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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 14, No 6: December 2024" : 111 Documents clear
Integration of renewable energy into San Andres Island electrical grid Archbold, Keyla Newball; Zambrano, Alvaro; Rosero Garcia, Javier
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.pp6160-6169

Abstract

Renewable energy (RE) sources integration in electrical grids is changing the dynamics of planning and operation. Overvoltage, overcurrent, and malfunction of protection schemes are some effects if it is limits are not controlled. This article presents a methodology based on the hosting capacity (HC) concept to estimate performance indexes by considering stochastic methods and systematic simulation taking as study case the grid of San Andres Island. RE is of special interest in islands where diesel generators produce energy with a high footprint and security of supply is low as there is a high dependence on fossil fuels and their transport regime. The simulations are carried out in DigSilent PowerFactory integrated with Python to automate the iterations over different penetration levels. The most limiting factor found is transformer rating. Voltage rise is a factor to be monitored at the end of the circuits. Emissions are reduced with the introduction of renewable energies, but variability needs to be controlled as it could require fast start-up of generators; this modifies monitoring and control schemes to maintain stability. The limit found is higher than the established regulation for non-interconnected zones (NIZ) in Colombia, showing the capability of the grid to integrate RE.
Optimal allocation of wind and solar power based distributed generation: case study Dodamani, Sateesh N.; Magadum, Rudresh B.
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.pp6086-6093

Abstract

The main goal of the power system is to congregate the power demand within the power grid while maintaining economical operation, system security and minimal environmental impact. Due to the increasing demand for electrical energy, many problems have arisen with the power systems. These problems include excessive load, uneven system performance, unsatisfactory voltage profile, and an increase in network power losses. To address these issues, more generation sources and improved transmission capacity are required. In order to meet increasing electricity demand, it is more efficient to integrate a sufficient number of smaller generation units. Utilities and consumers can get the significant benefit from installation of distributed generation (DG), which reduces power losses, progress voltage profile, increases power quality and reliability, delays system updates, supports local reactive power, standby generation and peak limiting. This article aims to enrich the performance of the entire network through the best possible placement and penetration of wind energy and solar photovoltaic (PV) dispersed generation.
Deep learning-based attention models for sarcasm detection in text Chandrasekaran, Ganesh; Chowdary, Mandalapu Kalpana; Babu, Jyothi Chinna; Kiran, Ajmeera; Kumar, Kotthuru Anil; Kadry, Seifedine
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.pp6786-6796

Abstract

Finding sarcastic statements has recently drawn a lot of curiosity in social media, mainly because sarcastic tweets may include favorable phrases that fill in unattractive or undesirable attributes. As the internet becomes increasingly ingrained in our daily lives, many multimedia information is being produced online. Much of the information recorded mostly on the internet is textual data. It is crucial to comprehend people's sentiments. However, sarcastic content will hinder the effectiveness of sentiment analysis systems. Correctly identifying sarcasm and correctly predicting people's motives are extremely important. Sarcasm is particularly hard to recognize, both by humans and by machines. We employ the deep bi-directional long-short memory (Bi-LSTM) and a hybrid architecture of the convolution neural network+Bi-LSTM (CNN+Bi-LSTM) with attention networks for identifying sarcastic remarks in a corpus. Using the SarcasmV2 dataset, we test the efficacy of deep learning methods BiLSTM, and CNN+BiLSTM with attention network) for the task of identifying text sarcasm. The suggested approach incorporating deep networks is consistent with various recent and advanced techniques for sarcasm detection. With attention processes, the improved CNN+Bi-LSTM model achieved an accuracy rate of 91.76%, which is a notable increase over earlier research.
Dipterocarpaceae trunk texture classification using two-stage convolutional neural network-based transfer learning model Wati, Masna; Puspitasari, Novianti; Hairah, Ummul; Widians, Joan Angelina; Tjikoa, Ade Fiqri
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.pp6874-6882

Abstract

The importance of plant identification has been recognized by academia and industry. There have been several attempts to utilize leaves and flowers for identification. However, the trunk can also be helpful, especially for tall trees. In Borneo, the Dipterocarpaceae family are the main constituents of the tropical rainforest ecosystem. This research focuses on the classification of the dipterocarp family, which can reach a height of between 70 and 85 m. Leveraging convolutional neural network (CNN) models, this research proposes a two-stage transfer learning strategy. In the first stage, the pre-trained CNN models are refined by only modifying the classification layer while keeping the feature layer frozen. The second stage involves selecting and freezing several convolutional layers to adapt the model to classify dipterocarp stems. The dataset consists of 857 images of different dipterocarp species. Experiments show that the VGG16 model with a two-stage transfer learning strategy achieves a high accuracy of 98.246%. This study aims to accurately identify species, benefiting conservation and ecological studies by enabling fast and reliable tree species classification based on stem texture images.
Aspect-based sentiment analysis: natural language understanding for implicit review Suhariyanto, Suhariyanto; Sarno, Riyanarto; Fatichah, Chastine; Abdullah, Rachmad
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.pp6711-6722

Abstract

The different types of implicit reviews should be well understood so that the developed extraction technique can solve all problems in implicit reviews and produce precise terms of aspects and opinions. We propose an aspect-based sentiment analysis (ABSA) method with natural language understanding for implicit reviews based on sentence and word structure. We built a text extraction method using a machine learning algorithm rule with a deep understanding of different types of sentences and words. Furthermore, the aspect category of each review is determined by measuring the word similarity between the aspect terms contained in each review and aspect keywords extracted from Wikipedia. Bidirectional encoder representations from transformers (BERT) embedding and semantic similarity are used to measure the word similarity value. Moreover, the proposed ABSA method uses BERT, a hybrid lexicon, and manual weighting of opinion terms. The purpose of the hybrid lexicon and the manual weighting of opinion terms is to update the existing lexicon and solve the problem of weighting words and phrases of opinion terms. The evaluation results were very good, with average F1-scores of 93.84% for aspect categorization and 92.42% for ABSA.
Aspect-based sentiment-analysis using topic modelling and machine-learning Dhanal, Radhika Jinendra; Ghorpade, Vijay Ram
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.pp6689-6698

Abstract

This study addresses the critical need for an accurate aspect-based sentiment-analysis (ABSA) model to understand sentiments effectively. The existing ABSA models often face challenges in accurately extracting aspects and determining sentiment polarity from textual data. Therefore, we propose a novel approach leveraging latent-Dirichlet-allocation (LDA) for aspect extraction and transformer-based bidirectional-encoder-representations from transformers (TF-BERT) for sentiment-polarity evaluation. The experiments were carried out on SemEval 2014 laptop and restaurant datasets. Also, a multi-domain dataset was generated by combining SemEval 2014, Amazon, and hospital reviews. The results demonstrate the superiority of the LDA-TF-BERT model, achieving 82.19% accuracy and 79.52% Macro-F1 score for the laptop task and 86.26% accuracy of 87.26% and 81.27% for Macro-F1 score for the restaurant task. This showcases the model's robustness and effectiveness in accurately analyzing textual data and extracting meaningful insights. The novelty of our work lies in combining LDA and TF-BERT, providing a comprehensive and accurate ABSA solution for various industries, thereby contributing significantly to the advancement of sentiment analysis techniques.
Performance enhancement of high-speed free space optical transmission link for the implementation of 5G and internet of things Ai, Duong Huu; Nguyen, Van Loi; Luong, Khanh Ty; Le, Viet Truong
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.pp6373-6379

Abstract

Internet of things (IoT) with continuous development allows multiple devices to be connected to each other through the external environment. With that, free space optical (FSO) transmission links provide high data transmission rates, so that enhanced quality of services, that is very suitable for deployment for fifth generation (5G) and IoT. FSO is known as license free, cost effective and line-of-sight green communication technology, which is employed in various circumstances, such as high data rate connections between buildings within campus or city. This study performs enhancement of FSO link for reconfigurable intelligent surfaces (RISs) aided over free space with gamma-gamma distribution channels. The paper analyzes the performance of FSO links affected by misalignment fading, RISs aided, and link distance with the subcarrier quadrature amplitude modulation scheme. Several numerical outcomes obtained for average electrical end-to-end signal-to-noise ratio, misalignment fading displacement standard deviation and link distance are shown to illustrate the average channel capacity of systems.
Performance analysis of cascade spline adaptive filtering based on normalized orthogonal gradient adaptive algorithm Wiangtong, Theerayod; Sitjongsataporn, Suchada
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.pp6351-6359

Abstract

In this paper, the cascade architecture of spline adaptive filtering (CSAF) for nonlinear systems is presented with the normalized version of orthogonal gradient adaptive (NOGA) algorithm. Spline adaptive filtering comprises a sandwich of the first linear adaptive filtering (LAF) and nonlinear adaptive look-up table. In this cascading architecture, SAF is connected to the second LAF. NOGA is considered as the fast convergence applied by stochastic gradient-based approach. Convergence properties of the proposed NOGA-CSAF algorithm in terms of instantaneous errors can be derived by using Taylor series expansion. Experimental results demonstrate the effectiveness of proposed NOGA-CSAF algorithm using the mean square error scheme. It clearly outperforms the traditional least mean square algorithm on CSAF model in the nonlinear identification system.
Design of decryption process for advanced encryption standard algorithm in system-on-chip Prathap, Joseph Anthony; Raj, Mrinal; Patnaik, Ritu
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.pp6838-6845

Abstract

This paper concentrates on the development of system-on-chip for the decryption algorithm in the advanced encryption standard (AES). This method includes the transformation of cipher text into plain text and consists of 4 sub-tasks based on the resolution. In this work, the 128-bit resolution is utilized to perform 10 rounds of transformation with the round key added at every round generated by the key expansion algorithm. Though there are many cryptography algorithms, the AES is simple, secure, faster in operation, and easy to develop compared to the others. The system-on-chip (SOC) design for the decryption of the AES depends on the synthesizable hardware description language (HDL) code development for all 10 rounds of processes with the key expansion algorithm. The lookup tables (LUTs) are used for the inverse S-box in the HDL code. The proposed SOC is designed using the Cadence electronic design automation (EDA) tools by making use of the synthesized HDL code for the proposed methods and analyzed for the very large-scale integration (VLSI) parameters.
An automated power of hydrogen controlled filtration system for enhanced aquarium fish farming Garcia, Fabio; Martel, Daniel; Paiva-Peredo, Ernesto
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.pp6265-6270

Abstract

The increasing popularity of fish keeping in aquariums and the need for electronic equipment to maintain an optimal environment. This article focuses on monitoring water purity to ensure fish health and longevity, addressing the issue of water pollution caused by chemicals and waste produced by fish. Solutions such as mechanical and biological filters are explored, highlighting the use of the mechanical filter composed of zeolite, ceramic rings, and activated carbon, which work to remove solid particles, toxic compounds, and pollutants from the aquarium water. The article presents the implementation of a mechanical filter controlled by a PIC18F4550 microcontroller using a pH sensor. The results indicate the stability of the pH of the water in the established range of 6.5 to 7.5, with a maximum error of 3% at the upper limit of the range and no error below the established lower limit. It is concluded that the system effectively maintains the desired levels and ensures the fish's health. A technological solution for monitoring and controlling water quality is presented, recognizing the possibility of improvements in aquaculture.

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