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All Journal Jurnal Pendidikan Teknologi dan Kejuruan Andalasian International Journal of Applied Science, Engineering, and Technology Engineering Science Letter Journal of Novel Engineering Science and Technology Journal of Engineering Researcher and Lecturer Innovation in Engineering
Tun, Hla Myo
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Performance analysis of inserted resonators in microstrip array antenna for biomedical applications Man, Cing Nuam; Win, Thanda; Tun, Hla Myo; Aye, Mya Mya
Journal of Engineering Researcher and Lecturer Vol. 4 No. 1 (2025): Regular Issue
Publisher : Researcher and Lecturer Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58712/jerel.v4i1.177

Abstract

This paper investigates the use of inserted resonators in designing microstrip patch array antenna for biomedical applications, such as respiratory rate detection. The purpose of this study is to analyze size and placement of resonator, and slots which influence the overall performance. The antenna was constructed by connecting two single microstrip patch antennas (11.7mm × 15.7 mm×1.6 mm) on an FR4 substrate with a dielectric constant (????r = 4.4) to form (26 mm × 50mm × 1.6 mm). It achieves a miniaturized design of the expected resonance frequency with directional polarization, and provides good gain and bandwidth. The simulations were operated using FEKO software. The results and size of antenna were compared with references designs. The antenna was also designed for a 5-6 GHz frequency range, making it suitable for ISM band (Industrial, Medical, and Science) band range, low-power wireless applications, including Wi-Fi, and Bluetooth, as well as robotic systems, low-noise amplifier (LNA), 5 G applications, and WiFi 6E standard applications.
Recognition human walking and running actions using temporal foot-lift features Tun, Khin Cho; Tun, Hla Myo; Win, Lei Lei Yin; Win, Khin Kyu Kyu
Innovation in Engineering Vol. 1 No. 1 (2024): Regular Issue
Publisher : Researcher and Lecturer Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58712/ie.v1i1.1

Abstract

The recognition of human walking and running actions becomes essential part of many different practical applications such as smart video-surveillance, patient and elderly people monitoring, health care as well as human-robot interaction. However, the requirements of a large spatial information and a large number of frames for each recognition phase are still open challenges. Aiming at reducing the number frames and joint information required, temporal foot-lift features were introduced in this study. The temporal foot-lift features and weighted KNN classifier were used to recognize “Walkin and“Running”actions from four different human action datasets. Half of the datasets were trained and the other half of datasets were experimentally tested for performance evaluation. The experimental results were presented and explained with justifications. An overall recognition accuracy of 88.6% was achieved using 5 frames and it was 90.7% when using 7 frames. The performance of proposed method was compared with the performances of existing methods. Skeleton joint information and temporal foot-lift features are promising features for real-time human moving action recognition.
Project-based learning module on creativity and entrepreneurship product subjects: Validity and empirical effect Aziz, Wildan Abdul; Wulansari, Rizky Ema; Putra, Randi Purnama; Tun, Hla Myo; Tin, Chau Trung; Ya, Kyaw Zay
Jurnal Pendidikan Teknologi Kejuruan Vol 6 No 3 (2023): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v6i3.34323

Abstract

The learning process of Creativity and Entrepreneurship Product subjects in Vocational High Schools still uses printed books, resulting the students’ boredom in learning the materials. Apart from that, the learning method used is the lecture method which is certainly less effective in supporting students' understanding on the materials so that learning is more teacher-centered. Meanwhile, the demand for the Emancipated Curriculum is that learning must be student-centered. This study aimed to develop learning tools for PjBL-based teaching module on the Creativity and Entrepreneurship Product subjects. This research was a research and development using the ADDIE development model. There were 12 experts who validated this module from 3 aspects, including material, media and model, and language aspects, and 30 students as participants for pilot study. The results of this research showed that this module is valid and has positive effects in supporting the learning process for the Creativity and Entrepreneurship Product subjects. This study brings pedagogical implications for the effectiveness of Creativity and Entrepreneurship Product subjects and is a method that can be implemented by teachers in the subject learning.
Innovative non-contact r-r intervals estimation using viterbi algorithm with Squared Branch Metric (VSBM) Zar, Win Thu; Tun, Hla Myo; Win, Lei Lei Yin; Naing, Zaw Min
Jurnal Pendidikan Teknologi Kejuruan Vol 7 No 1 (2024): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v7i1.35623

Abstract

Non-contact heartbeat detection with Doppler sensor is a critical component of remote health monitoring systems, enabling continuous and unobtrusive monitoring of an individual’s cardiovascular health. This paper reported an innovative approach for non-contact heartbeat detection using the Viterbi algorithm, leveraging the distribution of the difference of two adjacent R-R Intervals (RRIs). RRIs represented the time between successive peaks in the electrocardiogram (ECG) signal and are fundamental in analyzing heart rate variability, mental stress conditions and heart diseases. Numerous non-contact Doppler sensor-based methods have been proposed for heartbeat detection, leveraging the evaluation of RRIs without physical device attachment. However, challenges arise from unwanted peaks caused by respiration and slight body movements, even when the subject remains motionless with normal breathing. This study presented an innovative approach for selecting heartbeat peaks utilizing the Viterbi algorithm with the squared difference of two adjacent RRIs as the Branch Metric (BM). The preliminary experiments revealed that the difference between two adjacent RRIs closely follows a Gaussian distribution. Building upon this observation, this paper considered the Viterbi algorithm with Squared Branch Metric (VSBM) to estimate the heartbeat accurately. To assess the accuracy of peak selection method, an experiment was conducted by comparing it with two existing peak detection methods: (i) Doppler output after Low-Pass Filter (LPF)-based method and (ii) Spectrogram-based method. Results demonstrate that the proposed VSBM method is effective to detect the heartbeat accurately for each peak detection method. Furthermore, a comparison of the performance of “Spectrogram + VSBM” outperforms the “Doppler output after LPF + VSBM” method by the Root-Mean-Square Error (RMSE) of RRIs.
Co-Authors Aung, Chan Myae Aung, Myint Myat Aye, Mya Mya Aziz, Wildan Abdul Ei Khin, Ei Hlaing, Nway Nway Htike, Than Than Khin, Ei Ei Ko, Mg Myo Ko Man, Cing Nuam Mon, Ei Mon, Myint Myint Naing, Zaw Min Nyo, Hnin Wint War Oo, Nandar Oo, Thandar Pradhan, Devasis Putra, Randi Purnama Soe, Khaing Thandar Su Win, Naw Aye Myat Su Thar, Hla Aye Tin Swe, Hsu Myat Tin, Chau Trung Tin, Thein Aung Tun, Khin Cho Win, Khin Kyu Kyu Win, Lei Lei Yin Win, Soe Win, Thanda Wulansari, Rizky Ema Ya, Kyaw Zay Zar, Win Thu Zaw, Ko Ko