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Entropy generation for mixed convection flow in vertical annulus with two regions hydromagnetic viscous and Cu-Ag water hybrid nanofluid through porous zone: a comparative numerical study

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Propulsion and Power Research 2022年第3期11卷 401-415页

作者： T.Rahim J.Hasnain n.abid Z.Abbas Department of Mathematics The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Sciences Bahria UniversityIslamabad44000Pakistan

The primary determination of this study is a numerical investigation of the entropygeneration (EG) in the steady two-region flow of viscous fluid and hybrid nanofluid (nF) in along-infinite vertical annulus having a clear region as well as porous media. Stoke’s and single-phase nF models are used to study the viscous fluid and hybrid nanofluid (HnF) heat transferdevelopments, respectively. Two types of nanoparticles are taken, such as copper (Cu) and sil-ver (Ag) within base fluid water to make it a HnF. Darcy-Brinkman law is also used to examinethe flow through the porous zone in the annulus. necessary quantities have been used in thesystem of equations to transfer them into non-dimensional forms. For momentum and energytransport, the numerical results are evaluated for various model parameters and are examinedvia the shooting method in MATHEMATICA. It is noted that the momentum and energy trans-port are more significant when two immiscible fluids in a clear vertical annulus are taken. Thefindings also indicate that two-phase momentum and heat flow are greater when a nF is used in Region-II and lower when a HnF is used. The temperature (in Region-II) falls with a high na-nomaterials volume fraction (see Figure 4) while it is increased when the Hartman number isincreased. Moreover, velocity declines with increment in nanomaterials volume fraction. Thus,higher thermal conductivity can be accomplished by using a magnetic field.

关键词： Two-phase flow Hybrid nanofluid Viscous fluid Porous zone Vertical annulus Entropy generation

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Cybernet Model:A new Deep Learning Model for Cyber DDoS Attacks Detection and Recognition

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Computers, Materials & Continua 2024年第1期78卷 1275-1295页

作者： Azar abid Salih Maiwan Bahjat Abdulrazaq Department of Information Technology Technical College of DuhokDuhok Polytechnic UniversityDuhokIraq Department of Computer Science Faculty of ScienceUniversity of ZakhoDuhokIraq

Cyberspace is extremely dynamic,with new attacks arising *** cybersecurity controls is vital for network *** Learning(DL)models find widespread use across various fields,with cybersecurity being one of the most crucial due to their rapid cyberattack detection capabilities on networks and *** capabilities of DL in feature learning and analyzing extensive data volumes lead to the recognition of network traffic *** study presents novel lightweight DL models,known as Cybernet models,for the detection and recognition of various cyber Distributed Denial of Service(DDoS)*** models were constructed to have a reasonable number of learnable parameters,i.e.,less than 225,000,hence the name“lightweight.”This not only helps reduce the number of computations required but also results in faster training and inference ***,these models were designed to extract features in parallel from 1D Convolutional neural networks(Cnn)and Long Short-Term Memory(LSTM),which makes them unique compared to earlier existing architectures and results in better performance *** validate their robustness and effectiveness,they were tested on the CIC-DDoS2019 dataset,which is an imbalanced and large dataset that contains different types of DDoS *** results revealed that bothmodels yielded promising results,with 99.99% for the detectionmodel and 99.76% for the recognition model in terms of accuracy,precision,recall,and F1 ***,they outperformed the existing state-of-the-art models proposed for the same ***,the proposed models can be used in cyber security research domains to successfully identify different types of attacks with a high detection and recognition rate.

关键词： Deep learning Cnn LSTM Cybernet model DDoS recognition

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Film Flow of nano-Micropolar Fluid with Dissipation Effect

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2487-2512页

作者： Abuzar abid Siddiqui Mustafa Turkyilmazoglu Department of Basic Sciences&Humanities Faculty of Engineering&TechnologyBahauddin Zakariya UniversityMultanPakistan Department of Mathematics Hacettepe UniversityAnkaraTürkiye Department of Medical Research China Medical University HospitalChina Medical UniversityTaichungTaiwanChina

The physical problem of the thin film flow of a micropolar fluid over a dynamic and inclined substrate under the influence of gravitational and thermal forces in the presence of nanoparticles is *** different types of nanoparticle samples are accounted for in this current study,namely gold Au,silver Ag,molybdenum disulfide MoS_(2),aluminum oxide Al_(2)O_(3),and silicon dioxide SiO_(2).Blood,a micropolar fluid,serves as the common base *** exact closed-form solution for this problem is derived for the first time in the *** results are particularly validated against those for the newtonian fluid and show excellent *** was found that increasing values of the spin boundary condition and micropolarity lead to a reduction in both the thermal and momentum boundary layers.A quantitative decay in the nusselt number for a micropolar fluid,as compared to a newtonian one for all the tested nanoparticles,is *** and silver nanoparticles(i)intensify in the flow parameter as the concentration of nanoparticles increases(ii)yield a higher thermal transfer rate,whereas molybdenum disulfide,aluminum oxide,and silicon dioxide exhibit a converse attitude for both newtonian and micropolar *** reduction in film thickness for fluid comprising gold particles,as compared to the rest of the nanoparticles,is remarkable.

关键词： Thin film flow micropolar fluid nanoparticles molybdenum disulfide inclined substrate

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Dust particle surface potential in an argonhelium plasma using the(r,q)-distribution function

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Communications in Theoretical Physics 2024年第9期76卷 143-150页

作者： Bahaaudin M Raffah A A abid Abdullah Khan Amin Esmaeili Yas Al-Hadeethi M n S Qureshi Department of Physics Faculty of Sciences King Abdulaziz University Lithography in Devices Fabrication and Development Research Group Deanship of Scientific ResearchKing Abdulaziz University Joint Laboratory of Plasma Application Technology Institute of Advanced Technology University of Science and Technology of China CAS Key Laboratory of Geospace Environment University of Science and Technology of China Department of Physics Zhejiang Normal University Department of Physics Graduate School of Science Tokyo Metropolitan University Department of Physics GC University

In this paper, the dust particle surface potential for argon-helium plasma is evaluated analytically and numerically in the context of negatively charged dust particles by employing a power-law(r, q)-distribution function. Recent studies have reported the argon-helium plasma and conducted a brief theoretical and experimental survey. To deepen our understanding further, this study aims to analyze the argon-helium plasma comprehensively using the same pattern but with the(r, q)-distribution function. For this purpose, the current balance equations are derived for electron, helium and argon ions, when these charge species attain the quasineutrality *** numerically examined the currents of plasma species for a broad range of effective distribution function parameters r and q. It is revealed that the surface potential of dust particles is significantly affected by the parameters r and q, helium ion-to-electron temperature ratio,argon ion-to-electron temperature ratio, and helium ion to argon ion number density ratio. By incorporating the multi-ion(argon-helium) species, the significance of low-temperature nonMaxwellian dusty(complex) plasma is briefly examined.

关键词： dust charge potential dusty plasma helium argon plasma non-Maxwellian distribution plasma physics q distribution function r

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Experimental Study on Heat Storage Properties Comparison of Paraffin/Metal Foams Phase Change Material Composites

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Journal of Thermal Science 2024年第2期33卷 469-478页

作者： Waqar AHMED abid HUSSAIn Hanzla SHAHID Imran ALI Hafiz Muhammad ALI Department of Mechanical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Mechanical Engineering Institute of Space TechnologyIslamabadPakistan Department of Mechanical Mechatronics and Manufacturing EngineeringUniversity of Engineering and Technology LahoreFaisalabad CampusPunjabPakistan Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

Heat storage properties of phase change materials(PCMs) are essential characteristics that perform a key role in thermal heat energy storage *** thermal properties of PCMs can be improved by developing metal foam/PCM *** addition of metal foam in PCMs has a significant effect on the thermal characteristics of *** this paper,the heat storage properties of two different metal foam/PCM composites were experimentally *** behavior of paraffin in metal foam(copper and iron-nickel)/paraffin composites concerning pure paraffin at a constant heat flux of 1000 W/m^(2) in three directions simultaneously(x,y,and z) was *** was infiltrated into copper and iron-nickel foams to develop composite materials which resulted in enhancing the thermal conductivity of the paraffin.A comparative analysis is made on the heat storage properties of paraffin in copper and iron-nickel foams/paraffin *** temperature distribution during the phase transition process is experimentally *** comparison indicates that temperature uniformity in copper foam/paraffin composite is better than in iron-nickel foam/paraffin composite and pure paraffin at the same heat *** results show that at heat flux of 1000 W/m^(2),the heat storage time for copper foam/paraffin composite is 20.63% of that of iron-nickel foam/paraffin composite.

关键词： heat storage capacity paraffin/metal foam composite temperature uniformity heat storage rate phase transition process

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Computational Fluid Dynamics Approach for Predicting Pipeline Response to Various Blast Scenarios: A numerical Modeling Study

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2747-2777页

作者： Farman Saifi Mohd Javaid abid Haleem S.M.Anas Department of Mechanical Engineering Jamia Millia Islamia(A Central University)New Delhi110025India Department of Civil Engineering Jamia Millia Islamia(A Central University)New Delhi110025India

Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infras-tructure systems and networks capable of withstanding blast *** centered on high-profile facilities such as embassies and petrochemical plants,this concern now extends to a wider array of infrastructures and *** and scholars increasingly prioritize structural safety against explosions,particularly to prevent disproportionate collapse and damage to nearby *** has further amplified the reliance on oil and gas pipelines,making them vital for urban life and prime targets for terrorist ***,there is a growing imperative for computational engineering solutions to tackle blast loading on pipelines and mitigate associated risks to avert *** this study,an empty pipe model was successfully validated under contact blast conditions using Abaqus software,a powerful tool in mechanical engineering for simulating blast effects on buried *** a Eulerian-Lagrangian computational fluid dynamics approach,the investigation extended to above-surface and below-surface blasts at standoff distances of 25 and 50 *** descriptions in the numerical model relied on Abaqus’default mechanical *** analysis revealed varying pipe performance,with deformation decreasing as explosion-to-pipe distance *** explosion’s location relative to the pipe surface notably influenced deformation levels,a key finding highlighted in the ***,quantitative findings indicated varying ratios of plastic dissipation energy(PDE)for different blast scenarios compared to the contact blast(P0).Specifically,P1(25 mm subsurface blast)and P2(50 mm subsurface blast)showed approximately 24.07%and 14.77%of P0’s PDE,respectively,while P3(25 mm above-surface blast)and P4(50 mm above-surface blast)exhibited lower PDE values,accounting for about 18.08%and 9.67%of P0’s PDE,***

关键词： Blast loading computational fluid dynamics computer modeling pipe networks response prediction structural safety

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A novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

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Computers, Materials & Continua 2024年第5期79卷 3373-3395页

作者： Farhan Ullah Xuexia Zhang Mansoor Khan Muhammad abid Abdullah Mohamed School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China College of Intelligent Manufacturing and Control Engineering Qilu Institute of TechnologyJinan250200China College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China Research Centre Future University in EgyptNew Cairo11835Egypt

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance *** approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering *** approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

关键词： Ensemble learning machine learning real-time data analysis stakeholder analysis temporal convolutional network wind power forecasting

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Toward sustainable waste management in small islands developing states: integrated waste-to-energy solutions in Maldives context

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Frontiers of Environmental Science & Engineering 2024年第2期18卷 133-148页

作者： Yao Wang Alejandro Ruiz-Acevedo Eemaan Rameez Vijaya Raghavan.abid Hussain Xunchang Fei School of Civil and Environmental Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore United nations Office for Project Services(UnOPS) United Nations BuildingBuruzu MaguMale’20184Maldives Department of Bioresource Engineering McGill UniversitySte-Anne-De-BellevueQuebec H9X 3V9Canada Department of Civil and Environmental Engineering Carleton UniversityOttawaOntario K1S 5B6H9X 3V9Canada

Effective waste management is a major challenge for Small Island Developing States (SIDS) like Maldives due to limited land availability. Maldives exemplifies these issues as one of the most geographically dispersed countries, with a population unevenly distributed across numerous islands varying greatly in size and population density. This study provides an in-depth analysis of the unique waste management practices across different regions of Maldives in relation to its natural and socioeconomic context. Data shows Maldives has one of the highest population density and per capita waste generation among SIDS, despite its small land area and medium GDP per capita. Large disparities exist between the densely populated capital Male’ with only 5.8 km2 area generating 63% of waste and the ~194 scattered outer islands with ad hoc waste management practices. Given Male’s dense population and high calorific waste, incineration could generate up to ~30 GW/a energy and even increase Maldives’ renewable energy supply by 200%. In contrast, decentralized anaerobic digestion presents an optimal solution for outer islands to reduce waste volume while providing over 40%–100% energy supply for daily cooking in local families. This timely study delivers valuable insights into designing context-specific waste-to-energy systems and integrated waste policies tailored to Maldives’ distinct regions. The framework presented can also guide other SIDS facing similar challenges as Maldives in establishing sustainable, ecologically sound waste management strategies.

关键词： Anaerobic digestion Waste incineration Waste management Maldives Small Island Developing States Waste-to-energy

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Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

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Computers, Materials & Continua 2024年第3期78卷 3413-3429页

作者： Rabia abid Muhammad Rizwan Abdulatif Alabdulatif Abdullah Alnajim Meznah Alamro Mourade Azrour Department of Computer Science Kinnaird College for WomenLahorePakistan College of Science and Engineering University of DerbyDerbyDE221GBUK Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia STI Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsMeknesMorocco

Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and *** Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data *** this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare *** experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)*** experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.

关键词： Artificial intelligence data privacy federated machine learning healthcare system security

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Enhancing Communication Accessibility:UrSL-Cnn Approach to Urdu Sign Language Translation for Hearing-Impaired Individuals

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 689-711页

作者： Khushal Das Fazeel abid Jawad Rasheed Kamlish Tunc Asuroglu Shtwai Alsubai Safeeullah Soomro Department of Computer Engineering Modeling Electronics and Systems EngineeringUniversity of CalabriaRende Cosenza87036Italy Department of Information Systems University of Management and TechnologyLahore54770Pakistan Department of Computer Engineering Istanbul Sabahattin Zaim UniversityIstanbul34303Turkey Department of Software Engineering Istanbul Nisantasi UniversityIstanbul34398Turkey Department of Computer Science COMSATS University IslamabadLahore CampusLahore54700Pakistan Faculty of Medicine and Health Technology Tampere UniversityTampere33720Finland Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Second Department of Computer Science College of Engineering and ComputingGeorge Mason UniversityFairfaxVA 4418USA

Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other SLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrSL)using the UrSL-Cnn model,a convolutional neural network(Cnn)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,Gaussiannaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrSL alphabets dataset demonstrated the superiority of UrSL-Cnn,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.

关键词： Convolutional neural networks Pakistan sign language visual language

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