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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 74 Documents
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Search results for , issue "Vol 13, No 3: June 2024" : 74 Documents clear
Proposed threshold-based and rule-based approaches to detecting duplicates in bibliographic database Amin, M. Miftakul; Stiawan, Deris; Ermatita, Ermatita; Budiarto, Rahmat
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.v13i3.7665

Abstract

Bibliographic databases are used to measure the performance of researchers, universities and research institutions. Thus, high data quality is required and data duplication is avoided. One of the weaknesses of the threshold-based approach in duplication detection is the low accuracy level. Therefore, another approach is required to improve duplication detection. This study proposes a method that combines threshold-based and rule-based approaches to perform duplication detection. These two approaches are implemented in the comparison stage. The cosine similarity function is used to create weight vectors from the features. Then, the comparison operator is used to determine whether the pair of records are grouped as duplication or not. Three research databases: Web of Science (WoS), Scopus, and Google Scholar (GS) on the Science and Technology Index (SINTA) database are investigated. Rule 4 and Rule 5 provide the best performance. For WoS dataset, the accuracy, precision, recall, and F1-measure values were 100.00%. For Scopus dataset, the accuracy and precision values were 100.00%, recall: 98.00%, and the F1-measure value is 98.00%. For GS dataset, the accuracy value was 100.00%, precision: 99.00%, recall: 97.00%, and the F1-measure value is 98.00%. The proposed method is potential tool for accurate detection on duplication records in publication databases.
Load frequency control of interconnected power system using cuckoo search algorithm Mishra, Soumya; Kumar, Pujari Harish; Ramasamy, Rajarajan; Edayillam Nambiar, Renjini; Puvvada, Praveena
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.v13i3.6714

Abstract

This paper presents a new time-domain multi-objective function approach for solving load frequency control issue in an interconnected power system. The performance of interconnected power system in each area is validated for overshoot and settling time values of frequency change and tie-line power exchange. An objective function is created with the goal of enhancing proportional integral derivative (PID) controller settings by reducing overshoot and achieving faster time-domain settling times. The efficiency of the proposed time-domain multi-objective function is evaluated in a two-area thermal power plant using a nature-inspired cuckoo search optimization (CSA) technique. By comparing the time-domain simulation results of the test system with the existing integral error-based objective functions IAE, ISE, ITAE, and ITSE, the proposed objective function is validated. Further, a sensitivity analysis were carried out to analyze the robustness of the proposed multi-objective function under various uncertain conditions.
Speed control for traction motor of urban electrified train in field weakening region based on backstepping method Thu Anh, An Thi Hoai; Tung, Ngo Manh
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.v13i3.5209

Abstract

Tractor motors always operate in the speed region higher than rated speed, but is limited to the module of the stator current, stator voltage vectors. Additionally, mathematical model of traction motor has shown nonlinearity through the product of the state variables ???, ??? with the input variable ??:?????, ?????. Therefore, this paper focuses on the study of speed control of traction motors in weakening field region while optimizing torque control, and choosing the backstepping method in designing speed–flux controller in order to solve the nonlinear structure. The simulation results of the responses: speed, torque, power, and flux performed on MATLAB/Simulink software with parameters collected from metro Nhon-Hanoi Station, Vietnam have proven the correctness in theoretical research.
Experimental investigation of a hybrid photovoltaic-thermal energy system for hot air production Hiendro, Ayong; Husin, Fitriah; Taufiqurrahman, Muhammad; Aula, Abqori
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.v13i3.6823

Abstract

Solar energy as a non-fossil alternative energy source has become the best choice to overcome the problem of energy demand in most countries in the world. There are two different techniques to convert solar energy: photovoltaic (PV) panels to produce electricity and thermal collectors to generate heat. The two technologies can be combined to provide electrical and thermal energy either simultaneously or separately. In order to optimize the performance of a hybrid photovoltaic-thermal (PVT) solar air heater, it is necessary to collect experimental data on solar irradiation and temperature. This paper emphasized the development of a PVT energy system for hot air production in a temperature range of 50-55 °C. Additionally, experiments were constructed to monitor the information acquired from the proposed PVT solar air heater and the environment, such as hot air temperature, ambient temperature, and solar irradiation. The real-time monitoring system was set for five sample days. A microcontroller unit was used to control the hot air temperature and save the measurement data into memory. The experimental results showed that the proposed PVT solar air heater is capable of maintaining a certain level of hot air temperature throughout the day and night.
MyPharmaceutical: an interactive proof of concept Jie, Khor Ying; Zaaba, Zarul Fitri; Omar, Mohd Adib
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.v13i3.5896

Abstract

With the rise of health awareness, pharmaceutical and cosmetic products should be verified to protect ourselves from health risks. MyPharmaceutical is a proof-of-concept proposed to provide a mobile application for users to carry out product verification and reporting and a web application for administrative purposes. The data on the registered pharmaceutical and cosmetic products were extracted from national pharmaceutical regulatory agency (NPRA) website. MyPharmaceutical mobile application provides functionalities such as searching the registered product, bookmarking products, reporting products, and tracking report status. The mobile application also implemented a barcode scanner feature to provide ease of product verification. A named entity recognition algorithm is applied with the NLP.js library to provide an improved product search feature for the users, where products can be searched with multiple search criteria in a single input. The web application is proposed to support the mobile application, where the NPRA data admins and officers can manage reported products, publish announcements, verify product data, and utilize the analytic dashboard. The system proposed is expected to provide ease of product verification and reporting to assist the public in choosing safe registered products and a platform for NPRA to manage data and deliver information to the users.
Comparative analysis of reactive routing protocols for vehicular adhoc network communications Kaushal, Payal; Khurana, Meenu; Ramkumar, Ketti Ramchandran
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.v13i3.5322

Abstract

In the recent past, vehicular adhoc networks (VANETs) have gained a lot of importance. The routing protocols play a vital role to deliver payloads from one vehicle to another one while they are moving at relative speeds. It is a challenging task to select a routing protocol for VANETs because of the uneven distribution and high mobility of vehicles. In this paper, we have analysed the two standard reactive protocols, adhoc on-demand distance vector (AODV) and ant colony optimization (ACO). The performance comparison of AODV and ACO routing protocols has been presented in this paper. The results show AODV performed better in terms of energy consumption and routing overhead. While considering the throughput, energy loss ratio, and delay ACO has performed. ACO resulted as upperhand.
A novel method of detecting malware on Android mobile devices with explainable artificial intelligence Vanjire, Seema Sachin; Lakshmi, Mohandoss
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.v13i3.6986

Abstract

The increasing prevalence of malware targeting android mobile devices has raised significant concerns regarding user privacy and security. In response, effective methods for malware classification and detection are crucial to protect users from malicious applications. This paper presents an approach that leverages deep learning techniques and explainable artificial intelligence (XAI) for android mobile malware classification and detection. Convolutional neural networks (CNNs) are deep learning model that has shown impressive performance in several application areas, including image and text classification. In the context of android mobile malware, CNNs have shown promising results in capturing intricate patterns and features inherent in malware samples. By training these models on large datasets of benign and malicious applications, accurate classification can be achieved. To enhance transparency and interpretability, XAI techniques are integrated into the classification process. These techniques provide insights into the decision-making process of the deep learning models, enabling the identification of critical features and characteristics that contribute to the classification results. This research, by combining deep learning and XAI methods, presents a fresh strategy for identifying and categorizing Android malware. This research paper will focus on a fascinating CNN-based malware categorization technique.
Barium titanate–silicon elastomer based body coupled antenna for wearable microwave head imaging applications Tayab Sakib, Md Abu; Riza Bashri, Mohd Saiful; Islam, Md. Rafiqul
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.v13i3.6665

Abstract

This paper presents a flexible monopole antenna fed by a coplanar waveguide (CPW) feeding line with a barium titanate (BaTiO3) silicon-elastomer impedance matching layer for microwave head imaging applications. The operating frequency bandwidth of the proposed antenna is 614 MHz which is from 0.475 GHz to 1.089 GHz. In biomedical microwave sensing and imaging applications, the major challenge is the high power loss due to reflection between the BaTiO3 and the antenna due to impedance mismatch. Therefore, the proposed BaTiO3 silicon-elastomer composite is designed to have dielectric property of 20 which acts as an impedance matching layer for the monopole antenna. The proposed antenna has dimensions of 70×30×6 mm. The flexibility of the antenna is provided by the use of the silicon elastomer. It has been shown that the power radiated into an artificial head phantom improved by almost 160% as compared to antenna without impedance matching layer. Moreover, the SAR level is 0.0286 W/kg when 1 mW of power is transmitted, which is well below the limit set by the regulation. This makes the antenna suitable for wearable biomedical applications due to its wideband characteristic and improved power penetration into human head.
Nonlinear control of three level NPC inverter used in PV/grid system: comparison of topologies and control methods Atifi, Youness; Raihani, Abdelhadi; Kissaoui, Mohammed; Lajouad, Rachid; Errakkas, Khalid
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.v13i3.7122

Abstract

With the passage of time, the importance of using renewable energy systems to overcome energy consumption and improve the quality of the grid has emerged through the use of nonlinear control techniques and reliance on advanced types of inverters such as multi-level inverters. This research is focused on comparing two grid-connected converter topologies in a photovoltaic (PV) generation system connected to a three-phase grid that serves a non-linear load. Additionally, the study explores two different control techniques applied to this converter, evaluating their effects on the total harmonic distortion coefficient. A comparison has been made between the traditional inverter and the three-level inverter type neutral point clamped (NPC) inverter, with the use of integral backstepping (IBS) technique which was also compared with the proportional integral (PI) controller. The simulation results in MATLAB/Simulink are presented illustrating the performances and the strong effectiveness of the three-level NPC inverter controlled by the proposed technique (IBS).
Development of IoT based intelligent irrigation system using particle swarm optimization and XGBoost techniques Santosh, D. Teja; Anuradha, Nandula; Kolukuluri, Madhavi; Gupta, Gaurav; Pathak, Mrunal Kishor; Krishnan, V. Gokula; Raghuvanshi, Abhishek
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.v13i3.6332

Abstract

A crop needs regular watering throughout its life to grow well. Irrigation improves food growth. Machines irrigate plants. The dry Sahel, which gets a lot of rain during the summer season but is dry in winter, needs irrigation. When it doesn't rain enough, crops need watering. By constantly monitoring soil moisture, humidity, temperature, and pH, precision agriculture reduces water use and increases crop output. Precision gardening uses less water. In many wealthy nations, efficient farming requires the internet of things (IoT). Particle swarm optimization (PSO) and XGBoost are used in this IoT-based intelligent watering system. Humidity and moisture sensors gather soil data at grass roots. Sensors constantly gather this data. These data are useless for smart watering. PSOselects smart watering data. This reduces central cloud info storage. Then, machine learning methods are trained using soil humidity, moisture, crop, and weather data. These programs can calculate a crop's water requirements. IoT devices control irrigation system water flow and results in saving fresh water. XGBoost algorithm is saving water from 23% to 27% for different crops.

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