated by the result of signal-to-noise ratio (SNR) with a value of 105.29 dB. Comparative analysis was carried out against National Instruments® device and it was found that deep-wavelet method had a lower and higher of MAE and SNRdB values of 16.67% and 0.8% respectively. This study shows that the denoising-calibration method with deep-wavelet can improve the accuracy and reliability of data from low-cost thermocouple devices.
Design and analysis of a Sub-6 GHz antenna array with high gain for 5G mobile phone applications Bellekhiri, Abderrahim; Chahboun, Noha; Zbitou, Jamal; Oukaira, Aziz; Laaziz, Yassin
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6401-6410

Abstract

In this paper, we designed, analyzed, and simulated a 32-element antenna array for the sub-6 GHz band. Each radiating element is a square patch on a Rogers RT5880 substrate, featuring a relative dielectric permittivity of 2.2, a low-loss tangent of 0.0009, and a thickness of 0.508 mm, measuring 28.1×28.1 mm². Simulations were conducted using two electromagnetic solvers, advanced design system (ADS) and CST Microwave Studio, providing a comprehensive comparison of the results. To achieve a high balance between performance and antenna size, two 4×8 array antenna structures were designed. The simulations demonstrated excellent input impedance matching around 3.5 GHz for both configurations, with high gains of 20.5 dBi for the first and 18 dBi for the second configuration, along with directional radiation patterns. The dimensions were 315×576×0.578 mm³ for the first configuration and 170×961×0.578 mm³ for the second. These performance metrics make the proposed antenna arrays highly suitable for wireless communication technologies operating below 6 GHz, particularly for 5G mobile communications.
Performance analysis of a three-stage quadrature RC generator with operational amplifiers Karapenev, Boyan; Sadinov, Stanimir
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp175-183

Abstract

This paper presents the special features of RC harmonic oscillation generators and their widespread use and in particular the quadrature generators which provide two output signals dephased at 90º or 270º. Quadrature generators can be classified as those with an aperiodic frequency-determining circuit or with a phase inverter group which are used to generate oscillations of one or more fixed frequencies. Studies of a three-stage quadrature RC generator circuit with operational amplifiers have been performed. The results obtained from the simulation and experimental studies performed are presented for the selected circuit. It can be assumed that the experimental and simulation results completely coincide to an accuracy of up to 20% for the amplitude of the generated signals and to the total accuracy for the generated frequency. Quadrature generators are very widely used in communication technology and, most importantly, in the structure of digital frequency, phase and quadrature-amplitude modulators and demodulators, in vector RLC meters and many other electronic circuits and devices in practice.
Dual soft decoding of linear block codes using memetic algorithm Sliman, Rajaa; Azouaoui, Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5263-5273

Abstract

In this article we will approach the soft-decision decoding for the linear block codes, is a kind of decoding algorithms used to decode data to form better original estimated received message, it is considered as a NP-hard problem. In this article we present a new decoder using memetic algorithm such metaheuristic technic operates on the dual code rather than the code itself that aims to find the error caused when sending a codeword calculated from a message of k bits of information, the resulting codeword contains n bits, including the redundancy bits, the efficiency of an error-correcting code is equivalent to the ratio k/n, the rate is belong the interval [0,1]. Hence a good code is the one that ensures a certain error correcting capability at minimum ratio. The results proved that this approach using a combination of genetic algorithm and local search algorithm provides a sufficiently good solution to an optimization problem; the new decoder is applied on linear codes where the structure is given by a parity check matrix.

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