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All Journal Journal of Novel Engineering Science and Technology Journal of Engineering Researcher and Lecturer
Oo, Thandar
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Environmental Science Mechanical Engineering

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Journal : Journal of Novel Engineering Science and Technology

 1 
Analysis of Electromyography (EMG) Signal Processing with Filtering Techniques Oo, Nandar; Aye, Mya Mya; Oo, Thandar; Win, Lei Lei Yin; Tun, Hla; Pradhan, Devasis
Journal of Novel Engineering Science and Technology Vol. 3 No. 02 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i02.524

Abstract

The paper presents the Analysis of Electromyography (EMG) Signal Processing with Filtering Techniques. The problem in this study is how to consider the filtering techniques for fundamental EMG signal processing with high-level accuracy. The research method for designing the simulation codes for observing the EMG signal modeling and digital filtering techniques with mathematical approaches from the signals and systems concepts. The results confirm that the outcomes of this study met the performance target for noise removal techniques of EMG signals in real-world applications.
Performance Optimization of Brain Tumor Detection and Classification Based MRI by Using Batch Normalization Algorithms in Deep Convolution Neural Network Tin, Thein Aung; Aye, Mya Mya; Khin, Ei Ei; Oo, Thandar; Tun, Hla Myo; Pradhan, Devasis
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.567

Abstract

Brain tumor is represented as an essential part of critical cancers around the world. These cells multiply and accumulate uncontrolled, forming a mass or lump that can interfere with normal brain function. Primer detection systems not only took too must time in analyzing and setting error, but also extended more datasets to become overfitting, more computation time, and lack accuracy. Supervised ML and traditional CNN are not convenient for estimating the vita feature engineering in larger datasets and they need to be modified using normalization techniques in deep convolutional Neural Networks (CNNs) architectures. The proposed of the research MRI image datasets were evaluated and combined with two popular benchmark data sets, Kaggle, and BRATS. This main objective is to reduce the computational cost avoid overfitting and underfitting and then improve the classification accuracy. In addition, this paper follows the concept of the CNN model and evaluates the modified DCNN with six normalization layers benefits acceptable results with batch normalization techniques and the average number of epochs in a limited time. In this regard, we exploited to extend inside the layer DCNN for the problem of brain tumor classification. This model achieved the best result for the enhanced dataset, with a training accuracy of 99.9%, 98.9% in validation accuracy, 0.0074 in training loss, and a validation loss of 0.0566 in validation loss.
Implementation of the Process for Contamination in Electromyography (EMG) Signal by Using Noise Removal Techniques Oo, Nandar; Tun, Hla Myo; Pradhan, Devasis; Win, Lei Lei Yin; Aye, Mya Mya; Oo, Thandar
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.627

Abstract

The paper describes the analysis of electromyography (EMG) signals using noise removal techniques. The problem in this study is to consider a noise removal technique for basic EMG signal processing by the Band Pass Filter method. A research approach to designing simulation codes for observing EMG signal modeling and noise removal techniques through mathematical methods from signals and systems concepts. The results confirm that it can provide high-performance target monitoring of the EMG signal in real-world applications.
Compact Design of 1x2 MIMO Microstrip Patch Antenna with Corners Trimmed for Vehicle-to-Vehicle Communication Zaw, Ko Ko; Khin, Ei Ei; Oo, Thandar; Hla Myo Tun; Pradhan, Devasis
Journal of Novel Engineering Science and Technology Vol. 4 No. 01 (2025): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v4i01.694

Abstract

This paper mainly focuses on the compact design of circularly polarized microstrip patch antenna for vehicle-to-vehicle communication. The charging time of electric vehicle is longer waiting time than compared to traditional gasoline-based vehicles. The charging is done at the public charging stations. When the vehicles need charging while driving, they communicate with Dedicated Short Range Communications (DSRC) band to send the information to the nearest vehicles and receive information from the charging station. Moreover, the DSRC band is used in many application areas such as Intelligent Transportation System (ITS), Electronic Toll Collection (ETC), Collision Avoidance, and connected vehicles. The vehicle-to-vehicle communication system needs to achieve higher data rates multimedia. These requirements cannot be supported by using single microstrip patch antenna. However, some research challenges have been in MIMO antenna such as antenna miniaturization, decoupling, and isolation between the antennas. The research solution for the problem statement in this study is emphasized on the corner trimmed is added in the rectangular patch and ground plane to make the current part longer and the impedance matching better, and to get low ECC. After that, the mutual coupling can be reduced by adding suitable separation between two radiating patches. S12 and S21 are less than -20dB from 5.81 GHz to 5.930 GHz. So, the proposed antenna design is very appropriate for car-to-car (5.85-5.925 GHZ) communication. The measurement result of the proposed antenna is valid because the desired values such as minimum S11 ≤ -10 dB, VSWR ≤ 2, and ECC < 0.3 are obtained for V2V communication in both simulation and measurement results.
Co-Authors Aye, Mya Mya Hla Myo Tun Khin, Ei Ei Oo, Nandar Pradhan, Devasis Tin, Thein Aung Tun, Hla Tun, Hla Myo Win, Lei Lei Yin Zaw, Ko Ko