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Effectiveness of hepatitis B virus vaccination program in Egypt:Multicenter national project

World Journal of Hepatology 2015年第22期7卷 2418-2426页

作者： Iman I Salama Samia M Sami Zeinab Nabil Ahmed Said Manal H El-Sayed Lobna A El Etreby Thanaa M Rabah Dalia M Elmosalami Amany T abdel Hamid Somaia I Salama Aida M abdel Mohsen Hanaa M Emam Safaa M Elserougy Amal I Hassanain naglaa f abd alhalim fatma A Shaaban Samia A Hemeda Nihad A Ibrahim Ammal M Metwally Community Medicine Research Department National Research Center Child Health Department National Research Center Micro--biology and Immunology Department Faculty of Medicine (for girls)Al-Azhar University Pediatrics Department Faculty of MedicineAin-Shams University Dermatology and Venereology Department National Research Center Environmental and Occupational Medicine Department National Research Center

AIM:To assess the effectiveness of hepatitis B virus(HBV) vaccination program among fully vaccinated ***:A national community based crosssectional study was carried out in 6 governorates representing Egypt. A total of 3600 children aged from 9 mo to 16 years who were fully vaccinated with HBV vaccine during infancy were recruited. face to face interviews were carried out and sera were evaluated for hepatitis B surface antigen(HBsA g),anti-HBV core antibodies(total) and quantitative detection of hepatitis B surface antibody using enzyme linked immunoassays techniques. Samples positive to HBs Ag/anti-HBV core antibodies were subjected to quantitative HBV-DNA detection by real time polymerase chain reaction with 3.8 IU/L detection limit. RESULTS:Sero-protection was detected among 2059 children(57.2%) with geometric mean titers 75.4 ± 3.6 IU/L compared to 3.1 ± 2.1 IU/L among nonseroprotected children. Multivariate logistic analysis revealed that older age and female gender were the significant predicting variables for having non seroprotective level,with adjusted odds ratio 3.3,9.1and 14.2 among children aged 5 to fection was 0.36% and 0.39% depending on positivity of anti-HBc and DNA detection respectively. The prevalence of HBV infection was significantly higher among children aged ≥ 7 years(0.59%) compared to 0.07% among younger children with odds ratio equal to 8.4(95%CI:1.1-64.2) and P 0.05. C ON C LU S I ON :T he E gy pt ian c ompuls or y H B V vaccination program provides adequate protection. Occult HBV infection exists among apparently healthy vaccinated children. Adherence to infection control measures is mandatory.

关键词： Hepatitis B virus Immunization Seroprotection Brea

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An Efficient Breast Cancer Detection framework for Medical Diagnosis Applications

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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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A Hybrid Security framework for Medical Image Communication

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Computers, Materials & Continua 2022年第11期73卷 2713-2730页

作者： Walid El-Shafai Hayam A.abd El-Hameed Ashraf A.M.Khalaf naglaa f.Soliman Amel A.Alhussan fathi E.abd El-Samie Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt 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

Authentication of the digital image has much attention for the digital *** image authentication can be verified with image watermarking and image encryption *** schemes are widely used to protect images against forgery attacks,and they are useful for protecting copyright and rightful *** on the desirable applications,several image encryption and watermarking schemes have been proposed to moderate this *** framework presents a new scheme that combines a Walsh Hadamard Transform(WHT)-based image watermarking scheme with an image encryption scheme based on Double Random Phase Encoding(DRPE).first,on the sender side,the secret medical image is encrypted using *** the encrypted image is watermarking based on *** combination between watermarking and encryption increases the security and robustness of transmitting an *** performance evaluation of the proposed scheme is obtained by testing Structural Similarity Index(SSIM),Peak Signal-to-Noise Ratio(PSNR),Normalized cross-correlation(NC),and feature Similarity Index(fSIM).

关键词： Walsh hadamard transform watermarking encryption double random phase encoding structural similarity index

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Efficient forgery Detection Approaches for Digital Color Images

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Computers, Materials & Continua 2022年第5期71卷 3257-3276页

作者： Amira Baumy Abeer D.Algarni Mahmoud abdalla Walid El-Shafai fathi E.abd El-Samie naglaa f.Soliman Department of Communications High Institute for Engineering and TechnologyAl-Obour Obour CityEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia

This paper is concerned with a vital topic in image processing:color image forgery detection. The development of computing capabilitieshas led to a breakthrough in hacking and forgery attacks on signal, image,and data communicated over networks. Hence, there is an urgent need fordeveloping efficient image forgery detection algorithms. Two main types offorgery are considered in this paper: splicing and copy-move. Splicing isperformed by inserting a part of an image into another image. On the otherhand, copy-move forgery is performed by copying a part of the image intoanother position in the same image. The proposed approach for splicingdetection is based on the assumption that illumination between the originaland tampered images is different. To detect the difference between the originaland tampered images, the homomorphic transform separates the illuminationcomponent from the reflectance component. The illumination histogramderivative is used for detecting the difference in illumination, and henceforgery detection is accomplished. Prior to performing the forgery detectionprocess, some pre-processing techniques, including histogram equalization,histogram matching, high-pass filtering, homomorphic enhancement, andsingle image super-resolution, are introduced to reinforce the details andchanges between the original and embedded sections. The proposed approachfor copy-move forgery detection is performed with the Speeded Up Robustfeatures (SURf) algorithm, which extracts feature points and feature vectors. Searching for the copied partition is accomplished through matchingwith Euclidian distance and hierarchical clustering. In addition, some preprocessing methods are used with the SURf algorithm, such as histogramequalization and single-mage super-resolution. Simulation results proved thefeasibility and the robustness of the pre-processing step in homomorphicdetection and SURf detection algorithms for splicing and copy-move forgerydetection, respectively.

关键词： Image forgery splicing algorithm copy-move algorithm histogram matching homomorphic enhancement SISR SURf

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Secure and Robust Optical Multi-Stage Medical Image Cryptosystem

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Computers, Materials & Continua 2022年第1期70卷 895-913页

作者： Walid El-Shafai Moustafa H.Aly Abeer D.Algarni fathi E.abd El-Samie naglaa f.Soliman Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electronics and Communications Engineering College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Due to the rapid growth of telemedicine and healthcare services,color medical image security applications have been expanded *** this paper,an asymmetric PTfrfT(Phase Truncated fractional fourier Transform)-based color medical image cryptosystem is *** different phases in the fractional fourier and output planes are provided as deciphering ***,the ciphering keys will not be employed for the deciphering ***,the introduced PTfrfT algorithm comprises asymmetric ciphering and deciphering processes in contrast to the traditional optical symmetric OSH(Optical Scanning Holography)and DRPE(Double Random Phase Encoding)*** of the principal impacts of the introduced asymmetric cryptosystem is that it eliminates the onedimensionality aspects of the related symmetric cryptosystems due to its remarkable feature of phase nonlinear truncation *** comparisons on various colormedical images are examined and analyzed to substantiate the cryptosystem *** achieved experimental outcomes ensure that the introduced cryptosystem is robust and *** has terrific cryptography performance compared to conventional cryptography algorithms,even in the presence of noise and severe channel attacks.

关键词： Optical encryption medical image security symmetric and asymmetric encryption OSH DRPE PTfrfT

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An Efficient GCD-Based Cancelable Biometric Algorithm for Single and Multiple Biometrics

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Computers, Materials & Continua 2021年第11期69卷 1571-1595页

作者： naglaa f.Soliman Abeer D.Algarni Walid El-Shafai fathi E.abd El-Samie Ghada M.El Banby Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)*** objective of using cancelable biometrics is to save the original ones from hacking attempts.A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT *** original biometric is blurred with two co-prime ***,it can be recovered as the Greatest Common Divisor(GCD)between its two blurred *** changes if induced in the biometric image prior to processing with co-prime operators prevents the recovery of the original biometric image through a GCD ***,the ability to change cancelable templates is guaranteed,since the owner of the biometric can pre-determine and manage the minimal change induced in the biometric ***,we test the utility of the proposed algorithm in the single-and multi-biometric *** multi-biometric scenario depends on compressing face,fingerprint,iris,and palm print images,simultaneously,to generate the cancelable *** metrics such as Equal Error Rate(EER)and Area and Receiver Operator Characteristic curve(AROC)are *** results on single-and multi-biometric scenarios show high AROC values up to 99.59%,and low EER values down to 0.04%.

关键词： Cloud IoT cancelable biometrics GCD single-and multi-biometrics security applications

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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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Proposed Different Signal Processing Tools for Efficient Optical Wireless Communications

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Computers, Materials & Continua 2022年第5期71卷 3293-3318页

作者： Hend Ibrahim Abeer D.Algarni Mahmoud abdalla Walid El-Shafai fathi E.abd El-Samie naglaa f.Soliman Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh 11586Saudi Arabia

Optical Wireless Communication(OWC)is a new trend in communication systems to achieve large bandwidth,high bit rate,high security,fast deployment,and low *** basic idea of the OWC is to transmit data on unguided media with *** system requires multi-carrier modulation such as Orthogonal frequency Division Multiplexing(OfDM).This paper studies optical OfDM performance based on Intensity Modulation with Direct Detection(IM/DD)*** system requires a non-negativity *** paper presents a framework for wireless optical OfDM system that comprises(IM/DD)with different forms,Direct Current biased Optical OfDM(DCO-OfDM),Asymmetrically Clipped Optical OfDM(ACO-OfDM),Asymmetrically DC-biased Optical OfDM(ADO-OfDM),and *** also considers channel coding as a tool for error control,channel equalization for reducing deterioration due to channel effects,and investigation of the turbulence *** evaluation results of the proposed framework reveal enhancement of *** performance of the IM/DD-OfDM system is investigated over different channel models such as AWGN,log-normal turbulence channel model,and ceiling bounce channel *** simulation results show that the BER performance of the IM/DD-OfDM communication system is enhanced while the fading strength is *** results reveal also that Hamming codes,BCH codes,and convolutional codes achieve better BER ***,two algorithms of channel estimation and equalization are considered and *** algorithms include the Least Squares(LS)and the Minimum Mean Square Error(MMSE).The simulation results show that the MMSE algorithm gives better BER performance than the LS algorithm.

关键词： Optical communication systems OWC IM/DD OfDM MMSE LS ADO-OfDM DCO-OfDM ACO-OfDM

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An Efficient CNN-Based Hybrid Classification and Segmentation Approach for COVID-19 Detection

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Computers, Materials & Continua 2022年第3期70卷 4393-4410页

作者： Abeer D.Algarni Walid El-Shafai Ghada M.El Banby fathi E.abd El-Samie naglaa f.Soliman Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh 84428Saudi Arabia Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia 44519Egypt

COVID-19 remains to proliferate precipitously in the *** has significantly influenced public health,the world economy,and the persons’***,there is a need to speed up the diagnosis and precautions to deal with COVID-19 *** this explosion of this pandemic,there is a need for automated diagnosis tools to help specialists based onmedical *** paper presents a hybrid Convolutional Neural Network(CNN)-based classification and segmentation approach for COVID-19 detection from Computed Tomography(CT)*** proposed approach is employed to classify and segment the COVID-19,pneumonia,and normal CT *** classification stage is firstly applied to detect and classify the input medical CT ***,the segmentation stage is performed to distinguish between pneumonia and COVID-19 CT *** classification stage is implemented based on a simple and efficient CNN deep learning *** model comprises four Rectified Linear Units(ReLUs),four batch normalization layers,and four convolutional(Conv)*** layer depends on filters with sizes of 64,32,16,and 8.A2×2windowand a stride of 2 are employed in the utilized four max-pooling layers.A soft-max activation function and a fully-Connected(fC)layer are utilized in the classification stage to perform the detection *** the segmentation process,the Simplified Pulse Coupled Neural Network(SPCNN)is utilized in the proposed hybrid *** proposed segmentation approach is based on salient object detection to localize the COVID-19 or pneumonia region,*** summarize the contributions of the paper,we can say that the classification process with a CNN model can be the first stage a highly-effective automated diagnosis *** the images are accepted by the system,it is possible to perform further processing through a segmentation process to isolate the regions of interest in the *** region of interest can be assesses both automatically and through ***

关键词： COVID-19 segmentation classification CNN SPCNN CT images

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Encapsulation of Clove Oil Nanoemlusion in Chitosan-Based Nano-Composite: In Vitro and in Vivo Antifungal Activity against Rhizoctonia solani and Sclerotium rolfsii

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Phyton-International Journal of Experimental Botany 2024年第11期93卷 2787-2811页

作者： Ahmed Mahmoud Ismail Eman Said Elshewy Isra HAli naglaa abd Elbaki Sallam Muhanna Eman Yehia Khafagi Department of Arid Land Agriculture College of Agricultural and Food SciencesKing Faisal UniversityAl-Ahsa31982Saudi Arabia Pests and Plant Diseases Unit College of Agricultural and Food SciencesKing Faisal UniversityAl-Ahsa31982Saudi Arabia Vegetable Diseases Research Department Plant Pathology Research InstituteAgricultural Research Center(ARC)Giza12619Egypt Department of Pharmaceutics Faculty of PharmacyUniversity of Sadat CitySadat City32958Egypt Nanomedicine Laboratory Faculty of PharmacyUniversity of Sadat CitySadat City32958Egypt

Rhizoctonia solani Kühn and Sclerotium rolfsii *** the primary soil-borne plant diseases responsible for sig-niﬁcant reductions in global crop *** primary goal of this study was to investigate the antifungal potentials of clove essential oil(CEO),nanoemulsion form(CEONE)and chitosan/nanoemulsion nanocomposite(CS/CEONE)against *** and *** through in vitro and in vivo *** CEONE and CS/CEONE were prepared and investigated for their physical chemical and morphological *** poisoned medium method was utilized to evaluate the inhibitory effects of CEO,CEONE and CS/CEONE on the mycelial growth and enzymatic activity of *** and *** changes of hyphae of *** and *** in response to treating with CEONE and CS/CEONE were observed with scanning electron microscope(SEM).The results revealed that CEONE have larger size 86±3 nm and a broader range of PDI 0.121±0.011 on the ***,CS/CEONE has smaller size of 49±4 nm and narrower PDI of 0.099±*** nanoemulsions had uniform spherical nanodroplets form and exhibited acidic *** Transform Infrared Spectroscopy(fTIR)and UV-Visible Spectroscopy(UV-Vis)veriﬁed the successful incorporation of both CS and CEO within the nanoe-mulsion *** results demonstrated a sustained and prolonged release proﬁle from CS/CEONE for up to 4 *** inhibitory effect of CEONE and CS/CEONE showed dose-dependent activity against mycelial growth of both *** and CS/CEONE at concentration 500µL/L exhibited the strongest inhibition with a sig-niﬁcant(pfrom 56.11%to 71.94%and 52.2%to 79.2%,*** to control,CS/CEONE revealed the highest inhibitory effect against *** after 96 h followed by CEONE with value reached 50.6%and 44.1%,*** antifungal activity of the nanoemulsion showed strain–dependent behavior,where *** was the most *** images showed changes in the hy

关键词： Black scurf chitosan clove oil damping-off inhibitory nanocomposite nanoemulsion stem canker

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