Results for “"Fariya Bintay Shafi"”

Md. Faysal Ahamed, Md. Nahiduzzaman, Golam Mahmud, Fariya Bintay Shafi et al.

Malaria, which is spread via female Anopheles mosquitoes and is brought on by the Plasmodium parasite, persists as a serious illness, especially in areas with a high mosquito density. Traditional detection techniques, like examining blood samples with a microscope, tend to be labor-intensive, unreli...

Kevin V. Thomas, Ahasanur Rahman, Wesam Rohouma, Md. Faysal Ahamed et al.

Induction motors are critical to industrial operations but are prone to mechanical and electrical faults. This paper introduces a new dataset for comprehensive fault diagnosis of three-phase induction motors, featuring synchronized multi-sensor data collection. Real-time measurements of vibration, v...

Md. Himel Reza, Md. Noman Biswas Sibly, Md. Golam Rabbani, Shafayetul Huda Sadi et al.

Convolutional Neural Networks (CNNs) have emerged as a cornerstone in the field of deep learning, demonstrating remarkable performance across various domains, including computer vision and natural language processing. Their widespread acceptance on both academic and industrial levels has spurred muc...

Fariya Bintay Shafi, Md. Faysal Ahamed, Amith Khandakar, Mohamed Arselene Ayari et al.

• Hybrid EEG framework combining CG-DDPM reconstruction and EEGGX-Net classification. • For the first time, CG-DDPM restores EEG signals and suppresses artifacts. • EEGGX-Net models spatial and nonlinear EEG dynamics for accurate workload inference. • External validation was performed on self-collec...

Md. Faysal Ahamed, Fariya Bintay Shafi, Md. Rabiul Islam, Md. Fahmidun Nabi et al.

Prompt detection of colorectal polyps is essential for preventing colorectal cancer, a leading cause of cancer-related deaths worldwide. However, manual detection through medical imaging faces significant challenges, including high costs, reliance on skilled endoscopists, and susceptibility to error...

Fariya Bintay Shafi, Md. Faysal Ahamed, Amith Khandakar, Wesam Rohouma et al.

• Proposes CATT-Net framework by integrating PCA, LSTM and Transformer encoders. • Achieves high accuracy (99.74 %) across four diverse datasets excelling SOTA studies. • Optimizes for real-time use with 1.72 MB model, 144.15k parameters and 3.77 MFLOPs. • Incorporates SHAP-based explainability, enh...

Amith Khandakar, David G. Michelson, Shaikh Golam Rabbani, Fariya Bintay Shafi et al.

It's important to monitor road issues such as bumps and potholes to enhance safety and improve road conditions. Smartphones are equipped with various built-in sensors that offer a cost-effective and straightforward way to assess road quality. However, progress in this area has been slow due to the l...

Anish Kumar Biswas, Md. Faysal Ahamed, Fariya Bintay Shafi, M. Murugappan et al.

Accurate, fast, and interpretable fault identification on electrical transmission lines is essential for maintaining power system stability and reducing outage durations. In this study, we propose a hybrid 1D convolutional neural network-Decision Tree (1D-CNN-DT) for transmission line fault detectio...

Fariya Bintay Shafi, Md. Faysal Ahamed, Amith Khandakar

iNCog-EEG: A Multitasking EEG Dataset for Cognitive Workload Assessment with Controlled Task DifficultyThis dataset, named iNCog-EEG (Ideal vs. Noisy Cognitive EEG for Workload Assessment), contains EEG recordings from 40 participants engaged in a multitiered multitasking protocol designed to emulat...

Amith Khandakar, David G. Michelson, Fariya Bintay Shafi, Md. Faysal Ahamed et al.

Accurate measurement and monitoring of vehicle dynamics and road surface conditions are critical for ensuring road safety and improving transportation infrastructure maintenance. This paper presents CV-Net (Connected Vehicle Network), a novel instrumentation-oriented measurement and monitoring frame...