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Journal of Magnesium and Alloys 2024年第4期12卷 1518-1528页

作者： Annayath maqbool Abdul Khalad Noor Zaman Khan Department of Mechanical Engineering National Institute of Technology SrinagarJ&K 190006India Department of Mechanical Engineering Indian Institute of TechnologyHyderabadSangareddyTelangana 502284India School of Engineering Deakin UniversityVictoria 3216Australia

The corrosion rate is a crucial factor that impacts the longevity of materials in different *** undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion ***,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still *** current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 *** Taguchi L27 design of experiments was used for the experimental *** addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion *** shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified *** study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

关键词： Corrosion rate Friction stir processing Virtual sample generation Particle swarm optimization Machine learning Graphical user interface

Data-Based Filters for Non-Gaussian Dynamic Systems With Unknown Output Noise Covariance

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 866-877页

作者： Elham Javanfar mehdi Rahmani the Department of Electrical Engineering Imam Khomeini International UniversityQazvin ***Iran

This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output *** challenge of designing a suitable filter in the presence of an unknown covariance matrix is addressed by focusing on the output data set of the *** that data generated from a Gaussian distribution exhibit ellipsoidal scattering,we first propose the weighted sum of norms(SON)clustering method that prioritizes nearby points,reduces distant point influence,and lowers computational ***,by introducing the weighted maximum likelihood,we propose a semi-definite program(SDP)to detect outliers and reduce their impacts on each *** these weights paves the way to obtain an appropriate covariance of the output ***,two filtering approaches are presented:a cluster-based robust linear filter using the maximum a posterior(MAP)estimation and a clusterbased robust nonlinear filter assuming that output noise distribution stems from some Gaussian noise resources according to the ellipsoidal *** last,simulation results demonstrate the effectiveness of our proposed filtering approaches.

关键词： Data-based filter maximum likelihood estimation unknown covariance weighted maximum likelihood estimation weighted sum-of-norms clustering

Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 797-806页

作者： Edeh Vincent mehdi Korki mehdi Seyedmahmoudian Alex Stojcevski Saad Mekhilef School of Science Computingand Engineering TechnologiesSwinburne University of TechnologyMelbourneAustralia

The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.

关键词： Deep reinforcement learning graph convolutional network heterogeneous smart grid network

A novel mitigation measure for normal fault-induced deformations on pile-raft systems

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Earthquake Engineering and Engineering Vibration 2024年第1期23卷 15-33页

作者： Mohammadreza Jahanshahi Nowkandeh mehdi Ashtiani Faculty of Civil Engineering Babol Noshirvani University of TechnologyBabolIran

Evidence from recent earthquakes has shown destructive consequences of fault-induced permanent ground movement on *** observations have increased the demand for improvements in the design of structures that are dramatically vulnerable to surface fault *** this study a novel connection between the raft and the piles is proposed to mitigate the hazards associated with a normal fault on pile-raft systems by means of 3D finite element(FE)*** embarking on the parametric study,the strain-softening constitutive law used for numerical modeling of the sand has been validated against centrifuge test *** exact location of the fix-head and unconnected pile-raft systems relative to the outcropping fault rupture in the free-field is parametrically investigated,revealing different failure *** performance of the proposed connection for protecting the pile-raft system against normal fault-induced deformations is assessed by comparing the geotechnical and structural responses of both types of *** results indicate that the pocket connection can relatively reduce the cap rotation and horizontal and vertical displacements of the raft in most *** proposed connection decreases the bending moment response of the piles to their bending moment capacity,verging on a fault offset of 0.6 m at bedrock.

关键词： normal fault rupture failure mechanism pile-raft system pocket connection finite element modeling

Correlation between platinum–aluminide coating features and tensile behavior of nickel-based superalloy Rene?80

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Rare Metals 2024年第10期43卷 5391-5402页

作者： Mohammad mehdi Barjesteh Seyed mehdi Abbasi Karim Zangeneh Madar Kourosh Shirvani Metallic Materials Research Center Malek Ashtar University of Technology (MUT) Department of Advanced Materials and New Energies Iranian Research Organization for Science and Technology (IROST)

The effect of platinum （a rare metal）–aluminide coating parameters on the tensile properties of nickel-based superalloy Rene?80 was evaluated at 871。*** this purpose,initial layers of platinum with different thicknesses （2,4,6 and 8μm） were coated on tensile samples Then,low-temperature high-activity （LTHA） and hightemperature low-activity （HTLA） processes were used for *** of microstructural evaluations using scanning electron microscope （SEM） and phase analysis by X-ray diffraction （XRD） showed a three-layer structure coating for different platinum layer thicknesses and both aluminizing *** the thickness of the platinum layer from 2 to 8μm led to the improvement in the final coating thickness from 91.6 to 102.1μm in *** increase was from 128.1 to 148.6 μm in *** results of hot tensile tests at 871℃ showed a decrease in strength properties of the coated samples compared to the uncoated ***,HTLA and high thicknesses of the initial platinum layer showed an intense *** results of fractographic evaluations abou uncoated samples showed a ductile *** the other hand,coated samples showed a simultaneous ductile and brittle fracture failure *** the main fracture morphology was brittle cleavage fracture which was for the HTLA.

关键词： Aluminizing Fractography Platinum–aluminide Rene®80 Tensile properties

Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali maqbool Khan Khalil Khan Rehan Ullah Khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

On the occurrence of Neoplanorbulinella Matsumaru, 1976(Foraminifera) from the late Oligocene of Central Iran(Qom Formation):Palaeobiogeographic implications

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Journal of Palaeogeography 2024年第1期13卷 80-91页

作者： mehdi Sarfi Mohsen Yazdi-Moghadam School of Earth Sciences Damghan UniversityDamghan ***Iran National Iranian Oil Company Exploration Directorate Sheikh Bahaie SquareTehran ***Iran

The shallow marine carbonates of the upper Oligocene Qom Formation yielded several occurrences of the foraminiferan genus Neoplanorbulinella Matsumaru. Neoplanorbulinella saipanensis Matsumaru has so far been recorded from the late Eocene-early Miocene of Japan and late Oligocene of NE Italy whereas N. malatyaensis Gedik is only reported from the Oligocene from its type locality in the Malatya Basin, eastern Turkey. The new records reported here from the Qom Formation indicate that both species occur in the Dobaradar section, ca. 10 km south of the city of Qom in North-Central Iran. The palaeogeographic distribution of these two species therefore has to be extended as far as the palaeolongitude of current Central *** accompanying larger benthic foraminifers, including Miogypsinoides complanatus(Schlumberger),M. formosensis Yabe and Hanzawa, Spiroclypeus margaritatus(Schlumberger), Operculina complanata(Defrance), and Risananeiza pustulosa Boukhary et al., indicate the upper Chattian SBZ 23 Zone. The coexistence of the N. saipanensis and N. malatyaensis points to suitable palaeobiogeographic conditions of Central Iran to host Western and Eastern Tethyan taxa.

关键词： Larger foraminifers Planorbulinids Biostratigraphy Qom Formation Central Iran

Coupling of RANS and BEM Solvers for Simulation of Propeller Behind the Hull in Full Appended Model

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China Ocean Engineering 2024年第3期38卷 424-438页

作者： Saeed NAJAFI mehdi POURMOSTAFA LIU Peng-fei Iranian National Institute for Oceanography and Atmospheric Science(INIOAS) Tehran 14155-4781Iran Department of Maritime Engineering Amir Kabir University of TechnologyTehran 15875-4413Iran Marine Offshore and Subsea TechnologySchool of EngineeringNewcastle UniversityNewcastle upon TyneNE17RUUK

To design a propeller for ship power plant,the interaction between ship hull and propeller must be taken into *** main concern is to apply the wake effect of ship stern on the propeller *** this paper,a coupled BEM(Boundary Element Method)/RANS(Renolds-Averaged Navier−Stokes)solver is used to simulate propeller behind the hull in the self-propulsion *** motivation of this work is to develop a practical tool to design marine propulsion system without suffering long computational *** unsteady boundary element method which is also known as panel method is chosen to estimate the propeller *** wakes are treated using a time marching wake alignment ***,a RANS code coupled with VoF equation is developed to consider the ship motions and wake field effects in the problem.A coupling algorithm is developed to interchange ship wake field to the potential flow solver and propeller thrust to the RANS *** on the difference between hull resistance and the propeller thrust,a PI controller is developed to compute the propeller RPM in every time *** of the solver is carried out using the towing tank test report of a 50 m oceanography research *** factor and trust deduction coefficient are estimated ***,the wake rollup pattern of the propeller in open water is compared with the propeller in real wake field.

关键词： RANS BEM coupled method ship propeller self-propulsion wake sheet pattern

Microstructural analysis of marl stabilized with municipal solid waste and nano-MgO

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第8期16卷 3258-3269页

作者： Ali Ohadian Navid Khayat mehdi Mokhberi Department of Civil Engineering Ahvaz BranchIslamic Azad UniversityAhvazIran Department of Civil Engineering Estahban BranchIslamic Azad UniversityEstahbanIran

Municipal solid waste(MSW)is accumulating over elapsed time across the world,and it is observed in many projects associated with weak soils,such as ***,effective solutions to the environmental problem are *** techniques for stabilizing marl generally use substances such as lime and cement,which could exacerbate *** this,some new stabilizers,***-MgO,are *** are large quantities of marls and MSW in Shiraz City,*** present study aims to evaluate the feasibility of using nano-MgO as a green low-carbon binder to remove MSW from the environment and make construction projects more *** drained shear tests were conducted to evaluate the mechanical behaviors of the nano-MgO treated marl specimens at high normal *** marl specimens containing MSW percentages of 15%,25%,35%,and 45%and nano-MgO percentages of 0.25%,0.5%,0.75%,and 1%,were *** is found that the marl containing 15%and 25%MSW and 0.5%nano-MgO at 28-d curing can perform cation exchange and form new cementitious *** soils with merely MSW show good performance due to the removal of the kaolinite and the formation of ***,the soil with 25%MSW and 0.5%nano-MgO shows the same strength enhancement as the specimen with the optimal nano-MgO(0.75%)through the formation of dolomite,with a 20.59%increase in strain energy(SE).

关键词： Marl Shear strength Microstructure Nano-MgO Municipal solid waste(MSW)

Synergizing Wind,Solar,and Biomass Power:Ranking Analysis of Off-Grid System for Different Weather Conditions of Iran

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Energy Engineering 2024年第6期121卷 1381-1401页

作者： Razieh Keshavarzi mehdi Jahangiri Energy and Environment Research Center Shahrekord BranchIslamic Azad UniversityShahrekordIran

Nowadays,the use of renewable energies,especially wind,solar,and biomass,is essential as an effective solution to address global environmental and economic ***,the current study examines the energy-economic-environmental analysis of off-grid electricity generation systems using solar panels,wind turbines,and biomass generators in various weather conditions in *** over 25 years were conducted using HOMER v2.81 software,aiming to determine the potential of each region and find the lowest cost of electricity production per *** the end,to identify the most suitable location,the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)method was employed to rank different stations based on simulation output parameters and some other influential *** the evaluation of various parameters,the stations in Yazd,Marand,and Dezful achieved the best results,while the stations in Ramsar,Shahrekord,and Gonbad presented the least favorable *** Yazd,the wind turbine is an economic priority,and a 100 kW wind turbine is utilized in the optimal *** Yazd,where the simultaneous use of renewable energies is most prominent,the lowest pollutant production occurred with a quantity of 1174 kg/*** energy losses are highest in Jask station and lowest in Yazd.

关键词： Multi-criteria decision-making method residential scale biomass generators normalize weight