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The Development Trends and Research Fronts in Orbital Angular Momentum Technology:A Bibliometric Analysis

China Communications 2023年第2期20卷 289-310页

作者： Saleemullah Memon Xiuping Li Kamran Ali Memon Yuhan Huang junaid ahmed uqaili Muhammad Ishfaq School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Telecommunication Engineering Quaid-e-Awam University of EngineeringScience&TechnologyPakistan

Orbital angular momentum(OAM)technology,refers to Laguerre-Gaussian(LG)beams,twisted beams,vector/vortex beams,acoustic vortex beams and fractional vortex *** is an emerging and promising technology to improve the communication capacity,spectral efficiency,and anti-jamming capability due to its helical phase fronts and infinite orthogonal *** the OAM research began in the 1990s,the developing trends,current status,issues and characteristics through a systematic observation have not yet been *** paper presents a knowledge-based evolution of OAM research published in the Web of Science(WoS)from 2011 to 2021 using bibliometric analysis in *** results demonstrate that the bandwidth,efficiency,gain,divergence,phase quantization,bulky and complex feeding structures,misalignment,distortion,interferences atmospheric turbulence and diffraction were the key issues found in the OAM *** main research hotspots and categories,influential authors,leading journals,best institutions of OAM show a strong bias in favor of their functions and technology *** research on OAM was mainly performed by the counties that have developed the 5G and now moving towards 6G communications like China,USA and South *** study would serve as an inclusive guide on the future research trends and status especially for the OAM researchers.

关键词： orbital angular momentum(OAM) vortex beams bibliometric analysis CiteSpace

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COVID-19: cross-immunity of viral epitopes may influence severity of infection and immune response

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Signal Transduction and Targeted Therapy 2021年第4期6卷 1071-1072页

作者： junaid Kashir Khaled AlKattan ahmed Yaqinuddin College of Medicine Alfaisal UniversityRiyadhKingdom of Saudi Arabia Department of Comparative Medicine King Faisal Specialist Hospital and Research CenterRiyadhKingdom of Saudi Arabia

A recent study published in Science by Shrock et al.1 examined how responses to COVID-19 severity differed amongst patients with different prior viral exposure history,finding notable correlations between *** serological profiling provides a window into differential viral responses amongst patients with diverse outcomes,potentially mediating improved therapeutics and vaccines for SARS-CoV-2.

关键词： severity immunity al.

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Enhancing Cloud Performance Using File Format Classifications

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Computers, Materials & Continua 2022年第2期70卷 3985-4007页

作者： Muhammad junaid Adnan Sohail Monagi H.Alkinani Adeel ahmed Mehmood ahmed Faisal Rehman Department of Computing Iqra UniversityIslamabadPakistan Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Technology The University of Haripur Department of Computing COMSATS UniversityAbbottabad CampusPakistan

Metaheuristic approaches in cloud computing have shown significant results due to theirmulti-objective *** approaches are now considering hybridmetaheuristics combining the relative optimized benefits of two or more algorithms resulting in the least tradeoffs among several *** critical factors such as execution time,throughput time,response time,energy consumption,SLA violations,communication overhead,makespan,and migration time need careful attention while designing such dynamic *** improve such factors,an optimizedmulti-objective hybrid algorithm is being proposed that combines the relative advantages of Cat Swarm Optimization(CSO)with machine learning classifiers such as Support Vector Machine(SVM).The adopted approach is based on SVMone to many classification models of machine learning that performs the classifications of various data format types in the cloud with best *** CSO,grouping phase is used to divide the data files as audio,video,image,and text which is further extended by polynomial Kernel function based on various input features and used for optimized load ***,proposed approach works well and achieved performance efficiency in evaluated QoS metrics such as average energy consumption by 12%,migration time by 9%,and optimization time by 10%,in the presence of competitor baselines.

关键词： Classification load balancing optimization cloud computing

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A Hybrid Model for Improving Software Cost Estimation in Global Software Development

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Computers, Materials & Continua 2024年第1期78卷 1399-1422页

作者： Mehmood ahmed Noraini B.Ibrahim Wasif Nisar Adeel ahmed Muhammad junaid Emmanuel Soriano Flores Divya Anand Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit RajaBatu Pahat86400Malaysia Department of Computer Science COMSATS University Wah Cantt CampusIslamabad47010Pakistan Department of Information Technology The University of HaripurKhyber Pakhtunkhwa22620Pakistan Engineering Research Innovation Group Universidad Europea del AtlanticoSantander39011Spain

Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert *** models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate *** addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation ***,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost *** study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these *** proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry *** article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost *** the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing *** findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.

关键词： Artificial neural networks COCOMO II cost drivers global software development linear regression software cost estimation

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Current Trends and Perspectives of Detection and Location for Buried Non-Metallic Pipelines

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 118-146页

作者： Liang Ge Changpeng Zhang Guiyun Tian Xiaoting Xiao junaid ahmed Guohui Wei Ze Hu Ju Xiang Mark Robinson School of Mechanical and Electrical Engineering Southwest Petroleum UniversityChengdu 610500China School of Engineering Newcastle UniversityNewcastle NE17RUUK School of Electrical Information Southwest Petroleum UniversityChengdu 610500China Electrical Department Sukkur IBA UniversitySukkur 65200Pakistan School of Science Southwest Petroleum UniversityChengdu 610500China

Buried pipelines are an essential component of the urban infrastructure of modern *** buried pipes are mainly made of metal *** the development of material science and technology in recent years,non-metallic pipes,such as plastic pipes,ceramic pipes,and concrete pipes,are increasingly taking the place of pipes made from metal in various pipeline networks such as water supply,drainage,heat,industry,oil,and *** location technologies for the location of the buried metal pipeline have become mature,but detection and location technologies for the non-metallic pipelines are still *** this paper,current trends and future perspectives of detection and location of buried non-metallic pipelines are ***,this paper reviews and analyzes electromagnetic induction technologies,electromagnetic wave technologies,and other physics-based *** then focuses on acoustic detection and location technologies,and finally introduces emerging *** the technical characteristics of each detection and location method have been compared,with their strengths and weaknesses *** current trends and future perspectives of each buried non-metallic pipeline detection and location technology have also been ***,some suggestions for the future development of buried non-metallic pipeline detection and location technologies are provided.

关键词： Non-metallic pipeline Pipeline detection and location Non-destructive test and evaluation Acoustic technologies

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Effect of layer sliding on the interfacial electronic properties of intercalated silicene/indium selenide van der Waals heterostructure

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Communications in Theoretical Physics 2022年第3期74卷 112-118页

作者： Masood Yousaf M W Younis ahmed S Jbara M junaid Iqbal Khan G Murtaza M A Saeed Department of Physics Division of Science and TechnologyUniversity of EducationLahore54770Pakistan Department of Chemistry University of Management and TechnologyC-IIJohar TownLahore54770Pakistan Mathematics Department College of Education for Pure ScienceAl-Muthanna UniversitySamawah66001Iraq Laboratory of Theoretical and Experimental Physics Department of PhysicsBahauddin Zakariya UniversityMultan60800Pakistan Materials Modelling Lab Department of PhysicsIslamia College PeshawarKPPakistan Department of Mathematics&Natural Sciences Prince Mohammad Bin Fahd UniversityP.O.Box 1664Alkhobar 31952Saudi Arabia

Methods capable of tuning the properties of van der Waals(vdW)layered materials in a controlled and reversible manner are highly *** electronic properties of two-dimensional vdW heterostructure consisting of silicene and indium selenide(InSe)have been calculated using density functional theory-based computational ***,in order to vary the aforementioned properties,silicene is slid over a InSe layer in the presence of Li *** intercalation of the heterostructure,the buckling parameter associated with the corrugation of silicene decreases from 0.44A to 0.36A,whereas the InSe structure remains *** energy scans reveal a significant increase in the sliding energy barrier for the case of intercalated heterostructure as compared with the unintercalated *** sliding of the silicene encounters the maximum energy barrier of 0.14 *** analysis shows the noteworthy differences between calculated in-plane and out-of-plane part of dielectric function.A variation of the planar average charge density difference,dipole charge transfer and dipole moment have been discussed to elucidate the usability spectrum of the *** employed approach based on intercalation and layer sliding can be effectively utilized for obtaining next-generation multifunctional devices.

关键词： vdW heterostructure intercalation tuning of properties layer sliding interfacial electronic properties

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Detecting and Mitigating DDOS Attacks in SDNs Using Deep Neural Network

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Computers, Materials & Continua 2023年第11期77卷 2157-2178页

作者： Gul Nawaz Muhammad junaid Adnan Akhunzada Abdullah Gani Shamyla Nawazish Asim Yaqub Adeel ahmed Huma Ajab Department of Information Technology The University of HaripurHaripur22060Pakistan Faculty of Computing and Informatics University Malaysia SabahSabah88400Malaysia Department of Environmental Sciences COMSATS University Abbottabad CampusAbbottabad22010Pakistan Department of Chemistry COMSATS University Abbottabad CampusAbbottabad22010Pakistan

Distributed denial of service(DDoS)attack is the most common attack that obstructs a network and makes it unavailable for a legitimate *** proposed a deep neural network(DNN)model for the detection of DDoS attacks in the Software-Defined Networking(SDN)*** centralizes the control plane and separates it from the data *** simplifies a network and eliminates vendor specification of a *** of this open nature and centralized control,SDN can easily become a victim of DDoS *** proposed a supervised Developed Deep Neural Network(DDNN)model that can classify the DDoS attack traffic and legitimate *** Developed Deep Neural Network(DDNN)model takes a large number of feature values as compared to previously proposed Machine Learning(ML)*** proposed DNN model scans the data to find the correlated features and delivers high-quality *** model enhances the security of SDN and has better accuracy as compared to previously proposed *** choose the latest state-of-the-art dataset which consists of many novel attacks and overcomes all the shortcomings and limitations of the existing *** model results in a high accuracy rate of 99.76%with a low false-positive rate and 0.065%low loss *** accuracy increases to 99.80%as we increase the number of epochs to 100 *** proposed model classifies anomalous and normal traffic more accurately as compared to the previously proposed *** can handle a huge amount of structured and unstructured data and can easily solve complex problems.

关键词： Distributed denial of service(DDoS)attacks software-defined networking(SDN) classification deep neural network(DNN)

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Brain Tumor Segmentation using Multi-View Attention based Ensemble Network

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Computers, Materials & Continua 2022年第9期72卷 5793-5806页

作者： Noreen Mushtaq Arfat Ahmad Khan Faizan ahmed Khan Muhammad junaid Ali Malik Muhammad Ali Shahid Chitapong Wechtaisong Peerapong Uthansakul COMSATS University Islamabad Islamabad Campus45550Pakistan Suranaree University of Technology Nakhon Ratchasima30000Thailand COMSATS University Islamabad Lahore Campus54000Pakistan Virtual University of Pakistan Islamabad Campus45550Pakistan COMSATS University Islamabad Vehari Campus61100Pakistan

Astrocytoma IV or glioblastoma is one of the fatal and dangerous types of brain *** detection of brain tumor increases the survival rate and helps in reducing the fatality *** imaging modalities have been used for diagnosing by expert radiologists,and Medical Resonance Image(MRI)is considered a better option for detecting brain tumors as MRI is a non-invasive technique and provides better visualization of the brain *** of the challenging issues is to identify the tumorous region from the MRI scans *** segmentation is performed by medical experts,which is a time-consuming task and got chances of *** overcome this issue,automatic segmentation is performed for quick and accurate *** proposed approach is to capture inter-slice information and reduce the *** learning-based brain tumor segmentation techniques proved best among available segmentation ***,deep learning may miss some preliminary info while using MRI images during *** MRI volumes are volumetric,3D U-Net-based models are used but *** of multiple 2D U-Net predictions in axial,sagittal,and coronal views help to capture inter-slice *** approach may reduce the system ***,the Conditional Random Fields(CRF)reduce the predictions’false positives and improve the segmentation *** model is applied to Brain Tumor Segmentation(BraTS)2019 dataset,and cross-validation is performed to check the accuracy of *** proposed approach achieves Dice Similarity Score(DSC)of 0.77 on Enhancing Tumor(ET),0.90 on Whole Tumor(WT),and 0.84 on Tumor Core(TC)with reduced Hausdorff Distance(HD)of 3.05 on ET,5.12 on WT and 3.89 on TC.

关键词： Brain tumor deep learning detection conditional random field segmentation

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Cloud-based ***-based IoT:a comparative survey and way forward

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Frontiers of Information Technology & Electronic Engineering 2020年第4期21卷 563-586页

作者： Raheel ahmed MEMON Jian Ping LI junaid ahmed Muhammad Irshad NAZEER Muhammad ISMAIL Khursheed ALI School of Computer Science and Technology University of Electronic Science and Technology of ChinaChengdu 610031China Department of Computer Science Sukkur IBA UniversitySukkur 65200Pakistan School of Automation University of Electronic Science and Technology of ChinaChengdu 610031China

The Internet of Things(IoT)has been evolving for more than a *** advancements have increased its popularity,but concerns and risks related to IoT are growing considerably along with the increased number of connected *** 2013,a new cryptography-based infrastructure called blockchain emerged with the potential to replace the existing cloud-based infrastructure of IoT through *** this article,we provide a taxonomy of the challenges in the current IoT infrastructure,and a literature survey with a taxonomy of the issues to expect in the future of the IoT after adopting blockchain as an *** two architectures are compared based on their strengths and *** a brief survey of ongoing key research activities in blockchain is presented,which will have considerable impact on overcoming the challenges encountered in the applicability of blockchain in ***,considering the challenges and issues in both infrastructures and the latest research activities,we propose a high-level hybrid IoT approach that uses the cloud,edge/fog,and blockchain together to avoid the limitations of each infrastructure.

关键词： Internet of Things(IoT) Cloud Blockchain Data center Taxonomy

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Crop Yield Prediction Using Machine Learning Approaches on a Wide Spectrum

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Computers, Materials & Continua 2022年第9期72卷 5663-5679页

作者： SVinson Joshua ASelwin Mich Priyadharson Raju Kannadasan Arfat Ahmad Khan Worawat Lawanont Faizan ahmed Khan Ateeq Ur Rehman Muhammad junaid Ali Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Suranaree University of Technology Nakhon Ratchasima30000Thailand University of Central Punjab Lahore54000Pakistan Government College University Lahore54000Pakistan Virtual University of Pakistan Islamabad Campus45550Pakistan

The exponential growth of population in developing countries likeIndia should focus on innovative technologies in the Agricultural processto meet the future crisis. One of the vital tasks is the crop yield predictionat its early stage;because it forms one of the most challenging tasks inprecision agriculture as it demands a deep understanding of the growth patternwith the highly nonlinear parameters. Environmental parameters like rainfall,temperature, humidity, and management practices like fertilizers, pesticides,irrigation are very dynamic in approach and vary from field to field. In theproposed work, the data were collected from paddy fields of 28 districts in widespectrum of Tamilnadu over a period of 18 years. The Statistical model MultiLinear Regression was used as a benchmark for crop yield prediction, whichyielded an accuracy of 82% owing to its wide ranging input data. Therefore,machine learning models are developed to obtain improved accuracy, namelyBack Propagation Neural Network (BPNN), Support Vector Machine, andGeneral Regression Neural Networks with the given data set. Results showthat GRNN has greater accuracy of 97% (R2 = 0.97) with a normalizedmean square error (NMSE) of 0.03. Hence GRNN can be used for crop yieldprediction in diversified geographical fields.

关键词： Machine learning crop yield prediction computer simulation and modelling

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