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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 64 Documents
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Search results for , issue "Vol 11, No 4: August 2022" : 64 Documents clear
High efficiency dielectric resonator antenna using complementary ring resonator for bandwidth enhancement Aymen Dheyaa Khaleel Al-Obaidi; Osman Ghazali; Massudi Mahmuddin; Ahmed Jamal Abdullah Al-Gburi; Mohammed Najah Mahdi Al-Niamey; Mohd Fais Mansor
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3681

Abstract

A complementary ring resonator (CRR) technique is used to improve the bandwidth of the dielectric resonator antenna (DRA) while maintaining other parameters such as the efficiency and the gain. Parametric experiments were conducted in order to demonstrate the suggested antenna's working guideline. The bandwidth of the proposed Antenna is boosted by 769 percent as compared to the antenna without the CRR technique. The proposed antenna has high efficiency of 94 percent and a tiny dimension of around 30×30×12 mm. The suggested antenna has a frequency range from 2.61 to 3.65 GHz, which is suitable for S-band applications. Computer simulation technology (CST) was used to implement the design and obtain the results.
Taguchi's T-method with nearest integer-based binary bat algorithm for prediction Zulkifli Marlah Marlan; Khairur Rijal Jamaludin; Faizir Ramlie; Nolia Harudin
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3859

Abstract

Taguchi’s T-method is a new prediction technique under the Mahalanobis-Taguchi system to predict unknown output or future states based on available historical information. Conventionally, in optimizing the T-method prediction accuracy, Taguchi’s orthogonal array is utilized to determine a subset of significant features to be used in formulating the optimal prediction model. This, however, resulted in a sub-optimal prediction accuracy due to its fixed and limited feature combination offered for evaluation and lack of higher-order feature interaction. In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi’s T-method. A comparative study is conducted by comparing the performance of the proposed method against the conventional approach using mean absolute error as the performance measure on four benchmark case studies. The results from experimental studies show a significant improvement in the T-method prediction accuracy. A reduction in the total number of features results in a less complex model. Based on the general observation, the nearest integer-based binary bat algorithm successfully optimized the selection of significant features due to recursive and repetitive searchability, in addition to its adaptive element in response to the current best solution in guiding the search process towards optimality.
Machine learning in handling disease outbreaks: a comprehensive review Dianadewi Riswantini; Ekasari Nugraheni
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3612

Abstract

The changes in the global environment have made impact on the evolution of infectious diseases, virus mutations, or new diseases which are challenging to be tackled with new technological advances. This work aims to identify and analyze previous studies on machine learning applications in handling disease outbreaks. Bibliometric analysis was conducted on 3,447 scientific articles selected from the Scopus database. Further, latent dirichlet analysis (LDA) method was applied to identify the topic hotspots in attempting to deepen the analysis. The LDA results identified twelve topic hotspots that can be classified into three themes: COVID-19 disease, miscellaneous diseases, and public opinion on disease outbreaks for discussion. The study reveals that the scientific structure of this domain is dominated by machine learning research on COVID-19 diseases and miscellaneous diseases caused by pathogens or some genetic factors. A huge amount of multimodal medical data was used by previous studies for prediction, forecasting, classification, or screening purposes to resolve many problems of diseases, including epidemiological surveillance, diagnosis, treatment, health monitoring, epidemic management, viral infection, and pathogenesis. Public opinions toward new diseases are also an interesting topic in addition to the public perceptions in response to the health protocol and policies.
3D modelling of the mechanical behaviour of magnetic forming systems Boutana Ilhem; Boussalem Mohamed Elamin; Laouira Ahmed; Bouferroum Salaheddine
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3628

Abstract

High-speed forming methods become attractive in manufacturing and significantly reduce the cost and energy requirements. Electromagnetic forming is a high-velocity pulse forming technique that applies electromagnetic forces to sheet or tubular workpieces using a pulsed magnetic field. In order to understand the physical behaviours of materials, numerical modeling is highly desired. Therefore, in this study, we investigate the mechanical behaviour of the electromagnetic sheet stamping and magnetic tube expansion and compression systems. For these 3D simulations, COMSOL multiphysics software is used. It provides the possibility to model the electromagnetic aspects of the problem along with the thermal and mechanical aspects in a coupled method. The developed 3D numerical fully coupled models lead to analyze the transient magnetic fields, Lorentz forces acting on workpieces, and the plastic deformations obtained in several magnetic forming systems. The effects of systems parameters are also investigated such as the coil’s form and the number of its turns.

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