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Bulletin of Electrical Engineering and Informatics
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Core Subject : 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.
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Articles 2,901 Documents
A clustering method for energy efficient management of heterogeneous nodes of a flying ad hoc network Chaibi, Loubna; Sebgui, Marouane; Bah, Slimane
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6988

Abstract

The current paper presents a clustering method for energy efficient management of heterogeneous nodes of a flying ad hoc network (FANET). The technological advances of the last decade gave rise to emerging technologies. Unmanned aerial vehicles (UAVs) are small aircraft that proved their usefulness for different tasks nowadays. They can collaborate to achieve missions especially in areas where traditional networks cannot work or cannot accede. A FANET is composed by a number of these aircraft. For alike networks, the resources are limited. Indeed, an efficient energy management is required to extend the life of the network. This work is a clustering method for heterogeneous nodes of a FANET, each node is equipped with one sensor, and four different sensors are used. Clustering is grouping nodes with the aim of efficiency improvement. The clustering is done before the beginning of the rescue mission and depends on the types of sensors the nodes are equipped with and. The master election depends on the available energy of each one of the nodes. The simulation is done with a discrete event simulator (DES) and the results are compared to the algorithm of glowworm swarm optimization (GSO) to demonstrate the effectiveness of the suggested technique.
Classification of pediatric pneumonia using ensemble transfer learning convolutional neural network Cahyani, Denis Eka; Hariadi, Anjar Dwi; Setyawan, Faisal Farris; Gumilar, Langlang; Setumin, Samsul
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.v13i5.7825

Abstract

Pneumonia is a condition characterised by the sudden inflammation of lung tissue, which is triggered by microorganisms such as fungi, viruses, and bacteria. Chest X-ray imaging (CXR) can detect pneumonia, but it requires considerable time and medical expertise. Consequently, the objective of this study is to diagnose pneumonia using CXR imaging in order to effectively detect early cases of pneumonitis in children. The study employs the ensemble transfer learning convolutional neural network (ETL-CNN) transfer learning ensemble, which combines multiple CNN transfer learning models. Resnet50-VGG19 and VGG19-Xception are the ETL-CNN models used in this investigation. Comparing ETL-CNN models to CNN transfer learning models such as Resnet50, VGG19, and Xception. Pediatric CXR pneumonia, which consists of a normal and pneumonia image, is the source of these study results. The results of this analysis indicate that Resnet50-VGG19 achieved the highest level of accuracy, 99.14%. Additionally, the Resnet50-VGG19 obtained the highest levels of precision and recall when comparing to other models. Consequently, the conclusion of this study is that the Resnet50-VGG19 model can generate acceptable classification performance for pediatric pneumonia based on CXR. This study improves classification results for performance when compared to earlier studies.
On the use of historical data in context-aware multimedia documents adaptation processes Smaala, Aziz; Laboudi, Zakaria; Saighi, Asma; Moudjari, Abdelkader
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.v13i2.5297

Abstract

Playing multimedia documents in ubiquitous systems may require content adaptation based on gathered context information and accumulated historical data. Several approaches have already been proposed, in which adaptation actions are performed to provide adapted documents. Nevertheless, these approaches focus mainly on efficient use of context information without involving historical users data to improve the adaptation process. Thus, this paper allows for consideration of historical users data during the execution of the adaptation process. To do so, the context elements and the adaptation actions are first modeled using the oriented-object approach and then converted into relational and NoSQL databases schemes. Finally, algorithms for storing, retrieving and analysing data are designed. The proposal is validated by implementing scenarios through a real prototype. At a first step, the performances are measured to estimate the cost of data processing. The experiments show that NoSQL databases excel in data storage and ease of implementation, while relational databases perform well in data retrieve. At a second step, the proposal usefulness is highlighted by showing how historical data contribute to adaptation rules personalization using datadriven rule learning mechanisms rather than defining them explicitly. The analysis algorithm could retain personalized adaptation rules with confidence degree greater than 90%. Overall, the results are satisfactory.
Random sample consensus-based room mapping using light detection and ranging Latukolan, Merlyn Inova Christie; Pramudita, Aloysius Adya; Armi, Nasrullah; Hamdani, Nizar Alam; Susilawati, Helfy; Satyawan, Arief Suryadi
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.v13i6.6932

Abstract

Light detection and ranging (LiDAR) is a high-accuracy data source for geospatial providers that is displayed in two dimensions (2D) or three dimensions (3D). It is used to measure the distances or 2D or 3D maps of the environment. This study examines a random sample consensus (RANSAC)-based room mapping approach utilizing LiDAR. The RANSAC is used to achieve line fitting as a solution to acquire missing or incomplete point cloud data during the process of room scanning. The maximum x-y distance is proposed to achieve a proper model to fix the missing line during the LiDAR scanning process. Data retrieval uses ground-based LiDAR located in the middle of a certain room with the dimension of 5.76×4.95 m2. To explore a room mapping, a 2D LiDAR YDLIDAR G4 with an operating frequency of 7 Hz is used. The derived raw data is then visualized with MATLAB. The results show that the RANSAC can perform line-fitting for missing or illegible LiDAR point cloud data during the scanning process due to reflection or obstacles. The increase in the amount of data used is then directly proportional to the probability of the number of correct models.
Internet of things and radio frequency identification based embedded system to reduce shopping time in supermarkets Espino, Cesar Solis; Vargas, Favio Guerrero; Paiva-Peredo, Ernesto; Segura, Guillermo Wenceslao Zarate
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7343

Abstract

Doing daily shopping in a Peruvian supermarket means a large investment of time for many people, usually due to inaccurate and faulty scanning of products by barcodes at supermarket checkout counters. For this reason, an embedded system based on internet of things (IoT) and radio frequency identification (RFID) is designed to reduce shopping time in a supermarket. The system uses an ESP32 development board with embedded hardware specialized in IoT projects and firmware development based on C language and real-time operating systems (FreeRTOS) through espressif’s IoT development framework (ESP-IDF). RFID tags were used to scan the products and IoT with message queuing telemetry transport (MQTT) communication protocol are implemented to a local database in real time. The system achieves a significant reduction in terms of scanning time compared to self-service checkouts using barcodes, which allows to statistically analyze the reduced time per quantity of products and the linear trend of the 2 samples.
Improving cultural awareness and trust towards m-banking apps in Jordan Almuhairat, Ahmed; Alti, Adel; Alswailim, Mohannad
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.v13i5.7824

Abstract

Today’s mobile technology is improving our quality of life and changing our lifestyles by providing mobile financial applications that allow us to conduct daily financial transactions anytime and anywhere. As the number of mobile applications increases, great customer training offers innovative solutions suited to different customers’ cultures. Although Jordanian society has limited use of mobile banking applications due to a weak level of cultural awareness among consumers and financial security risks. Hence, we propose a culture-aware trust-based assistant to facilitate mobile banking transactions. It leverages the potential of guidance and behavior controllers to enhance awareness about available banking services while increasing confidence levels between Jordanians users for mobile apps. Particularly, an effective monitoring strategy and customer behavior controller aims to reduce fraud in mobile banking apps. An 18-user empirical study confirms that the completeness of financial culture and trust impact the customer’s attention to mobile banking apps. Therefore, the proposed assistant reaching an average interaction time of 20 seconds while achieving a high confidence rate of 74.05% which validates it is efficacy and practicability.
A novel modified mountain gazelle optimizer for tuning parameter proportional integral derivative of DC motor Aribowo, Widi; Abualigah, Laith; Oliva, Diego; Prapanca, Aditya
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.v13i2.5575

Abstract

This article presents a modified method of mountain gazelle optimizer (MMGO) as a direct current (DC) motor control. Mountain gazelle optimizer (MGO) is an algorithm inspired by the life of the mountain gazelle animal in nature. This animal concept has five essential steps that are duplicated in mathematical modeling. This article uses two tests to get the performance of the MMGO method. The first test uses a benchmark function test with a comparison method, namely the sine tree seed algorithm (STSA) and the original MGO. The second test is the application of MMGO as a DC motor control. The simulation results show that MMGO can reduce the overshoot of conventional proportional integral derivative (PID) control by 0.447% and has a better integral time square error (ITSE) value of 5.345 than conventional PID control. Thus, the MMGO method shows promising performance.
Applying convolutional neural network and Nadam optimization in flower classification Aini, Qurrotul; Zulfiandri, Zulfiandri; Firmansyah, Rezky; Arif, Yunifa Miftachul
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6203

Abstract

Flowers have a variety of shapes, colors and structures, the images of which need to be classified using guided learning techniques. Several studies classify flowers using machine learning, but their accuracy performance is not good. The thing is, the flowers come in a variety of colors that can sometimes look similar to the background. Therefore, this study aims to classify flowers using a convolutional neural network (CNN) and measure its performance. The method used is mixed methods by collecting existing data from previous studies and connecting it with the realities in the field. The Kozłowski and Steinbrener models were used, while the image data was obtained from the Oxford17 and Oxford102 dataset with 17 and 102 flower types, respectively. The results show 60% and 84% accuracy of CNN using the scratch and transfer learning approach for the Oxford17 dataset. The Oxford102 dataset shows 42% and 64%, respectively, with CNN from baseline and transfer learning.
Design and development of automatic voltage regulator using Ziegler-Nichols PID for electrical irons testing Sukma, Irawan; Suseno, Aji Dwi; Muhidin, Muhidin; Bakti, Prayoga; Ardiatna, Wuwus; Supono, Ihsan; Firdaus, Himma; Mandaris, Dwi
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.v13i6.7326

Abstract

This research presents an automated voltage regulation system crucial for a power input test of electric irons based on SNI IEC 60335-2-3 clause 11.4. The system is designed with an Arduino-based proportional-integral-derivative (PID) control mechanism to augment voltage stability and meet the standard requirement. The system comprises a microcontroller for PID control, a dimmer as the actuator, and a voltage sensor for error measurement. It utilizes the Ziegler-Nichols (Z-N) oscillation method to determine the PID control parameters. The simulation results identified a third-order transfer function as the best fit for the system, and the optimal PID parameters for the system are Kp=60, Ki=125, and Kd=500. The system was tested under the electric iron's active and non-active conditions. The proposed PID system demonstrated stable responses, effectively regulating the system voltage with minimal overshoot and settling time, and meeting standard requirements even under varying load conditions. It suggests potential applications beyond electric iron testing, promising efficiency improvements in broader household product testing.
On the outage performance analysis of α − κ − µ fading channels with non-orthogonal multiple access protocol Le, Si-Phu; Nguyen, Hong-Nhu; Thi Hau, Nguyen; Thi Thu Hang, Nguyen; Voznak, Miroslav
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.v13i2.5949

Abstract

In this paper, we consider effective performance transmission under generalized α − κ − µ the fading distribution. The source-user links are assumed to be non-orthogonal multiple access (NOMA) channels through a downlink power do-main. Two users are selected to service in a situation with perfect channel state information (CSI) in accordance with the NOMA protocol. The closed-form ex-pressions of outage probability (OP) and bit error rate (BER) are derived with the effect of power allocation coefficient, target rate, and channel fading param-eters. In addition, we calculate numerical results to demonstrate the asymptotic expansion in the high signal-to-noise ratio (SNR) analysis. Finally, Monte Carlo simulations are provided to validate and assess the accuracy of the analytical framework proposed.

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