Yazar "Elhaty, Ismail A. M." seçeneğine göre listele

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    Diagnosis of Oral Squamous Cell Carcinoma Using Deep Neural Networks and Binary Particle Swarm Optimization on Histopathological Images: An AIoMT Approach
    (HINDAWI LTD, ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON W1T 5HF, ENGLAND, 2022) Deif, Mohanad A.; Attar, Hani; Amer, Ayman; Elhaty, Ismail A. M.; Khosravi, Mohammad R.; Solyman, Ahmad Amin Ahmad
    Overall prediction of oral cavity squamous cell carcinoma (OCSCC) remains inadequate, as more than half of patients with oral cavity cancer are detected at later stages. It is generally accepted that the differential diagnosis of OCSCC is usually difficult and requires expertise and experience. Diagnosis from biopsy tissue is a complex process, and it is slow, costly, and prone to human error. To overcome these problems, a computer-aided diagnosis (CAD) approach was proposed in this work. A dataset comprising two categories, normal epithelium of the oral cavity (NEOR) and squamous cell carcinoma of the oral cavity (OSCC), was used. Feature extraction was performed from this dataset using four deep learning (DL) models (VGG16, AlexNet, ResNet50, and Inception V3) to realize artificial intelligence of medial things (AIoMT). Binary Particle Swarm Optimization (BPSO) was used to select the best features. The effects of Reinhard stain normalization on performance were also investigated. After the best features were extracted and selected, they were classified using the XGBoost. The best classification accuracy of 96.3% was obtained when using Inception V3 with BPSO. This approach significantly contributes to improving the diagnostic efficiency of OCSCC patients using histopathological images while reducing diagnostic costs.
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    Photocatalytic removal of nitrate from water using activated carbon-loaded with bimetallic Pd-Ag nanoparticles under natural solar radiation
    (ELSEVIER SCIENCE SA, PO BOX 564, 1001 LAUSANNE, SWITZERLAND, 2022) Soliman, Ahmed M.; Alshamsi, Dalal; Murad, Ahmed A.; Aldahan, Ala; Ali, Ismail M.; Ayesh, Ahmad I.; Elhaty, Ismail A. M.
    The increase of nitrate contamination of surface and groundwater has raised a concern, because of its impact on both environment and human health. In this study, photocatalysis for nitrate treatment in water was conducted using activated carbon prepared from date palm stone decorated with single and bimetals nanoparticles using solar radiation. The prepared catalyst was characterized by XPS, SEM, EDX, TGA, and surface area analyzer instruments. The photocatalytic effect of the prepared catalyst was studied using nitrate solution and acid scavengers with different concentrations. Significant photocatalytic activity was observed for activated carbon when modified with Pd–Ag. The obtained results showed that the conversion of nitrate takes place mainly through nitrogen gas (N2) rather than nitrite (NO2 – ) or ammonium (NH4 +). Formic acid as a hole scavenger with 0.05 M shows the maximum conversion for nitrate. The prepared photocatalyst shows stability for five cycles of nitrate ion reduction. Moreover, the results showed that the prepared catalyst could be applied for the removal of nitrate from groundwater and river water samples.
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    Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic
    (MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2022) Mohsan, Syed Agha Hassnain; Zahra, Qurat ul Ain; Khan, Muhammad Asghar; Alsharif, Mohammed H.; Elhaty, Ismail A. M.; Jahid, Abu
    The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease’s spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.
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    Synthesis and Antibacterial Activity of Rhodanine-Based Azo Dyes and Their Use as Spectrophotometric Chemosensor for Fe3+ Ions
    (MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2020) Akram, Dana; Elhaty, Ismail A. M.; AlNeyadi, Shaikha S.
    This research includes the design and synthesis of new derivatives for rhodanine azo compounds (4a–c) containing a naphthalene ring. Physiochemical properties of the synthesized compounds were determined by their melting points, FTIR, 1H-NMR, 13C-NMR, and elemental analysis spectroscopic techniques. The biological activities of the newly prepared azo rhodanine compounds were evaluated against some pathogenic bacteria using three different bacterial species including (Escherichia coli., Pseudomonas aeruginosa, Staphylococcus aureus) and compared with amoxicillin as a reference drug. The results showed that our compounds have moderate-to-good vital activity against the mentioned pathogenic bacteria. The selectivity and sensitivity of the newly prepared rhodanine azo compounds with transition metals Co2+, Cu2+, Zn2+, Ni2+, and Fe3+ were studied using UV–vis and fluorescence spectroscopy techniques. Among the synthesized azos, azo 4c showed affinity toward Fe3+ ions with an association constant of 4.63 × 108 M?1 . Furthermore, this azo showed high sensitivity toward Fe3+ ions with detection limits of 5.14 µM. The molar ratio and Benesi–Hildebrand methods confirmed the formation of complexes between azo 4c and Fe3+ with 1:2 binding stoichiometry. Therefore, azo 4c showed excellent potential for developing efficient Fe3+ chemosensors.