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An Efficient Breast Cancer Detection Framework for Medical Diagnosis Applications

Computers, Materials & Continua 2022年第1期70卷 1315-1334页

作者： naglaa F.soliman naglaa s.ali Mahmoud I.Aly Abeer D.Algarni Walid El-shafai Fathi E.Abd El-samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt International Academy for Engineering and Media science October CityEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Breast cancer is themost common type of cancer,and it is the reason for cancer death toll in women in recent *** diagnosis is essential to handle breast cancer patients for treatment at the right *** with mammography is the preferred examination for breast cancer,as it is available worldwide and ***-Aided Detection(CAD)systems are used to analyze medical images to detect breast cancer,*** death rate of cancer patients has decreased by detecting tumors early and having appropriate treatment after *** of mammogram images has four main steps:pre-processing,segmentation of the region of interest,feature extraction and classification of the images into normal or abnormal *** paper presents an efficient framework for processing of mammogram images and introduces an algorithm for segmentation of the images to detect *** pre-processing step of mammogram images includes removal of digitization noise using a 2D median filter,removal of artifacts using morphological operations,and contrast enhancement using a fuzzy enhancement *** proposed fuzzy image enhancement technique is analyzed and compared with conventional techniques based on an Enhancement Measure(EME)and local contrast *** comparison shows an outstanding performance of the proposed technique from the visual and numerical *** segmentation process is performed using Otsu’smultiple thresholding *** method segments the image regions into five classes with variable intensities using four *** effectiveness is measured based on visual quality of the segmentation output,as it gives details about the image and positions of *** performance of the proposed framework is measured using Dice coefficient,Hausdorff,and Peak signal-to-Noise Ratio(PsNR)*** segmented tumor region with the proposed segmentation method is 81%of the ground truth region provided by an ***,the proposed framew

关键词： Breast cancer mammogram images CAD contrast enhancement fuzzy logic segmentation

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COVID-19 Classification from X-Ray Images:An Approach to Implement Federated Learning on Decentralized Dataset

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Computers, Materials & Continua 2023年第5期75卷 3883-3901页

作者： ali Akbar siddique s.M.Umar Talha M.Aamir Abeer D.Algarni naglaa F.soliman Walid El-shafai Department of Telecommunication Engineering Sir Syed University of Engineering&TechnologyKarachi75300Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The COVID-19 pandemic has devastated our daily lives,leaving horrific repercussions in its *** to its rapid spread,it was quite difficult for medical personnel to diagnose it in such a big *** who test positive for Covid-19 are diagnosed via a nasal PCR *** comparison,polymerase chain reaction(PCR)findings take a few hours to a few *** PCR test is expensive,although the government may bear expenses in certain ***,subsets of the population resist invasive testing like ***,chest X-rays or Computerized Vomography(CT)scans are preferred in most cases,and more importantly,they are non-invasive,inexpensive,and provide a faster response *** advances in Artificial Intelligence(AI),in combination with state-of-the-art methods,have allowed for the diagnosis of COVID-19 using chest *** article proposes a method for classifying COVID-19 as positive or negative on a decentralized dataset that is based on the Federated learning *** order to build a progressive global COVID-19 classification model,two edge devices are employed to train the model on their respective localized dataset,and a 3-layered custom Convolutional Neural Network(CNN)model is used in the process of training the model,which can be deployed from the *** two edge devices then communicate their learned parameter and weight to the server,where it aggregates and updates the *** proposed model is trained using an image dataset that can be found on *** are more than 13,000 X-ray images in Kaggle Database collection,from that collection 9000 images of Normal and COVID-19 positive images are *** edge node possesses a different number of images;edge node 1 has 3200 images,while edge node 2 has *** is no association between the datasets of the various nodes that are included in the *** doing it in this manner,each of the nodes will have access to a separate image collection that has no correl

关键词： Artificial intelligence deep learning federated learning COVID-19 decentralized image dataset

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Gene expression of 49 kDa apyrase,cytoskeletal proteins,ATPase,ADPase and amino acid contents of Pisum sativum(L.)cells germinated in Euryops arabicus(*** Jaub.&spach)water extract

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BIOCELL 2019年第2期43卷 81-87页

作者： MAHMOUD MOUsTAFA sAAD ALAMRI HOIDA ZAKI naglaa LOUTFY TAREK TAHA ali sHATI MOHAMED ALKAHTANI sAJDA sIDDIQI Department of Biology College of ScienceKing Khalid University9004AbhaKingdom of Saudi Arabia(KSA) Department of Botany Faculty of ScienceSouth Valley UniversityQenaEgypt Environmental Biotechnology Department Genetic Engineering and Biotechnology Research Institute(GEBRI)City of Scientific Research and Technological Applications(SRTA-City)New Borg El-Arab City21934AlexandriaEgypt

The present research reports of quick and marked changes induced by plant extract of Euryops arabicus in the gene expression of 49-kDa apyrases,cytoskeletal proteins,ATPases,ADPase and amount of amino acid of pea(Pisum sativum ***).Pellets of cytoskeletals proteins(27000 xg)were probed with anti-apyrase antibody,biotinylated anti-rat,actin and alpha and beta-tubulin for Western *** and ADPase activities were determined based on the hydrolytic efficacy of adenine triphosphate and adenine *** 72 hours,the abundance of apyrases,cytoskeletal proteins and amount of amino acid in pellets of 27000 xg of germinated pea seeds in *** extracts were sharply increased than those sown in distilled *** the samples exhibited that the stems had more amount from apyrases,cytoskeletal proteins,amino acids and ATPase and ADPase activities than primary leaves and primary roots that were germinated either on *** water extract or in distilled *** on the enzyme’s capability to hydrolyse nucleotide triphosphate and nucleotide diphosphate as well as the direct association between expression of 49-kDa apyrase and cytoskeletal proteins,*** water extract had an important effect on plant germinations.

关键词： Cytoskeletal proteins ATPase ADPase Pisum sativum Euryops arabicus

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systematic framework for the efficient integration of wind technologies into buildings

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Frontiers of Architectural Research 2016年第1期5卷 1-14页

作者： Ashraf A. ELMokadem naglaa A. Megahed Dina s. Noaman Architecture and Urban Planning Department Faculty of Engineering Port-Said University Port SaidEgypt

The renewed interest that is being paid by architects, project developers and local governments to integrate wind turbines with buildings is mainly required a framework to unify much data, criteria and variables to ease the design process to many architects. Therefore, this paper introduces and elaborates the systematic framework towards the efficient integration of wind technologies into new building. Moreover, it evaluates the framework effectiveness by comparing the current status of wind technologies integration into a buitding with the suggested status if the framework is followed.

关键词： Building integratedwind technology Integration method systematic framework

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Hyperspectral Images-Based Crop Classification scheme for Agricultural Remote sensing

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Computer systems science & Engineering 2023年第7期46卷 303-319页

作者： Imran ali Zohaib Mushtaq saad Arif Abeer D.Algarni naglaa F.soliman Walid El-shafai Department of Mechanical Engineering National Taiwan University of Science and TechnologyTaipei City106335TaiwanChina Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Mechanical Engineering HITEC University TaxilaTaxila Cantt.47080Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia

Hyperspectral imaging is gaining a significant role in agricultural remote sensing *** data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third *** classification accuracy of hyperspectral images(HsI)increases significantly by employing both spatial and spectral *** this work,the data was acquired using an airborne hyperspectral imager system which collected HsI in the visible and near-infrared(VNIR)range of 400 to 1000 nm wavelength within 180 spectral *** dataset is collected for nine different crops on agricultural land with a spectral resolution of 3.3 nm wavelength for each *** data was cleaned from geometric distortions and stored with the class labels and annotations of global localization using the inertial navigation *** this study,a unique pixel-based approach was designed to improve the crops'classification accuracy by using the edge-preserving features(EPF)and principal component analysis(PCA)in *** preliminary processing generated the high-dimensional EPF stack by applying the edge-preserving filters on acquired *** the second step,this high dimensional stack was treated with the PCA for dimensionality reduction without losing significant spectral *** resultant feature space(PCA-EPF)demonstrated enhanced class separability for improved crop classification with reduced dimensionality and computational *** support vector machines classifier was employed for multiclass classification of target crops using *** classification performance evaluation was measured in terms of individual class accuracy,overall accuracy,average accuracy,and Cohen kappa *** proposed scheme achieved greater than 90%results for all the performance evaluation *** PCA-EPF proved to be an effective attribute for crop classification using hyperspectral imaging in the VNIR *** proposed scheme

关键词： Hyperspectral imaging visible and near-infrared edge preserving feature dimensionality reduction crop classification

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Wood By-Products as UV Protection:A Consequence Review

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Journal of Renewable Materials 2024年第4期12卷 699-720页

作者： naglaa salem El‑sayed Mohamed Hasanin samir Kamel Cellulose and Paper Department National Research CentreCairo12622Egypt

In recent decades,the ozone layer has suffered considerable damage,increasing the entry of ultraviolet(UV)light into the atmosphere and reaching the earth’s surface,negatively affecting ***,researchers aimed to solve this problem by synthesizing advanced UV-shielding *** the other hand,developing an easy and green strategy to prepare functional materials with outstanding properties based on naturally abundant and environmentally friendly raw materials is highly desirable for sustainable *** biomass-derived materials are sustainable and biodegradable,they present a promising substitute for petroleum-based *** three main structural constituents of the plant biomass-based materials that are naturally available are cellulose,hemicellulose,and *** review details current developments using wood-based products such as cellulose,hemicellulose,and lignin in UV-shielding *** will start with assembling the structure and chemistry of cellulose,hemicellulose,and lignin,followed by their contributions to preparing UV-shielding ***,it will briefly discuss the different processing methods for the design of UV-shielding *** wood by-products offer additional opportunities to use the whole tree harvest.

关键词： UV-shielding wood cellulose lignin hemicellulose sunlight protection

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Burden of pediatric hepatitis C

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World Journal of Gastroenterology 2013年第44期19卷 7880-7888页

作者： Mortada Hassan El-shabrawi naglaa Mohamed Kamal Alanani Pediatrics and Pediatric Hepatology Faculty of MedicineCairo University Giza 12411 Egypt

Hepatitis C virus(HCV)is a major health burden infecting 170-210 million people *** 3-4millions are newly-infected *** of pediatric infection varies from 0.05%-0.36%in the United states and Europe;up to 1.8%-5.8%in some developing *** highest prevalence occurs in Egypt,sub-saharan Africa,Amazon basin and *** has been present in some populations for several centuries,notably genotypes 1 and 2 in West *** anti-schistosomal therapy practiced in the 1960s until the early 1980s had spread HCV infection throughout *** acquisition of HCV remains a major route for infection among Egyptian *** screening of transfusions,unsterilized injection equipment and re-used needles and syringes continue to be major routes of HCV transmission in developing countries,whereas vertical transmission and adolescent high-risk behaviors(e.g.,injection drug abuse)are the major routes in developed *** risk of vertical transmission from an infected mother to her unborn/newborn infant is approximately 5%.Early stages of HCV infection in children do not lead to marked impairment in the quality of life nor to cognitive,behavioral or emotional dysfunction;however,caregiver stress and family system strain may *** slowly progresses to serious complications as cirrhosis(1%-2%)and hepatocellular carcinoma(HCC)especially in the presence of risk factors as hemolytic anemias,obesity,treated malignancy,and concomitant human immune deficiency and/or hepatitis B virus *** vaccine remains elusive to *** the immune mechanisms in patients who successfully cleared the infection is essential for vaccine *** pediatric standard of care treatment consists of pegylated interferon-α2a or b plus ribavirin for 24-48 *** new oral direct acting antivirals,approved for adults,need further evaluation in *** virologic response varies depending on the viral lo

关键词： Hepatitis C virus Burden Genotypes Cost Pediatrics

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Text-Independent Algorithm for source Printer Identification Based on Ensemble Learning

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Computers, Materials & Continua 2022年第10期73卷 1417-1436页

作者： naglaa F.El Abady Mohamed Taha Hala H.Zayed Department of Computer science Faculty of Computers and Artificial IntelligenceBenha University13518Egypt school of Information Technology and Computer science(ITCs) Nile University12677Egypt

Because of the widespread availability of low-cost printers and scanners,document forgery has become extremely *** or signatures are used to protect important papers such as certificates,passports,and identification *** the origins of printed documents is helpful for criminal investigations and also for authenticating digital versions of a document in today’s *** printer identification(sPI)has become increasingly popular for identifying frauds in printed *** paper provides a proposed algorithm for identifying the source printer and categorizing the questioned document into one of the printer classes.A dataset of 1200 papers from 20 distinct(13)laser and(7)inkjet printers achieved significant identification results.A proposed algorithm based on global features such as the Histogram of Oriented Gradient(HOG)and local features such as Local Binary Pattern(LBP)descriptors has been proposed for printer *** classification,Decision Trees(DT),k-Nearest Neighbors(k-NN),Random Forests,Aggregate bootstrapping(bagging),Adaptive-boosting(boosting),support Vector Machine(sVM),and mixtures of these classifiers have been *** proposed algorithm can accurately classify the questioned documents into their appropriate printer *** adaptive boosting classifier attained a 96%*** proposed algorithm is compared to four recently published algorithms that used the same dataset and gives better classification accuracy.

关键词： Document forensics source printer identification(sPI) HOG LBP principal component analysis(PCA) bagging AdaBoost

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Automated COVID-19 Detection Based on single-Image super-Resolution and CNN Models

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Computers, Materials & Continua 2022年第1期70卷 1141-1157页

作者： Walid El-shafai Anas M.ali El-sayed M.El-Rabaie naglaa F.soliman Abeer D.Algarni Fathi E.Abd El-samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

In developing countries,medical diagnosis is expensive and time ***,automatic diagnosis can be a good cheap *** task can be performed with artificial intelligence tools such as deep Convolutional Neural Networks(CNNs).These tools can be used on medical images to speed up the diagnosis process and save the efforts of *** deep CNNs allow direct learning from the medical ***,the accessibility of classified data is still the largest challenge,particularly in the field of medical *** learning can deliver an effective and promising solution by transferring knowledge from universal object detection CNNs to medical image ***,because of the inhomogeneity and enormous overlap in intensity between medical images in terms of features in the diagnosis of Pneumonia and COVID-19,transfer learning is not usually a robust ***-Image super-Resolution(sIsR)can facilitate learning to enhance computer vision functions,apart from enhancing perceptual image ***,it helps in showing the main features of *** by the challenging dilemma of Pneumonia and COVID-19 diagnosis,this paper introduces a hybrid CNN model,namely sIGTra,to generate super-resolution versions of X-ray and CT *** depends on aGenerative Adversarial Network(GAN)for the super-resolution reconstruction ***,Transfer learning with CNN(TCNN)is adopted for the classification of *** different categories of chest X-ray and CT images can be classified with the proposed model.A comparison study is presented between the proposed sIGTra model and the other relatedCNNmodels for COVID-19 detection in terms of precision,sensitivity,and accuracy.

关键词： Medical images sIGTra GAN CT and X-ray images sIsR TCNN

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Efficient Deep-Learning-Based Autoencoder Denoising Approach for Medical Image Diagnosis

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Computers, Materials & Continua 2022年第3期70卷 6107-6125页

作者： Walid El-shafai samy Abd El-Nabi El-sayed MEl-Rabaie Anas M.ali naglaa F.soliman Abeer D.Algarni Fathi E.Abd El-samie Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Effective medical diagnosis is dramatically expensive,especially in third-world *** of the common diseases is pneumonia,and because of the remarkable similarity between its types and the limited number of medical images for recent diseases related to pneumonia,themedical diagnosis of these diseases is a significant ***,transfer learning represents a promising solution in transferring knowledge from generic tasks to specific ***,experimentation and utilization of different models of transfer learning do not achieve satisfactory *** this study,we suggest the implementation of an automatic detectionmodel,namelyCADTra,to efficiently diagnose pneumonia-related *** model is based on classification,denoising autoencoder,and transfer ***,pre-processing is employed to prepare the medical *** depends on an autoencoder denoising(AD)algorithm with a modified loss function depending on a Gaussian distribution for decoder output to maximize the chances for recovering inputs and clearly demonstrate their features,in order to improve the diagnosis ***,classification is performed using a transfer learning model and a four-layer convolution neural network(FCNN)to detect *** proposed model supports binary classification of chest computed tomography(CT)images and multi-class classification of chest X-ray ***,a comparative study is introduced for the classification performance with and without the denoising *** proposed model achieves precisions of 98%and 99%for binary classification and multi-class classification,respectively,with the different ratios for training and *** demonstrate the efficiency and superiority of the proposed CADTra model,it is compared with some recent state-of-the-art CNN *** achieved outcomes prove that the suggested model can help radiologists to detect pneumonia-related diseases and improve the diagnostic efficiency compared to the exis

关键词： Medical images CADTra AD CT and X-ray images autoencoder

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