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Chemical Research in Chinese Universities 2014年第1期30卷 68-74页

作者： ai-bogami abdullah saad Department of Chemistry Faculty of Science King Abdulaziz University North Jeddah Jeddah 21589 Saudi Arabia

We reported the environmental benign synthesis of chalcones,2-pyrazolines and cyclohexanones under microwave *** were obtained by the condensation of each of 2-hydroxyacetophenone derivatives with a-naphthaldehyde under microwave *** condensation reactions of each of synthesized chalcones with phenyl hydrazine under microwave irradiation in the presence of dry acetic acid as a cyclizing agent gave ***,the new cyclohexenone derivatives,valuable intermediates to synthesize fused heterocycles,have been prepared by the cyclocondensation of each of hydroxychalcones with ethyl *** structures of the synthesized compounds were elucidated by infrared（IR） spectrometry,nuclear magnetic resonance（NMR）,mass spectrometry（MS） and elmental *** results indicate that unlike classical heating,microwave irradiation results in higher yields with shorter and cleaner *** synthesized compounds were screened for antimicrobial activity against Staphylococcus aureus,Escherichia coli,Candida Albicans and Aspergillus *** clarified the effects of different substituents in the tested compounds on the obtaind antibacterial activities and antifungal activities.

关键词： Microwave irradiation 2-Hydroxyacetophenone α-Naphthaldehyde Pyrazoline Cyclohexenone Antimicrobial activity

Artificial Intelligence Techniques Based Learner Authentication in Cybersecurity Higher Education Institutions

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Computers, Materials & Continua 2022年第8期72卷 3131-3144页

作者： abdullah saad AL-Malaise AL-Ghamdi Mahmoud Ragab Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt

Education 4.0 is being authorized more and more by the design of artificial intelligence(ai)*** education institutions(HEI)have started to utilize Internet technologies to improve the quality of the service and boost *** to the unavailability of information technology(IT)infrastructures,HEI is vulnerable to *** authentication can be used to authenticate a person based on biological features such as face,fingerprint,iris,and so *** study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions,named SRODLLAC *** proposed SRODL-LAC technique aims to authenticate the learner/student in HEI using fingerprint ***,the SRODLLACtechnique designs a median filtering(MF)based preprocessing approach to improving the quality of the *** addition,the Densely Connected Networks(DenseNet-77)model is applied for the extraction of ***,search and rescue optimization(SRO)algorithm with deep neural network(DNN)model is utilized for the classification ***,template matching process is done for fingerprint identification.A wide range of simulation analyses is carried out and the results are inspected under several *** experimental results reported the effective performance of the SRODL-LAC technique over the other methodologies.

关键词： Cybersecurity authentication biometrics security higher education institution deep learning

Electrodeposition and Surface Characterization of Sulfur on Polycrystalline Platinum from Sulfide Polluted Brine

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Journal of Chemistry and Chemical Engineering 2010年第2期4卷 15-21页

作者： Faiza Mohamed ai Kharafi aiman Yehia saad Badr Ghazy Ateya Ibrahim Mohamed Ghayad Chemistry Department Faculty of Science Kuwait University Kuwait Safat 13060 Kuwait

This paper investigated the electrodeposition of sulfur on polycrystalline platinum from sulfide polluted brine. Anodic polarization, potentiostatic and electrochemical impedance spectroscopy （EIS） techniques were performed. The slope of Warburg straight line in Nyquiest plot of the EIS spectra performed at 0.0 V indicates diffusion control mechanism of the electrodeposition process. At 0.5 V the Rp （determined from EIS measurements） increased rapidly with time indicating more sulfur deposition and more passivation of platinum surface. Samples subjected to potentiostatic experiments at 0.4, 0.9 and 1.0 V were investigated under Scanning Electron Microscope （SEM）. SEM images reveal the deposition of sulfur on the sample surfaces. The degree of sulfur deposit coverage and its morphology depend on both the potential and time of deposition.

关键词： Electrodeposition sulfur platinum sulfide pollution.

Contemporary Study for Detection of COVID-19 Using Machine Learning with Explainable ai

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Computers, Materials & Continua 2024年第7期80卷 1075-1104页

作者： saad Akbar Humera Azam Sulaiman Sulmi Almutairi Omar Alqahtani Habib Shah Aliya Aleryani Department of Computer Science University of KarachiKarachi75270Pakistan Department of Computing Faculty of Engineering Science and TechnologyHamdard UniversityKarachi75540Pakistan Department of Health Informatics College of Applied Medical SciencesQassim UniversityQassim51452Saudi Arabia Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia

The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic *** this article,a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplored dataset obtained from a private hospital for detecting COVID-19,pneumonia,and normal conditions in chest X-ray images(CXIs)is proposed coupled with Explainable Artificial Intelligence(Xai).Our study leverages less preprocessing with pre-trained cutting-edge models like InceptionV3,VGG16,and VGG19 that excel in the task of feature *** methodology is further enhanced by the inclusion of the t-SNE(t-Distributed Stochastic Neighbor Embedding)technique for visualizing the extracted image features and Contrast Limited Adaptive Histogram Equalization(CLAHE)to improve images before extraction of ***,an AttentionMechanism is utilized,which helps clarify how the modelmakes decisions,which builds trust in artificial intelligence(ai)*** evaluate the effectiveness of the proposed approach,both benchmark datasets and a private dataset obtained with permissions from Jinnah PostgraduateMedical Center(JPMC)in Karachi,Pakistan,are *** 12 experiments,VGG19 showcased remarkable performance in the hybrid dataset approach,achieving 100%accuracy in COVID-19 *** classification and 97%in distinguishing normal ***,across all classes,the approach achieved 98%accuracy,demonstrating its efficiency in detecting COVID-19 and differentiating it fromother chest disorders(Pneumonia and healthy)while also providing insights into the decision-making process of the models.

关键词： COVID-19 detection deep neural networks support vector machine CXIs InceptionV3 VGG16 VGG19 t-SNE embedding CLAHE attention mechanism Xai

ARTIFICIAL INTELLIGENCE(ai)-DRIVEN SPECTRUM MANAGEMENT

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China Communications 2020年第2期17卷 I0001-I0003页

作者： Zan Li Zhiguo Ding Jia Shi Walid saad Lie-Liang Yang the State Key Laboratory of Integrated Services Networks(ISN) School of Telecommunications EngineeringXidian University 不详 the State Key Laboratory of Integrated Services Networks(ISN) the Department of Electrical and Computer Engineering at Virginia Tech

Recent advances in communication and networking technologies are leading to a plethora of novel wireless services that range from unmanned aerial vehicle(UAV)communication to smart cognitive networks and massive Internet of Things(IoT)*** these emerging applications over the fifth generation(5G)of wireless cellular systems requires meeting numerous challenges pertaining to spectrum sharing and *** fact,most 5G applications will be highly reliant on intelligent spectrum management techniques,which should adapt to dynamic network environments while also guaranteeing high reliability and high quality-of-experience(QoE).

关键词： IoT spectrum guarantee

Intelligent Computational Model for Energy Efficiency and ai Automation of Network Devices in 5G Communication Environment

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TSINGHUA SCIENCE AND TECHNOLOGY 2024年第6期29卷 1728-1751页

作者： Bagwari, Ashish Logeshwaran, Jaganathan Raja, M. Devisivasankari, P. Bagwari, Jyotshana Rathi, Vikas saad, Asma Mohammed Elbashir Uttarakhand Tech Univ Dept Elect & Commun Engn Dehra Dun 248007 India Sri Eshwar Coll Engn Dept Elect & Commun Engn Coimbatore 641202 India CMR Inst Technol Dept Comp Sci & Engn Bengaluru 560037 Karnataka India CMR Inst Technol Dept Informat Sci & Engn Bengaluru 560037 Karnataka India Adv & Innovat Res Lab Dehra Dun 248001 India Grap Era Deemed Univ Dept Elect & Commun Engn Dehra Dun 248007 India Prince Sattam Bin Abdulaziz Univ Coll Sci & Humanities Dept Phys Al Kharj 16273 Saudi Arabia

Currently, the 4G network service has caused massive digital growth in high use. Video calling has become the go-to Internet application for many people, downloading even huge files in minutes. Everyone is looking for and buying only 4G Subscriber Identity Module (SIM)-capable mobiles. In this case, the expectation of 5G has increased in line with 2G, 3G, and 4G, where the G stands for generation, and it does not indicate Internet or Internet speed. 5G includes next-generation features that are more advanced than those available in 4G network services. The main objective of 5G is uninterrupted telecommunication service in hybrid energy storage system. This paper proposes an intelligent networking model to obtain the maximum energy efficiency and Artificial Intelligence (ai) automation of 5G networks. There is currently an issue where the signal cuts out when crossing an area with one tower and traveling to an area with another tower. The problem of "call drop", where the call is disconnected while talking, is not present in 5G. The proposed Intelligent Computational Model (ICM) model obtained 96.31% network speed management, 90.63% battery capacity management, 92.27% network device management, 93.57% energy efficiency, and 88.41% ai automation.

关键词： Microwave integrated circuits Automation 5G mobile communication Computational modeling Poles and towers Microwave devices Energy efficiency hybrid energy storage system 4G digital growth 5G downloading Subscriber Identity Module (SIM) generation network energy efficiency Artificial Intelligence (ai) automation

Repellent and Fumigant Effects of Essential Oil from Clove Buds Syzygium aromaticum L. against Tribofium castaneum （Herbest）（Coleoptera： Tenebrionidae）

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Journal of Agricultural Science and Technology(A) 2011年第4X期1卷 613-620页

作者： M. M. Abo-El-saad A. M. A1 Ajlan M. A. ai-Eid I. A. Bou-Khowh Date Palm Research Center (Center of Excellence ) King Faisal University P.O. Box 400 AI-Hassa 31982 Saudi Arabia College of Agriculture and Food Science King Faisal University P.O. Box 400 AI-Hassa 31982 Saudi Arabia

Essential oil from clove buds Syzygium aromaticum L. Merr. ＆ Perry （Myrtaceae） was extracted using petroleum ether in Soxhlet apparatus. The resultant oil contained eugenol （48.92%）, caryophyllene （18.55%）, α-caryophyllene （3.25%）, eugenol acetate （23%）, cis-13-docosenamide （3.2 1%）, presenting more than 96% of the oil. This oil was examined as a fumigant and repellent agent against adults of the red flour beetle, Tribolium castaneum. Data showed that various concentrations of the oil have revealed dramatic repellent activity against the tested insect, where it gave 100% repellency by 1.0, 0.8, and 0.2% clove oil at 4, 8, 10 min, respectively. The RTs0 and RT95 were 1.1 and 8.0 min at 0.2% and 0.4, 2.6 min at 0.8%, respectively. In addition, fumigation assay has also exhibited strong fumigant activity toward the adults of T. castaneum. At 100 μL oil/L air, mortality was 75, 80 and 100% after 6, 7, and 8 days exposure period with LCs0 and LC95 17 and 70 μL/L air, respectively. The utilization of clove oil for its potential effects against stored product insect is discussed.

关键词： Essential oils clove Syzygium aromaticum Tribolium castaneum fumigation repellency.