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All Journal Andalasian International Journal of Applied Science, Engineering, and Technology Journal of Novel Engineering Science and Technology Journal of Engineering Researcher and Lecturer
Khin, Ei Ei
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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 Mechanical Engineering

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Journal : Journal of Novel Engineering Science and Technology

 1 
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.
Development of Novel Solar Cell Design based on Current Energy Converted from Phonon Energy by Controlling the Phonon Transport Tin Swe, Hsu Myat; Hla Myo Tun; Pradhan, Devasis; Win, Lei Lei Yin; Khin, Ei Ei; Soe, Khaing 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.v3i03.626

Abstract

The paper mainly focuses on the Development of Novel Solar Cell Design based on Current Energy Converted from Phonon Energy by Controlling the Phonon Transport. The research challenges in this study are: to find a means of the control of phonon transport or phonon accumulation and propose a novel solar cell structure to convert the phonon energy to the current energy; to study phonon control method for III-nitrides and the properties of phonon transport; to analyze the phonon absorption in a short time for III-nitrides is higher than gallium arsenide by one order, which makes it possible to extract higher current than previous materials. The research objectives are: to design the novel solar cell structure to convert Phonon Energy to Current Energy; to analyze the physics of solar cell structure with numerical approaches; to model the Quantum Well in the proposed solar cell structure; to set the experimental measurement system for physical characteristics of novel solar cells; to confirm the results from the analysis of Control of Phonon Transport. The conversion of current energy from the phonon energy by controlling the phonon transport depends on the structure of the solar cell stacking system. The implementation of this study was accomplished based on the specific model, especially Quantum Well Structure. The results confirm that the performance specification of targeted solar cell structures 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.
Analysis of High-Performance Step-Down DC to DC Converter Design Based on Zero Voltage Switching with Pulse Width Modulation Technique for Electric Vehicles Nyo, Hnin Wint War; Tun, Hla Myo; Win, Lei Lei Yin; Win, Thanda; Khin, Ei Ei; Aye, Mya Mya; 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.v4i01.775

Abstract

The paper mainly focuses on analyzing high-performance step-down DC to DC converter based on zero voltage switching with pulse width modulation technique for electric vehicles. In this paper, PI, fuzzy PI, and adaptive network-based fuzzy inference system (ANFIS)control methods are applied to the phase shift full-bridge (PSFB) zero voltage switching (ZVS) converter for auxiliary components in electric vehicles. The robust analysis of three control methods is compared by using the AC small-signal mathematical model. Traditional PI control uses specific mathematical equations with errors and derivatives. Fuzzy PI control utilizes fuzzy logic rules with linguistic variables such as high, medium, and low. ANFIS combines fuzzy logic and neural networks to capture both benefits. The three control designs' switching losses and load changes are analyzed and implemented with the MATLAB/SIMULINK Software platform. From the simulation results, traditional PI control works with 92% efficiency. Fuzzy PI control and ANFIS work with 93% efficiency at full load capacity.
Co-Authors Aye, Mya Mya Hla Myo Tun Htay, Aung Kyaw Nyo, Hnin Wint War Oo, Thandar Pradhan, Devasis Soe, Khaing Thandar Tin Swe, Hsu Myat Tin, Thein Aung Tun, Hla Myo Tun, Hla Myo Tun Win, Lei Lei Yin Win, Thanda Zaw, Ko Ko