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Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

Applied Mathematics and Mechanics(English Edition) 2024年第4期45卷 633-648页

作者： E.GHAVANLOO s.el-BORGI school of Mechanical Engineering Shiraz UniversityShiraz 71963-16548Iran Mechanical Engineering Program Texas A&M University at QatarDoha 23874Qatar

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMs)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

关键词： nonlinear mass-spring chain discrete model continuum model LindstedtPoincare method(LPM) method of multiple scales(MMs) dispersion phase velocity

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Facies development and sedimentology of the Middle Miocene carbonates of the Raghama Formation, northeastern saudi Arabia

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Acta Geochimica 2024年第1期43卷 87-96页

作者： Mansour H.Al-Hashim Abdelbaset s.el-sorogy Meshal Wadani Department of Geology and Geophysics College of ScienceKing Saud University2455Riyadh 11451Saudi Arabia

Ragahama Formation comprises a siliciclastic continental deposits followed by marine carbonates, representing prograding alluvial fans from adjacent high hinterlands seaward into lagoons and fringing reef environments. The present work aimed to document the facies development and sedimentology of the Raghama carbonates exposed along the eastern coastal plain of the Red sea, northwestern saudi Arabia. Four stratigraphic sections were measured and sampled(D1–D4) and thin sections and major and trace element analyses were prepared and applied for petrographic and geochemical approaches. The carbonates were subdivided into three successive fore-reef, reef-core, and back-reef depositional facies. sandy stromatolitic boundstone, microbial laminites, dolomitic ooidal grainstone, bioclastic coralline algal wackestone, sandy bioclastic wackestone, and coral boundstones were the reported microfacies types. Petrographic analysis reveals that the studied carbonates were affected by dissolution, dolomitization, and aggrading recrystallization, which affects both the original micrite matrix and grains or acts as fracture and veinlet filling leading to widespread vuggy and moldic porosity. No evidence of physical compaction, suggesting rapid lithification and recrystallization during early diagenesis and prior to substantial burial and intensive flushing by meteoric waters. Most of the original microstructure of corals were leached and destructed. This is indicated by the higher depletion in sr and Ca levels and increase in Mg,Na, Fe, and Mn levels, especially in section D1, in comparison with the worldwide carbonates.

关键词： Raghama Formation Miocene Diagenesis Geochemistry saudi Arabia

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Optical Ciphering scheme for Cancellable speaker Identification system

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Computer systems science & Engineering 2023年第4期45卷 563-578页

作者： Walid el-shafai Marwa A.elsayed Mohsen A.Rashwan Moawad I.Dessouky adel s.el-fishawy Naglaa F.soliman Amel A.Alhussan Fathi EAbd el-samie Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of electronics and Communications Faculty of EngineeringCairo UniversityCairoEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Most current security and authentication systems are based on personal biometrics.The security problem is a major issue in the field of biometric systems.This is due to the use in databases of the original biometrics.Then biometrics will forever be lost if these databases are attacked.Protecting privacy is the most important goal of cancelable biometrics.In order to protect privacy,therefore,cancelable biometrics should be non-invertible in such a way that no information can be inverted from the cancelable biometric templates stored in personal identification/verification databases.One methodology to achieve non-invertibility is the employment of non-invertible transforms.This work suggests an encryption process for cancellable speaker identification using a hybrid encryption system.This system includes the 3D Jigsaw transforms and Fractional Fourier Transform(FrFT).The proposed scheme is compared with the optical Double Random Phase Encoding(DRPE)encryption process.The evaluation of simulation results of cancellable biometrics shows that the algorithm proposed is secure,authoritative,and feasible.The encryption and cancelability effects are good and reveal good performance.Also,it introduces recommended security and robustness levels for its utilization for achieving efficient cancellable biometrics systems.

关键词： Cancellable biometrics jigsaw transform FrFT DRPE speaker identification

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Efficient Deep CNN Model for COVID-19 Classification

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Computers, Materials & Continua 2022年第3期70卷 4373-4391页

作者： Walid el-shafai Amira A.Mahmoud el-sayed M.el-Rabaie Taha E.Taha Osama F.Zahran adel s.el-fishawy Mohammed Abd-elnaby Fathi E.Abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Coronavirus(COVID-19)infection was initially acknowledged as a global pandemic in Wuhan in China.World Health Organization(WHO)stated that the COVID-19 is an epidemic that causes a 3.4%death rate.Chest X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis applications.There are numerous ways to identify positive COVID-19 cases.One of the fundamental ways is radiology imaging through CXR,or CT images.The comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high quality.Hence,automated classification techniques are required to facilitate the diagnosis process.Deep Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical images.The deep Convolutional Neural Networks(CNNs)can learn and extract essential features from different medical image datasets.In this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is offered.Three activation functions as well as three optimizers are tested and compared for this task.The proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train it.The performance is tested and investigated on the CT and CXR datasets.Three activation functions:Tanh,sigmoid,and RelU are compared using a constant learning rate and different batch sizes.Different optimizers are studied with different batch sizes and a constant learning rate.Finally,a comparison between different combinations of activation functions and optimizers is presented,and the optimal configuration is determined.Hence,the main objective is to improve the detection accuracy of COVID-19 from CXR and CT images using DL by employing CNNs to classify medical COVID-19 images in an early stage.The proposed model achieves a classification accuracy of 91.67%on CXR image dataset,and a classification accuracy of 100%on CT dataset with training times of 58 min and 46 min on CXR and CT datasets,respectively.The best results are

关键词： COVID-19 image classification CNN DL activation functions optimizers

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Hybrid segmentation Approach for Different Medical Image Modalities

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Computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid el-shafai Amira A.Mahmoud el-sayed M.el-Rabaie Taha E.Taha Osama F.Zahran adel s.el-fishawy Naglaa F.soliman Amel A.Alhussan Fathi E.Abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar properties.Each sub-region has a group of pixels having the same characteristics,such as texture or intensity.This paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PsO)and improved fast fuzzy C-means clustering(IFFCM)algorithms.An extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation techniques.The existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed algorithms.This paper extensively analyzes and summarizes the comparative investigation of these techniques.Finally,a prediction of the improvement involves the combination of these techniques is suggested.The obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PET images MR images fuzzy c-mean morphological operations active contour

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Efficient segmentation Approach for Different Medical Image Modalities

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Computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid el-shafai Amira A.Mahmoud el-sayed M.el-Rabaie Taha E.Taha Osama F.Zahran adel s.el-fishawy Naglaa F.soliman Amel A.Alhussan Fathi E.Abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical images.The paper provides a solid introduction to image enhancement along with image segmentation fundamentals.In the first step,the morphological operations are employed to ensure image detail protection and noise-immunity.The objective of using morphological operations is to remove the defects in the texture of the image.secondly,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster centers.The proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster centers.It is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition matrix.simulation results are performed on different medical image modalities.Ultrasonic(Us),X-ray(Mammogram),Computed Tomography(CT),Positron Emission Tomography(PET),and Magnetic Resonance(MR)images are the main medical image modalities used in this work.The obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image segmentation.simulation results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PET,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PET MRI morphological operations FCM active contours

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Deep CNN Model for Multimodal Medical Image Denoising

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Computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid el-shafai Amira A.Mahmoud Anas M.Ali el-sayed M.el-Rabaie Taha E.Taha Osama F.Zahran adel s.el-fishawy Naglaa F.soliman Amel A.Alhussan Fathi E.Abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the single Image(sI)techniques.In the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the sI techniques.sI denoising techniques can be carried out both in a transform or spatial domain.This paper is concerned with single-image noise reduction techniques because we deal with single medical images.The most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,Frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,speckle reducing anisotropic diffusion(sRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are studied.Also,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are investigated.Finally,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and speckle noises in different medical image modalities.This model utilizes the Batch Normalization(BN)and the RelU as a basic structure.As a result,it attained a considerable improvement over the traditional techniques.The previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak signal-to-Noise Ratio(PsNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied universally.Based on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

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Mafic and felsic magmatism in the Wadi Kalalat area, south Eastern Desert, Egypt: mineralogy, geochemistry and geodynamic evolution during the Neoproterozoic in the Nubian shield

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Acta Geochimica 2024年第1期43卷 150-173页

作者： adel A.surour Ahmed A.Madani Mohamed A.el-sobky Faculty of science Galala UniversityNew Galala CitySuez 43511Egypt Department of Geology Faculty of ScienceCairo UniversityGiza 12613Egypt Egyptian Mineral Resources Authority P.O.Box 11517AbbasiyaCairoEgypt

In the south Eastern Desert of Egypt,two contrasting types of magmatism(mafic and felsic) are recorded in the Wadi Kalalat area,and form the Gabal el Motaghiarat and Gabal Batuga intrusions,respectively.The two intrusions post-dates ophiolitic and arc associations represented by serpentinite and metagabbro-diorite,respectively.The mafic intrusion has a basal ultramafic member represented by fresh peridotite,which is followed upward by olivine gabbro and anorthositic or leucogabbro.This mafic intrusion pertains to the Alaskan-type mafic-ultramafic intrusions in the Arabian-Nubian shield(ANs)being of tholeiitic nature and emplaced in a typical arc setting.On the other hand,the Gabal Batuga intrusion comprises three varieties of fresh A-type granites of high K-calc alkaline nature,which is peraluminous and garnetbearing in parts.A narrow thermal aureole in the olivine gabbro of the mafic intrusion was developed due to the intrusion of the Batuga granites.This results in the development of a hornfelsic melagabbro variety in which the composition changed from tholeiitic to a calc-alkaline composition due to the addition of s_(i)O_(2),Al_(2)O_(3),alkalis,lithosphile elements(LILEs) such as Rb(70 ppm) and Y(28 ppm) from the felsic intrusion.Outside the thermal aureole,Rb amounts 2-8 ppm and Y lies in the range s believed that the Gabal Batuga felsic intrusion started to emplace during the waning stage of an arc system,with transition from the pre-collisional(i.e.,arc setting) to post-collisional and within plate settings.Magma from which the Gabal Batuga granites were fractionated is high-K calc-alkaline giving rise to a typical post-collisional A-type granite(A_(2)-subtype) indicating an origin from an underplating crustal source.Accordingly,it is stressed here that the younger granites in the ANs are not exclusively post-collisional and within-plate but most likely they started to develop before closure of the arc system.The possible source(s) of mafic magmas that resulted in the formation of the two intru

关键词： Wadi Kalalat Gabal el Motaghairat mafic intrusion Gabal Batuga felsic intrusion Arc setting Post-collision Within-plate

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Improved Manta Ray Foraging Optimizer-based sVM for Feature selection Problems:A Medical Case study

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Journal of Bionic Engineering 2024年第1期21卷 409-425页

作者： adel Got Djaafar Zouache Abdelouahab Moussaoui Laith Abualigah Ahmed Alsayat Faculty of informatics University of Science and Technology Houari BoumedieneAlgiersAlgeria LRIA Laboratory University of Science and Technology Houari BoumedieneAlgiersAlgeria Computer science Department University of Mohamed El Bachir El IbrahimiBordj Bou ArreridjAlgeria Computer science Department University of Ferhat AbbasSetifAlgeria Computer science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq 25113Jordan Department of Computer science College of Computer and Information SciencesJouf UniversityJoufSaudi Arabia Department of electrical and Computer Engineering Lebanese American University13-5053ByblosLebanon Hourani Center for Applied scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied science research center Applied science private universityAmman 11931Jordan school of Computer sciences Universiti Sains Malaysia11800 PenangMalaysia school of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

support Vector Machine(sVM)has become one of the traditional machine learning algorithms the most used in prediction and classification tasks.However,its behavior strongly depends on some parameters,making tuning these parameters a sensitive step to maintain a good performance.On the other hand,and as any other classifier,the performance of sVM is also affected by the input set of features used to build the learning model,which makes the selection of relevant features an important task not only to preserve a good classification accuracy but also to reduce the dimensionality of datasets.In this paper,the MRFO+sVM algorithm is introduced by investigating the recent manta ray foraging optimizer to fine-tune the sVM parameters and identify the optimal feature subset simultaneously.The proposed approach is validated and compared with four sVM-based algorithms over eight benchmarking datasets.Additionally,it is applied to a disease Covid-19 dataset.The experimental results show the high ability of the proposed algorithm to find the appropriate sVM’s parameters,and its acceptable performance to deal with feature selection problem.

关键词： support vector machine Parameters tuning Feature selection Bioinspired algorithms Manta ray foraging optimizer

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Novel design of a compact tunable dual band wireless power transfer(TDB-WPT)system for multiple WPT applications

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Frontiers of Information Technology & electronic Engineering 2024年第4期25卷 616-628页

作者： Hany A.ATALLAH Rasha Hussein AHMED adel B.ABDel-RAHMAN Department of Communications and electronics Faculty of EngineeringSouth Valley UniversityQena 83523Egypt Egypt-Japan University of science and Technology Alexandria 21934Egypt

In this study we present the design and realization of a tunable dual band wireless power transfer(TDB-WPT)coupled resonator system.The frequency response of the tunable band can be controlled using a surface-mounted varactor.The transmitter(Tx)and the receiver(Rx)circuits are symmetric.The top layer contains a feed line with an impedance of 50Ω.Two identical half rings defected ground structures(HR-DGss)are loaded on the bottom using a varactor diode.We propose a solution for restricted WPT systems working at a single band application according to the operating frequency.The effects of geometry,orientation,relative distance,and misalignments on the coupling coefficients were studied.To validate the simulation results,the proposed TDB-WPT system was fabricated and tested.The system occupied a space of 40 mm×40 mm.It can deliver power to the receiver with an average coupling efficiency of 98%at the tuned band from 817 to 1018 MHz and an efficiency of 95%at a fixed band of 1.6 GHz at a significant transmission distance of 22 mm.The results of the measurements accorded well with those of an equivalent model and the simulation.

关键词： Defected ground structure(DGs) surface-mounted Tunable dual band wireless power transfer(TDB-WPT) Varactor

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