To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development...To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development.This involved exploring the deep integration of next-generation artificial intelligence technologies,such as sensing technology,automatic control technology,big data technology,deep learning,and machine vision,with key operational processes,including TBM excavation,direction adjustment,step changes,inverted arch block assembly,material transportation,and operation status assurance.The results of this integration are summarized as follows.(1)TBM key excavation parameter prediction algorithm was developed with an accuracy rate exceeding 90%.The TBM intelligent step-change control algorithm,based on machine vision,achieved an image segmentation accuracy rate of 95%and gripper shoe positioning error of±5 mm.(2)An automatic positioning system for inverted arch blocks was developed,enabling real-time perception of the spatial position and deviation during the assembly process.The system maintains an elevation positioning deviation within±3 mm and a horizontal positioning deviation within±10 mm,reducing the number of surveyors in each work team.(3)A TBM intelligent rail transportation system that achieves real-time human-machine positioning,automatic switch opening and closing,automatic obstacle avoidance,intelligent transportation planning,and integrated scheduling and command was designed.Each locomotive formation reduces one shunter and improves comprehensive transportation efficiency by more than 20%.(4)Intelligent analysis and prediction algorithms were developed to monitor and predict the trends of the hydraulic and gear oil parameters in real time,enhancing the proactive maintenance and system reliability.展开更多
How multi-unmanned aerial vehicles(UAVs)carrying a payload pass an obstacle-dense environment is practically important.Up to now,there have been few results on safe motion planning for the multi-UAVs cooperative trans...How multi-unmanned aerial vehicles(UAVs)carrying a payload pass an obstacle-dense environment is practically important.Up to now,there have been few results on safe motion planning for the multi-UAVs cooperative transportation system(CTS)to pass through such an environment.The prob-lem is challenging because it is difficult to analyze and explicitly take into account the swing motion of the payload in planning.In this paper,a modeling method of virtual tube is proposed by fus-ing the advantages of the existing modeling algorithm for regu-lar virtual tube and the expansion environment method.The pro-posed method can not only generate a safe and smooth tube for UAVs,but also ensure the payload stays away from the dense obstacles.Simulation results show the effectiveness of the method and the safety of the planned tube.展开更多
This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration s...This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.展开更多
Discrete event system(DES)models promote system engineering,including system design,verification,and assessment.The advancement in manufacturing technology has endowed us to fabricate complex industrial systems.Conseq...Discrete event system(DES)models promote system engineering,including system design,verification,and assessment.The advancement in manufacturing technology has endowed us to fabricate complex industrial systems.Consequently,the adoption of advanced modeling methodologies adept at handling complexity and scalability is imperative.Moreover,industrial systems are no longer quiescent,thus the intelligent operations of the systems should be dynamically specified in the model.In this paper,the composition of the subsystem behaviors is studied to generate the complexity and scalability of the global system model,and a Boolean semantic specifying algorithm is proposed for generating dynamic intelligent operations in the model.In traditional modeling approaches,the change or addition of specifications always necessitates the complete resubmission of the system model,a resource-consuming and error-prone process.Compared with traditional approaches,our approach has three remarkable advantages:(i)an established Boolean semantic can be fitful for all kinds of systems;(ii)there is no need to resubmit the system model whenever there is a change or addition of the operations;(iii)multiple specifying tasks can be easily achieved by continuously adding a new semantic.Thus,this general modeling approach has wide potential for future complex and intelligent industrial systems.展开更多
How to mine valuable information from massive multisource heterogeneous data and identify the intention of aerial targets is a major research focus at present. Aiming at the longterm dependence of air target intention...How to mine valuable information from massive multisource heterogeneous data and identify the intention of aerial targets is a major research focus at present. Aiming at the longterm dependence of air target intention recognition, this paper deeply explores the potential attribute features from the spatiotemporal sequence data of the target. First, we build an intelligent dynamic intention recognition framework, including a series of specific processes such as data source, data preprocessing,target space-time, convolutional neural networks-bidirectional gated recurrent unit-atteneion (CBA) model and intention recognition. Then, we analyze and reason the designed CBA model in detail. Finally, through comparison and analysis with other recognition model experiments, our proposed method can effectively improve the accuracy of air target intention recognition,and is of significance to the commanders’ operational command and situation prediction.展开更多
In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a...In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect.Firstly,a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed.In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow,a numerical simulation of the basic finner projectile without control is carried out.The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation.Secondly,combined with the real-time control requirements of aerodynamic,attitude and displacement parameters of the projectile during the flight process,the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative)control strategy and the intelligent PID control strategy respectively.The intelligent PID controller based on BP(Back Propagation)neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters.Compared with the traditional PID controller,the concerned control variable overshoot,rise time,transition time and steady state error and other performance indicators have been greatly improved,and the higher the learning efficiency or the inertia coefficient,the faster the system,the larger the overshoot,and the smaller the stability error.The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.展开更多
Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent...Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent personal assistants within the context of visual,auditory,and somatosensory interactions with drivers were discussed.Their impact on the driver’s psychological state through various modes such as visual imagery,voice interaction,and gesture interaction were explored.The study also introduced innovative designs for in-vehicle intelligent personal assistants,incorporating design principles such as driver-centricity,prioritizing passenger safety,and utilizing timely feedback as a criterion.Additionally,the study employed design methods like driver behavior research and driving situation analysis to enhance the emotional connection between drivers and their vehicles,ultimately improving driver satisfaction and trust.展开更多
We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reco...We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.展开更多
High-Entropy Alloys(HEAs)exhibit significant potential across multiple domains due to their unique properties.However,conventional research methodologies face limitations in composition design,property prediction,and ...High-Entropy Alloys(HEAs)exhibit significant potential across multiple domains due to their unique properties.However,conventional research methodologies face limitations in composition design,property prediction,and process optimization,characterized by low efficiency and high costs.The integration of Artificial Intelligence(AI)technologies has provided innovative solutions for HEAs research.This review presented a detailed overview of recent advancements in AI applications for structural modeling and mechanical property prediction of HEAs.Furthermore,it discussed the advantages of big data analytics in facilitating alloy composition design and screening,quality control,and defect prediction,as well as the construction and sharing of specialized material databases.The paper also addressed the existing challenges in current AI-driven HEAs research,including issues related to data quality,model interpretability,and cross-domain knowledge integration.Additionally,it proposed prospects for the synergistic development of AI-enhanced computational materials science and experimental validation systems.展开更多
The cold chain in the production area of fruits and vegetables is the primary link to reduce product loss and improve product quality,but it is also a weak link.With the application of big data technology in cold chai...The cold chain in the production area of fruits and vegetables is the primary link to reduce product loss and improve product quality,but it is also a weak link.With the application of big data technology in cold chain logistics,intelligent devices,and technologies have become important carriers for improving the efficiency of cold chain logistics in fruit and vegetable production areas,extending the shelf life of fruits and vegetables,and reducing fruit and vegetable losses.They have many advantages in fruit and vegetable pre-cooling,sorting and packaging,testing,warehousing,transportation,and other aspects.This article summarizes the rapidly developing and widely used intelligent technologies at home and abroad in recent years,including automated guided vehicle intelligent handling based on electromagnetic or optical technology,intelligent sorting based on sensors,electronic optics,and other technologies,intelligent detection based on computer vision technology,intelligent transportation based on perspective imaging technology,etc.It analyses and studies the innovative research and achievements of various scholars in applying intelligent technology in fruit and vegetable cold chain storage,sorting,detection,transportation,and other links,and improves the efficiency of fruit and vegetable cold chain logistics.However,applying intelligent technology in fruit and vegetable cold chain logistics also faces many problems.The challenges of high cost,difficulty in technological integration,and talent shortages have limited the development of intelligent technology in the field of fruit and vegetable cold chains.To solve the current problems,it is proposed that costs be controlled through independent research and development,technological innovation,and other means to lower the entry threshold for small enterprises.Strengthen integrating intelligent technology and cold chain logistics systems to improve data security and system compatibility.At the same time,the government should introduce relevant policies,provide necessary financial support,and establish talent training mechanisms.Accelerate the development and improvement of intelligent technology standards in the field of cold chain logistics.Through technological innovation,cost control,talent cultivation,and policy guidance,we aim to promote the upgrading of the agricultural industry and provide ideas for improving the quality and efficiency of fruit and vegetable cold chain logistics.展开更多
Lithium-oxygen batteries attract considerable attention due to exceptionally high theoretical energy density,while the development remains in its early stage.As is widely suggested,the solution mechanism induces great...Lithium-oxygen batteries attract considerable attention due to exceptionally high theoretical energy density,while the development remains in its early stage.As is widely suggested,the solution mechanism induces greater discharge capacity,while the surface mechanism induces greater cycle stability.Therefore,battery performance can be improved by adjusting the reaction mechanism.Previous studies predominantly focus on extremely thin or flat electrodes.In contrast,this work utilizes thick electrodes,emphasizing the importance of mass transport.Given that the electrolyte solvent is the main site of mass transport,the effects of two typical solvents on mass transport and battery performance are investigated:dimethyl sulfoxide with low viscosity and a high O_(2) diffusion rate and tetraethylene glycol dimethyl ether with high O_(2) solubility and high Li+transport capability.The results reveal a novel pathway for reaction mechanism induction where the mechanism varies with the spatial position of the electrode.As the spatial distribution of the electrode progresses,a layered appearance of solution mechanism products,transition state products,and surface mechanism products emerges,which is attributed to the increase in the mass transfer resistance.This work presents a distinct perspective on the way solvents influence reaction pathways and offers a new approach to regulating reaction pathways.展开更多
Mesoporous carbon supports mitigate platinum(Pt)sulfonic poisoning through nanopore-confined Pt deposition,yet their morphological impacts on oxygen transport remain unclear.This study integrates carbon support morpho...Mesoporous carbon supports mitigate platinum(Pt)sulfonic poisoning through nanopore-confined Pt deposition,yet their morphological impacts on oxygen transport remain unclear.This study integrates carbon support morphology simulation with an enhanced agglomerate model to establish a mathematical framework elucidating pore evolution,Pt utilization,and oxygen transport in catalyst layers.Results demonstrate dominant local mass transport resistance governed by three factors:(1)active site density dictating oxygen flux;(2)ionomer film thickness defining shortest transport path;(3)ionomer-to-Pt surface area ratio modulating practical pathway length.At low ionomer-to-carbon(I/C)ratios,limited active sites elevate resistance(Factor 1 dominant).Higher I/C ratios improve the ionomer coverage but eventually thicken ionomer films,degrading transport(Factors 2–3 dominant).The results indicate that larger carbon particles result in a net increase in local transport resistance by reducing external surface area and increasing ionomer thickness.As the proportion of Pt situated in nanopores or the Pt mass fraction increases,elevated Pt density inside the nanopores exacerbates pore blockage.This leads to the increased transport resistance by reducing active sites,and increasing ionomer thickness and surface area.Lower Pt loading linearly intensifies oxygen flux resistance.The model underscores the necessity to optimize support morphology,Pt distribution,and ionomer content to prevent pore blockage while balancing catalytic activity and transport efficiency.These insights provide a systematic approach for designing high-performance mesoporous carbon catalysts.展开更多
Background Verticillium dahliae,a soil-borne fungi,can cause Verticillium wilt,and seriously diminish the yield and quality of cotton.However,the pathogenic mechanism of V.dahliae is complex and not clearly understood...Background Verticillium dahliae,a soil-borne fungi,can cause Verticillium wilt,and seriously diminish the yield and quality of cotton.However,the pathogenic mechanism of V.dahliae is complex and not clearly understood at the moment.This study aimed to identify the high-affinity nicotinic acid transporter genes in V.dahliae.The gene expression profiles in V.dahliae following sensing of root exudates from susceptible and resistant cotton varieties were analyzed.The function of VdNAT1 in the pathogenic process of V.dahliae was studied using the tobacco rattle virus(TRV)-based host-induced gene silencing(HIGS)technique.Results Eight high-affinity nicotinic acid transporter genes were identified from V.dahliae through the bioinformatics method.Each protein contains a conserved major facilitator superfamily(MFS)domain,which belongs to the MFS superfamily.Evolutionary relationship analysis revealed that all 8 genes belong to the anion:cation symporter(ACS)subfamily.All proteins have transmembrane domains,ranging from 7 to 12.The expression levels of most VdNAT genes were significantly increased after induction by root exudates from susceptible cotton varieties.Silencing VdNAT1 gene by HIGS significantly inhibited the accumulation of fungal biomass in cotton plants,and alleviated the disease symptoms of cotton.Conclusions Eight VdNAT genes were identified from V.dahliae,and most VdNAT genes was up-regulated after induced by root exudates from susceptible cotton variety.In addition,VdNAT1 is required for the pathogenicity of V.dahliae.Overall,these findings will facilitate the pathogenic molecular mechanism of V.dahliae and provide candidate genes.展开更多
The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and e...The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.展开更多
In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuz...In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.展开更多
Based on the pipe transportation of paste-like backfilling system of a certain deep coal mine,its dynamics process was simulated and analyzed.A two-dimensional dynamic model of extraordinary deep and lone pipe was bui...Based on the pipe transportation of paste-like backfilling system of a certain deep coal mine,its dynamics process was simulated and analyzed.A two-dimensional dynamic model of extraordinary deep and lone pipe was built by GAMBIT,on the basis of which the simulation was done by implicit solver of FLUENT 2ddp.The results show that hydraulic loss of pipe transportation is less than the pressure produced by gravity,which means the backfilling material can flow by itself.When the inlet velocity is 3.2 m/s,the maximum velocity of 4.10 m/s is at the elbow and the maximum velocity in the horizontal pipe is 3.91 m/s,which can both meet the stability requirement.The results of the simulation are proved to be reliable by the residual monitor plotting of related parameter,so it can be concluded that the system of pipe transportation is safe.展开更多
文摘To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development.This involved exploring the deep integration of next-generation artificial intelligence technologies,such as sensing technology,automatic control technology,big data technology,deep learning,and machine vision,with key operational processes,including TBM excavation,direction adjustment,step changes,inverted arch block assembly,material transportation,and operation status assurance.The results of this integration are summarized as follows.(1)TBM key excavation parameter prediction algorithm was developed with an accuracy rate exceeding 90%.The TBM intelligent step-change control algorithm,based on machine vision,achieved an image segmentation accuracy rate of 95%and gripper shoe positioning error of±5 mm.(2)An automatic positioning system for inverted arch blocks was developed,enabling real-time perception of the spatial position and deviation during the assembly process.The system maintains an elevation positioning deviation within±3 mm and a horizontal positioning deviation within±10 mm,reducing the number of surveyors in each work team.(3)A TBM intelligent rail transportation system that achieves real-time human-machine positioning,automatic switch opening and closing,automatic obstacle avoidance,intelligent transportation planning,and integrated scheduling and command was designed.Each locomotive formation reduces one shunter and improves comprehensive transportation efficiency by more than 20%.(4)Intelligent analysis and prediction algorithms were developed to monitor and predict the trends of the hydraulic and gear oil parameters in real time,enhancing the proactive maintenance and system reliability.
基金supported by the National Natural Science Foundation of China(6237338661973327).
文摘How multi-unmanned aerial vehicles(UAVs)carrying a payload pass an obstacle-dense environment is practically important.Up to now,there have been few results on safe motion planning for the multi-UAVs cooperative transportation system(CTS)to pass through such an environment.The prob-lem is challenging because it is difficult to analyze and explicitly take into account the swing motion of the payload in planning.In this paper,a modeling method of virtual tube is proposed by fus-ing the advantages of the existing modeling algorithm for regu-lar virtual tube and the expansion environment method.The pro-posed method can not only generate a safe and smooth tube for UAVs,but also ensure the payload stays away from the dense obstacles.Simulation results show the effectiveness of the method and the safety of the planned tube.
基金funded by the National Natural Science Foundation of China(12102487)Basic and Applied Basic Research Foundation of Guangdong Province,China(2023A1515012339)+1 种基金Shenzhen Science and Technology Program(ZDSYS20210623091808026)the Discovery Grant(RGPIN-2024-06290)of the Natural Sciences and Engineering Research Council of Canada。
文摘This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.
基金supported by the National Natural Science Foundation of China(U21B2074,52105070).
文摘Discrete event system(DES)models promote system engineering,including system design,verification,and assessment.The advancement in manufacturing technology has endowed us to fabricate complex industrial systems.Consequently,the adoption of advanced modeling methodologies adept at handling complexity and scalability is imperative.Moreover,industrial systems are no longer quiescent,thus the intelligent operations of the systems should be dynamically specified in the model.In this paper,the composition of the subsystem behaviors is studied to generate the complexity and scalability of the global system model,and a Boolean semantic specifying algorithm is proposed for generating dynamic intelligent operations in the model.In traditional modeling approaches,the change or addition of specifications always necessitates the complete resubmission of the system model,a resource-consuming and error-prone process.Compared with traditional approaches,our approach has three remarkable advantages:(i)an established Boolean semantic can be fitful for all kinds of systems;(ii)there is no need to resubmit the system model whenever there is a change or addition of the operations;(iii)multiple specifying tasks can be easily achieved by continuously adding a new semantic.Thus,this general modeling approach has wide potential for future complex and intelligent industrial systems.
基金supported by the National Natural Science Foundation of China (61502523)。
文摘How to mine valuable information from massive multisource heterogeneous data and identify the intention of aerial targets is a major research focus at present. Aiming at the longterm dependence of air target intention recognition, this paper deeply explores the potential attribute features from the spatiotemporal sequence data of the target. First, we build an intelligent dynamic intention recognition framework, including a series of specific processes such as data source, data preprocessing,target space-time, convolutional neural networks-bidirectional gated recurrent unit-atteneion (CBA) model and intention recognition. Then, we analyze and reason the designed CBA model in detail. Finally, through comparison and analysis with other recognition model experiments, our proposed method can effectively improve the accuracy of air target intention recognition,and is of significance to the commanders’ operational command and situation prediction.
文摘In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect.Firstly,a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed.In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow,a numerical simulation of the basic finner projectile without control is carried out.The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation.Secondly,combined with the real-time control requirements of aerodynamic,attitude and displacement parameters of the projectile during the flight process,the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative)control strategy and the intelligent PID control strategy respectively.The intelligent PID controller based on BP(Back Propagation)neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters.Compared with the traditional PID controller,the concerned control variable overshoot,rise time,transition time and steady state error and other performance indicators have been greatly improved,and the higher the learning efficiency or the inertia coefficient,the faster the system,the larger the overshoot,and the smaller the stability error.The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.
文摘Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent personal assistants within the context of visual,auditory,and somatosensory interactions with drivers were discussed.Their impact on the driver’s psychological state through various modes such as visual imagery,voice interaction,and gesture interaction were explored.The study also introduced innovative designs for in-vehicle intelligent personal assistants,incorporating design principles such as driver-centricity,prioritizing passenger safety,and utilizing timely feedback as a criterion.Additionally,the study employed design methods like driver behavior research and driving situation analysis to enhance the emotional connection between drivers and their vehicles,ultimately improving driver satisfaction and trust.
基金funding from the Australian Government,via grant AUSMURIB000001 associated with ONR MURI Grant N00014-19-1-2571。
文摘We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.
文摘High-Entropy Alloys(HEAs)exhibit significant potential across multiple domains due to their unique properties.However,conventional research methodologies face limitations in composition design,property prediction,and process optimization,characterized by low efficiency and high costs.The integration of Artificial Intelligence(AI)technologies has provided innovative solutions for HEAs research.This review presented a detailed overview of recent advancements in AI applications for structural modeling and mechanical property prediction of HEAs.Furthermore,it discussed the advantages of big data analytics in facilitating alloy composition design and screening,quality control,and defect prediction,as well as the construction and sharing of specialized material databases.The paper also addressed the existing challenges in current AI-driven HEAs research,including issues related to data quality,model interpretability,and cross-domain knowledge integration.Additionally,it proposed prospects for the synergistic development of AI-enhanced computational materials science and experimental validation systems.
基金National Natural Science Foundation of China(32301718)Chinese Academy of Agricultural Sciences under the Special Institute-level Coordination Project for Basic Research Operating Costs(S202328)。
文摘The cold chain in the production area of fruits and vegetables is the primary link to reduce product loss and improve product quality,but it is also a weak link.With the application of big data technology in cold chain logistics,intelligent devices,and technologies have become important carriers for improving the efficiency of cold chain logistics in fruit and vegetable production areas,extending the shelf life of fruits and vegetables,and reducing fruit and vegetable losses.They have many advantages in fruit and vegetable pre-cooling,sorting and packaging,testing,warehousing,transportation,and other aspects.This article summarizes the rapidly developing and widely used intelligent technologies at home and abroad in recent years,including automated guided vehicle intelligent handling based on electromagnetic or optical technology,intelligent sorting based on sensors,electronic optics,and other technologies,intelligent detection based on computer vision technology,intelligent transportation based on perspective imaging technology,etc.It analyses and studies the innovative research and achievements of various scholars in applying intelligent technology in fruit and vegetable cold chain storage,sorting,detection,transportation,and other links,and improves the efficiency of fruit and vegetable cold chain logistics.However,applying intelligent technology in fruit and vegetable cold chain logistics also faces many problems.The challenges of high cost,difficulty in technological integration,and talent shortages have limited the development of intelligent technology in the field of fruit and vegetable cold chains.To solve the current problems,it is proposed that costs be controlled through independent research and development,technological innovation,and other means to lower the entry threshold for small enterprises.Strengthen integrating intelligent technology and cold chain logistics systems to improve data security and system compatibility.At the same time,the government should introduce relevant policies,provide necessary financial support,and establish talent training mechanisms.Accelerate the development and improvement of intelligent technology standards in the field of cold chain logistics.Through technological innovation,cost control,talent cultivation,and policy guidance,we aim to promote the upgrading of the agricultural industry and provide ideas for improving the quality and efficiency of fruit and vegetable cold chain logistics.
基金supported by the National Natural Science Foundation of China(52376080 and 52306122)the Anhui Provincial Natural Science Foundation(2308085QE174)+3 种基金the China Postdoctoral Science Foundation(2023TQ0346)the Postdoctoral Fellowship Program of CPSF(GZC20232522)the Fundamental Research Funds for the Central Universities(WK2090000057)the Students’Innovation and Entrepreneurship Foundation of USTC(CY2023C008).
文摘Lithium-oxygen batteries attract considerable attention due to exceptionally high theoretical energy density,while the development remains in its early stage.As is widely suggested,the solution mechanism induces greater discharge capacity,while the surface mechanism induces greater cycle stability.Therefore,battery performance can be improved by adjusting the reaction mechanism.Previous studies predominantly focus on extremely thin or flat electrodes.In contrast,this work utilizes thick electrodes,emphasizing the importance of mass transport.Given that the electrolyte solvent is the main site of mass transport,the effects of two typical solvents on mass transport and battery performance are investigated:dimethyl sulfoxide with low viscosity and a high O_(2) diffusion rate and tetraethylene glycol dimethyl ether with high O_(2) solubility and high Li+transport capability.The results reveal a novel pathway for reaction mechanism induction where the mechanism varies with the spatial position of the electrode.As the spatial distribution of the electrode progresses,a layered appearance of solution mechanism products,transition state products,and surface mechanism products emerges,which is attributed to the increase in the mass transfer resistance.This work presents a distinct perspective on the way solvents influence reaction pathways and offers a new approach to regulating reaction pathways.
基金supported by the Program of Ministry of Science and Technology of China(No.2023YFB2504200)support of Shanghai Rising-Star Program(Grant No.24QB2703200)the Major Science and Technology Projects of Yunnan Province(No.202302AH360001).
文摘Mesoporous carbon supports mitigate platinum(Pt)sulfonic poisoning through nanopore-confined Pt deposition,yet their morphological impacts on oxygen transport remain unclear.This study integrates carbon support morphology simulation with an enhanced agglomerate model to establish a mathematical framework elucidating pore evolution,Pt utilization,and oxygen transport in catalyst layers.Results demonstrate dominant local mass transport resistance governed by three factors:(1)active site density dictating oxygen flux;(2)ionomer film thickness defining shortest transport path;(3)ionomer-to-Pt surface area ratio modulating practical pathway length.At low ionomer-to-carbon(I/C)ratios,limited active sites elevate resistance(Factor 1 dominant).Higher I/C ratios improve the ionomer coverage but eventually thicken ionomer films,degrading transport(Factors 2–3 dominant).The results indicate that larger carbon particles result in a net increase in local transport resistance by reducing external surface area and increasing ionomer thickness.As the proportion of Pt situated in nanopores or the Pt mass fraction increases,elevated Pt density inside the nanopores exacerbates pore blockage.This leads to the increased transport resistance by reducing active sites,and increasing ionomer thickness and surface area.Lower Pt loading linearly intensifies oxygen flux resistance.The model underscores the necessity to optimize support morphology,Pt distribution,and ionomer content to prevent pore blockage while balancing catalytic activity and transport efficiency.These insights provide a systematic approach for designing high-performance mesoporous carbon catalysts.
基金supported by National Natural Science Foundation of China(No.32160615).
文摘Background Verticillium dahliae,a soil-borne fungi,can cause Verticillium wilt,and seriously diminish the yield and quality of cotton.However,the pathogenic mechanism of V.dahliae is complex and not clearly understood at the moment.This study aimed to identify the high-affinity nicotinic acid transporter genes in V.dahliae.The gene expression profiles in V.dahliae following sensing of root exudates from susceptible and resistant cotton varieties were analyzed.The function of VdNAT1 in the pathogenic process of V.dahliae was studied using the tobacco rattle virus(TRV)-based host-induced gene silencing(HIGS)technique.Results Eight high-affinity nicotinic acid transporter genes were identified from V.dahliae through the bioinformatics method.Each protein contains a conserved major facilitator superfamily(MFS)domain,which belongs to the MFS superfamily.Evolutionary relationship analysis revealed that all 8 genes belong to the anion:cation symporter(ACS)subfamily.All proteins have transmembrane domains,ranging from 7 to 12.The expression levels of most VdNAT genes were significantly increased after induction by root exudates from susceptible cotton varieties.Silencing VdNAT1 gene by HIGS significantly inhibited the accumulation of fungal biomass in cotton plants,and alleviated the disease symptoms of cotton.Conclusions Eight VdNAT genes were identified from V.dahliae,and most VdNAT genes was up-regulated after induced by root exudates from susceptible cotton variety.In addition,VdNAT1 is required for the pathogenicity of V.dahliae.Overall,these findings will facilitate the pathogenic molecular mechanism of V.dahliae and provide candidate genes.
基金Project(41574123)supported by the National Natural Science Foundation of ChinaProject(2015zzts250)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2013FY110800)supported by the National Basic Research Scientific Program of China
文摘The self-potential method is widely used in environmental and engineering geophysics. Four intelligent optimization algorithms are adopted to design the inversion to interpret self-potential data more accurately and efficiently: simulated annealing, genetic, particle swarm optimization, and ant colony optimization. Using both noise-free and noise-added synthetic data, it is demonstrated that all four intelligent algorithms can perform self-potential data inversion effectively. During the numerical experiments, the model distribution in search space, the relative errors of model parameters, and the elapsed time are recorded to evaluate the performance of the inversion. The results indicate that all the intelligent algorithms have good precision and tolerance to noise. Particle swarm optimization has the fastest convergence during iteration because of its good balanced searching capability between global and local minimisation.
文摘In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.
基金Project(2008BAB32B03) supported by the National Science and Technology Pillar Program during the 11th Five-year Plan Period of China
文摘Based on the pipe transportation of paste-like backfilling system of a certain deep coal mine,its dynamics process was simulated and analyzed.A two-dimensional dynamic model of extraordinary deep and lone pipe was built by GAMBIT,on the basis of which the simulation was done by implicit solver of FLUENT 2ddp.The results show that hydraulic loss of pipe transportation is less than the pressure produced by gravity,which means the backfilling material can flow by itself.When the inlet velocity is 3.2 m/s,the maximum velocity of 4.10 m/s is at the elbow and the maximum velocity in the horizontal pipe is 3.91 m/s,which can both meet the stability requirement.The results of the simulation are proved to be reliable by the residual monitor plotting of related parameter,so it can be concluded that the system of pipe transportation is safe.
