Results for “"Md. Shahadat Jaman"”

Md. Maniruzzaman, Md. Shahadat Jaman, Md Amzad Sadik Abid, Zamalia Mahmud et al.

Alzheimer's disease (AD) biomarkers are highly variable, which complicates early prediction. In this study, we provide a comparative study of machine learning (ML) and deep learning (DL) techniques integrated with strong feature selection methods in the context of AD classification. This paper mainl...

Md Abdul Ahad Juel, Md. Nazim Uddin, Md Amzad Sadik Abid, Md. Zahidul Islam et al.

This research presents an advanced relay selection framework that leverages artificial intelligence to enhance the reliability of power systems. The proposed approach integrates various machine learning (ML) models to identify and select smart relays in real-time, effectively mitigating blackout con...

Md Fazle Rabbe, M.M. Alam, Mohammad Firoj Jaman, M. Shahadat Hossain et al.

The spotted flap shell turtle, Lissemys punctata (Bonnaterre, 1789) has a distribution in Bangladesh, India, Myanmar, Nepal and Pakistan. In Bangladesh, this species is widely distributed throughout the freshwater wetlands and the low-lying floodplains, coastal islands, and hill districts. This spec...

Md Nazmus Shakib Khan, Md Abdul Ahad Juel, Md. Shahadat Jaman, Md Shawon et al.

M. A. M. Khan, Sayed Sayem, Md Amzad Sadik Abid, Muntasir Karim Chowdhury et al.

This study presents a comparative analysis of five well-known machine learning classifiers for predicting heart disease at an early stage. Using the UCI Cleveland dataset, which includes $\mathbf{1, 0 2 5}$ samples from four cohorts, we applied ANOVA and Relief feature selection methods to consisten...

Md. Haydar Ali, Md. Shahadat Hossain, Sharmin Shahid Labony, Mohammod Kamruj Jaman Bhuiyan et al.

Fasciolosis is a snail-borne zoonotic trematode infection caused by ingesting aquatic vegetation contaminated with the metacercariae of ruminant liver flukes such as Fasciola hepatica and Fasciola gigantica, and their hybrid or parthenogenetic forms. The disease significantly affects the health and ...

Md Nazmus Shakib Khan, Md Abdul Ahad Juel, Abu Anas Nasim, Md. Zahidul Islam et al.

This paper investigates the overvoltage stress distribution in transformer bushings subjected to high-frequency electromagnetic transients, such as lightning impulses. A comparative simulation approach was implemented using COMSOL Multiphysics to analyze both real and perfect conductor configuration...

Md Shahadat Jaman, Md. Maniruzzaman, Md Amzad Sadik Abid, Kazi Nazmul Hasan et al.

One of the major challenges in Alzheimer’s disease (AD) research is the filter out the risk genes and the enhancement of machine learning (ML) model performance when working with high-dimensional, low-sample-size datasets. In this study, we proposed a biologically informed feature selection strategy...

Muhammad Nasir Khan, Md Abdul Ahad Juel, Abu Anas Nasim, Md. Zahidul Islam et al.

The impact of inductance and skin effect in multilayer coaxial cables on the transient behavior of transformer bushings is studied in this paper. The transient behavior caused by lightning impulse is studied by creating an axisymmetric model with COMSOL Multiphysics. The research examines self and m...

Musfikul Islam, Sayed Sayem, Md Sumon, Raisa Tasneem et al.

This work addresses a key challenge in biomedical data analysis: building accurate models from high-dimensional datasets with limited sample sizes. We evaluated feature selection methods, including minimum redundancy maximum relevance (mRMR), recursive feature elimination (RFE), and a hybrid approac...

Syed Murtoza Mushrul Pasha, Chunxiao Ye, Md. Shakhauat Hossain Sumon, Md. Shahadat Jaman et al.

Accurate and timely fault detection is critical for the safe and reliable operation of power systems. This study introduces a robust Long Short-Term Memory (LSTM) model designed for fault detection and classification in power transmission lines. The proposed approach leverages operational data to ca...

Md Abdul Ahad Juel, Md. Monirul Islam, Sharmin Jahan, Abu Tarek et al.

In this study, a robust machine learning model was developed to enhance cybersecurity in banking systems by detecting credit card fraud using the European card benchmark dataset. The research addressed the critical challenge of class imbalance through a comparative analysis, ensuring both efficiency...

Ridwanul Haque Nibir, Md. Mutakabbir Khan, Mohammad Nakibul Ezaz, SM Majharul Islam et al.

In this study, a powerful machine learning model was developed to strengthen cyber security in banking systems by detecting fraud using the European card benchmark dataset. The study addressed the significant challenge of class imbalance through PCA-based comparative analysis, ensuring both efficien...

Md. Shahadat Jaman, Md Shamsul Arefin, Mifat Ahmed, Salahin Sourav

Late-onset Alzheimer's disease (AD) is a neurodegenerative disease that requires such study. This study investigates Deep learning techniques for early predicting Alzheimer’s disease using microarray gene expression data. We employed gene selection techniques such as Correlation Based Feature Select...

Ifte Khairul Amin, Md. Nahid Islam, Azam Jaman, Md. Kabir Hasan et al.

Bangladesh has a huge potential for utilizing renewable energy with the availability of sources for solar, wind, hydro, and biogas. This paper provides a comprehensive analysis of the potential for renewable energy sources and predicts optimal sites for renewable plant implementation in Bangladesh. ...