检索结果-南通市图书馆

A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第4期79卷 201-241页

作者： Naglaa F.Soliman Fatma E.Fadl-Allah Walid el-Shafai Mahmoud I.Aly Maali Alabdulhafith fathi E.abd el-samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The efficient transmission of images,which plays a large role inwireless communication systems,poses a significant challenge in the growth of multimedia ***-quality images require well-tuned communication *** Single Carrier Frequency Division Multiple Access(SC-FDMA)is adopted for broadband wireless communications,because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio(PAPR).Data transmission through open-channel networks requires much concentration on security,reliability,and *** data need a space away fromunauthorized access,modification,or *** requirements are to be fulfilled by digital image watermarking and *** paper ismainly concerned with secure image communication over the wireless SC-FDMA systemas an adopted communication *** introduces a robust image communication framework over SC-FDMA that comprises digital image watermarking and encryption to improve image security,while maintaining a high-quality reconstruction of images at the receiver *** proposed framework allows image watermarking based on the Discrete Cosine Transform(DCT)merged with the Singular Value Decomposition(SVD)in the so-called DCT-SVD *** addition,image encryption is implemented based on chaos and DNA *** encrypted watermarked images are then transmitted through the wireless SC-FDMA *** linearMinimumMean Square Error(MMSE)equalizer is investigated in this paper to mitigate the effect of channel fading and noise on the transmitted *** subcarrier mapping schemes,namely localized and interleaved schemes,are compared in this *** study depends on different channelmodels,namely PedestrianAandVehicularA,with a modulation technique namedQuadratureAmplitude Modulation(QAM).Extensive simulation experiments are conducted and introduced in this paper for efficient transmission of encrypted watermarked *** addition,different variants of SC-FDMA bas

关键词： Cybersecurity applications image transmission channel models modulation techniques watermarking and encryption

Optimization of Cooperative RelayingMolecular Communications for Nanomedical Applications

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2024年第2期138卷 1259-1275页

作者： Eman S.Attia Ashraf A.M.Khalaf fathi E.abd el-samie Saied M.abd el-atty Konstantinos A.Lizos Osama Alfarraj Heba M.el-Hoseny Department of electrical Engineering Faculty of EngineeringMinia UniversityMinia61111Egypt Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)OsloNorway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer science The Higher Future Institute for Specialized Technological StudiesEl ShoroukEgypt

Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)***,because the MCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is *** this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift *** fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by theModified Central Force Optimization(MCFO)*** the previous work,the probability of bit error is expressed in a closed-form *** is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano *** simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.

关键词： Nanomedical system molecular communication cooperative relay optimization

A novel hybrid cryptosystem based on DQFrFT watermarking and 3D-CLM encryption for healthcare services

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Information Technology & electronic Engineering 2023年第7期24卷 1045-1061页

作者： Fatma KHALLAF Walid el-SHAFAI el-sayed M.el-RABAIE Naglaa F.SOLIMAN fathi Eabd E.L-samie Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of electrical Engineering Faculty of EngineeringAhram Canadian University6^(th)October CityGiza 12451Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh I1586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia

Quaternion algebra has been used to apply the fractional Fourier transform(FrFT)to color images in a comprehensive ***,the discrete fractional random transform(DFRNT)with adequate basic randomness remains to be *** paper presents a novel multistage privacy system for color medical images based on discrete quaternion fractional Fourier transform(DQFrFT)watermarking and three-dimensional chaotic logistic map(3D-CLM)***,we describe quaternion DFRNT(QDFRNT),which generalizes DFRNT to handle quaternion signals effectively,and then use QDFRNT to perform color medical image adaptive *** efficiently evaluate QDFRNT,this study derives the relationship between the QDFRNT of a quaternion signal and the four components of the DFRNT ***,it uses the human vision system's(HVS)masking qualities of edge,texture,and color tone immediately from the color host image to adaptively modify the watermark strength for each block in the color medical image using the QDFRNT-based adaptive watermarking and support vector machine(SVM)*** limitations of watermark embedding are also explained to conserve watermarking ***,3D-CLM encryption is employed to improve the system's security and efficiency,allowing it to be used as a multistage privacy *** proposed security system is effective against many types of channel noise attacks,according to simulation results.

关键词： Color medical image Quaternion Adaptive watermarking Encryption Fractional transform Three-dimensional chaotic logistic map(3D-CLM)

Permutation-substitution image encryption scheme based on a modified chaotic map in transform domain

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Central South University 2017年第9期24卷 2049-2057页

作者： Ramadan Noha Ahmed Hossameldin H el-khamy Said E abd el-samie fathi E Faculty of electronic Engineering Menofia University Faculty of Engineering Alexandria University

A new chaotic image encryption scheme based on permutation and substitution in the Fourier domain is *** Fourier Transform(FRFT)is used before the encryption scheme to get a large degree of *** permutation is achieved by Baker map and the substitution by a key-related-to-plain-image algorithm based on the modified Logistic *** of the Logistic map is developed to increase the space of the encryption key,and hence increase the *** key of the encryption algorithm dependents on the plain image,and thus,the cipher image is sensitive to both the initial key and the plain image to resist known-plaintext and chosen plaintext *** key space is large and hence the algorithm can effectively resist brute-force *** proposed scheme is examined using different performance evaluation metrics and the results prove that the proposed scheme is highly secure,and it can effectively resist different attacks.

关键词： Backer map chaotic encryption fractional Fourier transform (FRFT) modified Logistic map

Analysis of BrainMRI: AI-Assisted Healthcare Framework for the Smart Cities

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第2期35卷 1843-1856页

作者： Walid el-Shafai Randa Ali Ahmed Sedik Taha el-sayed Taha Mohammed abd-elnaby fathi E.abd el-samie Department electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of ROBOTICS and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The use of intelligent machines to work and react like humans is vital in emerging smart ***-aided analysis of complex and huge MRI(Mag-netic Resonance Imaging)scans is very important in healthcare *** AI(Artiﬁcial Intelligence)driven healthcare applications,tumor detection is one of the contemporary researchﬁelds that have become attractive to *** are several modalities of imaging performed on the brain for the pur-pose of tumor *** paper offers a deep learning approach for detecting brain tumors from MR(Magnetic Resonance)images based on changes in the division of the training and testing data and the structure of the CNN(Convolu-tional Neural Network)*** proposed approach is carried out on a brain tumor dataset from the National Centre of Image-Guided Therapy,including about 4700 MRI images of ten brain tumor cases with both normal and abnormal *** dataset is divided into test,and train subsets with a ratio of the training set to the validation set of 70:*** main contribution of this paper is introdu-cing an optimum deep learning structure of CNN *** simulation results are obtained for 50 epochs in the training *** simulation results reveal that the optimum CNN architecture consists of four layers.

关键词： Healthcare smart cities clinical automation CNN machine learning brain tumor medical diagnosis

Combined Application of Biostimulants and EDTA Improved Wheat Productivity under Cadmium Stress

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Phyton-International Journal of Experimental Botany 2024年第7期93卷 1647-1665页

作者： Abida Aziz Shafiqa Bano Mubshar Hussain Muhammad Farooq Azhar Ghulam Yasin Naila Hadayat Iqra Arooj Abeer Hashem Ajay Kumar elsayed fathi abd_Allah Qamar uz Zaman Department of Botany The Women UniversityMultan54500Pakistan Institute of Agronomy Bahauddin Zakariya UniversityMultan60800Pakistan Department of Forestry and Range Management Bahauddin Zakariya UniversityMultan60800Pakistan Department of Botany Division of Science&TechnologyUniversity of EducationLahore54770Pakistan Department of Microbiology&Molecular Genetics The Women UniversityMultan54500Pakistan Botany and Microbiology Department College of ScienceKing Saud UniversityRiyadh201313Saudi Arabia Amity Institute of Biotechnology Amity UniversityNoida201313India Plant Production Department College of Food and Agricultural SciencesKing Saud UniversityRiyadh11451Saudi Arabia School of Agriculture Yunnan UniversityKunmingYunan650504China Department of Environmental Sciences The University of LahoreLahore54590Pakistan

Wheat(Triticum aestivum L.)exhibits a greater capacity for cadmium(Cd)absorption compared to other cereal crops,leading to elevated daily Cd intake,and posing a signiﬁcant threat to public *** the mitigation of Cd stress in sustainable and environmentally friendly way,a pot study was designed by using exogenous application of various biostimulants,i.e.,Nigella sativa and Ocimum sanctum extracts:0%,10%,and 20%in combination with the chelating agent ethylenediaminetetraacetic acid(EDTA)using 0 and 5 mg kg^(-1) under various levels of Cd stress(i.e.,0,5,10,and 15 mg kg^(-1) soil).Results revealed that Cd stress signiﬁcantly reduced the seed emergence,growth,root,and allometric characters and yield-related parameters of wheat *** most observable reduc-tion was documented in wheat plants exposed to a higher Cd concentration(15 mg kg^(-1)),followed by the lower Cd level(control).The combined application of bio-stimulants and EDTA minimized the negative impacts of Cd *** highest increase in seedling emergence(5.44%),leaf area(50.60%),number of tillers(31.02%),grain yield per plant(24.28%),biological yield(13.97%),and decrease in Cd levels in grains(40%)was noticed where 20%foliar application of *** and 10%of *** biostimulants were done using 5 mg kg^(-1) of soil-applied *** intervention demonstrated a notable reduction in Cd-induced negative effects,highlighting the potential of these substances in promoting sustainable wheat cultivation in contaminated ***,it is an eco-friendly and approachable method at theﬁeld level able to ensure food safety.

关键词： Abiotic stress allometric characters antioxidant activity crop yield seed emergence grain yield

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

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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

Automated COVID-19 Detection Based on Single-Image Super-Resolution and CNN Models

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

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

Efficient Deep CNN Model for COVID-19 Classification

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第3期70卷 4373-4391页

作者： Walid el-Shafai Amira A.Mahmoud el-sayed M.el-Rabaie Taha E.Taha Osama F.Zahran Adel S.el-Fishawy Mohammed abd-elnaby fathi E.abd el-samie Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Coronavirus(COVID-19)infection was initially acknowledged as a global pandemic in Wuhan in *** Health Organization(WHO)stated that the COVID-19 is an epidemic that causes a 3.4%death *** X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis *** are numerous ways to identify positive COVID-19 *** of the fundamental ways is radiology imaging through CXR,or CT *** comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high ***,automated classification techniques are required to facilitate the diagnosis *** Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical *** deep Convolutional Neural Networks(CNNs)can learn and extract essential features from different medical image *** this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is *** activation functions as well as three optimizers are tested and compared for this *** proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train *** performance is tested and investigated on the CT and CXR *** activation functions:Tanh,Sigmoid,and RelU are compared using a constant learning rate and different batch *** optimizers are studied with different batch sizes and a constant learning ***,a comparison between different combinations of activation functions and optimizers is presented,and the optimal configuration is ***,the main objective is to improve the detection accuracy of COVID-19 from CXR and CT images using DL by employing CNNs to classify medical COVID-19 images in an early *** proposed model achieves a classification accuracy of 91.67%on CXR image dataset,and a classification accuracy of 100%on CT dataset with training times of 58 min and 46 min on CXR an

关键词： COVID-19 image classification CNN DL activation functions optimizers