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Cognitive Computing-Based mammographic Image Classification on an Internet of medical

Computers, materials & Continua 2022年第8期72卷 3945-3959页

作者： Romany F.mansour maha m.althobaiti Department of mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Recently,the Internet of medical Things(IomT)has become a research hotspot due to its various applicability in medical ***,the data analysis and management in IomT remain challenging owing to the existence of a massive number of devices linked to the server environment,generating a massive quantity of healthcare *** such cases,cognitive computing can be employed that uses many intelligent technologies-machine learning(mL),deep learning(DL),artificial intelligence(AI),natural language processing(NLP)and others-to comprehend data ***,breast cancer(BC)has been found to be a major cause of mortality among ladies *** detection and classification of BC using digital mammograms can decrease the mortality *** paper presents a novel deep learning-enabled multi-objective mayfly optimization algorithm(DLmOmFO)for BC diagnosis and classification in the IomT *** goal of this paper is to integrate deep learning(DL)and cognitive computing-based techniques for e-healthcare applications as a part of IomT technology to detect and classify *** proposed DL-mOmFO algorithm involved Adaptive Weighted mean Filter(AWmF)-based noise removal and contrast-limited adaptive histogram equalisation(CLAHE)-based contrast improvement techniques to improve the quality of the digital *** addition,a U-Net architecture-based segmentation method was utilised to detect diseased regions in the ***,a SqueezeNet-based feature extraction and a fuzzy support vector machine(FSVm)classifier were used in the presented *** enhance the diagnostic performance of the presented method,the mOmFO algorithm was used to effectively tune the parameters of the SqueezeNet and FSVm *** DL-mOmFO technique was tested on the mIAS database,and the experimental outcomes revealed that the DL-mOmFO technique outperformed existing techniques.

关键词： Cognitive computing breast cancer digital mammograms image processing internet of medical things smart healthcare

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Federated Learning with Blockchain Assisted Image Classification for Clustered UAV Networks

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Computers, materials & Continua 2022年第7期72卷 1195-1212页

作者： Ibrahim Abunadi maha m.althobaiti Fahd N.Al-Wesabi Anwer mustafa Hilal mohammad medani manar Ahmed Hamza mohammed Rizwanullah Abu Serwar Zamani Department of Information Systems Prince Sultan UniversityRafha StreetRiyadh11586Saudi Arabia Department of Computer Science College of Computing and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer and Self Development Prince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia

The evolving“Industry 4.0”domain encompasses a collection of future industrial developments with cyber-physical systems(CPS),Internet of things(IoT),big data,cloud computing,***,the industrial Internet of things(IIoT)directs data from systems for monitoring and controlling the physical world to the data processing system.A major novelty of the IIoT is the unmanned aerial vehicles(UAVs),which are treated as an efficient remote sensing technique to gather data from large *** are commonly employed in the industrial sector to solve several issues and help decision *** the strict regulations leading to data privacy possibly hinder data sharing across autonomous *** learning(FL)becomes a recent advancement of machine learning(mL)which aims to protect user *** this aspect,this study designs federated learning with blockchain assisted image classification model for clustered UAV networks(FLBIC-CUAV)on IIoT *** proposed FLBIC-CUAV technique involves three major processes namely clustering,blockchain enabled secure communication and FL based image *** UAV cluster construction process,beetle swarm optimization(BSO)algorithm with three input parameters is designed to cluster the UAVs for effective *** addition,blockchain enabled secure data transmission process take place to transmit the data from UAVs to cloud ***,the cloud server uses an FL with Residual Network model to carry out the image classification process.A wide range of simulation analyses takes place for ensuring the betterment of the FLBIC-CUAV *** experimental outcomes portrayed the betterment of the FLBIC-CUAV approach over the recent state of art methods.

关键词： UAV networks clustering secure communication blockchain federated learning image classification

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Angiographic characteristics of central serous chorioretinopathy in an Egyptian population

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International Journal of Ophthalmology(English edition) 2013年第3期6卷 342-345页

作者： maha m Shahin mansoura Faculty of medicine Mansoura University

· AIm: To describe and analyze the demographic characteristics and to determine the angiographic features of acute central serous chorioretinopathy(CSCR) in an Egyptian population. ·mETHODS: A series of consecutive patients presenting with acute idiopathic CSCR to mansoura Ophthalmology Center mansoura University who underwent fluorescein angiography (FA) within a 3 -year -period (between January 1, 2007 and December 31, 2009) was retrospectively studied. Patient demographics and angiographic features were studied. Results were compared to those of other Western and Asian populations. ·RESULTS: Fluorescein angiograms of 86 patients were analyzed. 91% were males. The age range of patients was 24 -49 years, with a mean age of (38±6) years. The right eye was the presenting eye in 47% of patients. Eighty seven percent of eyes showed delayed choroidal filling. Thirty -five percent of patients had more than one point of leakage. The macula was the most common site of fluorescein leakage seen in 79% of patients. Peripheral leakage was seen in 14% of patients while peripapillary leakage was seen in 12% of patients. The inkblot leakage pattern was found in 53% of patients. The presenting eye had RPE atrophic changes in 84% of cases. The other eye was assessed in 44 patients (51%). Fifty-five percent of them had signs of RPE atrophic changes. ·CONCLUSION: In the Egyptian population, CSCR is seen at younger age with higher male -to -female ratio and more frequent smokestack leaks than other populations. Despite younger age group, this series of patient showed higher frequency of bilateral and multifocal disease compared to other studies. Roles of psychological stress and choroidal ischemia in pathogenesis of CSCR need further evaluation. ·

关键词： choroidal circulation central serous chorioretinopathy epidemiology fluorescein angiography medical retina

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Exploitation of Fenton and Fenton-like reagents as alternative conditioners for alum sludge conditioning

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Journal of Environmental Sciences 2009年第1期21卷 101-105页

作者： maha A. Tony Y. Q. Zhao Aghareed m. Tayeb Centre for Water Resources Research School of Architecture Landscape and Civil Engineering University College Dublin Newstead Belfield Dublin 4 Ireland. Basic Science of Engineering Department Faculty of Engineering Minoufiya University Minoufiya 32511 Egypt Chemical Engineering Department Faculty of Engineering Minia University Minia 61111 Egypt

The use of Fenton＇s reagent （Fe^2＋/H2O2） and Fenton-like reagents containing transition metals of Cu（Ⅱ）, Zn（Ⅱ）, Co（Ⅱ）, and mn（Ⅱ） for an alum sludge conditioning to improve its dewaterability was investigated. The results obtained were compared with those obtained from conditioning the same alum sludge using cationic and anionic polymers. Experimental results show that Fenton＇s reagent was the best among the Fenton and Fenton-like reagents for the alum sludge conditioning. A considerable effectiveness of capillary suction time （CST） reduction efficiency of 47% can be achieved under test conditions of Fe^2＋/H2O2 = 20/125 mg/g DS （dry solid） and pH 6.0. The observation of floc-like particles after Fenton＇s reagent conditioning of alum sludge suggested that the mechanism of Fenton＇s reagent conditioning was different from that of polymer conditioning. In spite of the lower efficiency in the CST reduction of Fenton＇s reagent in alum sludge conditioning compared to that of polymer conditioning, Fenton＇s reagent offers a more environmentally safe option. Tiffs study provided an example of proactive treatment engineering, which is aimed at seeking a safe alternative to the use of polymers in sludge conditioning towards achieving a more sustainable sludge management strategy.

关键词： alum sludge conditioning Fenton and Fenton-like reagents organic polymers cost estimate

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magnetically separable and visible light-active Ag/NiCo2O4 nanorods prepared by a simple route for superior photodegradation of atrazine in water

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Progress in Natural Science:materials International 2020年第2期30卷 160-167页

作者： Ahmed Shawky maha Alhaddad R.m.mohamed Nasser S.Awwad Hala A.Ibrahium Nanomaterials and Nanotechnology Department Advanced Materials DivisionCentral Metallurgical R&D Institute(CMRDI) P.O.Box 87 Helwan Department of mechanical Engineering School of EngineeringThe University of Tokyo Chemistry Department Faculty of ScienceKing Abdulaziz University Research Centre for Advanced materials Science (RCAmS) King Khalid University Department of Biology Nuclear Materials Authority

Atrazine（ATZ） is a known herbicide used in agriculture and caused many concerns according to its ***,we have prepared NiCo2O4nanorods that can work as a photocatalyst under visible light exposure by Ag loading through a simple *** characterizations revealed the role of Ag for improving the structural,optical and optoelectronic properties of the produced *** Ag loading with 5 wt% confirms the minimization of the bandgap from 3.6 down to 2.57 eV with enhanced visible light absorption and sustaining the magnetic *** Ag/NiCo2O4nanorods showed a superior photodegradation of ATZ within 20 min at2.0 g L-1with excellent *** enhancement of the photocatalytic activity is referred to the local surface plasmon resonance of Ag-loaded *** reduces the electron-hole recombination and outperforms the unloaded *** work is highlighting the application of magnetically separable spinel photocatalysts for the removal of herbicides and water remediation.

关键词： Spinel photocatalyst Visible light Photodegradation Atrazine magnetic separation

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A Double Threshold Energy Detection-Based Neural Network for Cognitive Radio Networks

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Computer Systems Science & Engineering 2023年第4期45卷 329-342页

作者： Nada m.Elfatih Elmustafa Sayed Ali maha Abdelhaq Raed Alsaqour Rashid A.Saeed Department of Electrical and Electronics Engineering Red Sea UniversityPort Sudan33311Sudan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic UniversityRiyadh93499Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Electronics Engineering Sudan University of Science and TechnologyKhartoum11111Sudan

In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection *** optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold ***,these methods do not take into account the effect of sample size and its effect on improving CoR *** general,a large sample size results in more reliable detection,but takes longer sensing time and increases ***,the locally sensed sample size is an optimization ***,optimizing the local sample size for each cognitive user helps to improve CoR *** this study,two new methods are proposed to find the optimum sample size to achieve objective-based improved(single/double)threshold energy detection,these methods are the optimum sample size N^(*)and neural networks(NN)*** the evaluation,it was found that the proposed methods outperform the traditional sample size selection in terms of the total error rate,detection probability,and throughput.

关键词： Cognitive radio spectrum sensing energy detection double threshold neural network machine learning optimization quality of service

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New Optical Soliton Solutions of the Perturbed Fokas-Lenells Equation

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Communications in Theoretical Physics 2019年第11期71卷 1275-1280页

作者： maha S.m.Shehata Hadi Rezazadeh Emad H.m.Zahran Eric Tala-Tebue Ahmet Bekir Departments of mathematics Zagazig UniversityFaculty of ScienceZagazigEgypt Faculty of Engineering Technology Amol University of Special Modern TechnologiesAmolIran Departments of mathematical and Physical Engineering Benha UniversityFaculty of EngineeringShubraEgypt Laboratoire D'Automatique et D'Informatique Appliquee(LAIA) IUT-FV of BandjounThe University of DschangBP 134BandjounCameroon Neighbourhood of Akcaglan Imarli StreetNumber:28/426030EskisehirTurkey

In this article, we employ the perturbed Fokas-Lenells equation(FLE), which represents recent electronic communications. The Riccati-Bernoulli Sub-ODE method which does not depend on the balance rule is used for thefirst time to obtain the new exact and solitary wave solutions of this equation. This technique is direct, effective and reduces the large volume of calculations.

关键词： perturbed Fokas-Lenells equation(FLE) Riccati-Bernoulli Sub-ODE method optical soliton solutions

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A Deep-CNN Crowd Counting model for Enforcing Social Distancing during COVID19 Pandemic: Application to Saudi Arabia’s Public Places

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Computers, materials & Continua 2021年第2期66卷 1315-1328页

作者： Salma Kammoun Jarraya maha Hamdan Alotibi manar Salamah Ali Department of Computer Science FCITKing Abdulaziz UniversityJeddahSaudi Arabia mIRACL-Laboratory Sfax UniversitySfaxTunisia Department of Computer Science King Khalid UniversityAbhaSaudi Arabia

With the emergence of the COVID19 virus in late 2019 and the declaration that the virus is a worldwide pandemic,health organizations and governments have begun to implement severe health precautions to reduce the spread of the virus and preserve human *** enforcement of social distancing at work environments and public areas is one of these obligatory *** management is one of the effective measures for social *** reducing the social contacts of individuals,the spread of the disease will be immensely *** this paper,a model for crowd counting in public places of high and low densities is *** model works under various scene conditions and with no prior knowledge.A Deep CNN model(DCNN)is built based on convolutional neural network(CNN)structure with small kernel size and two *** increase the efficiency of the model,a convolutional neural network(CNN)as the front-end and a multi-column layer with Dilated Convolution as the back-end were ***,the proposed method accepts images of arbitrary sizes/scales as inputs from different *** evaluate the proposed model,a dataset was created from images of Saudi people with traditional and non-traditional Saudi *** model was also trained and tested on some existing *** to current counting methods,the results show that the proposed model has significantly improved efficiency and reduced the error *** achieve the lowest mAE by 67%,32%.and 15.63%and lowest mSE by around 47%,15%and 8.1%than m-CNN,Cascaded-mTL,and CSRNet respectively.

关键词： CNN crowd counting COVID19

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Optimized Deep Learning model for Colorectal Cancer Detection and Classification model

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Computers, materials & Continua 2022年第6期71卷 5751-5764页

作者： mahmoud Ragab Khalid Eljaaly maha Farouk SSabir Ehab Bahaudien Ashary S.m.Abo-Dahab E.m.Khalil Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Center of Artificial Intelligence for Precision medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Department of mathematics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Department of Pharmacy Practice Faculty of PharmacyKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Computer Science Department Faculty of Computers and InformationLuxor University85951Egypt mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt Department of mathematics Faculty of ScienceTaif UniversityTaif21944Saudi Arabia

The recent developments in biological and information technologies have resulted in the generation of massive quantities of data it speeds up the process of knowledge discovery from biological *** to the advancements of medical imaging in healthcare decision making,significant attention has been paid by the computer vision and deep learning(DL)*** the same time,the detection and classification of colorectal cancer(CC)become essential to reduce the severity of the disease at an earlier *** existing methods are commonly based on the combination of textual features to examine the classifier results or machine learning(mL)to recognize the existence of *** this aspect,this study focuses on the design of intelligent DL based CC detection and classification(IDL-CCDC)model for bioinformatics *** proposed IDL-CCDC technique aims to detect and classify different classes of *** addition,the IDLCCDC technique involves fuzzy filtering technique for noise removal ***,water wave optimization(WWO)based EfficientNet model is employed for feature extraction ***,chaotic glowworm swarm optimization(CGSO)based variational auto encoder(VAE)is applied for the classification of CC into benign or *** design of WWO and CGSO algorithms helps to increase the overall classification *** performance validation of the IDL-CCDC technique takes place using benchmark Warwick-QU dataset and the results portrayed the supremacy of the IDL-CCDC technique over the recent approaches with the maximum accuracy of 0.969.

关键词： Colorectal cancer deep learning medical imaging bioinformatics metaheuristics parameter tuning

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Hyperledger Fabric Blockchain: Secure and Efficient Solution for Electronic Health Records

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Computers, materials & Continua 2021年第8期68卷 2377-2397页

作者： mueen Uddin m.S.memon Irfana memon Imtiaz Ali Jamshed memon maha Abdelhaq Raed Alsaqour Faculty of Science Universiti Brunei DarusslamGadongBE1410Negara Brunei Darussalam CSE Department QUESTNawabshahPakistan School of Computing and mathematics Ulster UniversityJordanstown CampusNewtownabbeyBT370QBUK Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic UniversityRiyadh93499Saudi Arabia

Background:Electronic Health Record(EHR)systems are used as an efficient and effective technique for sharing patient’s health records among different hospitals and various other key stakeholders of the healthcare industry to achieve better diagnosis and treatment of patients ***,the existing EHR systems mostly lack in providing appropriate security,entrusted access control and handling privacy and secrecy issues and challenges in current hospital ***:To solve this delicate problem,we propose a Blockchain-enabled Hyperledger Fabric Architecture for different EHR ***:In our EHR blockchain system,Peer nodes from various organizations(stakeholders)create a ledger network,where channels are created to enable secure and private communication between different stakeholders on the ledger *** patients and other stakeholders are identified and registered on the network by unique digital certificates issued by membership service provider(mSP)component of the fabric ***:We created and implemented different Chaincodes to handle the business logic for executing separate EHR transactions on the *** proposed fabric architecture provides a secure,transparent and immutable mechanism to store,share and exchange EHRs in a peer-to-peer network of different healthcare *** ensures interoperability,scalability and availability in adapting the existing EHRs for strengthening and providing an effective and secure method to integrate and manage patient records among medical institutions in the healthcare ecosystem.

关键词： Electronic health records blockchain hyperledger fabric patient data privacy private permissioned blockchain healthcare ecosystem

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