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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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Machine learning-based pavement crack detection, classification, and characterization: a review Ashraf, Arselan; Sophian, Ali; Shafie, Amir Akramin; Gunawan, Teddy Surya; Ismail, Norfarah Nadia
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5345

Abstract

The detection, classification, and characterization of pavement cracks are critical for maintaining safe road conditions. However, traditional manual inspection methods are slow, costly, and pose risks to inspectors. To address these issues, this article provides a comprehensive overview of state-of-the-art machine vision and machine learning-based techniques for pavement crack detection, classification, and characterization. The paper explores the process flow of these systems, including both machine learning and traditional methodologies. The paper focuses on popular artificial intelligence (AI) techniques like support vector machines (SVM) and neural networks. It underscores the significance of utilizing image processing methods for feature extraction in order to detect cracks. The paper also discusses significant advancements made through deep learning strategies. The main objectives of this research are to improve efficiency and effectiveness in pavement crack detection, reduce inspection costs, and enhance safety. Additionally, the article presents data gathering approaches, various datasets for developing road crack detection models, and compares different models to demonstrate their advantages and limitations. Finally, the paper identifies open challenges in the field and provides valuable insights for future research and development efforts. Overall, this paper highlights the potential of AI-based techniques to revolutionize pavement maintenance practices and significantly improve road safety.
Tracking controller for uncertain wheel mobile robot: adaptive sliding mode control approach Pham, Sen Huong Thi; Nguyen, Cuong Duc; Giap, Khanh Dang; Vu, Nga Thi-Thuy
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5586

Abstract

This paper presents a technique for developing a sliding mode controller (SMC) using the state model of wheel mobile robot (WMR). The control scheme which consists of a controller and a disturbances observer can eliminate system uncertainties, disturbances, and unknown wheel slips. To successfully implement the sliding mode tracking controller algorithm, first, the transformation is utilized to convert the kinematic and dynamic models to an equation of state, and then create a controller based on Lyapunov function. Subsequently, a disturbance observer is formulated based on a stable sliding surface, followed by the development of an adaptive sliding mode control (ASMC) for the system. Moreover, to verify the efficacy of the given strategy, simulations have been performed under the aforementioned disturbance conditions. Finally, the simulation results show that chattering effect is eliminated, and the impact of disturbances is also diminished, thus proving the viability and correctness of the proposed control algorithm.
The effects of Ca14Mg2(SiO4)8:Eu2+ phosphor on white light emission quality of LED-phosphor packages Thanh Tung, Ha; An Nguyen Thi, Dieu; Doan Quoc Anh, Nguyen
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4792

Abstract

Ca14Mg2(SiO4)8: Eu2+ (CMS:Eu2+) green phosphor is used for creating the white-light emitting diode (W-LED) packages with conversion phosphor materials. The phosphor shows the broadband green emission that peaks at 505 nm in the blue wavelength. The phosphor introduces the improvement in the blue and green emission spectra, which helps to heighten the luminous flux. Moreover, that the concentration of CMS:Eu2+ increases, the scattering events are enhanced to benefits the color blending for lower color variations or better color uniformity. The color renditions reduce with the rising green-phosphor concentration. The green-light amount becomes surplus and redundant for balancing color elements of white light emission. Thus, it should adjust and keep the concentration of CMS:Eu2+ in the range of ~2–8 wt%, to get the average number of color rendering index (CRI) (73–75), and color quality scale (CQS) (60–64). The CMS: Eu2+, hence, is suitable for white light realization, and the W-LED aiming at high-luminescence white light emission with improved color uniformity, and average rendering performances.
The novel strategy of electrical arc furnace design and control approach for voltage flicker investigation Thakre, Mohan P.; C. Tapre, Pawan; P. Kadam, Deepak; Sharma, Mousam; Somnath Kadlag, Sunil; Vilas Mahadik, Yogesh
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4880

Abstract

Voltage flickers and harmonics are power quality (PQ) problems in the electric system during a variation and arc furnace (AF) adaptability. AF creations must determine a harmonic and flicker. This article evaluates complex AF systems. This article presents a newly established time domain (TD) static become to on an AF's V-I attributes (VIA). Static arc configurations are useful for harmonic analyses, but dynamic methods are needed for PQ studies, especially voltage flicker analysis. The MATLAB-based dynamic AF configuration is simulated for four different configurations. A response with configurations 1 and 4 varies from the real AF outcomes. The  simulation results and numerical finding shows that configurations 2 and 3 are much more appropriate and produce better results for minimum 3rd harmonics for arc current, arc voltage, and point of common coupling (PCC) voltage. The novelty of this configuration is that the energy transferred to the load by the AF during the cycle of operation has been identified, making the developed scheme more reliable and dependent on the load's operational conditions. After that, effective applications of these configurations and other configurations' accuracy should be clarified.
An extended review of the application layer messaging protocol of the internet of things Ronok Bhowmik; Md. Hasnat Riaz
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5236

Abstract

In the internet of things (IoT), there are resource-constrained and immense heterogeneous electronic gadgets worldwide. Till now, no single IoT application layer messaging protocol is the best, nor is anyone axiomatic for every requirement. This paper exhaustively summarizes information on the messaging protocols from the available previous research sources online. Our goal is to encapsulate a simple guideline so that users can choose an optimal messaging protocol quickly according to development requirements and specifications. For this purpose, we have reviewed the literature on six enabling and evolving application layer messaging protocols used for IoT systems namely, message queuing telemetry transport (MQTT), advanced message queuing protocol (AMQP), the constrained application protocol (CoAP), extensible messaging and presence protocol (XMPP), data distribution service (DDS), and simple text-oriented messaging protocol (STOMP) in terms of some interrelated metrics. Additionally, we represented a critical analysis of the application layer messaging protocols. This study will be helpful to readers with valuable insights and guide research scholars and developers in choosing optimal application layer messaging protocols based on development specifications and requirements.
Clustering of students admission data using k-means, hierarchical, and DBSCAN algorithms Cahapin, Erwin Lanceta; Malabag, Beverly Ambagan; Santiago Jr., Cereneo Sailog; Reyes, Jocelyn L.; Legaspi, Gemma S.; Adrales, Karl Louise
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4849

Abstract

Admissions in the university undergo procedures and requirements before a student can be officially enrolled. The senior high school grades remain the most significant in college admission decisions. This paper presents the use of data mining to cluster students based on admission datasets. The admission dataset for 2019-2020 was obtained from the office of student affairs and services. This dataset contains 2,114 observations with 11 attributes. Data preparation and data standardization were performed to ensure that the dataset is ready for processing and implemented in R programming language. The optimal number of clusters (k) was identified using the silhouette method. This method gave an optimal number of k=2 which was used in the actual clustering using the k-means and hierarchical clustering algorithms. Both algorithms were able to cluster students into two: cluster 1-social sciences or board courses and cluster 2-management or non-board courses. Further, density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm was also used on the same dataset and it yielded a single cluster. This study can be replicated by using at least a 5-year dataset of students’ admission data employing other algorithms that would suggest students’ retention and turn over to board examinations.
Green SrSi2O2N2:Eu2+ phosphor for LED-phosphor applications: synthesis and characterization Ha Thanh Tung; My Hanh Nguyen Thi
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4721

Abstract

Green phosphors SrSi2O2N2:Eu2+ (SSON:Eu) are combined utilizing a simple solid-state reaction with SrSi2O2N2:Eu2+ like the forerunner. Various phosphor attributes were assessed following creation procedure. Differential thermal analysis (DTA) spectra and luminescence measurements are used to assess crystalline active power, electron-phonon conjunction, and heat quenching behavior. Because of their poor electron-phonon conjunction intensity (Huang-Rhys factor=4.2), SSON:Eu green phosphors have outstanding heating and color consistency. The heat quenching temperature (T50) of SSON:Eu is greater than 200 °C. SSON:Eu green phosphors have a wide stimulation range, strong heat steadiness and can absorb ultraviolet (UV) to blue energy and release green illumination, leading to the appropriate utilization in solid-state illumination and GaAsAl solar cells, according to the findings.
Investigating the effectiveness of deep learning approaches for deep fake detection Berrahal, Mohammed; Boukabous, Mohammed; Yandouzi, Mimoun; Grari, Mounir; Idrissi, Idriss
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.6221

Abstract

As a result of notable progress in image processing and machine learning algorithms, generating, modifying, and manufacturing superior quality images has become less complicated. Nonetheless, malevolent individuals can exploit these tools to generate counterfeit images that seem genuine. Such fake images can be used to harm others, evade image detection algorithms, or deceive recognition classifiers. In this paper, we propose the implementation of the best-performing convolutional neural network (CNN) based classifier to distinguish between generated fake face images and real images. This paper aims to provide an in-depth discussion about the challenge of generated fake face image detection. We explain the different datasets and the various proposed deep learning models for fake face image detection. The models used were trained on a large dataset of real data from CelebA-HQ and fake data from a trained generative adversarial network (GAN) based generator. All testing models achieved high accuracy in detecting the fake images, especially residual neural network (ResNet50) which performed the best among with an accuracy of 99.43%.
Develop a new handling method for selfish nodes in mobile ad-hoc networks Al-Shakarchi, Sanaa Jafaar Hassan; Alubady, Raaid
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4895

Abstract

Mobile ad-hoc networks (MANETs) have been a crucial element of next-generation wireless networking technologies during the last decade. Because they allow users to access information and communicate with each other without infrastructure. Selfishness is one of the numerous undesirable behaviors that MANET network nodes may exhibit since this selfish node attempts to safeguard its own resources while accessing the services of other nodes and consuming their resources. Hence, a potential that the network's overall performance may degrade. This study developed a new method named detection, reintroduced, and collaborative of selfish node (DRCSN) that proposed detecting selfish nodes based on two factors: energy and the communication ratio (CR) and handling the rate of selfish nodes. Thus, selfish nodes were exploited to the maximum degree and significantly improve network performance. DRCSN was implemented inside ad-hoc on-demand distance vector (AODV) protocol. The test scenarios were implemented using the network simulator-2 (NS-2); many scenarios were created according to two important network parameters: the number of nodes and movement nodes. The proposed method improved the MANET's performance by increasing both the throughput and packet delivery ratio in the network in addition to that it reduced retransmission rate, delay, and power consumption compared to the related methods.
Survey on cryptocurrency security attacks and detection mechanisms Almamoori, Amenah Abdulabbas; Bhaya, Wesam S.
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4434

Abstract

Cryptocurrencies have become extremely popular as a form of payment in recent years. They are supported by blockchain, a cutting-edge advanced technology that makes extensive use of cryptographic mechanisms and other sophisticated distributed computing techniques. On these grounds, cryptocurrencies have been a target of several attacks. Cyber-attacks, for example, are exogenous events that can robustly affect cryptocurrencies by influencing their stabilization of price and market valuation. This study describes an overview of cybercriminals’ activities on cryptocurrencies. It provides a detailed discussion on the most popular types of attacks on the cryptocurrency ecosystem. Moreover, it provides possible countermeasures to these attacks. Finally, it produces insights into the most impactful attacks on cryptocurrencies and the best methods that have been proposed for detecting cryptocurrency attacks. The main goal of this survey is to obtain a thorough understanding of cryptocurrency attacks, which have been the subject of major studies concerning financial risks on cryptocurrency. A large number of existing publications have reviewed and assessed various forms of attacks to achieve this goal. However, these works have considerably flawed. To the best of our knowledge, the present survey sheds light on future research directions.

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