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Results for “"Mohammad Ashfak Habib"”

28 results

A New Approach to Simplifying Boolean Functions

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Mohammad Ashfak Habib, Md. Abdus Salam, Zia Nadir, Hemen Goswami

Journal: The Journal of Engineering Research [TJER]Year: 2004Citations: 3

There are many benefits to simplifying Boolean functions before they are implemented in hardware. A reduced number of gates decreases considerably the cost of the hardware, reduces the heat generated by the chip and, most importantly, increases the speed. But no method is effective for the simplific...

Physical SciencesComputer ScienceSoftwareOpen Access
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Quantitative EEG Features and Machine Learning Classifiers for Eye-Blink Artifact Detection: A Comparative Study

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Maliha Rashida, Mohammad Ashfak Habib

Journal: Research SquareYear: 2022Citations: 2

Abstract Ocular artifact, namely eye-blink artifact, is an unavoidable and one of the most destructive noises in EEG signals. Many solutions were proposed regarding the detection of the eye-blink artifact. Different subsets of EEG features and Machine Learning (ML) classifiers were used for this pur...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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COVID-19 Detection from Chest X-ray Images Using Deep Learning Approach

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Anika Bushra, Mohammad Ashfak Habib, Md. Jahidul Hasan Jahid

Year: 2023Citations: 1

Lung diseases has multiplied in recent years and now kills millions of people every year. An effective, trustworthy, and reasonably priced method of diagnosing lung diseases has become crucial to addressing the epidemic. In addition to the less accurate traditional technique of identifying lung illn...

Health SciencesMedicineRadiology, Nuclear Medicine and Imaging
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SDN-Qache: A Q-Learning-based Hybrid Caching Scheme in SDN-based Mobile Named Data Networks (MNDN)

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Shahid Md. Asif Iqbal, Asaduzzaman Asaduzzaman, Mohammad Ashfak Habib

Journal: Ad Hoc NetworksYear: 2025
Physical SciencesComputer ScienceComputer Networks and Communications
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Weighted Cross-Entropy Loss Based Respiratory Diseases Classification

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Karnis Fatema, Mohammad Ashfak Habib

Year: 2025

I. Respiratory sounds contain critical diagnostic information for the early identification of severe lung diseases. The COVID-19 pandemic has amplified the demand for contactless healthcare solutions enabled by electronic stethoscopes. Consequently, advanced deep-learning models have been developed ...

Health SciencesMedicinePulmonary and Respiratory Medicine
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Developing a Computer-Assisted System for Malignant Melanoma-Skin Cancer Detection Using Convolutional Neural Network

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Tanha Kabir Koly, Mohammad Ashfak Habib

Year: 2025

In recent years, Melanoma-Skin Cancer has emerged as a major health issue worldwide. Early detection plays a vital role in improving the prognosis of the disease. Leveraging computer vision in both the industrial and medical sectors presents promising opportunities. Our study focuses on introducing ...

Health SciencesMedicineOncology
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Advancing Subjectivity Detection in Bengali News Articles Using Transformer Models with POS-Aware Features

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Md. Minhazul Kabir, Kawsar Ahmed, Mohammad Ashfak Habib, Mohammed Moshiul Hoque

Year: 2025

Distinguishing fact from opinion in text is a nuanced but essential task, particularly in news articles where subjectivity can influence interpretation and reception.Identifying whether content is subjective or objective is critical for sentiment analysis, media bias detection, and content moderatio...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Rain-Free Vision: Leveraging ICA for Enhanced Object Detection with YOLOv8 in Rainy Conditions

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Omar Farook, Mohammad Ashfak Habib

Year: 2024

Autonomous vehicles in particular depends on visual data to detect and classify objects. However, in challenging weather conditions, such as rainy weather, the performance of object detection techniques may be hampered. In this paper, we introduced a meticulous approach to make the objects more visi...

Physical SciencesEngineeringElectrical and Electronic Engineering
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Quantitative EEG Features and Machine Learning Classifiers for Eye-Blink Artifact Detection: A Comparative Study

Verified

Maliha Rashida, Mohammad Ashfak Habib

Journal: Research SquareYear: 2022

Abstract Ocular artifact, namely eye-blink artifact, is an inevitable and one of the most destructive noises of EEG signals. Many solutions of detecting the eye-blink artifact were proposed. Different subsets of EEG features and Machine Learning (ML) classifiers were used for this purpose. But no co...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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An Alternate Solution for Smartphone-Based Urinalysis

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Abir Ebna Harun, Mohammad Ashfak Habib

Year: 2021

Urinalysis is a common medical test that can be costly and inconvenient in medical facilities. The use of point-of-care(POC) test devices, smartphones, manifolds, and other additional tools can make urinalysis easier in a home-based environment. In this paper, we are proposing a new system that can ...

Physical SciencesEngineeringBiomedical Engineering
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Developing a Framework for Acquisition and Analysis of Speeches

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Md. Billal Hossain, Mohammad Shamsul Arefin, Mohammad Ashfak Habib

Journal: Advances in intelligent systems and computingYear: 2020
Physical SciencesComputer ScienceArtificial Intelligence
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Parallel Self-Timed Adder with Lookahead-Carry Generator

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Mohammad Ashfak Habib

Journal: OALibYear: 2020

Parallel self-timed adder (PASTA) is a newly introduced asynchronous adder. It shows appreciable average-case performance without any special speedup circuitry or look-ahead schema, but its worst-case performance is almost similar to that of ripple carry adder. It is therefore an important research ...

Physical SciencesEngineeringElectrical and Electronic EngineeringOpen Access
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Effects of Coherent Noise on Ictal Component Selection for EEG Source Imaging

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Mohammad Ashfak Habib, Fatimah Ibrahim, Mas Sahidayana Mohktar, Shahrul Bahyah Kamaruzzaman et al.

Journal: World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, GermanyYear: 2015
Life SciencesNeuroscienceCognitive Neuroscience
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