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Acta Geologica Sinica(English Edition) 2022年第3期96卷 1082-1097页

作者： Alzahraa Abo HABIBAH Kamal DAHAB ashraf shabana Samir KAMH Hekmat IBRAHIM Geology Department Faculty of ScienceMenoufia UniversityShebin ElkoomEgypt Geology Department Desert Research CenterCairoEgypt Geology Department Faculty of ScienceTanta UniversityTantaEgypt

The El Minia governorate lies within the Nile Valley,surrounded by calcareous plateaus to the east and west.The present study focuses on the hydrogeochemistry of the Eocene limestone aquifer at some wadis in the east El Minia governorate,Eastern Desert,Egypt.Hydrogeologically,two main aquifers are encountered in the study area,namely the Maghagha marly limestone and the Samalut chalky limestone aquifers.The Maghagha aquifer is composed of alternating layers of marly limestone and shale with thicknesses ranging from 3.49 m to 177.05 m and a groundwater depth ranging from 8.5 m to 59.27 m which reflects low groundwater potentiality.The groundwater salinity representing this aquifer ranges from 603.5 mg/L to 978.5 mg/L,reflecting fresh water type.Samalut aquifer is made up of chalky,cavernous and fractured limestone with thickness ranging from 30 m to 205 m and groundwater depth ranging from 9 m to 86.77 m,which indicates good groundwater potential.The groundwater salinity of the concerned aquifer ranges from 349.7 mg/L to 2043.9 mg/L,reflecting fresh to possibly brackish water types.Groundwater in the study area is of meteoric water origin;recent recharge is mainly controlled through the presence of fractures and their densities.The majority of groundwater samples in the study area are suitable for drinking and irrigation purposes.

关键词： groundwater limestone aquifers El Minia governorate Eastern Desert

An Ingenious IoT Based Crop Prediction System Using ML and EL

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Computers, Materials & Continua 2024年第4期79卷 183-199页

作者： shabana Ramzan Yazeed Yasin Ghadi Hanan Aljuaid Aqsa Mahmood Basharat Ali Department of Computer Science&IT Government Sadiq CollegeWomen UniversityBahawalpur63100Pakistan Department of Computer Science/Software Engineering Al Ain UniversityAl Ain64141UAE Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman University(PNU)Riyadh11671Saudi Arabia Agronomic Research Station Bahawalpur63100Pakistan

Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers haveno proper knowledge to select which crop is suitable to grow according to the environmental factors and soilcharacteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sectorof the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning,and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC),and environmental factors like temperature to improve crop yield. These parameters play a vital role in suggestinga suitable crop to cope the food scarcity. This paper proposes a systemcomprised of twomodules, first module usesstatic data and the second module takes hybrid data collection (IoT-based real-time data and manual data) withmachine learning and ensemble learning algorithms to suggest the suitable crop in the farm to maximize the yield.Python is used to train the model that predicts the crop. This system proposed an intelligent and low-cost solutionfor the farmers to process the data and predict the suitable crop.We implemented the proposed system in the field.The efficiency and accuracy of the proposed system are confirmed by the generated results to predict the crop.

关键词： Machine learning Internet of Things sensors ensemble learning

Facile synthesis of hierarchical NiO/NiFe2O4 microsphere composite as efficient visible photocatalyst for 2,4-DCP degradation

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Rare Metals 2024年第4期43卷 1580-1588页

作者： shabana Shaheen Shuai Xu Ji Bian Amir Zada Zi-Qing Zhang Yang Qu Li-Qiang Jing Key Laboratory of Functional Inorganic Materials Chemistry (Ministry of Education) International Joint Research Center and Lab for Catalytic TechnologySchool of Chemistry and Materials ScienceHeilongjiang University Department of Chemistry Abdul Wali Khan University

It is highly desired to develop efficient photocatalysts with recycling property for practical application to degrade toxic pollutants.Herein,nanosheet-assembled NiFe2O4microspheres with commendable activity are successfully synthesized by a facile solvothermal reaction with NH4F as the modifier,and their photoactivities are further improved by coupling with NiO through an in situ growth process.The optimized nickel oxide（NiO）/nickel ferrite（NiFe2O4） microsphere composite（5NiO/NFO-4）exhibits a satisfactory photocatalytic activity for 2,4-dichlorophenol（2,4-DCP） degradation under visible-light irradiation,which is attributed to its wide visible-light response,well-designed hierarchical structure and enhanced charge transfer and separation by coupling NiO as a high-level energy platform to accept electrons.Moreover,it is found that the NiO/NiFe2O4microsphere photocatalysts can be easily collected and recycled owing to the distinctive magnetic properties.This work provides a feasible route to rational design visible-light-driven photocatalysts with high-activity for environmental remediation and purification with good recyclability.

关键词： NiFe 2 O 4 microspheres NiO/NiFe 2 O 4 composite Charge separation Visible-light photocatalysis 2,4-Dichlorophenol degradation

Nominal geometry and force measures for solids and fluids

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International Journal of Mechanical System Dynamics 2022年第3期2卷 249-252页

作者： Ahmed A.shabana Department of Mechanical and Industrial Engineering University of Illinois at ChicagoChicagoIllinoisUSA

Understanding solid‐and fluid‐inertia forces and their coupling with the gravity potential in complex motion scenarios is necessary for evaluating system stability and identifying root causes of system failure and accidents.Because solids and fluids have an infinite number of degrees of freedom and distributed inertia and elasticity,having meaningful qualitative and quantitative nominal measures of the kinematics and forces will contribute to a better understanding of the system dynamics.This paper proposes developing new continuum‐based nominal measures for the characterization of the oscillations and forces.By using a material‐point approach,these new nominal measures,which have their roots in the continuum‐mechanics partial‐differential equations of equilibrium and Frenet geometry,are independent of the formulation or generalized coordinates used to develop the dynamic equations of motion.The paper proposes a data‐driven‐science approach to define a nominal continuum space‐curve geometry with nominal curvature and torsion;a nominal instantaneous motion plane(IMP),which contains the resultant of all forces including the inertia forces;and a nominal instantaneous zero‐force axis(IZFA)along which the resultant of all forces vanishes.While using the material‐point approach eliminates the need for introducing moment equations associated with orientation coordinates,the IMP and IZFA concepts can be used to define the instantaneous axis of significant moment components,which can lead to accidents such as in the case of vehicle rollovers.

关键词： nominal geometry and force measures instantaneous motion plane instantaneous zero-force axis Frenet geometry nominal continuum mechanics measures

Fuzzy User Access Trust Model for Cloud Access Control

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Computer Systems Science & Engineering 2023年第1期44卷 113-128页

作者： Aakib Jawed Khan shabana Mehfuz Department of Electrical Engineering Jamia Millia IslamiaNew Delhi110025India

Cloud computing belongs to a set of policies,protocols,technologies through which one can access shared resources such as storage,applications,net-works,and services at relatively low cost.Despite the tremendous advantages of cloud computing,one big threat which must be taken care of is data security in the cloud.There are a dozen of threats that we are being exposed to while avail-ing cloud services.Insufficient identity and access management,insecure inter-faces and Applications interfaces(APIs),hijacking,advanced persistent threats,data threats,and many more are certain security issues with the cloud platform.APIs and service providers face a huge challenge to ensure the security and integ-rity of both network and data.To overcome these challenges access control mechanisms are employed.Traditional access control mechanisms fail to monitor the user operations on the cloud platform and are prone to attacks like IP spoofing and other attacks that impact the integrity of the data.For ensuring data integrity on cloud platforms,access control mechanisms should go beyond authentication,identification,and authorization.Thus,in this work,a trust-based access control mechanism is proposed that analyzes the data of the user behavior,network beha-vior,demand behavior,and security behavior for computing trust value before granting user access.The method that computes thefinal trust value makes use of the fuzzy logic algorithm.The trust value-based policies are defined for the access control mechanism and based on the trust value outcome the access control is granted or denied.

关键词： Cloud architecture fuzzy logic trust-based access mechanism

A Constant Gain and Miniaturized Antipodal Vivaldi Antenna for 5G Communication Applications

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Computers, Materials & Continua 2022年第12期73卷 4909-4921页

作者： Amruta SDixit Sumit Kumar shabana Urooj Symbiosis Institute of Technology Symbiosis International(Deemed University)Pune412115India Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

This paper proposes a stable gain and a compact Antipodal Vivaldi Antenna(AVA)for a 38GHz band of 5G communication.A novel compact AVA is designed to provide constant gain,high front to back ratio(FBR),and very high efficiency.The performance of the proposed AVA is enhanced with the help of a dielectric lens(DL)and corrugations.A rectangular-shaped DL is incorporated in conventional AVA(CAVA)to enhance its gain up to 1 dBi and the bandwidth by 1.8 GHz.Next,the rectangular corrugations are implemented in CAVA with lens(CAVA-L)to further improve the gain and bandwidth.The proposed AVA with lens and corrugations(AVA-LC)gives a constant and high gain of 8.2 to 9 dBi.The designed AVA-LC operates from 34 to 45GHz frequency which covers 38GHz(37.5 to 43.5 GHz)band of 5G applications.Further,the presented AVA-LC mitigates the back lobe and sidelobe levels,resulting in FBR and efficiency improvement.The FBR is in the range of 12.2 to 22 dB,and efficiency is 99%,almost constant.The AVA-LC is fabricated on Roger’s RT/duroid 5880 substrate,and it is tested to verify the simulated results.The proposed compact AVA-LC with high gain,an improved FBR,excellent efficiency,and stable radiation patterns is suitable for the 38GHz band of 5G devices.

关键词： Antipodal Vivaldi Antenna(AVA) constant gain dielectric lens(DL) 5G communication corrugations front to back ratio(FBR)

Novel Computer-Aided Diagnosis System for the Early Detection of Alzheimer’s Disease

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Computers, Materials & Continua 2023年第3期74卷 5483-5505页

作者： Meshal Alharbi shabana R.Ziyad Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl KharjSaudi Arabia

Aging is a natural process that leads to debility,disease,and dependency.Alzheimer’s disease(AD)causes degeneration of the brain cells leading to cognitive decline and memory loss,as well as dependence on others to fulfill basic daily needs.AD is the major cause of dementia.Computer-aided diagnosis(CADx)tools aid medical practitioners in accurately identifying diseases such as AD in patients.This study aimed to develop a CADx tool for the early detection of AD using the Intelligent Water Drop(IWD)algorithm and the Random Forest(RF)classifier.The IWD algorithm an efficient feature selection method,was used to identify the most deterministic features of AD in the dataset.RF is an ensemble method that leverages multiple weak learners to classify a patient’s disease as either demented(DN)or cognitively normal(CN).The proposed tool also classifies patients as mild cognitive impairment(MCI)or CN.The dataset on which the performance of the proposed CADx was evaluated was sourced from the Alzheimer’s Disease Neuroimaging Initiative(ADNI).The RF ensemble method achieves 100%accuracy in identifying DN patients from CN patients.The classification accuracy for classifying patients as MCI or CN is 92%.This study emphasizes the significance of pre-processing prior to classification to improve the classification results of the proposed CADx tool.

关键词： Alzheimer’s disease dementia mild cognitive impairment computer-aided diagnosis intelligent water drop algorithm random forest

Learning Patterns from COVID-19 Instances

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Computer Systems Science & Engineering 2022年第2期40卷 765-777页

作者： Rehan Ullah Khan Waleed Albattah Suliman Aladhadh shabana Habib Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

Coronavirus disease,which resulted from the SARS-CoV-2 virus,has spread worldwide since early 2020 and has been declared a pandemic by the World Health Organization(WHO).Coronavirus disease is also termed COVID-19.It affects the human respiratory system and thus can be traced and tracked from the Chest X-Ray images.Therefore,Chest X-Ray alone may play a vital role in identifying COVID-19 cases.In this paper,we propose a Machine Learning(ML)approach that utilizes the X-Ray images to classify the healthy and affected patients based on the patterns found in these images.The article also explores traditional,and Deep Learning(DL)approaches for COVID-19 patterns from Chest X-Ray images to predict,analyze,and further understand this virus.The experimental evaluation of the proposed approach achieves 97.5% detection performance using the DL model for COVID-19 versus normal cases.In contrast,for COVID-19 versus Pneumonia Virus scenario,we achieve 94.5% accurate detections.Our extensive evaluation in the experimental section guides and helps in the selection of an appropriate model for similar tasks.Thus,the approach can be used for medical usages and is particularly pertinent in detecting COVID-19 positive patients using X-Ray images alone.

关键词： Coronavirus COVID-19 machine learning deep learning convolutional neural network

Diagnosis of Autism Spectrum Disorder by Imperialistic Competitive Algorithm and Logistic Regression Classifier

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Computers, Materials & Continua 2023年第11期77卷 1515-1534页

作者： shabana R.Ziyad Liyakathunisa Eman Aljohani I.A.Saeed Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl Kharj16274Saudi Arabia Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah41411Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl Kharj16274Saudi Arabia

Autism spectrum disorder(ASD),classified as a developmental disability,is now more common in children than ever.A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection of autism in children.Parents can seek professional help for a better prognosis of the child’s therapy when ASD is diagnosed under five years.This research study aims to develop an automated tool for diagnosing autism in children.The computer-aided diagnosis tool for ASD detection is designed and developed by a novel methodology that includes data acquisition,feature selection,and classification phases.The most deterministic features are selected from the self-acquired dataset by novel feature selection methods before classification.The Imperialistic competitive algorithm(ICA)based on empires conquering colonies performs feature selection in this study.The performance of Logistic Regression(LR),Decision tree,K-Nearest Neighbor(KNN),and Random Forest(RF)classifiers are experimentally studied in this research work.The experimental results prove that the Logistic regression classifier exhibits the highest accuracy for the self-acquired dataset.The ASD detection is evaluated experimentally with the Least Absolute Shrinkage and Selection Operator(LASSO)feature selection method and different classifiers.The Exploratory Data Analysis(EDA)phase has uncovered crucial facts about the data,like the correlation of the features in the dataset with the class variable.

关键词： Autism spectrum disorder feature selection imperialist competitive algorithm LASSO logistic regression random forest

Computation of Stiffness and Damping Derivatives of an Ogive in a Limiting Case of Mach Number and Specific Heat Ratio

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Fluid Dynamics & Materials Processing 2023年第5期19卷 1249-1267页

作者： Aysha shabana Asha Crasta Sher Afghan Khan Abdul Aabid Muneer Baig Department of Mathematics Mangalore Institute of Technology and EngineeringMoodabidri574225India Department of Mathematics Sahyadri College of Engineering&ManagementMangalore575007India Department of Mechanical and Aerospace Engineering Faculty of EngineeringInternational Islamic UniversityKuala Lumpur53100Malaysia Department of Engineering Management College of EngineeringPrince Sultan UniversityRiyadh11586Saudi Arabia

This work aims to compute stability derivatives in the Newtonian limit in pitch when the Mach number tends to infinity.In such conditions,these stability derivatives depend on the Ogive’s shape and not the Mach number.Generally,the Mach number independence principle becomes effective from M=10 and above.The Ogive nose is obtained through a circular arc on the cone surface.Accordingly,the following arc slopes are consideredλ=5,10,15,−5,−10,and−15.It is found that the stability derivatives decrease due to the growth inλfrom 5 to 15 and vice versa.Forλ=5 and 10,the damping derivative declines with an increase inλfrom 5 to 10.Yet,for the damping derivatives,the minimum location remains at a pivot position,h=0.75 for large values ofλ.Hence,whenλ=−15,the damping derivatives are independent of the cone angles for most pivot positions except in the early twenty percent of the leading edge.

关键词： Aerodynamic stability derivative Mach number specific heat ratio Ogive