Search

Now showing items 1-7 of 7

Modeling of permeability impairment dynamics in porous media: A machine learning approach

Ahmed, Elrahmani; Al-Raoush, Riyadh I.; Ayari, Mohamed Arselene ( Elsevier , 2023 , Article)

The prediction of clogging and permeability impairment dynamics in porous media is crucial for the optimization of various industrial and natural processes. This paper presents a novel machine learning-based approach for ...

IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques

Ahamed, Md Faysal; Syfullah, Md Khalid; Sarkar, Ovi; Islam, Md Tohidul; Nahiduzzaman, Md; ... more authors ... less authors ( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)

Colorectal polyps in the colon or rectum are precancerous growths that can lead to a more severe disease called colorectal cancer. Accurate segmentation of polyps using medical imaging data is essential for effective ...

Explainable deep learning model for automatic mulberry leaf disease classification

Nahiduzzaman, Md; Chowdhury, Muhammad E.H.; Salam, Abdus; Nahid, Emama; Ahmed, Faruque; ... more authors ... less authors ( Frontiers Media SA , 2023 , Article)

Mulberry leaves feed Bombyx mori silkworms to generate silk thread. Diseases that affect mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the world’s raw silk. Manual leaf disease ...

Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection

Behzad, Vaferi; Dehbashi, Mohsen; Khandakar, Amith; Ayari, Mohamed Arselene; Amini, Samira ( Elsevier , 2024 , Article)

Zinc oxide (ZnO) nanocomposite sensors decorated with various dopants are popular tools for detecting even low hydrogen (H2) concentrations. The nanocomposite's chemistry, temperature, and H2 concentration impact the success ...

Robust and General Model to Forecast the Heat Transfer Coefficient for Flow Condensation in Multi Port Mini/Micro‐Channels

Hosseini, Seyyed Hossein; Ayari, Mohamed Arselene; Khandakar, Amith A.; Moradkhani, Mohammad Amin; Jowkar, Mehdi; ... more authors ... less authors ( Multidisciplinary Digital Publishing Institute (MDPI) , 2022 , Article)

A general correlation for predicting the two‐phase heat transfer coefficient (HTC) during condensation inside multi‐port mini/micro‐channels was presented. The model was obtained by correlating the two‐phase multiplier, ...

Application of Green Polymeric Nanocomposites for Enhanced Oil Recovery by Spontaneous Imbibition from Carbonate Reservoirs

Ahmadi, Yaser; Ayari, Mohamed Arselene; Olfati, Meysam; Hosseini, Seyyed Hossein; Khandakar, Amith; ... more authors ... less authors ( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)

This study experimentally investigates the effect of green polymeric nanoparticles on the interfacial tension (IFT) and wettability of carbonate reservoirs to effectively change the enhanced oil recovery (EOR) parameters. ...

Differentiation among stability regimes of alumina-water nanofluids using smart classifiers

Daryayehsalameh, Bahador; Ayari, Mohamed Arselene; Tounsi, Abdelouahed; Khandakar, Amith; Vaferi, Behzad ( Techno Press , 2022 , Article)

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, ...