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Efficient Deep CNN Model for COVID-19 Classification

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 *** Health Organization(WHO)stated that the COVID-19 is an epidemic that causes a 3.4%death *** X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis *** are numerous ways to identify positive COVID-19 *** of the fundamental ways is radiology imaging through CXR,or CT *** comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high ***,automated classification techniques are required to facilitate the diagnosis *** Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical *** deep Convolutional Neural Networks(CNNs)can learn and extract essential features from different medical image *** this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is *** activation functions as well as three optimizers are tested and compared for this *** proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train *** performance is tested and investigated on the CT and CXR *** activation functions:Tanh,Sigmoid,and ReLU are compared using a constant learning rate and different batch *** optimizers are studied with different batch sizes and a constant learning ***,a comparison between different combinations of activation functions and optimizers is presented,and the optimal configuration is ***,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 *** 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 an

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 *** sub-region has a group of pixels having the same characteristics,such as texture or *** 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)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** 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 *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,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 *** 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 *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(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 *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** 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)*** 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 *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** 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 ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the ReLU as a basic *** a result,it attained a considerable improvement over the traditional *** 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 *** 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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A secure image steganography algorithm based on least significant bit and integer wavelet transform

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Journal of Systems Engineering and Electronics 2018年第3期29卷 639-649页

作者： ELSHAZLY Emad ABDELWAHAB Safey ABOUZAID Refaat zahran osama ELARABY Sayed ELKORDY Mohamed Engineering Department Nuclear Research CenterAtomic Energy AuthorityCairo 11787Egypt Electronics and Electrical Communications Engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt

The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.

关键词： image steganography image processing integer wavelet transform

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Optimizing Resource Allocation framework for Multi-Cloud Environment

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Computers, Materials & Continua 2023年第5期75卷 4119-4136页

作者： Tahir Alyas Taher M.Ghazal Badria Sulaiman Alfurhood Ghassan f.Issa osama Ali Thawabeh Qaiser Abbas Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Information Technology Skyline University CollegeUniversity City Sharjah1797SharjahUAE Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebansaan Malaysia(UKM)43600BangiSelangorMalaysia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia Skyline University College University City Sharjah1797SharjahUAE faculty of Computer and Information Systems Islamic University of Madinah Madinah42351Saudi Arabia

Cloud computingmakes dynamic resource provisioning more *** a functioning service is crucial,and changes are made when particular criteria are *** research explores the decentralized multi-cloud environment for allocating resources and ensuring the Quality of Service(QoS),estimating the required resources,and modifying allotted resources depending on workload and parallelism due to *** allocation is a complex challenge due to the versatile service providers and resource *** engagement of different service and resource providers needs a cooperation strategy for a sustainable quality of *** objective of a coherent and rational resource allocation is to attain the quality of *** also includes identifying critical parameters to develop a resource allocation mechanism.A framework is proposed based on the specified parameters to formulate a resource allocation process in a decentralized multi-cloud *** three main parameters of the proposed framework are data accessibility,optimization,and *** an optimization technique,these three segments are further divided into subsets for resource allocation and long-term service *** CloudSim simulator has been used to validate the suggested *** experiments have been conducted to find the best configurations suited for enhancing collaboration and resource allocation to achieve sustained *** results support the suggested structure for a decentralized multi-cloud environment and the parameters that have been determined.

关键词： Multi-cloud query optimization cloud resources allocation modelling virtualization

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On Modules Satisfying S-Noetherian Spectrum Condition

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Communications in Mathematics and Statistics 2023年第3期11卷 649-662页

作者： MehmetÖzen osama A.Naji Ünsal Tekir Suat Koç Department of Mathematics Sakarya UniversitySakaryaTurkey Department of Mathematics Marmara UniversityIstanbulTurkey

Let R be a commutative ring having nonzero identity and M be a unital *** that S⊆R is a multiplicatively closed subset of ***,M satisﬁes S-Noetherian spectrum condition if for each submodule N of M,there exist s∈S and aﬁnitely generated submodule f⊆N such that sN⊆radM(f),where radM(f)is the prime radical of f in the sense(McCasland and Moore in Commun Algebra 19(5):1327–1341,1991).Besides giving many properties and characterizations of S-Noetherian spectrum condition,we prove an analogous result to Cohen’s theorem for modules satisfying S-Noetherian spectrum ***,we characterize modules having Noetherian spectrum in terms of modules satisfying the S-Noetherian spectrum condition.

关键词： Noetherian modules S-Noetherian modules Noetherian spectrum S-Noetherian spectrum condition

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floc meal as potential substitute for soybean meal in tilapia diets under biofloc system conditions

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Journal of Oceanology and Limnology 2019年第1期37卷 313-320页

作者： Rania S. MABROKE osama M. EL-HUSSEINY Abd El-Naem f. A. ZIDAN Al-Azab TAHOUN Ashraf SULOMA fish Nutrition Laboratory (fNL) Animal Production Department Faculty of Agriculture Cairo University Aquaculture Department Faculty of Fish ResourcesSuez University

This study was conducted to evaluate the ef fect of replacing soybean meal(SBM) by low protein ?oc meal(LPfM; 24% CP) in tilapia diets on growth performance, feed utilization and ?sh chemical composition. Three isonitrogenous and isocaloric diets were formulated; control diet(C; without LPfM),fM 25(25% of SBM protein was substituted by LPfM) and fM 50(50% of SBM protein was substituted by LPfM). Nine 55 l circular plastic tanks were stocked by 12 ?sh to form three experimental *** dif ferences in tilapia performance were observed between the control and the fM 25 diet. Chemical composition of ?sh did not dif fer signi?cantly among treatments except for protein and selenium contents where the highest values were recorded in the control treatment. The highest mineral content was recorded in ?oc collected from the control tanks, while calcium content showed its highest value in ?oc collected from fM 50 e ? uent. These data indicate that replacing soybean meal with LPfM up to 25%, had no negative ef fect on growth performance and potentially may improve the system sustainability. Meanwhile, the adverse ef fect of more inclusion of LPfM in tilapia diet may be attributed to the higher content of ash. In other word,minerals seem to cause more energy utilization in ?sh fed ?oc meal since it is needed to maintain osmotic homeostasis.

关键词： microbial flocs alternative protein sources tilapia diet sustainability

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An Optimized Approach for Spectrum Utilization in mmWave Massive MIMO 5G Wireless Networks

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Computer Systems Science & Engineering 2023年第11期47卷 1493-1505页

作者： Elsaid Md.Abdelrahim Mona Alduailij Mai Alduailij Romany f.Mansour osama A.Ghoneim faculty of Science Northern Border UniversityArarSaudi Arabia faculty of Science Tanta UniversityTantaEgypt Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt faculty of Computers and Information Tanta UniversityEl-GieshEgypt

Massive multiple-input multiple-output(MIMO)systems that use the millimeter-wave(mm-wave)band have a higher frequency and more antennas,which leads to significant path loss,high power consumption,and server *** to these issues,the spectrum efficiency is significantly reduced,making spectral efficiency improvement an important research topic for 5G *** with communication in the terahertz(THz)bands,mmWave communication is currently a component of the 5G standards and is seen as a solution to the commercial bandwidth *** quantity of continuous,mostly untapped bandwidth in the 30–300 GHz band has presented a rare opportunity to boost the capacity of wireless *** wireless communications and consumer electronics industries have recently paid a lot of attention to wireless data transfer and media streaming in the mmWave frequency *** massive MIMO beamforming technology cannot successfully prevent interference between multiple networks in the current spectrum-sharing schemes,particularly the complex interference dispersed in indoor communication systems such as homes,workplaces,and *** effectively improve spectrum utilization and reduce co-channel interference,this paper proposes a novel *** main idea is to utilize the spectrum in software-defined mmWave massive MIMO networks through coordinated and unified ***,the optimal interference threshold is determined through the beam alignment ***,a greedy optimization algorithm is used to allocate optimal spectral resources to the *** results show that the proposed algorithm improved spectral efficiency and reduced interference.

关键词： mmWave massive MIMO 5G networks SDN spectral efficiency

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A Novel Inherited Modeling Structure of Automatic Brain Tumor Segmentation from MRI

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Computers, Materials & Continua 2022年第11期73卷 3983-4002页

作者： Abdullah AAsiri Tariq Ali Ahmad Shaf Muhammad Aamir Muhammad Shoaib Muhammad Irfan Hassan A.Alshamrani fawaz f.Alqahtani osama M.Alshehri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Informatics and Systems University of Management and TechnologyLahore54000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Clinical Laboratory Sciences Collage of Applied Medical ScienceNajran UniversityNajranSaudi Arabia

Brain tumor is one of the most dreadful worldwide types of cancer and affects people leading to *** resonance imaging methods capture skull images that contain healthy and affected *** checked the affected tissue in the slice-by-slice manner,which was timeconsuming and hectic ***,auto segmentation of the affected part is needed to facilitate ***,we have considered a hybrid model that inherits the convolutional neural network(CNN)properties to the support vector machine(SVM)for the auto-segmented brain tumor *** CNN model is initially used to detect brain tumors,while SVM is integrated to segment the tumor region *** proposed method was evaluated on a publicly available BraTS2020 *** statistical parameters used in this work for the mathematical measures are precision,accuracy,specificity,sensitivity,and dice ***,our method achieved an accuracy value of 0.98,which is most prominent than existing ***,the proposed approach is more suitable for medical experts to diagnose the early stages of the brain tumor.

关键词： Brain tumor support vector machine convolutional neural network BraTS classification

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