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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

Evaluation of phosphorus bioavailability in el Mex Bay and Lake Mariut sediments

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International Journal of Sediment Research 2017年第3期32卷 432-441页

作者： naglaa f.Soliman Gehan M.el Zokm Mohamed A.Okbah Department of Environmental Studies Institute of Graduate Studies and Research University of Alexandria National Institute of Oceanography and fisheries

Phosphorus(P) fractions and their bioavailability in the sediments from el Mex Bay and Lake Mariut in Egypt were investigated using different chemical extraction methods. Sodium bicarbonate(NaHC03)extractable P(Olsen-P) was the largest fraction(14.42%), followed by algal available P(AAP)(3.56%),water soluble P(WSP)(0.79%), and readily desorbable P(RDP)(0.06%) for el Mex Bay. While AAP contributed 9.94% to total P in sediments from Lake Mariut, Olsen-P 8.53%, WSP 4.11%, and RDP 0.92%.Summation of the bioavailable P fractions didn’t exceed the sediment quality guidelines, and, therefore, P doesn’t represent a danger to marine organisms. Correlation coefficients showed that no apparent relations between total P(TP) and iron(fe), aluminum(Al), and calcium(Ca) in the sediments. furthermore, fe:P ratio was less than 15 indicting that there was not enough fe in surface sediments to bind to P at most of the sampling sites. The positive correlation between TP and organic matter(OM) for Lake Mariut and el Mex Bay sediments indicated that the organic matter content of the sediment was a useful predictor of the total phosphorus content. Data from this study constitute a baseline of phosphorus bioavailability in sediments from el Mex Bay and Lake Mariut and could be used as a reference for future studies on the changes of bioavailable and residual phosphorus fractions over time.

关键词： Phosphorus bioavailability Sediments el Mex Bay Lake Mariut

Dynamic S-Box Generation Using Novel Chaotic Map with Nonlinearity Tweaking

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Computers, Materials & Continua 2023年第5期75卷 3011-3026页

作者： Amjad Hussain Zahid Muhammad Junaid Arshad Musheer Ahmad naglaa f.Soliman Walid el-Shafai School of Systems and Technology University of Management and TechnologyLahore54700Pakistan Department of Computer Science University of Engineering and TechnologyLahore54700Pakistan Department of Computer Engineering Jamia Millia IslamiaNew Delhi110025India 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

A substitution box(S-Box)is a crucial component of contemporary cryptosystems that provide data protection in block *** the moment,chaotic maps are being created and extensively used to generate these SBoxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical *** this paper,the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking *** projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their workingmakes both of these dynamic in *** tweak approach employs cubic polynomials while permuting the values of an initial S-Box to enhance its cryptographic *** of the parameters are provided using the cipher key and a small variation in values of these parameters results in a completely different unique *** analysis and exploration confirmed that the projected chaoticmap exhibits a significant amount of chaotic *** security assessment in terms of bijectivity,nonlinearity,bits independence,strict avalanche,linear approximation probability,and differential probability criteria are utilized to critically investigate the effectiveness of the proposed S-Box against several *** proposed S-Box’s cryptographic performance is comparable to those of recently projected S-Boxes for its adaption in real-world security *** comparative scrutiny pacifies the genuine potential of the proposed S-Box in terms of its applicability for data security.

关键词： Substitution-box chaotic map data security tweaking

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

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

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

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

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

Enhancing Early Detection of Lung Cancer through Advanced Image Processing Techniques and Deep Learning Architectures for CT Scans

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Computers, Materials & Continua 2024年第10期81卷 271-307页

作者： Nahed Tawfik Heba M.Emara Walid el-Shafai naglaa f.Soliman Abeer D.Algarni fathi EAbd el-Samie Computers and Systems Department Electronics Research InstituteEl NozhaHuckstep Cairo12622Egypt Department of.electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Lung cancer remains a major concern in modern oncology due to its high mortality rates and multifaceted origins,including hereditary factors and various clinical *** stands as the deadliest type of cancer and a significant cause of cancer-related deaths *** diagnosis enables healthcare providers to administer appropriate treatment measures promptly and accurately,leading to improved prognosis and higher survival *** significant increase in both the incidence and mortality rates of lung cancer,particularly its ranking as the second most prevalent cancer among women worldwide,underscores the need for comprehensive research into efficient screening *** in diagnostic techniques,particularly the use of computed tomography(CT)scans,have revolutionized the identification of lung *** scans are renowned for their ability to provide high-resolution images and are particularly effective in detecting small,calcified areas,crucial for identifying earlystage lung ***,there is growing interest in enhancing computer-aided detection(CAD)*** algorithms assist radiologists by reducing false-positive interpretations and improving the accuracy of early cancer *** study aims to enhance the effectiveness of CAD systems through various ***,the Contrast Limited Adaptive Histogram Equalization(CLAHE)algorithm is employed to preprocess CT scan images,thereby improving their visual *** refinement is achieved by integrating different optimization strategies with the CLAHE *** CutMix data augmentation technique is applied to boost the performance of the proposed model.A comparative analysis is conducted using deep learning architectures such as InceptionV3,ResNet101,Xception,and *** study evaluates the performance of these architectures in image classification tasks,both with and without the implementation of the CLAHE *** empirical findings of the study demonst

关键词： Lung cancer detection CLAHE algorithm optimization deep learning classification feature extraction healthcare applications