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Food and Nutrition Sciences 2023年第8期14卷 746-776页

作者： mohammed haydar awad abd-alrazig mohammed abd-Almajid Omer Dakeen mohammed Ali Hamza Mohamed Ali Rashid Mohamed Hassan Nasr College of Medicine Karary University Omdurman Sudan

Background: Nutritional knowledge and practise is an important measure to improve dietary habits and food choices. The daily food should contain balanced nutrition as needed to support optimal growth, avoid deficiency diseases and prevent the diseases which might interfere with the children health. Materials & Methods: A descriptive cross-sectional non-interventional hospital-based study was carried out among 122 mothers and 122 children by using a non-probability convenience sampling technique in the period of 15 March to 15 April 2023, and using interviews with structural questionnaires, the data was analyzed using SPSS version 26. Results: We found that most of the children had moderate health, while most of the mothers had moderate nutritional knowledge and practise towards their children, also we found that the relationship between mothers’ knowledge and practise and child health was significant (P Conclusion: Mothers’ knowledge and practise among children was moderate and children had moderate health. Wrong beliefs and cultural taboos play major roles in decreasing knowledge and practise.

关键词： Mothers Knowledge Practise Health children Infant Nutrition Cultural Taboos

Web Security:Emerging Threats and Defense

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Computer Systems Science & Engineering 2022年第3期40卷 1233-1248页

作者： abdulwahed awad Almutairi Shailendra Mishra mohammed AlShehri Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia

Web applications have become a widely accepted method to support the internet for the past *** they have been successfully installed in the business activities and there is a requirement of advanced functionalities,the configuration is growing and becoming more *** growing demand and complexity also make these web applications a preferred target for intruders on the *** with the support of security specialists,they remain highly problematic for the complexity of penetration and code reviewing *** requires considering different testing patterns in both codes reviewing and penetration *** a result,the number of hacked websites is increasing day by *** of these vulnerabilities also occur due to incorrect input validation and lack of result validation for lousy programming practices or coding *** scanners for web applications can detect a few vulnerabilities in a dynamic *** are quite easy to use;however,these often miss out on some of the unique critical vulnerabilities in a different and static *** these are time-consuming,they can find complex vulnerabilities and improve developer knowledge in coding and best *** scanners choose both dynamic and static approaches,and the developers can select them based on their requirements and *** research explores and provides details of SQL injection,operating system command injection,path traversal,and cross-site scripting vulnerabilities through dynamic and static *** also examines various security measures in web applications and selected five tools based on their features for scanning PHP,and JAVA code focuses on SQL injection,cross-site scripting,Path Traversal,operating system ***,this research discusses the approach of a cyber-security tester or a security developer finding out vulnerabilities through dynamic and static approaches using manual and automated web vulnerability scanners.

关键词： SQL injection attack cross-site scripting attack command injection attack path traversal attack

The impact of bank lending on Palestine economic growth:an econometric analysis of time series data

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Financial Innovation 2019年第1期5卷 219-239页

作者： Ibrahim M.awad mohammed S.Al Karaki Faculty of Business and Economics Al-Quds University–Abu Dis CampusP.O.Box 51000JerusalemPalestine College of Graduate Studies and Academic Research Hebron UniversityHebronPalestine

Banking is an essential sector of Palestine’s *** credits provided by banks are considered to have a positive impact on economic growth so that the overall objective of this study is to examine the impact of bank lending on economic growth in *** study employs the Augmented Dickey-Fuller to test for stationarity in the time series,The Johansen co-integration,Vector Autoregressive Model and Vector Error Correction Model are employed to identify the long-run and short-run dynamics among the variables,and Granger causality test in order to determine the direction of *** study finds that a long run relationship exists among the variables and insignificant short run ***,the study findings show that there is unidirectional causality and runs from GDP to bank *** insignificant contribution of bank lending to GDP is attributed to the fact that banks are not highly interested in lending to the production sector of the economy due to the high level of ***,the primary empirical evidence reveals that bank lending doesn’t cause economic growth,but economic growth causes bank lending.

关键词： Economic growth Error correction model Bank lending Granger causality test Palestine Unit root tests Solow growth model

Kaoline-based catalyst for a high stability desulfurization of sour heavy naphtha in a three-phase oscillatory baffled reactor

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Particuology 2024年第1期84卷 249-260页

作者： Hassan M.Hmood Saba A.Gheni Safaa M.R.Ahmed Mudheher M.Ali Hamid Yonis Saleh mohammed H.mohammed awad E.mohammed Marwan A.Mahomood Hiba R.mohammed Ahmed A.Hassan Adam Harvey North Refineries Company Ministry of OilIraq Chemical Engineering Department Tikrit UniversityIraq Ministry of Oil Iraq AL-Hawija Technical Institute Northern Technical UniversityMoselIraq School of Engineering Newcastle UniversityUK

To meet the rapidly increasing demand for energy and the dramatic depletion of conventional crude oil,it is imperative to utilize sour *** no coke being produced,oxidative desulfurization(ODS)of naphtha lowers its sulfur content and average molecular *** this article,we outline a method for heavy naphtha non-extractive ODS using a very stable *** technique involves the use of a solid catalyst with oxygen gas as the *** necessitated relatively high mixing intensities;hence a three-phase Oscillatory Baffled Reactor(OBR)was *** catalyst was based on the zeolite ZSM-5,prepared from natural kaolin by a series of delamination and activation steps and impregnated with Fe.A TiO2 nanolayer was applied,using the sol-gel method,to prevent rapid *** reactor performance was evaluated to minimize the sulfur content in the naphtha *** to the protective coating,the sulfur conversion stabilized at 90%.The results of this work establish the use of natural clay-based catalysts in a continuous,three-phase ODS,particularly with regard to proving long-term *** also showed that modest ODS can be achieved using an environmentally friendly oxidant,at mild operating conditions,whilst maintaining stability.

关键词： Natural kaoline Desulfurization Three-phase Oscillatory baffled reactor

Phishing Attacks Detection Using EnsembleMachine Learning Algorithms

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Computers, Materials & Continua 2024年第7期80卷 1325-1345页

作者： Nisreen Innab Ahmed abdelgader Fadol Osman mohammed awad mohammed Ataelfadiel Marwan Abu-Zanona Bassam Mohammad Elzaghmouri Farah H.Zawaideh Mouiad Fadeil Alawneh Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26110Jordan Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjloun26767Jordan

Phishing,an Internet fraudwhere individuals are deceived into revealing critical personal and account information,poses a significant risk to both consumers and web-based *** indicates a persistent rise in phishing ***,these fraudulent schemes are progressively becoming more intricate,thereby rendering them more challenging to ***,it is imperative to utilize sophisticated algorithms to address this *** learning is a highly effective approach for identifying and uncovering these harmful *** learning(ML)approaches can identify common characteristics in most phishing *** this paper,we propose an ensemble approach and compare it with six machine learning techniques to determine the type of website and whether it is normal or not based on two phishing *** that,we used the normalization technique on the dataset to transform the range of all the features into the same *** findings of this paper for all algorithms are as follows in the first dataset based on accuracy,precision,recall,and F1-score,respectively:Decision Tree(DT)(0.964,0.961,0.976,0.968),Random Forest(RF)(0.970,0.964,0.984,0.974),Gradient Boosting(GB)(0.960,0.959,0.971,0.965),XGBoost(XGB)(0.973,0.976,0.976,0.976),AdaBoost(0.934,0.934,0.950,0.942),Multi Layer Perceptron(MLP)(0.970,0.971,0.976,0.974)and Voting(0.978,0.975,0.987,0.981).So,the Voting classifier gave the best *** in the second dataset,all the algorithms gave the same results in four evaluation metrics,which indicates that each of them can effectively accomplish the prediction ***,this approach outperformed the previous work in detecting phishing websites with high accuracy,a lower false negative rate,a shorter prediction time,and a lower false positive rate.

关键词： Social engineering attacks phishing attacks machine learning security artificial intelligence

A deep learning fusion model for accurate classification of brain tumours in Magnetic Resonance images

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 790-804页

作者： Nechirvan Asaad Zebari Chira Nadheef mohammed Dilovan Asaad Zebari Mazin Abed mohammed Diyar Qader Zeebaree haydar abdulameer Marhoon Karrar Hameed abdulkareem Seifedine Kadry Wattana Viriyasitavat Jan Nedoma Radek Martinek Department of Information Technology Lebanese French UniversityErbilIraq Department of Computer Science University of ZakhoZakhoKurdistan RegionIraq Department of Computer Science College of ScienceNawroz UniversityDuhokKurdistan RegionIraq Department of Artificial Intelligence College of Computer Science and Information TechnologyUniversity of AnbarRamadiIraq Department of Telecommunications VSB‐Technical University of OstravaOstravaCzech Republic Department of Cybernetics and Biomedical Engineering VSB‐Technical University of OstravaOstravaCzech Republic Department of Computer Network and Information Security Technical College of Informatics-AkreDuhok Polytechnic UniversityDuhokIraq Information and Communication Technology Research Group Scientific Research CenterAl‐Ayen UniversityThi‐QarIraq College of Computer Sciences and Information Technology University of KerbalaKarbalaIraq College of Agriculture Al‐Muthanna UniversitySamawahIraq Department of Applied Data Science Noroff University CollegeKristiansandNorway Faculty of Commerce and Accountancy Chulalongkorn Business SchoolChulalongkorn UniversityBangkokThailand

Detecting brain tumours is complex due to the natural variation in their location, shape, and intensity in images. While having accurate detection and segmentation of brain tumours would be beneficial, current methods still need to solve this problem despite the numerous available approaches. Precise analysis of Magnetic Resonance Imaging (MRI) is crucial for detecting, segmenting, and classifying brain tumours in medical diagnostics. Magnetic Resonance Imaging is a vital component in medical diagnosis, and it requires precise, efficient, careful, efficient, and reliable image analysis techniques. The authors developed a Deep Learning (DL) fusion model to classify brain tumours reliably. Deep Learning models require large amounts of training data to achieve good results, so the researchers utilised data augmentation techniques to increase the dataset size for training models. VGG16, ResNet50, and convolutional deep belief networks networks extracted deep features from MRI images. Softmax was used as the classifier, and the training set was supplemented with intentionally created MRI images of brain tumours in addition to the genuine ones. The features of two DL models were combined in the proposed model to generate a fusion model, which significantly increased classification accuracy. An openly accessible dataset from the internet was used to test the model's performance, and the experimental results showed that the proposed fusion model achieved a classification accuracy of 98.98%. Finally, the results were compared with existing methods, and the proposed model outperformed them significantly.

关键词： brain tumour deep learning feature fusion model MRI images multi‐classification

Exploring internship nursing students’ perception of gerontological nursing competencies: A descriptive study at Cairo University Hospitals

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Journal of Integrative Nursing 2023年第4期5卷 235-242页

作者： Naglaa El-Sayed ELDARDERY Ebtesam Mo’awad El-Sayed EBIED Yousef mohammed Kholoud KHODARY Basmala mohammed Sara mohammed Kholoud mohammed Ahmed KAMAL Mostafa SHABAN Department of Geriatric Nursing Faculty of NursingCairo UniversityGizaEgypt

Objective:This research study explores the perceptions of gerontological nursing competencies,attitudes toward older individuals,and the willingness to provide care for the elderly among internship nursing *** and Methods:A convenience sample of 350 internship nursing students from Cairo University Faculty of Nursing participated in the *** were collected using a set of comprehensive tools,including personal data and work experience assessment,the Hartford geriatric nurse competency tool,Kogan’s attitudes toward old people scale,and the modified elderly patient care ***:Descriptive analysis revealed balanced gender representation,with 60%identifying as *** percent of participants reported prior experience in gerontological ***-assessed competency scores indicated moderate proficiency in communication,physiological changes,and functional status *** such as pain management and restraint use demonstrated potential gaps in self-perceived *** toward older individuals were predominantly positive,and the willingness to provide care showed positive tendencies,with a minor degree of hesitation ***:The findings underscore the need for targeted interventions in nursing education to address competency gaps,enhance positive attitudes,and alleviate potential hesitations in caregiving for older *** the elderly population continues to grow,nursing education programs must prepare future practitioners to deliver comprehensive and compassionate care tailored to the unique needs of older adults.

关键词： Attitudes competencies elderly care gerontological nursing internship nursing students willingness

A Comprehensive Investigation of Machine Learning Feature Extraction and ClassificationMethods for Automated Diagnosis of COVID-19 Based on X-ray Images

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Computers, Materials & Continua 2021年第3期66卷 3289-3310页

作者： Mazin Abed mohammed Karrar Hameed abdulkareem Begonya Garcia-Zapirain Salama A.Mostafa Mashael S.Maashi Alaa S.Al-Waisy mohammed Ahmed Subhi Ammar awad Mutlag Dac-Nhuong Le College of Computer Science and Information Technology University of AnbarRamadi31001Iraq College of Agriculture Al-Muthanna UniversitySamawah66001Iraq eVIDA Lab University of DeustoBilbao48007Spain Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaJohor86400Malaysia Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia Faculty of Engineering and Built Environment Universiti Kebangsaan MalaysiaBangi43600Malaysia Pure Science Department Ministry of EducationGeneral Directorate of CurriculaBaghdad10Iraq Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam

The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global *** biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 *** this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 ***(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection *** on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 *** comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.

关键词： Coronavirus disease COVID-19 diagnosis machine learning convolutional neural networks resnet50 artificial neural network support vector machine X-ray images feature transfer learning

Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing

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Computers, Materials & Continua 2022年第7期72卷 1951-1965页

作者： Manar Ahmed Hamza abdelzahir abdelmaboud Souad Larabi-Marie-Sainte Haya Mesfer Alshahrani Mesfer Al Duhayyim Hamza awad Ibrahim mohammed Rizwanullah Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Department of Information Systems College of Science and ArtsKing Khalid UniversityMahayil Asir62529Saudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversityP.O.Box No.66833Rafha StreetRiyadh11586Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz University16278Saudi Arabia College of Computer at Al-Gunfudah Umm Al-Qura UniversityAl-Gunfudah24382Saudi Arabia

Generally,software testing is considered as a proficient technique to achieve improvement in quality and reliability of the ***,the quality of test cases has a considerable influence on fault revealing capability of software testing *** Case Prioritization(TCP)remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected(APFD)and time spent upon execution *** ismainly intended to design a collection of test cases that can accomplish early optimization using preferred *** studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection rate during software *** this aspect,the current study designs aModified Harris Hawks Optimization based TCP(MHHO-TCP)technique for software *** aim of the proposed MHHO-TCP technique is to maximize APFD and minimize the overall execution *** addition,MHHO algorithm is designed to boost the exploration and exploitation abilities of conventional HHO *** order to validate the enhanced efficiency of MHHO-TCP technique,a wide range of simulations was conducted on different benchmark programs and the results were examined under several *** experimental outcomes highlight the improved efficiency of MHHO-TCP technique over recent approaches under different measures.

关键词： Software testing harris hawks optimization test case prioritization apfd execution time metaheuristics

A Novel Hybrid Architecture for Superior IoT Threat Detection through Real IoT Environments

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Computers, Materials & Continua 2024年第11期81卷 2299-2316页

作者： Bassam Mohammad Elzaghmouri Yosef Hasan Fayez Jbara Said Elaiwat Nisreen Innab Ahmed abdelgader Fadol Osman mohammed awad mohammed Ataelfadiel Farah H.Zawaideh Mouiad Fadeil Alawneh Asef Al-Khateeb Marwan Abu-Zanona Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26150Jordan Computer Engineering Department College of Engineering&Information Technology Buraydah CollegesBuraydah51418Saudi Arabia Faculty of Architecture and Design Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjlun26810Jordan Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia

As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense *** paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world *** proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive *** integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT *** evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated *** research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive *** model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security *** our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of *** model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat *** achievemen

关键词： A hybrid deep learning model IoT threat detection real IoT environments cybersecurity attention mechanism