Browsing by Author "Mahbubur Rahman"

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    Analysis of an electronic phase shift circuit for starting a single phase induction motor
    (Department of Electrical and Electronic Engineering, 1996-07) Mahbubur Rahman; Choudhury, Dr. Mohammad Ali
    Fractional horse power single phase induction motors have no starting torque of their own. As a result, these motors are started by auxiliary methods. Now-a- days, single phase induction motors having large horse power rating are also in use in rural areas and in industries. These large horse .power single phase induction motors require medium size capacitors for their start and running purpose. In this thesis static cycloconverter and inverter topologies have been proposed to perform the function of capacitors. Static converters are used for conversion of ac and dc power to ac and de having frequency, magnitude and phase other than supply voltage. Several of the conventional static converters can replace the starting and running capacitors of single phase induction motors. When sinusoidal supply is switched at every quarter cycle, switched waveform shifted by 90° can be obtained. This waveform may be utilized in the starting purposes of large hp single phase. motors. This would replace the bulky capacitorsotherwise required for starting these motors alid may also serve the purpose of power factor and other type of controls of the motors .. The quarter . cycle switched waveform though fulfils the required phase shift, pulse width modulated switching is proposed in the thesis for better harmonic performance of output waveform. Analysis and implementation of the PWM phase shift circuit has been carried out and reported in this thesis to justify the feasibility of using these circuitsin the practical field. It has been found by analysis that over modulated sine PWM switched static cycloconverters provide necessary phase shift for motor start and at the same time keep the low order harmonics of the phase shift circuit output voltage within acceptable limit. Motor operation by the proposed circuits has not been studied in detail in this thesis and left for future investigation ..
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    COVID-19 Diagnosis and Classification from CXR Images based on Vision Transformer (ViT)
    (North South University, 2021) Mahbubur Rahman; Shihabur Rahman Samrat; Abdullah Al Ahad; Ashfia Binte Habib
    The COVID-19 pandemic is far from over, and the current primary method of diagnosis is Reverse Transcription Polymerase Chain Reaction (RT-PCR). Although RT-PCR is reliable, it is known to have a long turnaround time and high false-negative rates that can severely hinder the accuracy of diagnosis. Alongside RT-PCR, Rapid Antigen Tests (RAT) are also used, but they have much lower accuracy than RT-PCR. Motivated by the flaws of the current diagnosis methods, we present a Vision Transformer-based classifier for the successful diagnosis and classification of COVID-19 using chest X-Ray (CXR) images. A 15000-sample CXR dataset was compiled, which consisted of 5000 CXRs per class. Afterwards, a Vision Transfer (ViT) was fine-tuned on the dataset. ResNet-50 and DenseNet121 were used as baseline models. It is observed that the Vision Transformer-based model had the highest classification accuracy of 96.2% with an F1 score of 0.965 and the average precision and recall of 0.9617 and 0.962, respectively. This study demonstrates the adequacy of the ViT for the identification and classification of COVID-19 and Pneumonia.