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Fluid Dynamics & Materials Processing 2024年第2期20卷 293-310页

作者： G.Dharmaiah F.Mebarek-Oudina k.s.balamurugan N.Vedavathi Department of Mathematics Narasaraopeta Engineering CollegeNarasaraopetIndia Department of Physics Faculty of SciencesUniversity of 20 Août 1955-SkikdaSkikdaAlgeria Department of Mathematics RVR&JC College of EngineeringGunturIndia Department of Mathematics Koneru Lakshmaiah Education FoundationVaddeswaramIndia

The effects of a magnetic dipole on a nonlinear thermally radiative ferromagnetic liquidﬂowing over a stretched surface in the presence of Brownian motion and thermophoresis are *** means of a similarity transformation,ordinary differential equations are derived and solved afterwards using a numerical(the BVP4C)*** impact of various parameters,namely the velocity,temperature,concentration,is presented *** is shown that the nanoparticles properties,in conjunction with the magnetic dipole effect,can increase the thermal conductivity of the engineered nanoﬂuid and,consequently,the heat *** with earlier studies indicates high accuracy and effectiveness of the numerical *** increase in the Brow-nian motion parameter and thermophoresis parameter enhances the concentration and the related boundary *** skin-friction rises when the viscosity parameter is increased.A larger value of the ferromagnetic para-meter results in a higher skin-friction and,vice versa,in a smaller Nusselt number.

关键词： Brownian motion thermo-phoresis radiation magnetic dipole BVP4C non-linear

A Novel Framework for Learning and Classifying the Imbalanced Multi-Label Data

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Computer systems science & Engineering 2024年第5期48卷 1367-1385页

作者： P.k.A.Chitra s.Appavu alias balamurugan s.Geetha seifedine kadry Jungeun kim keejun Han Department of Computer science and Engineering SRM Institute of Science and TechnologyTiruchirappalliTamil Nadu603203India Department of Computer science and Engineering Periyar Maniammai Institute of Science&Technology(Deemed to be University)ThanjavurTamil Nadu613403India school of Computer science and Engineering ChennaiTamil Nadu600048India Department of Applied Data science Noroff University CollegeKristiansand4612Norway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityP.O.Box 346AjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblos10150Lebanon Department of software Kongju National UniversityCheonan31080Republic of Korea Division of Computer Engineering Hansung UniversitySeoul02876Republic of Korea

A generalization of supervised single-label learning based on the assumption that each sample in a dataset may belong to more than one class simultaneously is called multi-label *** main objective of this work is to create a novel framework for learning and classifying imbalancedmulti-label *** work proposes a framework of two *** imbalanced distribution of themulti-label dataset is addressed through the proposed Borderline MLsMOTE resampling method in phase ***,an adaptive weighted l21 norm regularized(Elastic-net)multilabel logistic regression is used to predict unseen samples in phase *** proposed Borderline MLsMOTE resampling method focuses on samples with concurrent high labels in contrast to conventional *** minority labels in these samples are called difficult minority labels and are more prone to penalize classification *** concurrentmeasure is considered borderline,and labels associated with samples are regarded as borderline labels in the decision *** phase II,a novel adaptive l21 norm regularized weighted multi-label logistic regression is used to handle balanced data with different weighted synthetic *** on various benchmark datasets shows the outperformance of the proposed method and its powerful predictive performances over existing conventional state-of-the-art multi-label methods.

关键词： Multi-label imbalanced data multi-label learning Borderline MLsMOTE concurrent multi-label adaptive weighted multi-label elastic net difficult minority label

Understanding the corrosion and bio-corrosion behaviour of Magnesium composites – a critical review

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Journal of Magnesium and Alloys 2024年第3期12卷 890-939页

作者： Prithivirajan sekar s.k.Panigrahi Department of Mechanical Engineering Indian Institute of Technology MadrasChennai600036India Applied Magnesium Research Center Center of Excellence in Materials and Manufacturing for Futuristic MobilityIndian Institute of Technology MadrasChennai600036India

Realising the potential of Magnesium(Mg),several globally leading ventures have invested in the Mg industry,but their relatively poor corrosion resistance is a never ending saga till *** corrosion and bio-corrosion behaviour of Mg has gained research attention and still remains a hot topic in the application of automobile,aerospace and biomedical *** intrinsic high electrochemical nature of Mg limits their utilization in diverse *** scenario has prompted the development of Mg composites with an aim to achieve superior corrosion and bio-corrosion *** present review enlightens the influence of grain size(Gs),secondary phase,texture,type of matrix and reinforcement on the corrosion and bio-corrosion behaviour of Mg ***,the corrosion and bio-corrosion behaviour of Mg composites manufactured by primary and secondary processing routes are ***,the comprehensive corrosion and bio-corrosion mechanisms of these Mg composites are ***,the individual role of Gs,texture and corrosive medium on corrosion and bio-corrosion behaviour of Mg composites are clarified and *** challenges encountered,unanswered issues in this field are explained in detail and accordingly the scope for future research is *** review is presented from basic concrete background to advanced corrosion mechanisms with an aim of creating interest among the readers like students,researchers and industry experts from various research ***,the corrosion and bio-corrosion behaviour of Mg composites are critically reviewed for the first time to:(i)contribute to the body of knowledge,(ii)foster research and development,(iii)make breakthrough,and(iv)create life changing innovations in the field of Mg composite corrosion.

关键词： Corrosion Bio corrosion Magnesium alloys Magnesium composites Magnesium implants.

A new route to weak force sensing beyond sQL:squeezed magnons in cavity magnomechanics

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science China(Physics,Mechanics & Astronomy) 2024年第10期67卷 166-167页

作者： s.k.Özdemir Department of Engineering science and Mechanics and Materials Research Institute(MRI)The Pennsylvania State UniversityUniversity ParkPA 16802USA

Quantum mechanics imposes limits on measurement accuracy through quantum noise which typically has two components:First is the shot noise originating from vacuum fluctuations and referred to as the imprecision *** is ... 详细信息

关键词： quantum typically vacuum

Hybrid-Vlasov simulation of soft X-ray emissions at the Earth’s dayside magnetospheric boundaries

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Earth and Planetary Physics 2024年第1期8卷 70-88页

作者： M.Grandin H.k.Connor s.Hoilijoki M.Battarbee Y.Pfau-kempf U.Ganse k.Papadakis M.Palmroth Department of Physics University of HelsinkiHelsinkiFinland NAsA Goddard space Flight Center GreenbeltMD20771USA space and Earth Observation Centre Finnish Meteorological InstituteHelsinkiFinland

solar wind charge exchange produces emissions in the soft X-ray energy range which can enable the study of near-Earth space regions such as the magnetopause,the magnetosheath and the polar cusps by remote sensing *** solar wind Magnetosphere Ionosphere Link Explorer(sMILE)and Lunar Environment heliospheric X-ray Imager(LEXI)missions aim to obtain soft Xray images of near-Earth space thanks to their soft X-ray Imager(sXI)*** earlier modeling works have already simulated soft X-ray images as might be obtained by sMILE sXI during its mission,the numerical models used so far are all based on the magnetohydrodynamics description of the space *** investigate the possible signatures of ion-kinetic-scale processes in soft Xray images,we use for the first time a global hybrid-Vlasov simulation of the geospace from the Vlasiator *** simulation is driven by fast and tenuous solar wind conditions and purely southward interplanetary magnetic *** first produce global X-ray images of the dayside near-Earth space by placing a virtual imaging satellite at two different locations,providing meridional and equatorial *** then analyze regional features present in the images and show that they correspond to signatures in soft X-ray emissions of mirrormode wave structures in the magnetosheath and flux transfer events(FTEs)at the *** results suggest that,although the time scales associated with the motion of those transient phenomena will likely be significantly smaller than the integration time of the sMILE and LEXI imagers,mirror-mode structures and FTEs can cumulatively produce detectable signatures in the soft X-ray *** instance,a local increase by 30%in the proton density at the dayside magnetopause resulting from the transit of multiple FTEs leads to a 12%enhancement in the line-of-sight-and time-integrated soft X-ray emissivity originating from this ***,a proton density increase by 14%in the magnetosheath

关键词： magnetosphere magnetosheath numerical simulation sMILE LEXI soft X-ray emissions hybrid-Vlasov model polar cusp flux transfer events mirror-mode waves

Extended Deep Learning Algorithm for Improved Brain Tumor Diagnosis system

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Intelligent Automation & soft Computing 2024年第1期39卷 33-55页

作者： M.Adimoolam k.Maithili N.M.balamurugan R.Rajkumar s.Leelavathy Raju kannadasan Mohd Anul Haq Ilyas khan Elsayed M.Tag El Din Arfat Ahmad khan Department of Computer Engineering Government Polytechnic CollegeSevvapetTiruvallurTamil Nadu602025India Department of Computer science and Engineering KG Reddy College of Engineering and TechnologyHyderabadTelangana500075India Department of Computer science and Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India Department of Computer science and Engineering Annamalai UniversityChidambaramTamil Nadu608002India Department of Computer science and Engineering Aarupadai Veedu Institute of TechnologyVinayaka Mission Research FoundationPaiyanurTamil Nadu603104India Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Department of Computer science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand

At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system ***,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative *** addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the sPss tool,and respective graphical illustrations were *** results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten *** in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved *** EDLA algorithm introduces novelty concerning its performance and particular activation *** proposed method will be utilized effectively in brain tumor detection in a precise and accurate *** algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses *** the quantity of dataset records is enormous,then themethod’s computation power has to be updated.

关键词： Brain tumor extended deep learning algorithm convolution neural network tumor detection deep learning

Dispersion effect of nano-structure pyrolytic carbon on mechanical,electrical,and microstructural characteristics of cement mortar composite

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International Journal of smart and Nano Materials 2024年第3期15卷 534-578页

作者： N.k.karthikeyan s.Elavenil school of Civil Engineering Vellore Institute of TechnologyChennaiIndia

In material science,converting waste into nanomaterials by green technologies highlights the interest in producing sus-tainable carbon nanomaterial(sCN).This study first-ever uti-lized tyre-char as a Nano-structure Pyrolytic Carbon(NsPC)to develop electrically conductive *** other car-bon nanomaterials,the efficiency of NsPC particle as an sCN in developing electrically conductive composites was investi-gated in terms of dispersion,mechanical,water absorption,electrical resistivity,and *** results of sedi-mentation and zeta potential(-19 mV)showed the excellent dispersion of NsPC particle in water with the combined effect of superplasticizer and *** compressive(40.37%)and flexural strength(10.76%)than that of plain cement mortar composite(CMC)is achieved with 2 wt.%and 1.5 wt.%of NsPC particle,*** water absorption rate and volume of permeable voids were reduced,exhibiting less *** percolation zone of AC and DC resis-tivity of NsPC composite ranges between 1 and 2 wt.%,and the established percolation threshold is at 2 wt.%.XRD analysis showed C-s-H formation consistently increased with curing age,and HR-sEM with EDAX analysis exhibits the dense micro-structure and well-distributed NsPC particle at the *** experimental outcomes significantly enhanced the relia-bility and provided a framework for tailoring NsPC particle as sCN for developing electrically conductive composite.

关键词： sustainable nanomaterial dispersion mechanical properties electrical resistivity microstructure analysis

Enhancing Multicriteria-Based Recommendations by Alleviating scalability and sparsity Issues Using Collaborative Denoising Autoencoder

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Computers, Materials & Continua 2024年第2期78卷 2269-2286页

作者： s.Abinaya k.Uttej kumar school of Computer science&Engineering Vellore Institute of TechnologyChennaiTamilnadu600127India

A Recommender system(Rs)is a crucial part of several firms,particularly those involved in *** conventional Rs,a user may only offer a single rating for an item-that is insufficient to perceive consumer ***,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’*** the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested ***,the cost of these computations increases nonlinearly as the number of items and users *** triumph over the issues,a novel expanded stacked autoencoder(EsAE)with kernel Fuzzy C-Means Clustering(kFCM)technique is proposed with two *** the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the EsAE approach and users are clustered using the kFCM *** the next phase of online,the top-N recommendation prediction is made by the EsAE approach involving only the most similar user from multiple *** the EsAE_kFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation *** experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the EsAE_kFCM model constantly outperforms conventional Rs algorithms on a variety of assessment measures.

关键词： Recommender systems multicriteria rating collaborative filtering sparsity issue scalability issue stacked-autoencoder kernel Fuzzy C-Means Clustering

Emission colour tuning in kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)phosphor

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Journal of Rare Earths 2024年第1期42卷 57-65,I0002页

作者： Janani k Gayathri E Vijayatha V Ramasubramanian s Thiyagarajan P Department of science and Humanities Nehru Institute of TechnologyKaliapuramThirumalayampalayamCoimbatoreIndia Department of sciences Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatoreIndia Department of Physics Anna UniversityChennaiIndia

kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)(Ln=Y,Yb,Gd)phosphors were prepared by solid-state reaction *** each of the Yb^(3+)/Er^(3+)and Yb^(3+)/Ho^(3+)co-doped phosphors independently,phase confirmation and morphological examination were accomplished using the X-ray diffraction technique and scanning electron microscope analysis.X-ray photoelectron spectroscopy analysis shows the charge state and existence of lanthanides and *** luminescence emissions of green and red colour were detected for the synthesized *** changes in the upconverted emission intensities and colour output pertaining to the change of the lanthanide host matrix along with dopants were investigated for the prepared *** the upconversion luminescence,erbium-doped samples exhibit a predominance of red emission while holmium-doped samples display a prevalence of green *** rare-earth Er/Ho doped kYbF4shows strong red emission compared to other ***_(4):Yb,Er/Ho exhibits relatively significant green upconve rsion emissions,while Yb,Er-doped kGdF_(4)host displays a 10-fold increase in green/red emission ratio with an increase in the input power of 20-780 *** photoluminescence studies and decay curve analysis were carried out using UV light excitation for the developed phosphors.A higher lifetime of 2.2 ms was measured for the downshifting red emission in the Ho doped kYbF_(4)*** study suggests a potential for colour tunability in the upconversion and downshifting emissions through host modifications to the fluoride phosphor.

关键词： Rare earths Energy transfer upconversion Downshifting Colour coordinates

High-precision inverse potentials for neutron-proton scattering using piece-wise smooth Morse functions

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Chinese Physics C 2024年第10期48卷 201-213页

作者： Ayushi Awasthi Arushi sharma Ishwar kant O.s.k.s.sastri Department of Physics and Astronomical science Central University of Himachal PradeshDharmshala176215India

The aim of this study is to construct inverse potentials for various ℓ-channels of neutron-proton scattering using a piece-wise smooth Morse function as a *** phase equations for single-channel states and the coupled equations of multi-channel scattering are solved numerically using the 5^(th) order Runge-kutta *** employ a piece-wise smooth reference potential comprising three Morse functions as the initial *** a machine learning-based genetic algorithm,we optimize the model parameters to minimize the mean-squared error between simulated and anticipated phase *** approach yields inverse potentials for both single and multichannel scattering,achieving convergence to a mean-squared error≤10^(-3).The resulting scattering lengths"a_(0)"and effective ranges"r"for ^(3)s_(1) and ^(1)s_(0) states,expressed as[a_(0),r],are found to be[5.445(5.424),1.770(1.760)]and[–23.741(–23.749),2.63(2.81)],respectively;these values are in excellent agreement with experimental ***,the calculated total scattering cross-sections are highly consistent with their experimental counterparts,having a percentage error of less than 1%.This computational approach can be easily extended to obtain interaction potentials for charged particle scattering.

关键词： inverse potentials neutron-proton scattering piece-wise smooth Morse function phase function method reference potential approach genetic algorithm