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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 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. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 2,901 Documents
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White light-emitting diode daubed via CaSc2O4:Ho3+/Yb3+ nanocrystal sheets enclosed using SiO2 Tung, Ha Thanh; Nguyen Thi, Dieu An
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.4971

Abstract

Our investigation assesses the downshifting (DS), periodicity up-transmutation as well as internal light consistency from phosphor samples of CaSc2O4 incorporated with Ho3+/Yb3+ along with up-conversion from CaY2O4 incorporated with Ho3+/Yb3+. These samples are created via precursor antecedent compound technique. The generation for the crystalline samples having orthorhombic stage is validated by the X-ray powder diffraction. The dispersal reflectance spectra exhibit several lines within the zones of ultraviolet–visible–near infrared (UV-vis-NIR), resulting from the ions of Ho3+ as well as Yb3+. The optical band gap (Eg) results reach 5.69 and 5.58 eV, corresponding to CaSc2O4:Ho3+/Yb3+ and CaY2O4:Ho3+/Yb3+. The CaSc2O4:Ho3+/Yb3+ samples exhibit potent downshifting discharge in green hue when excited under 454 nm. CaSc2O4:Ho3+/Yb3+, as well as CaY2O4:Ho3+/Yb3+, exhibit potent discharges in green hue as well as near-infrared up-transmutation discharges in faint blue and red hues when excited under 980 nm. The spectrum hue clarity -Sgr – for CaSc2O4:Ho3+(1%)/Yb3+(5%) reaches 0.78. The disparity in pumping force yields internal light consistency for said sample with the green discharge, being nonexistent in the CaY2O4:Ho3+(1%)/Yb3+(5%) sample. As such, CaSc2O4:Ho3+/Yb3+ may prove useful when applied to up-transmutation apparatuses.
Parasitic isolation structure for mutual coupling reduction in a multiple input multiple output antenna Godi, Revati C.; Patil, Rajendra R.; Kinagi, Revansiddappa S.
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7860

Abstract

This paper reports a design of 2×1 multiple input multiple output (MIMO) structure of antenna with 23×45 mm2 dimension. Each element in the MIMO antenna is a quarter wave transformer fed microstrip patch antenna. To lessen the effect of coupling, a rectangular parasitic decoupler is positioned between the two elements. Results report that antenna resonates at 6 GHz, coupling is reduced by 14 dB using parasitic decoupler S12 and S21 obtained with parasitic decoupler are same which -33.06 dB. The diversity gain (DG) is 9.99 dB, which is nearly close to 10 dB, and the envelope correlation coefficient (ECC) is less than 0.00034. These values reflect the good diversity performance. Measured findings match those from the simulation. As we confront the delicate environment, the proposed antenna is suited for number of wireless applications, including 802.11, 802.16 standards of IEEE.
A Thai-language chatbot analyzing mosquito-borne diseases using Jaccard similarity Chanakot, Benjamin; Sanrach, Charun
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.6048

Abstract

The objective of this study is to create a Thai-language chatbot analyzing mosquito-borne diseases using Jaccard similarity with an aim to develop an artificial intelligence (AI)-based chatbot used to analyze Aedes-borne diseases through natural language processing. The analysis occurred when the symptoms provided by users on the chatbot were assessed to select relevant words as text attributes using the term frequency-inverse document frequency (TF-IDF) before the Jaccard similarity was used to measure the similarity of the information on the mosquito-borne disease database. The Line Messaging API was applied to facilitate communication between users and the chatbot through the Line application. The chatbot applied PHP 7.2.34 and MySQL 5.7.32 for database management, with Apache 2.2.29 serving as the bot server. The performance evaluation of the chatbot revealed that the chatbot accurately understood user intentions with an intent accuracy of 85.00%. Likewise, the usability of the chatbot was assessed using the system usability scale (SUS), and it received a score of 89.75, indicating a high level of user-friendliness. Furthermore, it has been found that appropriate tokenization enables accurate feature selection. This leads to improved accuracy in measuring Jaccard similarity. Consequently, the chatbot is capable of providing precise responses that align with the user's intent.
Integration of MQTT-SN and CoAP protocol for enhanced data communications and resource management in WSNs Nwankwo, Emmanuel; David, Michael; Onwuka, Elizabeth Nonye
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.5158

Abstract

Lightweight communication protocols for wireless sensor networks (WSNs) are unfolding for machine to machine (M2M) communications and thus there is always going to be a possible conflict of interest on which protocol is best suited for any particular application. The two protocols of interest in this study are the message queue telemetry transport protocol for sensor network (MQTT-SN), a variant of message queue telemetry transport (MQTT) protocol and the constrained application protocol (CoAP). There have been studies that reveal that these protocols perform differently based on the underlying network conditions. CoAP experience lower delays than MQTT for higher packet loss and higher delays for lower packet loss. MQTT default communication via a broker is easier to scale compared to CoAP direct request-response paradigm. Although this is a huge advantage over CoAP, it presents the single point-of-failure problem. In this paper we propose an integration of MQTT-CoAP protocol using an abstraction layer that enables both MQTT-SN and CoAP protocol to be used in the same sensor node. Resources are managed by directly modifying sensor node configuration using CoAP protocol. Performance evaluation of these protocols under the integrated scenario shows acceptable levels of latency and energy consumption for internet of thing (IoT) operations.
Glaucoma detection in retinal fundus images using residual network architecture Islami, Fajrul; Sumijan, Sumijan; Defit, Sarjon
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7621

Abstract

Glaucoma is a significant eye disease that can lead to irreversible vision loss if not detected and treated early. This research focuses on developing an automated glaucoma detection system using a combination of a convolutional neural network (CNN) with the residual network 18 (ResNet18) architecture, locality sensitive hashing (LSH), and Hamming distance calculation. The CNN model is trained to extract meaningful features from retinal images, while LSH enables efficient indexing and retrieval of similar images. Hamming distance calculations are utilized to measure the dissimilarity between binary codes obtained from LSH. A dataset of 506 retinal images, consisting of 117 glaucoma images, 19 glaucoma suspect images, and 370 healthy images. The proposed glaucoma detection system achieved an average accuracy of 99.96%, sensitivity of 99.97%, and specificity of 99.94% during training, and 82.37% accuracy, 86.78% sensitivity, and 73.55% specificity during testing. Comparative analysis demonstrated its superiority over traditional methods. Further research should focus on larger datasets and explore multi-class classification for different glaucoma stages. The proposed system has potential for early glaucoma detection, facilitating timely intervention, and preventing vision loss.
Design and analysis of sustainable photovoltaic solar charging system with battery storage for electric vehicles Radwan, Eyad; Awada, Emad; Nour, Mutasim
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7508

Abstract

This paper presents a sustainable electric vehicle (EV) charging system that operates in three modes of operation to maximize the yield of photovoltaic (PV) system. The design and analysis of the EV charging system is customized based on the operational or office hours of a corporation. The proposed system incorporates a battery pack capable of providing at least one day of autonomy to overcome the weather conditions during early morning, shading times, or cloudy days. In this study, the perturb and observe (PO) algorithm is modified and used to operate the PV system at maximum power point (MPP) when charging either the EV or the storage battery. The load current, in both cases, is regulated using proportional integral (PI) controllers and pulse width modulation (PWM) switching of DC-DC converter. The proposed system operation is switched between three modes (boost operation for direct charging of EV and discharging of storage battery, and buck operation for charging of storage battery) by a simple event-driven finite state machine (FSM). Simulation results showed excellent tracking behavior of the proposed system when supplying a 5 kW load with variation in solar irradiance between 1000 and 400 W/m2, battery state of charge (SOC) between 40% and 100%, and temperature between 15 to 39 ℃.
Efficient k-way partitioning of very-large-scale integration circuits with evolutionary computation algorithms P., Rajeswari; Chandra S., Theodore; Sasi, Smitha
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.5781

Abstract

The standardization of very-large-scale integration (VLSI) physical architecture for VLSI chips and multichip platforms is now in its early stages of development. The purpose of VLSI partitioning is to divide the circuit into numerous smaller circuits with few connections in between. Partitioning is the fundamental problem in circuit design and division. The efficient method of evolutionary computation may be used to tackle the partitioning problem in VLSI circuit design. It provides a heuristic approach to solve this problem by exploring the solution space and incrementally improving the quality of the solutions. In order to obtain the shortest wire length (WL), area, and connections, an evolutionary optimized simulated annealing memetic algorithm (OSAMA) that incorporates one or more local search phases inside its evolutionary cycle was developed.
Dissecting of the two-stages object detection models architecture and performance Bouraya, Sara; Belangour, Abdessamad
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6424

Abstract

Artificial intelligence (AI) is the discipline focused on enabling computers to operate autonomously without explicit programming. Within AI, computer vision is an emerging field tasked with endowing machines with the ability to interpret visual data from images and videos. Over recent decades, computer vision has found applications in diverse fields such as autonomous vehicles, information retrieval, surveillance, and understanding human behavior. Object detection, a key aspect of computer vision, employs deep neural networks to continually advance detection accuracy and speed. Its goal is to precisely identify objects within images or videos and assign them to specific classes. Object detection models typically consist of three components: a backbone network for feature extraction, a neck model for feature aggregation, and a head for prediction. The focus of this study lies on two stage detectors. This study aims to provide a comprehensive review of two stage detectors in object detection, followed by benchmarking to offer insights for researchers and scientists. By analyzing and understanding the efficacy of these models, this research seeks to guide future developments in the field of object detection within computer vision.
Ensemble neural networks with input optimization for flood forecasting Mohd Khairudin, Nazli; Mustapha, Norwati; Mohd Aris, Teh Noranis; Zolkepli, Maslina
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.6863

Abstract

Machine learning model has been widely used to provide flood forecasting including the ensemble model. This paper proposed an ensemble of neural networks for long-term flood forecasting that combine the output of backpropagation neural network (BPNN) and extreme learning machine (ELM). The proposed ensemble neural networks model has been applied towards the rainfall data from eight rainfall stations of Kelantan River Basin to forecast the water level of Kuala Krai. The aim is to highlight the improvement on accuracy of the forecast. Prior to the development of such ensemble model, data are optimized in two steps which are decomposed it using discrete wavelet transform (DWT) to reduce variations in the rainfall series and selecting dominant features using entropy called mutual information (MI) for the model. The result of the experiments indicates that ensemble neural networks model based on the data decomposition and entropy feature selection has outperformed individually executed forecast model in term of RMSE, MSE and NSE. This study proved that the proposed method has reduce the data variance and provide better forecasting with minimal error. With minimal forecast error the generalization of the model is improved.
A novel cost-effective power supply model for industrial appliances based on triangular magnetic shunt transformer design Lahame, Mouhcine; Outzguinrimt, Hamid; Oumghar, Rajaa; Bahani, Boubkar; Chraygane, Mohammed
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6459

Abstract

This paper presents a new design of a magnetic shunt transformer for use in industrial microwave generators. The proposed transformer has a triangular shape and offers several advantages over existing transformer designs, including reduced volume and maintenance costs. We provide a detailed analysis of the transformer's dimensions and an equivalent model of the three-phase high voltage power supply system. The results of this study have significant implications for the field of industrial microwave generator design and could lead to the development of more efficient and costeffective systems. The resulting model is comprised of saturable inductors capable of accounting for the non-linear phenomena of saturation. The power supply is simulated using MATLAB/Simulink with a neuro-fuzzy ANFIS approach. The results are compared to experimental validations of a single-phase reference power supply for a magnetron, validating the proposed power supply. Additionally, the simulation results demonstrate the effectiveness of the proposed design, which outperforms existing transformers in terms of volume, energy efficiency and maintenance costs.

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