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Performance Framework for Virtual Machine Migration in Cloud Computing

Computers, Materials & Continua 2023年第3期74卷 6289-6305页

作者： Tahir Alyas Taher M.Ghazal Badria Sulaiman Alfurhood Munir Ahmad Ossma ali Thawabeh khalid alissa Qaiser Abbas Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Information Technology Skyline University CollegeUniversity City SharjahSharjah1797UAE Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebansaan Malaysia(UKM)Bangi43600SelangorMalaysia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Dean of Student Affairs Skyline University CollegeUniversity City SharjahSharjah1797UAE Networks and Communications Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Faculty of Computer and Information Systems Islamic University Madinah Madinah42351Saudi Arabia

In the cloud environment,the transfer of data from one cloud server to another cloud server is called *** can be delivered in various ways,from one data centre to *** research aims to increase the migration performance of the virtual machine(VM)in the cloud *** allow cloud customers to store essential data and ***,server usage has grown dramatically due to the virtualization of computer systems,resulting in higher data centre power consumption,storage needs,and operating *** VMs on one data centre manage share resources like central processing unit(CPU)cache,network bandwidth,memory,and application ***-cloud,VMmigration addresses the performance degradation due to cloud server configuration,unbalanced traffic load,resource load management,and fault situations during data *** speed is influenced by the size of the VM,the dirty rate of the running application,and the latency ofmigration *** a result,evaluating VM migration performance while considering all of these factors becomes a difficult *** effort of this research is to assess migration problems on *** simulation results in Matlab show that if the VMsize grows,themigration time of VMs and the downtime can be impacted by three orders *** dirty page rate decreases,themigration time and the downtime grow,and the latency time decreases as network bandwidth increases during the migration time and post-migration overhead calculation when the VMtransfer is *** the simulated cases of VMs migration were performed in a fuzzy inference system with performance graphs.

关键词： Latency cloud computing dirty page ratio storage migration performance

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Nasal Dermoid Cyst with Sinus Tract Intranasal Bone: A Case Report

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International Journal of Otolaryngology and Head & Neck Surgery 2024年第2期13卷 149-156页

作者： Sultan Kadasah Abdullah Alhelali Saud Aldhabaan Abdulaziz Al Qahtani Abdullah Musleh ali Alshahrani Shahd Dlboh Sahar Al-Otaibi Department of Surgery College of Medicine University of Bisha Bisha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Abha Children’s Hospital Abha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Armed Forces Southern Region Hospital Khamis Mushait Saudi Arabia Department of Surgery College of Medicine King Khalid University Abha Saudi Arabia College of Medicine King Khalid University Abha Saudi Arabia

Dermoid cysts are benign tumors originating from germ cells, which can form in various locations, including the nasal area in rare cases. They are of unknown exact etiology, but it is suggested that it is due to abnormal tissue migration during early embryonic development. Nasal dermoid cysts albeit rare, can present in various forms such as sinuses, fistulas, or intracranially extending tracts. They can be asymptomatic and incidentally discovered or present with a visible external mass or sinus that is either painful, infected or cosmetically concerning. If nasal dermoid cysts with an intra-nasal bone sinus tract are left untreated, they can lead to life-threatening complications. This report describes the case of a 6-year-old girl with a nasal dermoid cyst connected to a superficial punctum by an intra-nasal tract. She had undergone surgical excision of a nasal swelling previously diagnosed as a dermoid cyst. One year later, she returned to our clinic with a recurrence of the nasal swelling. Imaging tests revealed a nasal dermoid cyst with a tract extending to the nasal tip, without intracranial expansion. The cyst, along with the entire tract, was successfully removed surgically, and the postoperative follow-up indicated no complications. Histopathology confirmed the diagnosis of a dermoid cyst. This case underscores the significance of considering the dermoid tract in nasal cyst cases and the necessity of its complete removal to prevent recurrence.

关键词： Dermoid Cyst Nasal Sinus Sinus Tract Intranasal Bone Benign Tumor Congenital Anomaly

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Ambient ammonia production via electrocatalytic nitrite reduction catalyzed by a CoP nanoarray

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Nano Research 2022年第2期15卷 972-977页

作者： Guilai Wen Jie Liang Qian Liu Tingshuai Li Xuguang An Fang Zhang Abdulmohsen ali Alshehri khalid Ahmed Alzahrani Yonglan Luo Qingquan Kong Xuping Sun Chemical Synthesis and Pollution Control Key Laboratory of Sichuan Province School of Chemistry and Chemical EngineeringChina West Normal UniversityNanchong 637002China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China Institute for Advanced Study Chengdu UniversityChengdu 610106China National Engineering Research Center for Nanotechnology No.28 East Jiang Chuan RoadShanghai 200241China Chemistry Department Faculty of ScienceKing Abdulaziz UniversityP.O.Box 80203Jeddah21589Saudi Arabia

Industrial-scale ammonia(NH_(3))production mainly relies on the energy-intensive and environmentally unfriendly Haber-Bosch *** issue can be avoided by electrocatalytic N_(2) reduction which however suffers from limited current efficiency and NH3 ***,we demonstrate ambient NH_(3) production via electrochemical nitrite(NO_(2)^(-))reduction catalyzed by a CoP nanoarray on titanium mesh(CoP NA/TM).When tested in 0.1 M PBS(pH=7)containing 500 ppm N0_(2)^(-),such CoP NA/TM is capable of affording a large NH_(3) yield of 2,260.7±51.5μg·h^(-1)·cm^(-2) and a high Faradaic efficiency of 90.0±2.3%at-0.2 V vs.a reversible hydrogen *** functional theory calculations reveal that the potential-determining step for NO_(2)^(-)reduction over CoP(112)is*NO2→*NO_(2)H.

关键词： CoP nanoarray NO_(2)^(-)reduction reaction ambient NH_(3)synthesis electrocatalysis density functional theory

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A Novel-based Swin Transfer Based Diagnosis of COVID-19 Patients

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Intelligent Automation & Soft Computing 2023年第1期35卷 163-180页

作者： Yassir Edrees Almalki Maryam Zaffar Muhammad Irfan Mohammad ali Abbas Maida khalid K.S.Quraishi Tariq ali Fahad Alshehri Sharifa khalid Alduraibi Abdullah AAsiri Mohammad Abd Alkhalik Basha Alaa Alduraibi M.K.Saeed Saifur Rahman Department of Medicine Division of RadiologyMedical CollegeNajran UniversityNajran11001Saudi Arabia Department of Computer Science and Information Technology Ibadat International UniversityIslamabad44000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran11001Saudi Arabia Department of Chemical Engineering PIEAS UniversityIslamabad44000Pakistan Department of Computer Science COMSATS University Islamabad(CUI)Sahiwal Campus57000Pakistan Department of Radiology College of MedicineQassim UniversityBuraydah52571Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran11001Saudi Arabia Faculty of Human Medicine Zagazig University44631Egypt

The numbers of cases and deaths due to the COVID-19 virus have increased daily all around the *** X-ray is considered very useful and less time-consuming for monitoring COVID *** doubt,X-ray is considered as a quick screening method,but due to variations in features of images which are of X-rays category with Corona confirmed cases,the domain expert is *** address this issue,we proposed to utilize deep learning *** this study,the dataset of COVID-19,lung opacity,viral pneumonia,and lastly healthy patients’images of category X-rays are utilized to evaluate the performance of the Swin transformer for predicting the COVID-19 patients *** performance of the Swin transformer is compared with the other seven deep learning models,including ResNet50,DenseNet121,InceptionV3,EfficientNetB2,VGG19,ViT,CaIT,Swim transformer provides 98%recall and 96%accuracy on corona affected images of the X-ray *** proposed approach is also compared with state-of-the-art techniques for COVID-19 diagnosis,and proposed technique is found better in terms of *** system could support clin-icians in screening patients for COVID-19,thus facilitating instantaneous treatment for better effects on the health of COVID-19 ***,this paper can contribute to saving humanity from the adverse effects of trials that the Corona virus might bring by performing an accurate diagnosis over Corona-affected patients.

关键词： Biomedical systems chest X-ray images CNN COVID-19 swin transformer image processing

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Graph Transformer for Communities Detection in Social Networks

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Computers, Materials & Continua 2022年第3期70卷 5707-5720页

作者： G.Naga Chandrika khalid Alnowibet K.Sandeep Kautish E.Sreenivasa Reddy Adel F.Alrasheedi ali Wagdy Mohamed Department of Computer Science and Engineering ANU College of Engineering and TechnologyGuntur522510India Statistics and Operations Research Department College of ScienceKing Saud UniversityRiyadh11451Kingdom of Saudi Arabia LBEF Campus Kathmandu44600Nepal Department of Computer Science and Engineering ANUGuntur522510India Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12588Egypt

Graphs are used in various disciplines such as telecommunication,biological networks,as well as social *** large-scale networks,it is challenging to detect the communities by learning the distinct properties of the *** deep learning hasmade contributions in a variety of domains,we try to use deep learning techniques to mine the knowledge from large-scale graph *** this paper,we aim to provide a strategy for detecting communities using deep autoencoders and obtain generic neural attention to *** advantages of neural attention are widely seen in the field of NLP and computer vision,which has low computational complexity for large-scale *** contributions of the paper are summarized as ***,a transformer is utilized to downsample the first-order proximities of the graph into a latent space,which can result in the structural properties and eventually assist in detecting the ***,the fine-tuning task is conducted by tuning variant hyperparameters cautiously,which is applied to multiple social networks(Facebook and Twitch).Furthermore,the objective function(crossentropy)is tuned by L0 ***,the reconstructed model forms communities that present the relationship between the *** proposed robust model provides good generalization and is applicable to obtaining not only the community structures in social networks but also the node *** proposed graph-transformer shows advanced performance on the social networks with the average NMIs of 0.67±0.04,0.198±0.02,0.228±0.02,and 0.68±0.03 on Wikipedia crocodiles,Github Developers,Twitch England,and Facebook Page-Page networks,respectively.

关键词： Social networks graph transformer community detection graph classification

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Breast Cancer Detection in Saudi Arabian Women Using Hybrid Machine Learning on Mammographic Images

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Computers, Materials & Continua 2022年第9期72卷 4833-4851页

作者： Yassir Edrees Almalki Ahmad Shaf Tariq ali Muhammad Aamir Sharifa khalid Alduraibi Shoayea Mohessen Almutiri Muhammad Irfan Mohammad Abd Alkhalik Basha Alaa khalid Alduraibi Abdulrahman Manaa Alamri Muhammad Zeeshan Azam Khalaf Alshamrani Hassan A.Alshamrani Division of Radiology Department of MedicineMedical CollegeNajran UniversityNajran61441Kingdom of Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Radiology College of MedicineQassim UniversityBuraidah52571Kingdom of Saudi Arabia Department of Radiology King Fahad Specialist HospitalBuraydah52571Kingdom of Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Kingdom of Saudi Arabia Radiology Department Human Medicine CollegeZagazig UniversityZagazig44631Egypt Department of Surgery College of MedicineNajran UniversityNajran61441Kingdom of Saudi Arabia Department of Computer Science Bahauddin Zakariya UniversityMultan66000Pakistan Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Kingdom of Saudi Arabia

Breast cancer(BC)is the most common cause of women’s deaths *** mammography technique is the most important modality for the detection of *** detect abnormalities in mammographic images,the Breast Imaging Reporting and Data System(BI-RADs)is used as a *** correct allocation of BI-RADs categories for mammographic images is always an interesting task,even for *** this work,to detect and classify the mammogram images in BI-RADs,a novel hybrid model is presented using a convolutional neural network(CNN)with the integration of a support vector machine(SVM).The dataset used in this research was collected from different hospitals in the Qassim health cluster of Saudi *** collection of all categories of BI-RADs is one of the major contributions of this *** significant contribution is the development of a hybrid approach through the integration of CNN and *** proposed hybrid approach uses three CNN models to obtain ensemble CNN model *** ensemble model saves the values to integrate them with *** proposed system achieved a classification accuracy,sensitivity,specificity,precision,and F1-score of 93.6%,94.8%,96.9%,96.6%,and 95.7%,*** proposed model achieved better performance compared to previously available methods.

关键词： Breast cancer CNN SVM BIRADS classification

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Analytical Investigation of Soliton Solutions to Three Quantum Zakharov-Kuznetsov Equations

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Communications in Theoretical Physics 2018年第10期70卷 405-412页

作者： Rahmatullah Ibrahim Nuruddeen khalid Suliman Aboodh khalid K. ali Department of Mathematics Federal University Dutse Department of Mathematics Faculty of Science & Technology Omdurman Islamic University Department of Mathematics Faculty of Science & Arts University of Bisha Mathematics Department Faculty of Science Al-Azhar University

In the present paper, the two-dimensional quantum Zakharov-Kuznetsov(QZK) equation, three-dimensional quantum Zakharov-Kuznetsov equation and the three-dimensional modified quantum Zakharov-Kuznetsov equation are analytically investigated for exact solutions using the modified extended tanh-expansion based method. A variety of new and important soliton solutions are obtained including the dark soliton solution, singular soliton solution, combined dark-singular soliton solution and many other trigonometric function solutions. The used method is implemented on the Mathematica software for the computations as well as the graphical illustrations.

关键词：方程 Mathematica 函数解三角法三维修改分解

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Deep Stacked Ensemble Learning Model for COVID-19 Classification

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Computers, Materials & Continua 2022年第3期70卷 5467-5486页

作者： G.Madhu B.Lalith Bharadwaj Rohit Boddeda Sai Vardhan K.Sandeep Kautish khalid Alnowibet Adel F.Alrasheedi ali Wagdy Mohamed Department of Information Technology VNRVJIETHyderabad500090India Department of Computer Science and Engineering VNRVJIETHyderabad500090India LBEF Campus Kathmandu44600Nepal Statistics and Operations Research Department College of ScienceKing Saud UniversityRiyadh11451Kingdom of Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12588Egypt

COVID-19 is a growing problem worldwide with a high mortality *** a result,the World Health Organization(WHO)declared it a *** order to limit the spread of the disease,a fast and accurate diagnosis is required.A reverse transcript polymerase chain reaction(RT-PCR)test is often used to detect the ***,since this test is time-consuming,a chest computed tomography(CT)or plain chest X-ray(CXR)is sometimes *** value of automated diagnosis is that it saves time and money by minimizing human *** significant contributions are made by our *** initial purpose is to use the essential finetuning methodology to test the action and efficiency of a variety of vision models,ranging from Inception to Neural Architecture Search(NAS)***,by plotting class activationmaps(CAMs)for individual networks and assessing classification efficiency with AUC-ROC curves,the behavior of these models is visually ***,stacked ensembles techniques were used to provide greater generalization by combining finetuned models with six ensemble neural *** stacked ensembles,the generalization of the models ***,the ensemble model created by combining all of the finetuned networks obtained a state-of-the-art COVID-19 accuracy detection score of 99.17%.The precision and recall rates were 99.99%and 89.79%,respectively,highlighting the robustness of stacked *** proposed ensemble approach performed well in the classification of the COVID-19 lesions on CXR according to the experimental results.

关键词： COVID-19 classification class activation maps(CAMs)visualization finetuning stacked ensembles automated diagnosis deep learning

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Managing Delivery of Safeguarding Substances as a Mitigation Against Outbreaks of Pandemics

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Computers, Materials & Continua 2021年第7期68卷 1161-1181页

作者： Said ali Hassan khalid Alnowibet Prachi Agrawal ali Wagdy Mohamed Department of Operations Research and Decision Support Faculty of Computers and Articial IntelligenceCairo UniversityGiza12613Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadhSaudi Arabia Trafc Safety Technologies Chair Vice Deanship of Scientic ResearchKing Saud UniversityRiyadhSaudi Arabia Department of Mathematics and Scientic Computing National Institute of TechnologyHamirpur177005India Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt School of Engineering and Applied Sciences Wireless Intelligent Networks Center(WINC)Nile UniversityGizaEgypt

The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics.A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specic time period.A nonlinear binary mathematical programming model for the problem is *** decision variables are binary ones that represent whether to choose a specic consumer,and design constraints are formulated to keep track of the chosen *** better illustrate the problem,objective,and problem constraints,a real application case study is *** case study involves the optimum delivery of safeguarding substances to several hospitals in the Al-Gharbia Governorate in *** hospitals are selected to represent the consumers of safeguarding substances,as they are the rst crucial frontline for mitigation against a pandemic outbreak.A distribution truck is used to distribute the substances from the main store to the hospitals in specied required quantities during a given working *** objective function is formulated in order to maximize the total amount of delivered quantities during the specied time *** case study is solved using a novel Discrete Binary Gaining Sharing Knowledge-based Optimization algorithm(DBGSK),which involves two main stages:discrete binary junior and senior gaining and sharing *** has the ability of nding the solutions of the introduced problem,and the obtained results demonstrate robustness and convergence toward the optimal solutions.

关键词： Safeguarding substances mitigation against pandemic outbreaks supply chain management metaheuristic optimization

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Robowler:Design and development of a cricket bowling machine ensuring ball seam position

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Journal of Central South University 2014年第11期21卷 4142-4149页

作者： RAZA ali DIEGEL Olaf ARIF khalid Mahmood Mechatronics and Control Engineering University of Engineering & TechnologyLahore 54890 Pakistan School of Engineering and Advanced Technology Massey UniversityAuckland 0632 New Zealand

The art of cricket bowling is complex and arduous owing to the run-up and ball release time energy requirement to achieve speed and variations. Therefore, human bowlers cannot bowl for extended periods and numerous mechanical bowling machines have been built to help batsmen improve their skills during practice sessions. However, most of these existing machines are designed for spherical balls ignoring the distinguishing physical feature of a cricket ball: the raised equatorial seam, which makes it less of a sphere. The bowlers are known to often benefit from this seam in their pursuit to taking the batsmen's wicket by imparting swing, spin and bounce variations along-with other bowling variables. This lack of the seam consideration creates a void between human and mechanical bowling. In this work, we present design and development of an automatic bowling machine termed as ROBOWLER to make mechanical bowling more realistic. This machine ensures ball seam position as well as fulfills other constraints. Ball pitching and seam position accuracy results underscore the suitability of this design to enhance the capabilities of mechanical bowling.

关键词：保龄球馆焊缝位置开发板设计机械设备释放时间物理特征位置精度

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