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

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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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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Enhanced Robotic Vision System Based on Deep Learning and Image Fusion

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Computers, materials & Continua 2022年第10期73卷 1845-1861页

作者： E.A.Alabdulkreem Ahmed Sedik Abeer D.Algarni ghada m.el banby Fathi E.Abd el-Samie Naglaa F.Soliman Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of the Robotics and Intelligent machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafrelsheikh33511Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Image fusion has become one of the interesting fields that attract researchers to integrate information from different image *** is involved in several *** of the recent applications is the robotic *** application necessitates image enhancement of both infrared(IR)and visible *** paper presents a Robot Human Interaction System(RHIS)based on image fusion and deep *** basic objective of this system is to fuse visual and IR images for efficient feature extraction from the captured ***,an enhancement model is carried out on the fused image to increase its *** image enhancement models such as fuzzy logic,Convolutional Neural Network(CNN)and residual network(ResNet)pre-trained model are utilized on the fusion results and they are compared with each other and with the state-of-the-art *** results prove that the fuzzy logic enhancement gives the best results from the image quality ***,the proposed system can be considered as an efficient solution for the robotic vision problem with multi-modality images.

关键词： Deep learning fuzzy logic image fusion IR images

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Efficient Deep Learning modalities for Object Detection from Infrared Images

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Computers, materials & Continua 2022年第8期72卷 2545-2563页

作者： Naglaa F.Soliman E.A.Alabdulkreem Abeer D.Algarni ghada m.el banby Fathi E.Abd el-Samie Ahmed Sedik 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 Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of the Robotics and Intelligent machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafr el-sheikhEgypt

For military warfare purposes,it is necessary to identify the type of a certain weapon through video stream tracking based on infrared(IR)video *** vision is a visual search trend that is used to identify objects in images or video *** military applications,drones take a main role in surveillance tasks,but they cannot be confident for longtime ***,there is a need for such a system,which provides a continuous surveillance task to support the drone *** a system can be called a Hybrid Surveillance System(HSS).This system is based on a distributed network of wireless sensors for continuous *** addition,it includes one or more drones to make short-time missions,if the sensors detect a suspicious *** paper presents a digital solution to identify certain types of concealed weapons in surveillance applications based on Convolutional Neural Networks(CNNs)and Convolutional Long Short-Term memory(ConvLSTm).Based on initial results,the importance of video frame enhancement is obvious to improve the visibility of objects in video *** accuracy of the proposed methods reach 99%,which reflects the effectiveness of the presented *** addition,the experimental results prove that the proposed methods provide superior performance compared to traditional ones.

关键词： Deep learning object detection military applications OFDm SPIHT IoT

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An Efficient CNN-Based Automated Diagnosis Framework from COVID-19 CT Images

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Computers, materials & Continua 2021年第10期69卷 1323-1341页

作者： Walid el-Shafai Noha A.el-Hag ghada m.el-banby Ashraf A.m.Khalaf Naglaa F.Soliman Abeer D.Algarni Fathi E.Abd el-Samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of EngineeringMinia UniversityEgypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Corona Virus Disease-2019(COVID-19)continues to spread rapidly in the *** has dramatically affected daily lives,public health,and the world *** paper presents a segmentation and classification framework of COVID-19 images based on deep ***,the classification process is employed to discriminate between COVID-19,non-COVID,and pneumonia by Convolutional Neural Network(CNN).Then,the segmentation process is applied for COVID-19 and pneumonia CT ***,the resulting segmented images are used to identify the infected region,whether COVID-19 or *** proposed CNN consists of four Convolutional(Conv)layers,four batch normalization layers,and four Rectified Linear Units(RelUs).The sizes of Conv layer used filters are 8,16,32,and *** maxpooling layers are employed with a stride of 2 and a 2×2 *** classification layer comprises a Fully-Connected(FC)layer and a soft-max activation function used to take the classification decision.A novel saliencybased region detection algorithm and an active contour segmentation strategy are applied to segment COVID-19 and pneumonia CT *** acquired findings substantiate the efficacy of the proposed framework for helping the specialists in automated diagnosis applications.

关键词： Classification segmentation COVID-19 CNN deep learning diagnosis applications

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Gauss Gradient and SURF Features for Landmine Detection from GPR Images

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Computers, materials & Continua 2022年第6期71卷 4457-4486页

作者： Fatma m.el-Ghamry Walid el-Shafai mahmouad I.Abdalla ghada m.el-banby Abeer D.Algarni moawad I.Dessouky Adel S.elfishawy Fathi E.Abd el-Samie Naglaa F.Soliman Department of electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Recently,ground-penetrating radar(GPR)has been extended as a well-known area to investigate the subsurface ***,its output has a low resolution,and it needs more processing for more *** paper presents two algorithms for landmine detection from GPR *** first algorithm depends on a multi-scale technique.A Gaussian kernel with a particular scale is convolved with the image,and after that,two gradients are estimated;horizontal and vertical ***,histogram and cumulative histogram are estimated for the overall gradient *** bin values on the cumulative histogram are used for discrimination between images with and without ***,a neural classifier is used to classify images with cumulative histograms as feature *** second algorithm is based on scale-space analysis with the number of speeded-up robust feature(SURF)points as the key parameter for *** addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient *** further classification steps can be performed on images after *** sensitivity of classification accuracy to the interpolation process is studied in detail.

关键词： GPR images cumulative histogram gradient image neural classifier SURF

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Advanced Functional electromagnetic Shielding materials:A Review Based on micro‑Nano Structure Interface Control of Biomass Cell Walls

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Nano-micro Letters 2025年第1期17卷 98-134页

作者： Yang Shi mingjun Wu Shengbo Ge Jianzhang Li Anoud Saud Alshammari Jing Luo mohammed A.Amin Hua Qiu Jinxuan Jiang Yazeed m.Asiri Runzhou Huang Hua Hou Zeinhom m.el‑Bahy Zhanhu Guo Chong Jia Kaimeng Xu Xiangmeng Chen Co‑Innovation Center of Efficient Processing and Utilization of Forest Resources College of Materials Science and EngineeringNanjing Forestry UniversityNanjing 210037People’s Republic of China State Key Laboratory of Efficient Production of Forest Resourced Beijing Forestry UniversityQinghua East Road 35Haidian DistrictBeijing 100083People’s Republic of China Department of Physics Faculty of Sciences‑ArarNorthern Border UniversityArar 91431Saudi Arabia Department of Chemistry College of ScienceTaif UniversityP.O.Box 1109921944 TaifSaudi Arabia Shaanxi Key Laboratory of macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’anShaanxi 710072People’s Republic of China Integrated Composites Lab Department of Mechanical and Construction EngineeringNorthumbria UniversityNewcastle Upon Tyne NE18STUK College of materials Science and Engineering Taiyuan University of Science and TechnologyTaiyuan 030024People’s Republic of China Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr CityCairo 11884Egypt Yunnan Provincial Key Laboratory of Wood Adhesives and Glued Products International Joint Research Center for Biomass MaterialsSouthwest Forestry UniversityKunming 650224People’s Republic of China School of Science Henan Agricultural UniversityZhengzhou 450002People’s Republic of China

Research efforts on electromagnetic interference(EmI)shielding materials have begun to converge on green and sustainable biomass *** materials offer numerous advantages such as being lightweight,porous,and *** to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EmI shielding *** concerted efforts on the EmI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EmI shielding *** particular,a more comprehensive study and summary of the factors influencing biomass EmI shielding materials including the pore structure adjustment,preparation process,and micro-control would be *** preparation methods and characteristics of wood,bamboo,cellulose and lignin in EmI shielding field are critically discussed in this paper,and similar biomass EmI materials are summarized and *** composite methods and fillers of various biomass materials were *** paper also highlights the mechanism of EmI shielding as well as existing prospects and challenges for development trends in this field.

关键词： Biomass materials electromagnetic interference shielding micro-nano structure interface control Conductivity

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Safety of intravitreal triamcinolone acetonide:an electrophysiologic and histopathological study in rabbits

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International Journal of Ophthalmology(English edition) 2013年第6期6卷 790-795页

作者： Laila Hassan m.el-Shazly Amal Ahmad el-Gohary ghada Ghanem.el-Hossary Department of Ophthalmology Memorial Institute of Ophthalmology Department of Physiology Research Institute ofOphthalmology Department of Pharmacology Research Institute ofOphthalmology

AIm:To evaluate the retinal safety of various doses of intravitreal triamcinolone acetonide(TA)in ***:Thirty New Zealand albino rabbits were divided into five groups(six animals each).In group 1(control group),each animal received a single intravitreal injection of 0.1 mL phosphate buffered *** groups2,3,4 and 5,each rabbit received a single intravitreal injection of 4,8,16 and 32mg of TA,*** dose was contained in 0.1 mL phosphate buffered *** ocular examinations were performed before the injection and on the 1st,3rd,10th and 17th postinjection days.A standard dark adapted electroretinogram(ERG)was obtained before injection and on the 3rd,10th and 17th post-injection ***17d,animals were sacrificed and their eyes prepared for pathological ***:By monitoring ERG as a functional index for the retina,intravitreal injection of 4mg TA showed no significant ERG *** doses of 8,16 and 32,hyper-abnormal responses in a-and b-waves of ERG were detected on the 3rd post-injection *** changes gradually returned back to normal limits *** examination of the retina of all animals showed no pathological ***:High doses of intravitreal TA seemed to have enhancing effects on the retinal function with gradual return to normal limits with no pathological changes detected in examined eyes.

关键词： triamcinolone acetonide intravitreal injection electroretinogram

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Diffusion coefficient of vacancies and jump length of electrons in Co_(1-x)Zn_(x)Fe_(2)O_(4)ferrites

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Journal of Advanced Ceramics 2012年第2期1卷 144-149页

作者： m.el-SAADAWY Physics Department Faculty of ScienceKafrelsheikh UniversityKafrelsheikh CityEgypt

A series of polycrystalline samples of Co_(1-x)Zn_(x)Fe_(2)O_(4)where(x=0.1,0.2,0.3,0.4,0.5 and 0.6)were prepared by the usual ceramic technique.X-ray diffraction patterns confirmed the spinel cubic *** diffusion coefficients of oxygen vacancies were estimated from dc conductivity *** was noticed that the diffusion coefficient decreases with increasing Zn^(2+)*** increase of temperature increases the diffusion of lattice *** Curie temperature,lattice parameter and jump length of electrons were studied as a function of Zn^(2+)*** the correlation between the ionic radius and the radii of octahedral and tetrahedral sites,the theoretical lattice parameters were calculated and suggested cation distribution for the given ferrites was determined.

关键词： diffusion coefficient lattice parameter jump length and jump rate of vacancies Curie temperature cation distribution

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CO oxidation and 4-nitrophenol reduction over ceria-promoted platinum nanoparticles impregnated with ZSm-5 zeolite

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Journal of Rare Earths 2022年第8期40卷 1247-1254页

作者： Zeinhom m.el-Bahy mohammed T.Alotaibi Salah m.el-Bahy Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City11884CairoEgypt Department of Chemistry Turabah University CollegeTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

Active new ceria-promoted platinum supported on ZSm-5 catalysts were prepared and characterized by X-ray diffraction(XRD),Fourier transform infrared spectra(FTIR),transform.electron microscopy(TEm),temperature programmed desorption(TPD),and FTIR of CO *** samples were prepared by the incipient wetness impregnation method and calcined at 500℃.The XRD patterns and FTIR spectra prove that the zeolite framework is kept unaltered after metal *** images prove the presence of Pt nanoparticles with particle size starting from 14 to 27 *** FTIR data suggest the formation of Pt-O-Ce ***-situ FTIR of CO adsorption over reduced samples proves the presence of Pt~0 only,and no Pt^(n+)-CO species are *** prepared catalysts were tested in both oxidation reaction(CO oxidation) in the gas phase and in reduction reaction(4-nitrophenol reduction) in the aqueous ***,CO oxidation by O_(2) results in the formation of a CO_(2) peak at 2347 cm^(-1) as the only CO oxidation product in the studied frequency *** intensity of the CO_(2) peak increases after the addition of Ce,and it is 4 times higher in Pt_(1) Ce_(0.5)ZSm-5 than that in the Ce-free *** to the FTIR data and previous reports,the increase in the catalytic activity may be due to the formation of Pt-O-Ce ***,Ce-promoted Pt_(1) ZSm5 also exhibits enhanced catalytic activity towards the reduction of 4-nitrophenol to 4-aminophenol by NaBH_(4) in the aqueous *** first-order rate constant of the reduction increases ≈13 times after incorporating equal ratios of Pt and Ce(Pt_(1) Ce_(1)ZSm-5),and the activation energy(E_(a)) decreases to 40% of that in the reaction over Pt_(1) ZSm-5.

关键词： 4-Nitrophenol CO oxidation TPD-CO Platinum-cerium ZSm-5 Rare earths

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