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All Journal JURNAL NASIONAL TEKNIK ELEKTRO JOIV : International Journal on Informatics Visualization Andalas Journal of Electrical and Electronic Engineering Technology
Muguro, Joseph
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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A Comprehensive Review of Intelligent Reflecting Surfaces from Hardware to Industrial Integration and Future Directions Munira, Anne; Muguro, Joseph; njeri, waweru
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 4 No. 1 (2024): May 2024
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v4i1.100

Abstract

An Intelligent Reflecting Surface (IRS) has emerged as a key solution to performance bottlenecks in wireless communication. Its ability to combat multipath fading and improve signal and energy efficiencies has made it relevant to various industry applications, including the Internet of Things (IoT), smart manufacturing, cognitive radio, radar, and Multiple-Input Multiple-Output (MIMO) systems. This paper presents a comprehensive review of the IRS’s structure and hardware requirements, channel estimation, optimization methods, and key applications to enable readers to understand how the IRS operates, its benefits, and some of the challenges involved in its application. The structure and hardware requirements are important to understand as they dictate the material composition, number, and arrangement of reflecting elements, and their reconfigurability. Channel State Information (CSI) plays a crucial role in optimized transmission as it gives information on the channel conditions, enabling users to tailor their transmission accordingly. In this work, all scholarly papers related to the IRS published between 2010-2024 were considered, sampled, and categorized based on the key themes. An analysis of the hardware and architecture reveals that transceiver hardware imperfections significantly affect IRS optimization and should be considered. While several channel estimation techniques offer comparable benefits, accuracy turns out to be the most important factor to consider. Further, results show that flexibility and inference accuracy make machine learning techniques superior to other optimization methods. Still, challenges remain in relation to IRS standardization, privacy concerns, and handover techniques that ought to be addressed for future industrial integration.
Enhancing Interface Efficiency: Adaptive Virtual Keyboard Minimizing Keystrokes in Electrooculography-Based Control Anandika, Arrya; Laksono, Pringgo Dwi; Suhaimi, Muhammad Syaiful Amri bin; Muguro, Joseph; Rusydi, Muhammad Ilhamdi
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 3: November 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n3.1160.2023

Abstract

Rapid technological developments, one of which is technology to build communication relationships between humans and machines using Biosignals. One of them is Electrooculography (EOG). EOG is a type of biosignals obtained from eye movement. Research related to EOG has also developed a lot, especially for virtual keyboard control. Research on virtual keyboard control based on eye gaze motion using electrooculography technology has been widely developed. Previous research mostly drew conclusions based on time consumption in typing paragraphs. However, it has not been seen based on the number of eye gaze motions made by the user. In this research, an adaptive virtual keyboard system is built, controlled using EOG signals. The adaptive virtual keyboard is designed with 7x7 dimensions and has 49 buttons, including main buttons, letters, numbers, symbols, and unused buttons. The layout of the adaptive virtual keyboard has six zones. Each zone has a different number of steps. Characters located in the same zone have the same number of steps. The adaptive feature is to rearrange the position of the character's button based on the previously used characters. In the experiments, 30 respondents controlled static and adaptive virtual keyboards with 7 paragraphs typed. Adaptive mode rearranges the position of buttons based on k-selection activities from respondents. the k numbers are 10, 30, 50, 70 and 100. Two virtual keyboard modes are evaluated based on the number of steps required to type the paragraphs. Test results show that the performance of the adaptive virtual keyboard can shorten the number of user steps compared to static mode. There are tests of the optimal system that can be reduced up to 283 number of steps and from respondents, that can reduced up to 258 number of steps or about 40% of steps. This research underscores the promise of EOG-driven adaptive virtual keyboards, signaling a notable stride in augmenting user interaction efficiency in typing experiences, heralding a promising direction for future human-machine interface advancements.
Electro-Mechanical Characterization of Graphite/Epoxy Composites as Potential External-Layer Material for Antenna Radome Aruma, John; Njeri, Waweru; Muguro, Joseph
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.167

Abstract

Graphite is widely recognized in electrical applications for its inherent conductivity. As a reinforcement in composite materials, graphite fibers greatly improve both strength and rigidity, making them ideal for constructing radomes. Traditionally, radomes used in ground and naval settings are made from high-cost materials, such as fiberglass, quartz, and aramid fibers, which are often combined with resins like polyester and epoxy. Nonetheless, issues in structural formation continue to pose challenges. This study aims to investigate the electrical and mechanical properties of graphite/epoxy composites using a dynamic mechanical analyzer (DMA) in double cantilever mode, in accordance with ASTM D7028-07 standards. The objective is to prepare epoxy/graphite composites on a high-density polyethylene (HDPE) substrate with varying composition levels. The study further aims to evaluate the electrical and mechanical properties of electrostatic discharge (ESD) composites using the dynamic materials testing (DMT) method, with a focus on analyzing graphite-epoxy composites as an external layer on antenna radomes. Various specimen types—pure epoxy, surface-coated, and mixed samples with different graphite particle concentrations—were tested at temperatures from 0 to 140°C. A 30V voltage was applied to each specimen, and the resulting current and sheet resistivity were recorded. The electro-mechanical and viscoelastic properties were analyzed, revealing that stress-induced plastic flow occurred in some specimens, accompanied by increased strain energy in graphite-weighted samples. Surface-coated specimens demonstrated distinct behavior, while mixed samples showed a linear strain energy increase up until fracture. Conductivity in epoxy composites was affected by filler content, with conductivity improvements up to a certain filler percentage.
Image Presentation Method for Human Machine Interface Using Deep Learning Object Recognition and P300 Brain Wave Nakajima, Rio; Rusydi, Muhammad Ilhamdi; Ramadhani, Salisa Asyarina; Muguro, Joseph; Matsushita, Kojiro; Sasaki, Minoru
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.949

Abstract

Welfare robots, as a category of robotics, seeks to improve the quality of life of the elderly and patients by availing a control mechanism to enable the participants to be self-dependent. This is achieved by using man-machine interfaces that manipulate certain external processes like feeding or communicating. This research aims to realize a man-machine interface using brainwave combined with object recognition applicable to patients with locked-in syndrome. The system utilizes a camera with pretrained object-detection system that recognizes the environment and displays the contents in an interface to solicit a choice using P300 signals. Being a camera-based system, field of view and luminance level were identified as possible influences. We designed six experiments by adapting the arrangement of stimuli (triangular or horizontal) and brightness/colour levels. The results showed that the horizontal arrangement had better accuracy than the triangular method. Further, colour was identified as a key parameter for the successful discrimination of target stimuli. From the paper, the precision of discrimination can be improved by adopting a harmonized arrangement and selecting the appropriate saturation/brightness of the interface.
Co-Authors Anandika, Arrya Aruma, John Laksono, Pringgo Dwi Matsushita, Kojiro Muhammad Rusydi H. Munira, Anne Nakajima, Rio Njeri, Waweru Ramadhani, Salisa 'Asyarina Sasaki, Minoru Suhaimi, Muhammad Syaiful Amri Bin