Browsing by Author "Ayari, Mohamed Arselene"
Now showing items 1-18 of 18
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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; Vaferi, Behzad; Olazar, Martin... 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. ... -
Assessment of Aesthetic Control in Qatar’s Urban Design
Valdeolmillos, Nur Alah Abdelzayed; Al-Malki, Almaha Ahmad E R; Pokharel, Shaligram; Ayari, Mohamed Arselene ( Qatar University Press , 2023 , Conference Paper)Aesthetic control is concerned with the visual appearance of the built environment, specifically in the urban setting. The built environment aesthetics can directly influence place identity, property values and the business ... -
Challenges facing faculty members when using a learning management system
Abu-Shanab, Emad; Samara, Jumana; Ayari, Mohamed Arselene ( IGI Global , 2020 , Article)Universities use learning management systems (LMS) to support teaching practices and add value to the educational system. A leading university in the gulf region (XYZ) provides support for faculty members (FMs) through its ... -
Deep Learning Framework for Liver Segmentation from T1-Weighted MRI Images
Hossain, Md Sakib Abrar; Gul, Sidra; Chowdhury, Muhammad E.H.; Khan, Muhammad Salman; Sumon, Md Shaheenur Islam; Bhuiyan, Enamul Haque; Khandakar, Amith; Hossain, Maqsud; Sadique, Abdus; Al-Hashimi, Israa; Ayari, Mohamed Arselene; Mahmud, Sakib; Alqahtani, Abdulrahman... more authors ... less authors ( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)The human liver exhibits variable characteristics and anatomical information, which is often ambiguous in radiological images. Machine learning can be of great assistance in automatically segmenting the liver in radiological ... -
Deep learning techniques for liver and liver tumor segmentation: A review
Gul, Sidra; Khan, Muhammad Salman; Bibi, Asima; Khandakar, Amith; Ayari, Mohamed Arselene; Chowdhury, Muhammad E.H.... more authors ... less authors ( Elsevier , 2022 , Article)Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the medical image processing domain for the last few decades. The existence of other organs such as the heart, spleen, stomach, ... -
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 ... -
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, ... -
Explainable deep learning model for automatic mulberry leaf disease classification
Nahiduzzaman, Md; Chowdhury, Muhammad E.H.; Salam, Abdus; Nahid, Emama; Ahmed, Faruque; Al-Emadi, Nasser; Ayari, Mohamed Arselene; Khandakar, Amith; Haider, Julfikar... 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 ... -
Fuzzy Logic-Based Model to Predict the Impact of Flow Rate and Turbidity on the Performance of Multimedia Filters
Hawari Alaa H.; Elamin Mazen; Benamor Abdelbaki; Hasan Shadi W.; Ayari Mohamed Arselene; Electorowicz Maria... more authors ... less authors ( American Society of Civil Engineers (ASCE) , 2017 , Article)This paper uses fuzzy logic-based models to predict and evaluate the performance of multimedia filters utilized in wastewater treatment. A fuzzy logic-based model is constructed and trained to predict the operating time ... -
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; Islam, Md Rabiul; Khandakar, Amith; Ayari, Mohamed Arselene; Chowdhury, Muhammad E.H.... 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 ... -
Mitigation of urban voids in traditional neighborhoods: The case of the Al-Najada zone in Doha, Qatar
Asmaa Saleh, AL-Mohannadi; AL-Mohannadi, Mooza Saqr; Pokharel, Shaligram; Ayari, Mohamed Arselene; Furlan, Raffaello ( Elsevier , 2023 , Article)Urban voids and leftover spaces challenge the urban development of cities and result in land vacancy and other spatial planning issues. Such spaces have great potential for innovative intervention through piece-by-piece ... -
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 ... -
Novel and robust machine learning approach for estimating the fouling factor in heat exchangers
Hosseini, Saleh; Khandakar, Amith; Chowdhury, Muhammad E.H.; Ayari, Mohamed Arselene; Rahman, Tawsifur; Chowdhury, Moajjem Hossain; Vaferi, Behzad... more authors ... less authors ( Elsevier , 2022 , Article)The fouling factor (Rf) is an operating index for measuring an undesirable effect of solids’ deposition on the heat transfer ability of heat exchangers. Accurate prediction of the fouling factor helps appropriate scheduling ... -
Perspectives on food waste management: Prevention and social innovations
Al-Obadi, Muna; Ayad, Hiba; Pokharel, Shaligram; Ayari, Mohamed Arselene ( Elsevier , 2022 , Article Review)Food waste is one of the challenging issues humans are facing. A third of the food produced in the world is wasted at various points along the food supply chain. Food waste can be reduced by developing technology that can ... -
Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization
Rahman, Tawsifur; Khandakar, Amith; Kadir, Muhammad Abdul; Islam, Khandaker Rejaul; Islam, Khandakar F.; Mazhar, Rashid; Hamid, Tahir; Islam, Mohammad Tariqul; Kashem, Saad; Mahbub, Zaid Bin; Ayari, Mohamed Arselene; Chowdhury, Muhammad E. H.... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one of the top 10 leading causes of death. Accurate and early detection of TB is very important, otherwise, it could be life-threatening. ... -
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; Panahi, Mohammad; Ahmadi, Goodarz; Tavoosi, Jafar... 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, ... -
Self-ChakmaNet: A deep learning framework for indigenous language learning using handwritten characters
Kanchon Kanti, Podder; Emdad Khan, Ludmila; Chakma, Jyoti; Chowdhury, Muhammad E.H.; Dutta, Proma; Salam, Khan Md Anwarus; Khandakar, Amith; Ayari, Mohamed Arselene; Bhawmick, Bikash Kumar; Islam, S M Arafin; Kiranyaz, Serkan... more authors ... less authors ( Elsevier , 2023 , Article)According to UNESCO's Atlas of the World's Languages in Danger, 40% of the languages today are counted as endangered in the future. Indigenous languages are endangered because of the less availability of interactive learning ... -
Signer-Independent Arabic Sign Language Recognition System Using Deep Learning Model
Podder, Kanchon Kanti; Ezeddin, Maymouna; Chowdhury, Muhammad E.H.; Sumon, Md Shaheenur Islam; Tahir, Anas M.; Ayari, Mohamed Arselene; Dutta, Proma; Khandakar, Amith; Mahbub, Zaid Bin; Kadir, Muhammad Abdul... more authors ... less authors ( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)Every one of us has a unique manner of communicating to explore the world, and such communication helps to interpret life. Sign language is the popular language of communication for hearing and speech-disabled people. When ...