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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 2: April 2023" : 111 Documents clear
Effects of different geometric patterns on free form gridshell structures Marjan Goodarzi; Mahshad Azimi; Ali Mohades; Majid Forghani-elahabad
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1698-1707

Abstract

Gridshells are commonly known as structures with the shape and rigidity of a double curvature shell consisting of a grid, not a continuous surface. In recent decades, these structures have attracted significant attention. The impact of various geometric patterns on free form gridshell structures is investigated here to demonstrate the necessity of collaboration between structural and architectural characteristics in enhancing structure efficiency. To that goal, a framework is proposed where three shells are first designed, and then six geometric patterns are formed on them. The main factors for evaluation of gridshells are decreasing the steel weight as an economic index and decreasing the displacement as a structural index, also, finite element method is used for structurally analyzing the gridshells, and the generated gridshells are compared to each other based on the mentioned indices. For the optimization process, an approach is suggested to find the most optimum gridshell, then numerical results show the efficiency of the proposed alternative approach.
Crane monitoring system based on internet of things using long range Ng Wen Jun; Norlezah Hashim; Fakrulradzi Idris; Ida Syafiza; Nurbahirah Noordin
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2223-2232

Abstract

The four main causes of crane accidents are overturned, falls, mechanical failure, and contact with power lines. It is important to keep track of the crane’s health and condition as it is always too late when a failure of the crane was found. Any abrupt accidents will interrupt or delay the work progress and cause the operational costs to increase. Crane monitoring system is developed using long range (LoRa) technology due to its long range of detections making it suitable for monitoring machines that require large space including the dock area. It also consumes low power and is suitable for battery-operated systems. This paper discusses the design and development crane monitoring system using Arduino Uno together with NodeMCU ESP8266 as the hardware for this project. Temperature, power consumption, lifting activities, and total operating hours will be measured using appropriate sensors. The data will then be sent to the database where users can monitor each crane from a developed Android application using a mobile phone. This project allows users to view, monitor, and analyze real-time or past data in a graph or table view. Experimental results prove the proposed system is applicable and effective.
Bone age assessment based on deep learning architecture Alaa Jamal Jabbar; Ashwan A. Abdulmunem
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2078-2085

Abstract

The fast advancement of technology has prompted the creation of automated systems in a variety of sectors, including medicine. One application is an automated bone age evaluation from left-hand X-ray pictures, which assists radiologists and pediatricians in making decisions about the growth status of youngsters. However, one of the most difficult aspects of establishing an automated system is selecting the best approach for producing effective and dependable predictions, especially when working with large amounts of data. As part of this work, we investigate the use of the convolutional neural networks (CNNs) model to classify the age of the bone. The work’s dataset is based on the radiological society of North America (RSNA) dataset. To address this issue, we developed and tested deep learning architecture for autonomous bone assessment, we design a new deep convolution network (DCNN) model. The assessment measures that use in this work are accuracy, recall, precision, and F-score. The proposed model achieves 97% test accuracy for bone age classification.
Self-admitted technical debt classification using natural language processing word embeddings Ahmed F. Sabbah; Abualsoud A. Hanani
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2142-2155

Abstract

Recent studies show that it is possible to detect technical dept automatically from source code comments intentionally created by developers, a phenomenon known as self-admitted technical debt. This study proposes a system by which a comment or commit is classified as one of five dept types, namely, requirement, design, defect, test, and documentation. In addition to the traditional term frequency-inverse document frequency (TF-IDF), several word embeddings methods produced by different pre-trained language models were used for feature extraction, such as Word2Vec, GolVe, bidirectional encoder representations from transformers (BERT), and FastText. The generated features were used to train a set of classifiers including naive Bayes (NB), random forest (RF), support vector machines (SVM), and two configurations of convolutional neural network (CNN). Two datasets were used to train and test the proposed systems. Our collected dataset (A-dataset) includes a total of 1,513 comments and commits manually labeled. Additionally, a dataset, consisting of 4,071 labeled comments, used in previous studies (M-dataset) was also used in this study. The RF classifier achieved an accuracy of 0.822 with A-dataset and 0.820 with the M-dataset. CNN with A-dataset achieved an accuracy of 0.838 using BERT features. With M-dataset, the CNN achieves an accuracy of 0.809 and 0.812 with BERT and Word2Vec, respectively.
Maximum power point tracking controller using Lyapunov theorem of wind turbine under varying wind conditions Maamar Yahiaoui; Benameur Afif; Brahim Brahmi; Mohamed Horch; Mohamed Serraoui
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1281-1290

Abstract

Due to the instantaneous variation in wind speed, it is necessary to identify the optimal rotational speed that ensures maximum energy efficiency and system stability. We proposed a controller based on the Lyapunov theorem to extract the maximum power from wind speed and to ensure the overall stability of the controlled system under random operating conditions imposed by wind speed and parameter variations. The control of the Tip speed ratio is based on the Lyapunov theorem (TSR_LT), which is a controller based on Lyapunov's theory and the definition of a positive, energetic function, to ensure the stability of the system being controlled, the dynamics of this function must be negative. The viability of this work is demonstrated by MATLAB-based mathematical and simulation models and a comparison with the results obtained using proportional integral (PI) controller-based tip speed ratio control (TSR_PI controller). The simulation results demonstrate the controller's effectiveness.
Design and simulation of Arduino Nano controlled DC-DC converters for low and medium power applications Sivasankar Nallusamy; Devabalaji Kaliaperumal Rukmani
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1400-1409

Abstract

This paper mainly focuses on the controller of portable direct current to direct current (DC-DC) converter which may be simple, low cost and efficient. Nowadays, proportional integral (PI) controller and opto-isolator based circuits are used for switching control. The switching control through the controller makes the DC-DC converter into larger circuit and less efficient. This problem will be rectified using the Arduino Nano controller which is small and low cost-effective controller. It is useful for low and medium power applications like residential solar power system, electronic gadgets, and academic laboratories. Arduino Nano-based DC chopper has been developed, and the Proteus software used for simulation. The different topologies of DC choppers like buck, boost, and buck-boost converter have been designed with mathematical calculations and simulated.
Person identification based on facial biometrics in different lighting conditions Marem H. Abdulabas; Noor D. Al-Shakarchy
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2086-2092

Abstract

Technological development is an inherent feature of this time, that reliance on electronic applications in all daily transactions (business management, banking, financial transfers, health, and other important aspects of life). Identifying and confirming identity is one of the complex challenges. Therefore, relying on biological properties gives reliable results. People can be identified in pictures, films, or real-time using facial recognition technology. A face individual is a unique identifying biological characteristic to authenticate them and prevents permits another person to assume that individual’s identity without their knowledge or consent. This article proposes the identification model by facial individual characteristics, based on the deep neural network (DNN). The proposed method extracts the spatial information available in an image, analysis this information to extract the salient features, and makes the identifying decision based on these features. This model presents successful and promising results, the accuracy achieves by the proposed system reaches 99.5% (+/- 0.16%) and the values of the loss function reach 0.0308 over the Pins Face Recognition dataset to identify 105 subjects.
Ship routing optimization using bacterial foraging optimization algorithm for safety and efficient navigation Phan Van Hung; Dang Quang Viet; Nguyen Minh Duc; Thanh Dat Le
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2309-2315

Abstract

Efficient operation plays a vital role to develop a sustainable shipping fleet with cost competitive. The requirements for economic efficiency, energy efficiency, reducing emissions, and increasing safety and security lead to an innovative model in the optimal weather routing system. The vessel routing is influenced by the quality of meteorological and oceanographic data such as wind, waves, and currents. In this study, the model optimization of weather routing considers the meteorological and oceanographic information, ship's characteristics combined with an adaptive bacterial foraging optimization algorithm (BFOA) will be introduced and applied to the ship’ navigation at sea. The simulation results will be evaluated the effectiveness and reliability of the model. This model will support ships’ navigation to be safer and more comfortable, operate more efficiently and reduce emissions.
Energy-efficient non-orthogonal multiple access for wireless communication system Muhamad Firdaus Darus; Fakrulradzi Idris; Norlezah Hashim
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1654-1668

Abstract

Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed.
Efficiency of two decoders based on hash techniques and syndrome calculation over a Rayleigh channel Seddiq El Kasmi Alaoui; Zouhair Chiba; Hamza Faham; Mohammed El Assad; Said Nouh
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1880-1890

Abstract

The explosive growth of connected devices demands high quality and reliability in data transmission and storage. Error correction codes (ECCs) contribute to this in ways that are not very apparent to the end user, yet indispensable and effective at the most basic level of transmission. This paper presents an investigation of the performance and analysis of two decoders that are based on hash techniques and syndrome calculation over a Rayleigh channel. These decoders under study consist of two main features: a reduced complexity compared to other competitors and good error correction performance over an additive white gaussian noise (AWGN) channel. When applied to decode some linear block codes such as Bose, Ray-Chaudhuri, and Hocquenghem (BCH) and quadratic residue (QR) codes over a Rayleigh channel, the experiment and comparison results of these decoders have shown their efficiency in terms of guaranteed performance measured in bit error rate (BER). For example, the coding gain obtained by syndrome decoding and hash techniques (SDHT) when it is applied to decode BCH (31, 11, 11) equals 34.5 dB, i.e., a reduction rate of 75% compared to the case where the exchange is carried out without coding and decoding process.

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