Browsing by Author "Ahmed, Aziz"

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    Enhancing VIA screening for cervical cancer: a comprehensive system integrating image processing, risk factors and follow-up facilitation
    (BRAC University, 2024-05) Nain, Zulkar; Ahmed, Rezwan; Ahmed, Aziz; Mitu, Tasmia Rahman; Sultana, Kawser; Alam, Md. Ashraful
    Visual Inspection of cervix with Acetic Acid (VIA) is an inexpensive and effective screening test which is being conducted in many under-developped and developing regions. In medical image processing applications, the performance of Computer Vision has been promising. This research aims to establish a systematic process for VIA (Visual Inspection with Acetic Acid) screening of the cervix by incorporating Computer Vision and Machine Learning techniques. The paper analyzes the performance of VGG16, ResNet-50, YOLOv9, YOLO-NAS(Medium) on cervix images with Acetic Acid (VIA), with VGG-16 achieving 96% accuracy, ResNet-50 achieving 95%, YOLOv9 achieving 93%, and YOLO-NAS achieving 91%. Furthermore, we use feature importance scores from the Random Forest model to extract key features associated with cervical cancer from demographic, behavioral, and clinical factors. Training an ensemble model on these features yields an accuracy of 94%. The goal is to analyze the cervical images during VIA inspection and predict its outcome using Computer Vision and integrate patient risk factors so that our proposed system identifies high-risk individuals, even among VIA-negative cases and improves overall screening accuracy, surpassing the existing VIA screening method.
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    Numerical Investigation for Flexural Response of Stainless-Steel Reinforced Concrete Beams
    (Research and Development Wing, MIST, 2025-12-30) Tabassum, Nusrat; Al-Moneim, Abdullah; Razu, Said; Ahmed, Aziz; Ahmed, Khondaker Sakil
    Stainless steel (SS) is becoming increasingly popular as reinforcement across the globe, owing to its superior mechanical and durability properties. This study numerically investigates the flexural behavior of concrete beams reinforced with stainless steel. Primarily, the experimental results are validated by developing 3D finite element (FE) models with stainless steel rebars, considering the actual test data. In the modelling process, 8-node brick element for concrete and 2-node beam element for reinforcement were employed in the finite element model. The numerical results are presented in terms of load displacement response, yield, and ultimate capacity with respective deformation, ductility, etc. The numerical results depicted reasonably good precision in predicting the load deformation response and ultimate load of the concrete beam reinforced with stainless-steel. The models have been regenerated for concrete beams with conventional mild steel to investigate the comparative behaviour in terms of significant changes in their load-carrying capacity and the corresponding ultimate deformation. Results revealed that the peak loads remained approximately the same for 30 MPa and 40 MPa concrete strengths, although the stainless-steel reinforced beams showed greater deformability and ductility. In addition, a parametric study of reinforced concrete beam models consisting of Grade 201 stainless steel rebars and 60-grade mild steel rebars with varying concrete grades of 30 MPa, 40 MPa, and 50 MPa was also performed to inspect their influence on the initial stiffness, ductility, and ultimate load-carrying capability of the concrete beams. The numerical response rendered that beams reinforced with stainless steel provide similar ultimate flexural capacity with improved stiffness and ductility in contrast to that of the mild steel rebars.