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

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.

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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

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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

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Juxtapose of system Performance for Food Calorie Estimation Using IoT and Web-based Indagation

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Journal of Harbin Institute of Technology(New series) 2024年第1期31卷 54-63页

作者： Anusuya s sharmila k Department of Computer science VISTASChennai 600117India Department of Computer science Dr.MGR Janaki College for WomenChennai 600028India

A rudimentary aspect of human life is the health of an individual,and most commonly the wellbeing is impacted in a colossal manner through the consumption of food. The intake of calories therefore is a crucial aspect that must be meticulously monitored. Various health gremlins can be largely circumvented when there is a substantial balance in the number of calories ingested versus the quantity of calories *** food calorie estimation is a popular domain of research in recent times and is meticulously analyzed through various image processing and machine learning techniques. However,the need to scrutinize and evaluate the calorie estimation through various platforms and algorithmic approaches aids in providing a deeper insight on the bottlenecks involved,and in improvising the bariatric health of an individual. This paper pivots on comprehending a juxtaposed approach of food calorie estimation through the use of employing Convolution Neural Network(CNN)incorporated in Internet of Things(IoT),and using the Django framework in Python,along with query rule-based training to analyze the subsequent actions to be followed post the consumption of food calories in the constructed webpage. The comparative analysis of the food calorie estimate implemented in both platforms is analyzed for the swiftness of identification,error rate and classification accuracy to appropriately determine the optimal method of use. The simulation results for IoT are carried out using the Raspberry Pi4B model,while the Anaconda prompt is used to run the server holding the web page.

关键词： food calorie estimation convolution neural network Django framework internet of things raspberry Pi

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5G Resource Allocation Using Feature selection and Greylag Goose Optimization Algorithm

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Computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： Amel Ali Alhussan s.k.Towfek Department of Computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer science and Intelligent systems Research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of k-Nearest Neighbors(kNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination R squared value equal *** proposed framework is supported by several statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test

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Predictive active control of building structures using LQR and artificial intelligence

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 489-502页

作者： Nirmal s.Mehta Vishisht Bhaiya k.A.Patel Ehsan Noroozinejad Farsangi Department of Civil Engineering SVNIT SuratGujarat 395007India Urban Transformations Research Centre Western Sydney UniversityNSWAustralia

This study presents a neural network-based model for predicting linear quadratic regulator(LQR)weighting matrices for achieving a target response *** on the expected weighting matrices,the LQR algorithm is used to determine the various responses of the *** responses are determined by numerically analyzing the governing equation of motion using the state-space *** training a neural network,four input parameters are considered:the time history of the ground motion,the percentage reduction in lateral displacement,lateral velocity,and lateral acceleration,Output parameters are LQR weighting *** study the effectiveness of an LQR-based neural network(LQRNN),the actual percentage reduction in the responses obtained from using LQRNN is compared with the target percentage ***,to investigate the efficacy of an active control system using LQRNN,the controlled responses of a system are compared to the corresponding uncontrolled *** trained neural network effectively predicts weighting parameters that can provide a percentage reduction in displacement,velocity,and acceleration close to the target percentage *** on the simulation study,it can be concluded that significant response reductions are observed in the active-controlled system using ***,the LQRNN algorithm can replace conventional LQR control with the use of an active control system.

关键词： active control system linear quadratic regulator artificial neural networks state-space approach response effectiveness factor resilience

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LiDAR-based estimation of bounding box coordinates using Gaussian process regression and particle swarm optimization

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Biomimetic Intelligence & Robotics 2024年第1期4卷 24-35页

作者： Vinodha k. E.s.Gopi Tushar Agnibhoj Department of Electronics and Communication Engineering National Institute of Technology TiruchirappalliTamil Nadu620015India

Camera-based object tracking systems in a given closed environment lack privacy and *** this study,light detection and ranging(LiDAR)was applied to track objects similar to the camera tracking in a closed environment,guaranteeing privacy and *** primary objective was to demonstrate the efficacy of the proposed technique through carefully designed experiments conducted using two *** scenario I,the study illustrates the capability of the proposed technique to detect the locations of multiple objects positioned on a flat surface,achieved by analyzing LiDAR data collected from several locations within the closed *** II demonstrates the effectiveness of the proposed technique in detecting multiple objects using LiDAR data obtained from a single,fixed ***-time experiments are conducted with human subjects navigating predefined *** individuals move within an environment,while LiDAR,fixed at the center,dynamically tracks and identifies their locations at multiple *** demonstrate that a single,strategically positioned LiDAR can adeptly detect objects in motion around ***,this study provides a comparison of various regression techniques for predicting bounding box *** process regression(GPR),combined with particle swarm optimization(PsO)for prediction,achieves the lowest prediction mean square error of all the regression techniques examined at *** tuning of GPR using PsO significantly minimizes the regression *** of the experiment pave the way for its extension to various real-time applications such as crowd management in malls,surveillance systems,and various Internet of Things scenarios.

关键词： LiDAR Data acquisition Bounding box Gaussian process regression Particle swarm optimization(PsO)

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On the existence and stability of traversable wormhole solutions with novel shapefunctions in the framework of F(R,L_(m))gravity

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Communications in Theoretical Physics 2024年第5期76卷 114-127页

作者： sourav Chaudhary Jitendra kumar s k Maurya sweeti kiroriwal Abdul Aziz Department of Mathematics Central University of HaryanaJant-PaliMahendergarhIndia Department of Mathematical and Physical sciences College of Arts and ScienceUniversity of NizwaP.O.Box 33Nizwa 616Oman

In this work,we have explored wormhole(WH)solutions in F(R,L_(m))gravity by assuming the Morris-Thorne WH metric and F(R,Lm)=R/2+(1+γR)L_(m),whereγis the free model *** determined the WH solutions by utilizing two newly developed shape functions(sF)that satisfy all basic conditions for a WH’s physical *** also observe that the null energy condition(NEC)behaves ***,for both models,we use the volume integral quantifier(VIQ)and Tolman-Oppenheimer-Volkoff(TOV)equation to determine how much exotic matter is needed near the WH throat and the stability of the *** extensive detailed discussions of the matter components have been done via graphical *** obtained WH geometries meet the physically acceptable conditions for a stable wormhole.

关键词： energy conditions wormhole exotic matter F(R L_(m))gravity

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Inclusive quasielastic neutrino-nucleus scattering with energy density functional nuclear models

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Chinese Physics C 2024年第8期48卷 153-158页

作者： k.s.kim soonchul Choi Hana Gil Chang Ho Hyun school of liberal arts and science korea aerospace universitygoyang 10540korea Center for exotic nuclear studies institute for basic sciencedaejeon 34126korea Center for extreme nuclear matters korea universityseoul 02841korea Department of physics education daegu universitygyeongsan 38453korea

In this study,we calculated the inclusive charged-current neutrino-nucleus scattering from ^(40)Ar in the quasielastic *** explore the effect of uncertainties stemming from the nuclear structure,we used the kIDs(korea-IBs-Daegu-skkU)nuclear energy density functional and skyrme force models,namely sLy4,skI3,and *** models were selected to have distinct behavior in terms of the density dependence of the symmetry energy and the effective mass of the *** the charged-current neutrino scattering,the single-and double-differential cross sections were calculated for various *** cross sections are reported as a function of the incident neutrino *** theoretical cross sections were compared with experimental data,and the roles of the effective mass and symmetry energy were investigated in terms of charged-current neutrino-nucleus scattering.

关键词： energy density functional neutrino-nucleus scattering symmetry energy effective mass of the nucleon

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An Evidence-Based CoCoso Framework with Double Hierarchy Linguistic Data for Viable selection of Hydrogen storage Methods

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Computer Modeling in Engineering & sciences 2024年第3期138卷 2845-2872页

作者： Raghunathan krishankumar Dhruva sundararajan k.s.Ravichandran Edmundas kazimieras Zavadskas Information Technology systems and Analytics Area Indian Institute of Management Bodh GayaBodh GayaBihar824234India Department of Mathematics Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatore641112India Institute of sustainable Construction Vilnius Gediminas Technical UniversityVilnius10223Lithuania

Hydrogen is the new age alternative energy source to combat energy demand and climate *** of hydrogen is vital for a nation’s *** of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green ***,hydrogen storage is associated with diverse sustainable and circular economy(sCE)*** a result,the authors consider the situation a multi-criteria decision-making(MCDM)*** infer that previous models for hydrogen storage method(HsM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HsM is *** by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoso)for ranking *** applicability of the developed framework is testified by using a case example of HsM selection in *** and comparative analysis reveal the merits and limitations of the developed framework.

关键词： Hydrogen storage methods double hierarchy hesitant fuzzy linguistic term set evidence theory CoCoso method sustainability circular economy

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