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Frontiers of Structural and Civil Engineering 2024年第2期18卷 170-183页

作者： r.MOHANA S.M.Leela BHArATHI Department of Civil Engineering Mepco Schlenk Engineering CollegeSivakasi 626123India

The hazardous environmental effects of greenhouse gas emissions and climate change demand alternative sources for cementitious materials in the construction *** development of geopolymer structures provides a way of producing 100%cement-free *** this research work,a novel and simple way of deriving nano particles from waste fly ash particles is *** effect of adding the synthesized nano fly ash particles as a filler medium in geopolymer mortars was investigated by considering strength and durability *** optimization was done by using regression analysis on the geopolymer mortar and the impact of adding nano fly ash particles was studied by varying different percentages of addition ranging from 0 to 7.5%by weight of binder *** the results,it was observed that 1%nano fly ash acted not only as a filler but also as nano-sized precursors of the polymerization process,resulting in denser geopolymer *** can explain the extraordinary gain in strength of 72.11 MPa as well as the denser core with negligible level of chloride ion penetration,making the material suitable for the development of structures susceptible to marine environment.

关键词： geopolymer nano fly ash chloride ion penetration durability polymerization fillers

Nonlinear dynamic modeling of planar moving Timoshenko beam considering non-rigid non-elastic axial effects

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Applied Mathematics and Mechanics(English Edition) 2024年第3期45卷 479-496页

作者： M.ABBASI GAVArI M.r.HOMAEINEZHAD Faculty of Mechanical Engineering K.N.Toosi University of TechnologyTehran 19991-43344Iran

Due to the importance of vibration effects on the functional accuracy of mechanical systems,this research aims to develop a precise model of a nonlinearly vibrating single-link mobile flexible *** manipulator consists of an elastic arm,a rotary motor,and a rigid carrier,and undergoes general in-plane rigid body motion along with elastic transverse *** accurately model the elastic behavior,Timoshenko’s beam theory is used to describe the flexible arm,which accounts for rotary inertia and shear deformation *** applying Newton’s second law,the nonlinear governing equations of motion for the manipulator are derived as a coupled system of ordinary differential equations(ODEs)and partial differential equations(PDEs).Then,the assumed mode method(AMM)is used to solve this nonlinear system of governing equations with appropriate shape *** assumed modes can be obtained after solving the characteristic equation of a Timoshenko beam with clamped boundary conditions at one end and an attached mass/inertia at the *** addition,the effect of the transverse vibration of the inextensible arm on its axial behavior is *** the axial rigidity,the effect makes the rigid body dynamics invalid for the axial behavior of the ***,numerical simulations are conducted to evaluate the performance of the developed model,and the results are compared with those obtained by the finite element *** comparison confirms the validity of the proposed dynamic model for the *** to the mentioned features,this model can be reliable for investigating the system’s vibrational behavior and implementing vibration control algorithms.

关键词： planar moving Timoshenko beam non-rigid non-elastic axial effect as-sumed mode method(AMM) nonlinear motion analysis

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

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Computers, Materials & Continua 2024年第2期78卷 1669-1686页

作者： r.Sujatha K.Nimala Department of Networking and Communications SRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India

Sentence classification is the process of categorizing a sentence based on the context of the *** categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic *** existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing *** ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation *** conversational sentences are classified into four categories:information,question,directive,and *** classification label sequences are for analyzing the conversation progress and predicting the pecking order of the *** of Bidirectional Encoder for representation of Transformer(BErT),robustly Optimized BErT pretraining Approach(roBErTa),Generative Pre-Trained Transformer(GPT),DistilBErT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with *** tuning approach is carried out for better performance on sentence *** Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation *** proposed approach outperformed compared to the base BErT,GPT,DistilBErT and XLNet transformer *** proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

关键词： Bidirectional encoder for representation of transformer conversation ensemble model fine-tuning generalized autoregressive pretraining for language understanding generative pre-trained transformer hyperparameter tuning natural language processing robustly optimized BErT pretraining approach sentence classification transformer models

Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive radio Networks

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2339-2356页

作者： r.Saravanan r.Muthaiah A.rajesh School of Computing SASTRA Deemed UniversityThanjavur613401India School of Electrical&Electronics Engineering SASTRA Deemed UniversityThanjavur613401India

This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio *** threshold identification method is implemented in the received signal at the secondary user based on the square *** proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division ***,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio *** the dynamic threshold,the signal ratio-based threshold is *** threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and *** general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user *** limitations undermine the sensing accuracy of the energy identification ***,the ETBED technique is developed to enhance the energy efficiency of cognitive radio *** projected approach is executed and analyzed with performance and comparison *** proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.

关键词： Cognitive radio network spectrum sensing noise uncertainty modified black widow optimization algorithm energy detection technique

Unsteady MHD Casson Nanofluid Flow Past an Exponentially Accelerated Vertical Plate:An Analytical Strategy

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 431-460页

作者： T.Aghalya r.Tamizharasi Department of Mathematics School of Advanced SciencesVellore Institute of TechnologyVelloreTamilnadu632014India

In this study,the characteristics of heat transfer on an unsteady magnetohydrodynamic(MHD)Casson nanofluid over an exponentially accelerated vertical porous plate with rotating effects were *** flow was driven by the combined effects of the magnetic field,heat radiation,heat source/sink and chemical *** oxide(CuO)and titanium oxide(TiO2)are acknowledged as nanoparticle *** nondimensional governing equations were subjected to the Laplace transformation technique to derive closed-form *** representations are provided to analyze how changes in physical parameters,such as the magnetic field,heat radiation,heat source/sink and chemical reaction,affect the velocity,temperature and concentration *** computed values of skin friction,heat and mass transfer rates at the surface were tabulated for various sets of input *** is perceived that there is a drop in temperature due to the rise in the heat source/sink and the Prandtl *** should be noted that a boost in the thermal radiation parameter prompts an increase in *** increase in the Prandtl number,heat source/sink parameter,time and a decrease in the thermal radiation parameter result in an increase in theNusselt *** computed values of the skin friction,heat andmass transfer rates at the surface were tabulated for various values of the flow *** present results were compared with those of previously published studies andwere found to be in excellent *** research has practical applications in areas such as drug delivery,thermal medicine and cancer treatment.

关键词： Thermal radiation radiative flux nanofluid copper oxide titanium oxide accelerated plate

An Efficient Modelling of Oversampling with Optimal Deep Learning Enabled Anomaly Detection in Streaming Data

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China Communications 2024年第5期21卷 249-260页

作者： r.rajakumar S.Sathiya Devi Srinivasa ramanujan Centre SASTRA Deemed UniversityKumbakonamTamil Nadu 612001India University College of Engineering BIT CampusAnna UniversityTiruchirappalli 620024India

recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,*** recent developments of deep learning(DL)models find helpful in the detection and classification of *** article designs an oversampling with an optimal deep learning-based streaming data classification(OS-ODLSDC)*** aim of the OSODLSDC model is to recognize and classify the presence of anomalies in the streaming *** proposed OS-ODLSDC model initially undergoes preprocessing *** streaming data is unbalanced,support vector machine(SVM)-Synthetic Minority Over-sampling Technique(SVM-SMOTE)is applied for oversampling ***,the OS-ODLSDC model employs bidirectional long short-term memory(Bi LSTM)for AD and ***,the root means square propagation(rMSProp)optimizer is applied for optimal hyperparameter tuning of the Bi LSTM *** ensuring the promising performance of the OS-ODLSDC model,a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDS 2018,KDD-Cup 1999,and NSL-KDD datasets.

关键词： anomaly detection deep learning hyperparameter optimization oversampling SMOTE streaming data

Peri-implant gas accumulation in response to magnesium-based musculoskeletal biomaterials:reframing current evidence for preclinical research and clinical evaluation

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Journal of Magnesium and Alloys 2024年第1期12卷 59-71页

作者： Yu Sun Heike Helmholz regine Willumeit-römer Institute of Metallic Biomaterials Helmholtz-Zentrum HereonMax-Planck-Str.1Geesthacht 21502Germany

Historically,the rapid degradation and massive gas release from magnesium(Mg)implants resulted in severe emphysema and mechanical *** the advent of new alloys and surface treatment methods,optimized Mg implants have re-entered clinics since last decade with reliable ***,the optimization aims at slowing down the degradation process,rather than exemption of the gas *** study involved a systematic evaluation of current preclinical and clinical evidence,regarding the physical signs,symptoms,radiological features,pathological findings and complications potentially associated with peri±implant gas accumulation(PIGA)after musculoskeletal Mg *** literature search identified 196 potentially relevant publications,and 51 papers were enrolled for further analysis,including 22 preclinical tests and 29 clinical studies published from 2005 to *** Mg-based materials have been evaluated in animal research,and the application of pure Mg and Mg alloys have been reported in clinical follow-ups involving multiple anatomical sites and musculoskeletal *** tissue and intraosseous PIGA are common in both animal tests and clinical follow-ups,and potentially associated with certain adverse *** examinations especially micro-CT and clinical CT scans provide valuable information for quantitative and longitudinal *** according to simulation tests involving Mg implantation and chemical processing,tissue fixation could lead to an increase in the volume of gas cavity,thus the results obtained from ex vivo imaging or histopathological evaluations should be interpreted with *** still lacks standardized procedures or consensus for both preclinical and clinical evaluation of ***,by providing focused insights into the topic,this evidence-based study will facilitate future animal tests and clinical evaluations,and support developing biocompatible Mg implants for the treatment of musculoskeletal

关键词： Magnesium implant Degradation Hydrogen Gas release Postoperative follow-up

Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: radiological exploration enhanced with PCA-based machine learning in a rat femoral model

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Journal of Magnesium and Alloys 2024年第3期12卷 1009-1020页

作者： Yu Sun Heike Helmholz regine Willumeit-römer Institute of Metallic Biomaterials Helmholtz-Zentrum HereonGermany

The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo ***,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based ***,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment *** primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat *** addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical *** to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D *** bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in *** the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy *** component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D *** study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.

关键词： Magnesium Implants Bone fracture Mineralization Systemic modulation Principal component analysis.

Design of computer vision assisted machine learning based controller for the Stewart platform to track spatial objects

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Frontiers of Structural and Civil Engineering 2024年第8期18卷 1195-1208页

作者： Dev Kunwar Singh CHAUHAN Pandu r.VUNDAVILLI Indian Institute of Technology Bhubaneswar Bhubaneswar 752050India

The present work aims to develop an object tracking controller for the Stewart platform using a computer vision-assisted machine learning-based *** research is divided into two *** first module focuses on the design of a motion controller for the Physik Instrumente(PI)-based Stewart *** contrast,the second module deals with the development of a machine-learning-based spatial object tracking algorithm by collecting information from the Zed 2 stereo vision ***,simple feed-forward neural networks(NN)are used to predict the orientation of the top table of the *** training,the x,y,and z coordinates of the three-dimensional(3D)object,extracted from images,are used as the input to the *** contrast,the orientation information of the platform(that is,rotation about the x,y,and z-axes)is considered as the output from the *** orientation information obtained from the network is fed to the inverse kinematics-based motion controller(module 1)to move the platform while tracking the *** training,the optimised NN is used to track the continuously moving 3D *** experimental results show that the developed NN-based controller has successfully tracked the moving spatial object with reasonably good accuracy.

关键词： Stewart platform feed-forward neural networks motion controller inverse kinematics stereo vision

Soil security and global food security

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Frontiers of Agricultural Science and Engineering 2024年第2期11卷 297-302页

作者： David r.MONTGOMErY Department of Earth and Space Sciences University of Washington townSeattleWA 98105USA

Over the course of the postglacial period has managed to add degrade a substantial portion of the world's potential agricultural land. The soil loss and degradation that has repeatedly impacted regional societies around the world resulted from agricultural practices that increased the physical loss of soil(erosion), reduced soil organic matter, changed p H(acidification) or salinity,and disrupted or altered communities of soil life. In the coming century, as continued soil degradation threatens global food security while the global population keeps rising it is imperative that farmers develop and adopt soilhealth building(regenerative) practices to solve a problem that has plagued societies throughout history. Growing evidence suggests that agricultural systems that combine cover crops, reduced tillage, and diverse crop rotations can reduce erosion, enhance soil health and rebuild soil organic matter to cultivate beneficial soil life and harvest both economic and environmental benefits. In the coming post-oil world, global food security would benefit from a global effort to promote soil restoration to help addresses the challenge of sustainably feeding the world, increase soil-based carbon sequestration,protect on-farm biodiversity and reduce off-farm water pollution. Because soil security sets a solid foundation for global food security, agricultural policies and subsidies should be reformed to encourage farmers to adopt regenerative,soil-building practices.

关键词： Agriculture soil security food security regenerative