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Numerical Study of Computer Virus Reaction Diffusion Epidemic Model

Computers, Materials & Continua 2021年第3期66卷 3183-3194页

作者： Umbreen Fatima Dumitru Baleanu Nauman Ahmed shumaila azam Ali Raza Muhammad Rafiq Muhammad Aziz-ur Rehman Department of Computer Science The University of LahoreLahorePakistan Department of Mathematics Cankaya UniversityAnkaraTurkey Institute of Space Sciences Magurele-BucharestRomania Department of Medical Research China Medical University HospitalChina Medical UniversityTaichungTaiwan Department of Mathematics and Statistics The University of LahoreLahorePakistan Department of Mathematics National College of Business Administration and Economics LahoreLahorePakistan Faculty of Engineering University of Central PunjabLahorePakistan Department of Mathematics University of Management and TechnologyLahorePakistan

Reaction–diffusion systems are mathematical models which link to several physical *** most common is the change in space and time of the meditation of one or more ***–diffusion modeling is a substantial role in the modeling of computer propagation like infectious *** investigated the transmission dynamics of the computer virus in which connected to each other through network *** current study devoted to the structure-preserving analysis of the computer propagation *** manuscript is devoted to finding the numerical investigation of the reaction–diffusion computer virus epidemic model with the help of a reliable *** designed technique is finite difference scheme which sustains the important physical behavior of continuous model like the positivity of the dependent variables,the stability of the *** theoretical analysis of the proposed method like the positivity of the approximation,stability,and consistency is discussed in detail.A numerical example of simulations yields the authentication of the theoretical results of the designed technique.

关键词： Computer virus dynamics reaction-diffusion system positive solution simulations

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A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1217-1238页

作者： Zeshan Faiz Iftikhar Ahmed Dumitru Baleanu shumaila Javeed Department of Mathematics COMSATS University IslamabadIslamabad45550Pakistan Department of Mathematics Cankaya UniversityAnkara06790Turkey Institute of Space Sciences Magurele-Bucharest077125Romania Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung40402Taiwan Department of Computer Science and Mathematics Lebanese American UniversityBeirut135053Lebanon Department of Mathematics Mathematics Research CenterNear East UniversityNicosia/Mersin99138Turkey

The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)*** fractional dengue transmission model(FDTM)consists of 12 *** human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and *** investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression *** effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).

关键词： Wolbachia dengue neural network vertical transmission mean square error Levenberg-Marquardt

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Numerical Analysis of Novel Coronavirus (2019-nCov) Pandemic Model with Advection

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Computers, Materials & Continua 2021年第6期67卷 2933-2953页

作者： shumaila azam Nauman Ahmed Ali Raza Muhammad Sajid Iqbal Muhammad Rafiq Ilyas Khan Kottakkaran Sooppy Nisar Muhammad Ozair Ahmad Zafar Iqbal Department of Mathematics and Statistics The University of LahoreLahorePakistan Department of Mathematics National College of Business Administration and Economics LahorePakistan Faculty of Engineering University of Central Punjab Lahore Pakistan Faculty of Mathematics and Statistics Ton Duc Thang UniversityHo Chi Minh City72915Vietnam Department of Mathematics College of Arts and Science at Wadi AldawaserPrince Sattam Bin Abdulaziz University11991AlkharjKingdom of Saudi Arabia Department of Mathematics University of Management and TechnologyLahorePakistan

Recently,the world is facing the terror of the novel corona-virus,termed as *** health institutes and researchers are continuously striving to control this *** this article,the SEIAR(susceptible,exposed,infected,symptomatically infected,asymptomatically infected and recovered)infection model of COVID-19 with a constant rate of advection is studied for the disease propagation.A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the *** continuous model is transposed into a discrete numerical model by discretizing the domains,*** analyze the disease dynamics,a structure preserving non-standard finite difference scheme is *** steady states of the continuous system are described i.e.,virus free steady state and virus existing steady *** results show that both the steady states of the numerical design coincide with the fixed points of the continuous SEIAR *** of the state variables is ensured by applying the M-matrix theory.A result for the positivity property is *** the proposed numerical design,two different types of the stability are *** stability and linear stability for the projected scheme is examined by applying some standard *** Neuman stability test is applied to ensure linear *** reproductive number is described and its pivotal role in stability analysis is also *** and convergence of the numerical model is also *** graphs are presented via computer simulations to prove the worth and efficiency of the quarantine factor is explored graphically,which is helpful in controlling the disease *** the end,the conclusion of the study is also rendered.

关键词： 2019-nCov infectious model with advection reproductive number stability analysis numerical graphs

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Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies

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Computers, Materials & Continua 2024年第5期79卷 2609-2623页

作者： Muhammad Ahmad Nawaz Ul Ghani Kun She Muhammad Arslan Rauf shumaila Khan Javed Ali Khan Eman Abdullah Aldakheel Doaa Sami Khafaga School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu611731China Department of Computer Science University of Science&TechnologyBannu28100Pakistan Department of Computer Science University of HertfordshireHatfieldAL109ABUK Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a varietyof industries, including access control, law enforcement, surveillance, and internet communication. However,the growing usage of face recognition technology has created serious concerns about data monitoring and userprivacy preferences, especially in context-aware systems. In response to these problems, this study provides a novelframework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain,and distributed computing to solve privacy concerns while maintaining exact face recognition. The framework’spainstaking design and execution strive to strike a compromise between precise face recognition and protectingpersonal data integrity in an increasingly interconnected environment. Using cutting-edge tools like Dlib for faceanalysis,Ray Cluster for distributed computing, and Blockchain for decentralized identity verification, the proposedsystem provides scalable and secure facial analysis while protecting user privacy. The study’s contributions includethe creation of a sustainable and scalable solution for privacy-aware face recognition, the implementation of flexibleprivacy computing approaches based on Blockchain networks, and the demonstration of higher performanceover previous methods. Specifically, the proposed StyleGAN model has an outstanding accuracy rate of 93.84%while processing high-resolution images from the CelebA-HQ dataset, beating other evaluated models such asProgressive GAN 90.27%, CycleGAN 89.80%, and MGAN 80.80%. With improvements in accuracy, speed, andprivacy protection, the framework has great promise for practical use in a variety of fields that need face recognitiontechnology. This study paves the way for future research in privacy-enhanced face recognition systems, emphasizingt

关键词： Facial recognition privacy protection blockchain GAN distributed systems

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Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

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Computer Systems Science & Engineering 2024年第2期48卷 363-394页

作者： Nasser Alshammari shumaila Shahzadi Saad Awadh Alanazi Shahid Naseem Muhammad Anwar Madallah Alruwaili Muhammad Rizwan Abid Omar Alruwaili Ahmed Alsayat Fahad Ahmad Department of Computer Science College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72341Saudi Arabia Department of Computer Sciences Kinnaird College forWomenLahorePunjab54700Pakistan Department of Information Sciences Division of Sciences and TechnologyUniversity of EducationLahore54770Pakistan Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72341Saudi Arabia Computer Science Florida Polytechnic UniversityLakelandFlorida33805USA Delta3T LahorePunjab54700Pakistan Department of Basic Sciences Common First YearJouf UniversitySakaka72341Saudi Arabia

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies *** vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end *** anomaly detector investigates these identified risks and provides secure network *** enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)*** anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation *** classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

关键词： Software defined network network function virtualization network function virtualization management and orchestration virtual infrastructure manager virtual network function Kubernetes Kubectl artificial intelligence machine learning

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Clinicopathological features and medium-term outcomes of histologic variants of primary focal segmental glomerulosclerosis in adults:A retrospective study

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World Journal of Nephrology 2024年第1期13卷 14-24页

作者： Nazarul Hassan Jafry shumaila Manan Rahma Rashid Muhammed Mubarak Department of Nephrology Sindh Institute of Urology and TransplantationSindhKarachi 74200Pakistan Department of Pathology Sindh Institute of Urology and TransplantationSindhKarachi 74200Pakistan

BACKGROUND The Columbia classification identified five histological variants of focal segmental glomerulosclerosis(FSGS).The prognostic significance of these variants remains *** To evaluate the relative frequency,clinicopathologic characteristics,and medium-term outcomes of FSGS variants at a single center in *** This retrospective study was conducted at the Department of Nephrology,Sindh Institute of Urology and Transplantation,Karachi,Pakistan on all consecutive adults(≥16 years)with biopsy-proven primary FSGS from January 1995 to December *** subjects were treated with steroids as a first-line *** response rates,doubling of serum creatinine,and kidney failure(KF)with replacement therapy were compared between histological variants using ANOVA or Kruskal Wallis,and Chi-square tests as *** were analyzed by SPSS version 22.0.P-value≤0.05 was considered *** A total of 401 patients were diagnosed with primary FSGS during the study *** these,352(87.7%)had a designated histological *** not otherwise specified(NOS)variant was the commonest,being found in 185(53.9%)patients,followed by the tip variant in 100(29.1%)***(COL),cellular(CEL),and perihilar(PHI)variants were seen in 58(16.9%),6(1.5%),and 3(0.7%)patients,*** and PHI variants were excluded from further analysis due to small patient *** mean follow-up period was 36.5±29.2 *** response rates of variants,patients with TIP lesions achieved remission more frequently(59.5%)than patients with NOS(41.8%)and COL(24.52%)variants(P<0.001).The hazard ratio of complete response among patients with the COL variant was 0.163[95%confidence interval(CI):0.039-0.67]as compared to patients with *** TIP variant showed a hazard ratio of 2.5(95%CI:1.61-3.89)for complete remission compared to the NOS ***,progressive KF was observed more frequently in patients with the COL variant,43.

关键词： Adults Columbia classification Focal segmental glomerulosclerosis Histological variants Kidney failure Kidney failure with replacement therapy

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Transcription regulators differentiate mesenchymal stem cells into chondroprogenitors,and their in vivo implantation regenerated the intervertebral disc degeneration

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World Journal of Stem Cells 2022年第2期14卷 163-182页

作者： shumaila Khalid Sobia Ekram Asmat Salim G.Rasul Chaudhry Irfan Khan Dr.Panjwani Center for Molecular Medicine and Drug Research International Center for Chemical and Biological SciencesUniversity of KarachiKarachi 75270SindhPakistan Department of Biological Sciences Oakland UniversityRochesterMI 48309United States

BACKGROUND Intervertebral disc degeneration(IVDD)is the leading cause of lower back *** degeneration is characterized by reduced cellularity and decreased production of extracellular matrix(ECM).Mesenchymal stem cells(MSCs)have been envisioned as a promising treatment for degenerative ***-based therapy using ECM-producing chondrogenic derivatives of MSCs has the potential to restore the functionality of the intervertebral disc(IVD).AIM To investigate the potential of chondrogenic transcription factors to promote differentiation of human umbilical cord MSCs into chondrocytes,and to assess their therapeutic potential in IVD *** MSCs were isolated and characterized morphologically and immunologically by the expression of specific *** were then transfected with Sox-9 and Six-1 transcription factors to direct differentiation and were assessed for chondrogenic lineage based on the expression of specific *** differentiated MSCs were implanted in the rat model of *** regenerative potential of transplanted cells was investigated using histochemical and molecular analyses of *** Isolated cells showed fibroblast-like morphology and expressed CD105,CD90,CD73,CD29,and Vimentin but not CD45 *** of Sox-9 and Six-1 greatly enhanced the gene expression of transforming growth factor beta-1 gene,BMP,Sox-9,Six-1,and Aggrecan,and protein expression of Sox-9 and *** implanted cells integrated,survived,and homed in the degenerated intervertebral *** grading showed that the transfected MSCs regenerated the IVD and restored normal *** Genetically modified MSCs accelerate cartilage regeneration,providing a unique opportunity and impetus for stem cell-based therapeutic approach for degenerative disc diseases.

关键词： Intervertebral disc degeneration Human umbilical cord Transcription factors Mesenchymal stem cells Gene expression Regeneration

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A Novel Stochastic Framework for the MHD Generator in Ocean

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Computers, Materials & Continua 2022年第11期73卷 3383-3402页

作者： Sakda Noinang Zulqurnain Sabir shumaila Javeed Muhammad Asif Zahoor Raja Dostdar Ali Wajaree Weera Thongchai Botmart Department of Mathematics Statistics and Computer Faculty of ScienceUbon Ratchathani UniversityUbon Ratchathani 34190Thailand Department of Mathematics and Statistics Hazara UniversityMansehraPakistan Department of Mathematics Comsats University Islamabad45550 Islamabad CampusIslamabadPakistan Future Technology Research Center National Yunlin University of Science and TechnologyYunlin 64002Taiwan Department of Mathematics Faculty of ScienceKhon Kaen UniversityKhon Kaen 40002Thailand

This work aims to study the nonlinear ordinary differential equations(ODEs)system of magnetohydrodynamic(MHD)past over an inclined plate using Levenberg-Marquardt backpropagation neural networks(LMBNNs).The stochastic procedures LMBNNs are provided with three categories of sample statistics,testing,training,and *** nonlinear MHD system past over an inclined plate is divided into three profiles,dimensionless momentum,species(salinity),and energy(heat)*** data is applied 15%,10%,and 75%for validation,testing,and training to solve the nonlinear system of MHD past over an inclined plate.A reference data set is designed to compare the obtained and proposed solutions for the MHD *** plots of the absolute error(AE)are provided to check the accuracy and precision of the considered nonlinear system of *** obtained numerical solutions of the nonlinear magnetohydrodynamic system have been considered to reduce the mean square error(MSE).For the capability,dependability,and aptitude of the stochastic LMBNNs procedure,the numerical performances are provided to authenticate the relative arrangements of MSE,error histograms(EHs),state transitions(STs),correlation,and regression.

关键词： MHD energy salinity levenberg-marquardt backpropagation Soret number nonlinear

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Zinc enhances the cell adhesion,migration,and self-renewal potential of human umbilical cord derived mesenchymal stem cells

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World Journal of Stem Cells 2023年第7期15卷 751-767页

作者： Iqra Sahibdad shumaila Khalid G Rasul Chaudhry Asmat Salim Sumreen Begum Irfan Khan Dr.Panjwani Center for Molecular Medicine and Drug Research International Center for Chemical and Biological SciencesUniversity of KarachiKarachi 75270SindhPakistan Department of Biological Sciences Oakland UniversityRochesterMI 48309United States Stem Cell Research Laboratory(SCRL) Sindh Institute of Urology and Transplantation(SIUT)Karachi 74200SindhPakistan

BACKGROUND Zinc(Zn)is the second most abundant trace element after Fe,present in the human *** is frequently reported in association with cell growth and proliferation,and its deficiency is considered to be a major disease contributing *** To determine the effect of Zn on in vitro growth and proliferation of human umbilical cord(hUC)-derived mesenchymal stem cells(MSCs).METHODS hUC-MSCs were isolated from human umbilical cord tissue and characterized based on immunocytochemistry,immunophenotyping,and tri-lineage *** impact of Zn on cytotoxicity and proliferation was determined by MTT and Alamar blue *** determine the effect of Zn on population doubling time(PDT),hUC-MSCs were cultured in media with and without Zn for several *** in vitro scratch assay was performed to analyze the effect of Zn on the wound healing and migration capability of hUC-MSCs.A cell adhesion assay was used to test the surface adhesiveness of *** analysis of genes involved in the cell cycle,proliferation,migration,and selfrenewal of hUC-MSCs was performed by quantitative real-time polymerase chain *** protein expression of Lin28,a pluripotency marker,was analyzed by *** Zn at lower concentrations enhanced the rate of proliferation but at higher concentrations(>100μM),showed concentration dependent cytotoxicity in ***-MSCs treated with Zn exhibited a significantly greater healing and migration rate compared to untreated *** also increased the cell adhesion rate,and colony forming efficiency(CFE).In addition,Zn upregulated the expression of genes involved in the cell cycle(CDC20,CDK1,CCNA2,CDCA2),proliferation(transforming growth factorβ1,GDF5,hypoxia-inducible factor 1α),migration(CXCR4,VCAM1,VEGF-A),and self-renewal(OCT4,SOX2,NANOG)of *** of Lin28 protein was significantly increased in cells treated with *** Our findings suggest that zinc enhances the proliferat

关键词： Human umbilical cord Mesenchymal stem cells Zinc Cell proliferation In vitro expansion

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Deep Learning-Based Trees Disease Recognition and Classification Using Hyperspectral Data

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Computers, Materials & Continua 2023年第10期77卷 681-697页

作者： Uzair Aslam Bhatti Sibghat Ullah Bazai shumaila Hussain Shariqa Fakhar Chin Soon Ku Shah Marjan Por Lip Yee Liu Jing College of Information and Communication Engineering Hainan UniversityHaikou570228China Department of Computer Engineering Balochistan University of Information TechnologyEngineeringand Management Sciences(BUITEMS)QuettaPakistan Department of Computer Science Sardar Bahadur Khan Women’s UniversityQuettaPakistan Department of Computer Science Universiti Tunku Abdul RahmanKampar31900Malaysia Department of Software Engineering Balochistan University of Information TechnologyEngineeringand Management Sciences(BUITEMS)QuettaPakistan Faculty of Computer Science and Information Technology University of MalayaKuala Lumpur50603Malaysia

Crop diseases have a significant impact on plant growth and can lead to reduced *** methods of disease detection rely on the expertise of plant protection experts,which can be subjective and dependent on individual experience and *** address this,the use of digital image recognition technology and deep learning algorithms has emerged as a promising approach for automating plant disease *** this paper,we propose a novel approach that utilizes a convolutional neural network(CNN)model in conjunction with Inception v3 to identify plant leaf *** research focuses on developing a mobile application that leverages this mechanism to identify diseases in plants and provide recommendations for overcoming specific *** models were trained using a dataset consisting of 80,848 images representing 21 different plant leaves categorized into 60 distinct *** rigorous training and evaluation,the proposed system achieved an impressive accuracy rate of 99%.This mobile application serves as a convenient and valuable advisory tool,providing early detection and guidance in real agricultural *** significance of this research lies in its potential to revolutionize plant disease detection and management *** automating the identification process through deep learning algorithms,the proposed system eliminates the subjective nature of expert-based diagnosis and reduces dependence on individual *** integration of mobile technology further enhances accessibility and enables farmers and agricultural practitioners to swiftly and accurately identify diseases in their crops.

关键词： Plant disease Inception v3 CNN crop diseases

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