Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real...Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real-world monitoring,the process will use RTK-GNSS positional perception technology,by projecting the left side of the earth from Gauss-Krueger projection method,and then carry out the Cartesian conversion based on the characteristics of drawing;steering control system is the core of the electric drive unmanned module,on the basis of the analysis of the composition of the steering system of unmanned engineering vehicles,the steering system key components such as direction,torque sensor,drive motor and other models are established,the joint simulation model of unmanned engineering vehicles is established,the steering controller is designed using the PID method,the simulation results show that the control method can meet the construction path demand for automatic steering.The path planning will first formulate the construction area with preset values and realize the steering angle correction during driving by PID algorithm,and never realize the construction-based path planning,and the results show that the method can control the straight path within the error of 10 cm and the curve error within 20 cm.With the collaboration of various modules,the automatic construction simulation results of this robot show that the design path and control method is effective.展开更多
In order to improve the consistency between the recommended retrieval results and user needs,improve the recommendation efficiency,and reduce the average absolute deviation of resource retrieval,a design method of int...In order to improve the consistency between the recommended retrieval results and user needs,improve the recommendation efficiency,and reduce the average absolute deviation of resource retrieval,a design method of intelligent recommendation retrieval model for Fujian intangible cultural heritage digital archive resources based on knowledge atlas is proposed.The TG-LDA(Tag-granularity LDA)model is proposed on the basis of the standard LDA(Linear Discriminant Analysis)model.The model is used to mine archive resource topics.The Pearson correlation coefficient is used to measure the relevance between topics.Based on the measurement results,the FastText deep learning model is used to achieve archive resource classification.According to the classification results,TF-IDF(term frequency–inverse document frequency)algorithm is used to calculate the weight of resource retrieval keywords to achieve resource retrieval,and a recommendation model of intangible cultural heritage digital archives resources is built through the knowledge map to achieve comprehensive and personalized recommendation of resources.The experimental results show that the recommendation and retrieval results of the proposed method are more in line with users’needs,can provide users with personalized digital archive resources,and the average absolute deviation of resource retrieval is low,the recommendation efficiency is high,and the utilization effect of archive resources is effectively improved.展开更多
Self-powered flexible devices with skin-like multiple sensing ability have attracted great attentions due to their broad applications in the Internet of Things(IoT).Various methods have been proposed to enhance mechan...Self-powered flexible devices with skin-like multiple sensing ability have attracted great attentions due to their broad applications in the Internet of Things(IoT).Various methods have been proposed to enhance mechano-optic or electric performance of the flexible devices;however,it remains challenging to realize the display and accurate recognition of motion trajectories for intelligent control.Here,we present a fully self-powered mechanoluminescent-triboelectric bimodal sensor based on micronanostructured mechanoluminescent elastomer,which can patterned-display the force trajectories.The deformable liquid metals used as stretchable electrode make the stress transfer stable through overall device to achieve outstanding mechanoluminescence(with a gray value of 107 under a stimulus force as low as 0.3 N and more than 2000 cycles reproducibility).Moreover,a microstructured surface is constructed which endows the resulted composite with significantly improved triboelectric performances(voltage increases from 8 to 24 V).Based on the excellent bimodal sensing performances and durability of the obtained composite,a highly reliable intelligent control system by machine learning has been developed for controlling trolley,providing an approach for advanced visual interaction devices and smart wearable electronics in the future IoT era.展开更多
Relying on the construction management of Hangzhouxi Railway Station,this paper analyses the comprehensive application of intelligent construction technology and the establishment of the common data environment(CDE)by...Relying on the construction management of Hangzhouxi Railway Station,this paper analyses the comprehensive application of intelligent construction technology and the establishment of the common data environment(CDE)by using BIM technology.This paper gives the idea that such issues are deeply explored as large-span curved surface structure improvement,steel structure construction monitoring,special-shaped ticket check canopy construction,prefabricated machine room construction,grid construction management,etc.so as to form an intelligent construction management system based on BIM technology.The system has achieved good application results in economic benefits,social benefits and environmental benefits,which can promote the gradual transformation to a more digitalized,networked and intelligent Hangzhouxi Railway Station,and lay a solid foundation for achieving the construction goals of controllable construction period,excellent quality,green and low carbon,etc.展开更多
Discrete Tomography(DT)is a technology that uses image projection to reconstruct images.Its reconstruction problem,especially the binary image(0–1matrix)has attracted strong attention.In this study,a fixed point iter...Discrete Tomography(DT)is a technology that uses image projection to reconstruct images.Its reconstruction problem,especially the binary image(0–1matrix)has attracted strong attention.In this study,a fixed point iterative method of integer programming based on intelligent optimization is proposed to optimize the reconstructedmodel.The solution process can be divided into two procedures.First,the DT problem is reformulated into a polyhedron judgment problembased on lattice basis reduction.Second,the fixed-point iterativemethod of Dang and Ye is used to judge whether an integer point exists in the polyhedron of the previous program.All the programs involved in this study are written in MATLAB.The final experimental data show that this method is obviously better than the branch and bound method in terms of computational efficiency,especially in the case of high dimension.The branch and bound method requires more branch operations and takes a long time.It also needs to store a large number of leaf node boundaries and the corresponding consumptionmatrix,which occupies a largememory space.展开更多
To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most importa...To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction phase.Excessive cutting waste increases construction costs and generates a considerable amount of CO_(2)emission.This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction.In the proposed algorithm,the integer linear programming algorithm was applied to solve the problem.It was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation.The proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction costs.As the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation efficiency.When the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.展开更多
In this paper,the intelligent construction of prefabricated components is analyzed based on building information modeling(BIM).It includes an overview of BIM-based prefabricated components and intelligent construction...In this paper,the intelligent construction of prefabricated components is analyzed based on building information modeling(BIM).It includes an overview of BIM-based prefabricated components and intelligent construction,intelligent production lines in BIM-based intelligent construction systems,and analysis of the application of intelligent manufacturing in BIM-based prefabricated components.It was found that the determination of construction goals,the establishment of intelligent construction systems,and the application of intelligent construction systems are all areas that need to be emphasized in producing prefabricated building components through intelligent construction.It is hoped that this analysis can provide some reference for the application of intelligent construction and the improvement of the quality of prefabricated building components.展开更多
Cultivating application-oriented talents have become essential in vocational and higher education.This concept also applies to BIM intelligent construction programs.Based on literature review and general observations,...Cultivating application-oriented talents have become essential in vocational and higher education.This concept also applies to BIM intelligent construction programs.Based on literature review and general observations,we analyzed the connotation,key points,and value of developing a BIM intelligent construction program based on application-oriented talent cultivation.We also identified problems in the development of the program such as lack of comprehensive planning and the school being the sole authority in program development.Therefore,we proposed several strategies to address these problems,including systematic program development planning and fostering a multi-faceted partnership between schools and the industry.The goal is to provide valuable insights for the development of relevant programs in the new era.展开更多
In view of the problems such as backward production mode,poor quality stability,high safety risk and incomplete control system during erection of the reinforcement framework of simply-supported box girders for high-sp...In view of the problems such as backward production mode,poor quality stability,high safety risk and incomplete control system during erection of the reinforcement framework of simply-supported box girders for high-speed railway(HSR),and in combination with the key points and main challenges in the reinforcement framework construction of Guangzhou-Zhanjiang HSR,the overall technical route for the intelligent manufacturing of reinforcement framework of simply-supported box girders is put forward.The component design of reinforcement framework of simply supported box girder is carried out based on BIM,and the feasibility of the scheme is verified through segment assembly test.The assembly techniques are studied in combination with the mesh design scheme to achieve rapid forming of the reinforcement framework.R&D of automatic processing equipment for components,material transshipment equipment,automatic hoisting equipment and technological equipment for assembly clamping fixture are carried out to realize the overall design of equipment production line.An intelligent control system is developed for the whole-process intelligent construction of reinforcement framework to realize the full life-cycle applications for the workshop production and visual management including intelligent layout and quality traceability.The research results systematically optimize and innovate the assembly and forming technologies of reinforcement framework in the prefabrication beam yard of high-speed railway,realize the component processing,automatic assembly and information technology management,improve the construction quality,efficiency and information technology level of intelligent manufacturing of reinforcement framework of railway prefabricated beam as a whole,and reduce the construction cost of the project.The research has realized a major breakthrough in the construction technology of railway prefabricated box girders,which has the extensive technical and market promotion values.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
Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO sate...Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.展开更多
With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivo...With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.展开更多
Food security is a strategic priority for a country’s economic development.In China,high-standard farmland construction(HSFC)is an important initiative to stabilize grain production and increase grain production capa...Food security is a strategic priority for a country’s economic development.In China,high-standard farmland construction(HSFC)is an important initiative to stabilize grain production and increase grain production capacity.Based on panel data from 31 sample provinces,autonomous regions,and municipalities in China from 2005–2017,this study explored the impact of HSFC on grain yield using the difference-in-differences(DID)method.The results showed that HSFC significantly increased total grain production,which is robust to various checks.HSFC increased grain yield through three potential mechanisms.First,it could increase the grain replanting index.Second,it could effectively reduce yield loss due to droughts and floods.Last,HSFC could strengthen the cultivated land by renovating the low-and medium-yielding fields.Heterogeneity analysis found that the HSFC farmland showed a significant increase in grain yield only in the main grain-producing areas and balanced areas.In addition,HSFC significantly increased the yields of rice,wheat,and maize while leading to a reduction in soybean yields.The findings suggest the government should continue to promote HSFC,improve construction standards,and strictly control the“non-agriculturalization”and“non-coordination”of farmland to increase grain production further.At the same time,market mechanisms should be used to incentivize soybean farming,improve returns and stabilize soybean yields.展开更多
A large amount of mobile data from growing high-speed train(HST)users makes intelligent HST communications enter the era of big data.The corresponding artificial intelligence(AI)based HST channel modeling becomes a tr...A large amount of mobile data from growing high-speed train(HST)users makes intelligent HST communications enter the era of big data.The corresponding artificial intelligence(AI)based HST channel modeling becomes a trend.This paper provides AI based channel characteristic prediction and scenario classification model for millimeter wave(mmWave)HST communications.Firstly,the ray tracing method verified by measurement data is applied to reconstruct four representative HST scenarios.By setting the positions of transmitter(Tx),receiver(Rx),and other parameters,the multi-scenarios wireless channel big data is acquired.Then,based on the obtained channel database,radial basis function neural network(RBF-NN)and back propagation neural network(BP-NN)are trained for channel characteristic prediction and scenario classification.Finally,the channel characteristic prediction and scenario classification capabilities of the network are evaluated by calculating the root mean square error(RMSE).The results show that RBF-NN can generally achieve better performance than BP-NN,and is more applicable to prediction of HST scenarios.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
Structure-soil interface friction characteristics is of importance to investigate the interaction between engineering structures and soils,especially for offshore structures.The interface friction behavior between mar...Structure-soil interface friction characteristics is of importance to investigate the interaction between engineering structures and soils,especially for offshore structures.The interface friction behavior between marine clay and structural materials with different roughness was studied in this paper by using 3D optical scanning tests,a modified direct shear device and numerical simulation.Relationships between the surface roughness of structures,water content and interface friction angle were presented by model tests.The increase of water contents decreased the interface friction angles.For interfaces with different roughness,the interface friction angles will be smaller than that of the soil when the water content exceeds a certain value.The roughness of the interface and the water content of the soil are mutually coupled to influence the coefficient of friction(COF).This paper proposed a Finite Element Method(FEM)to simulate the interface direct shear tests of structures with different roughness.The surface models with different roughness are established based on the structure data obtained by 3D scanning.The Coupled Eulerian-Lagrangian(CEL)approach was employed to analyse soils sheared by irregular surfaces.The interface behavior for interfaces with different roughness under cyclic shear stresses was analyzed by FEM.展开更多
Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this uniq...Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.展开更多
AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally ...AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally 914 CFPs of healthy people and patients with RVO were collected as experimental data sets,and used to train,verify and test the diagnostic model of RVO.All the images were divided into four categories[normal,central retinal vein occlusion(CRVO),branch retinal vein occlusion(BRVO),and macular retinal vein occlusion(MRVO)]by three fundus disease experts.Swin Transformer was used to build the RVO diagnosis model,and different types of RVO diagnosis experiments were conducted.The model’s performance was compared to that of the experts.RESULTS:The accuracy of the model in the diagnosis of normal,CRVO,BRVO,and MRVO reached 1.000,0.978,0.957,and 0.978;the specificity reached 1.000,0.986,0.982,and 0.976;the sensitivity reached 1.000,0.955,0.917,and 1.000;the F1-Sore reached 1.000,0.9550.943,and 0.887 respectively.In addition,the area under curve of normal,CRVO,BRVO,and MRVO diagnosed by the diagnostic model were 1.000,0.900,0.959 and 0.970,respectively.The diagnostic results were highly consistent with those of fundus disease experts,and the diagnostic performance was superior.CONCLUSION:The diagnostic model developed in this study can well diagnose different types of RVO,effectively relieve the work pressure of clinicians,and provide help for the follow-up clinical diagnosis and treatment of RVO patients.展开更多
Taking the changes of construction land in Wan’an County over the years as the research object,the quantity and spatial characteristics of construction land in Wan’an County were analyzed,and the overall situation a...Taking the changes of construction land in Wan’an County over the years as the research object,the quantity and spatial characteristics of construction land in Wan’an County were analyzed,and the overall situation and regional differences of construction land utilization in Wan’an County were revealed.From the aspects of main influencing factors such as land use structure,land use intensity,land input intensity and output benefit,an evaluation indicator system was established to evaluate the economical and intensive use level of construction land in Wan’an County.The results show that the score of the economical and intensive use level of construction land in Wan’an County was 56.92,which was the lowest among all the districts and counties in Ji’an City.Based on the evaluation results,the corresponding economizing and intensive strategies were put forward,and the safeguard measures for its implementation were explored.The purpose is to provide some support for the preparation of territorial spatial planning,the delineation of urban development boundaries,and the potential exploitation of construction land stock,hoping to improve the utilization efficiency and benefit of construction land in Wan’an County,and promote the economic growth of Wan’an County to the stage of high-quality development.展开更多
This research is concentrated on the longitudinal vibration of a tapered pipe pile considering the vertical support of the surrounding soil and construction disturbance.First,the pile-soil system is partitioned into f...This research is concentrated on the longitudinal vibration of a tapered pipe pile considering the vertical support of the surrounding soil and construction disturbance.First,the pile-soil system is partitioned into finite segments in the vertical direction and the Voigt model is applied to simulate the vertical support of the surrounding soil acting on the pile segment.The surrounding soil is divided into finite ring-shaped zones in the radial direction to consider the construction disturbance.Then,the shear complex stiffness at the pile-soil interface is derived by solving the dynamic equilibrium equation for the soil from the outermost to innermost zone.The displacement impedance at the top of an arbitrary pile segment is obtained by solving the dynamic equilibrium equation for the pile and is combined with the vertical support of the surrounding soil to derive the displacement impedance at the bottom of the upper adjacent segment.Further,the displacement impedance at the pile head is obtained based on the impedance function transfer technique.Finally,the reliability of the proposed solution is verified,followed by a sensitivity analysis concerning the coupling effect of the pile parameters,construction disturbance and the vertical support of the surrounding soil on the displacement impedance of the pile.展开更多
文摘Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real-world monitoring,the process will use RTK-GNSS positional perception technology,by projecting the left side of the earth from Gauss-Krueger projection method,and then carry out the Cartesian conversion based on the characteristics of drawing;steering control system is the core of the electric drive unmanned module,on the basis of the analysis of the composition of the steering system of unmanned engineering vehicles,the steering system key components such as direction,torque sensor,drive motor and other models are established,the joint simulation model of unmanned engineering vehicles is established,the steering controller is designed using the PID method,the simulation results show that the control method can meet the construction path demand for automatic steering.The path planning will first formulate the construction area with preset values and realize the steering angle correction during driving by PID algorithm,and never realize the construction-based path planning,and the results show that the method can control the straight path within the error of 10 cm and the curve error within 20 cm.With the collaboration of various modules,the automatic construction simulation results of this robot show that the design path and control method is effective.
文摘In order to improve the consistency between the recommended retrieval results and user needs,improve the recommendation efficiency,and reduce the average absolute deviation of resource retrieval,a design method of intelligent recommendation retrieval model for Fujian intangible cultural heritage digital archive resources based on knowledge atlas is proposed.The TG-LDA(Tag-granularity LDA)model is proposed on the basis of the standard LDA(Linear Discriminant Analysis)model.The model is used to mine archive resource topics.The Pearson correlation coefficient is used to measure the relevance between topics.Based on the measurement results,the FastText deep learning model is used to achieve archive resource classification.According to the classification results,TF-IDF(term frequency–inverse document frequency)algorithm is used to calculate the weight of resource retrieval keywords to achieve resource retrieval,and a recommendation model of intangible cultural heritage digital archives resources is built through the knowledge map to achieve comprehensive and personalized recommendation of resources.The experimental results show that the recommendation and retrieval results of the proposed method are more in line with users’needs,can provide users with personalized digital archive resources,and the average absolute deviation of resource retrieval is low,the recommendation efficiency is high,and the utilization effect of archive resources is effectively improved.
基金the National Natural Science Foundation of China(52173112 and 51873123)Sichuan Provincial Natural Science Fund for Distinguished Young Scholars(2021JDJQ0017)the Program for Featured Directions of Engineering Multidisciplines of Sichuan University(No:2020SCUNG203)for financial support。
文摘Self-powered flexible devices with skin-like multiple sensing ability have attracted great attentions due to their broad applications in the Internet of Things(IoT).Various methods have been proposed to enhance mechano-optic or electric performance of the flexible devices;however,it remains challenging to realize the display and accurate recognition of motion trajectories for intelligent control.Here,we present a fully self-powered mechanoluminescent-triboelectric bimodal sensor based on micronanostructured mechanoluminescent elastomer,which can patterned-display the force trajectories.The deformable liquid metals used as stretchable electrode make the stress transfer stable through overall device to achieve outstanding mechanoluminescence(with a gray value of 107 under a stimulus force as low as 0.3 N and more than 2000 cycles reproducibility).Moreover,a microstructured surface is constructed which endows the resulted composite with significantly improved triboelectric performances(voltage increases from 8 to 24 V).Based on the excellent bimodal sensing performances and durability of the obtained composite,a highly reliable intelligent control system by machine learning has been developed for controlling trolley,providing an approach for advanced visual interaction devices and smart wearable electronics in the future IoT era.
文摘Relying on the construction management of Hangzhouxi Railway Station,this paper analyses the comprehensive application of intelligent construction technology and the establishment of the common data environment(CDE)by using BIM technology.This paper gives the idea that such issues are deeply explored as large-span curved surface structure improvement,steel structure construction monitoring,special-shaped ticket check canopy construction,prefabricated machine room construction,grid construction management,etc.so as to form an intelligent construction management system based on BIM technology.The system has achieved good application results in economic benefits,social benefits and environmental benefits,which can promote the gradual transformation to a more digitalized,networked and intelligent Hangzhouxi Railway Station,and lay a solid foundation for achieving the construction goals of controllable construction period,excellent quality,green and low carbon,etc.
基金funded by the NSFC under Grant Nos.61803279,71471091,62003231 and 51874205in part by the Qing Lan Project of Jiangsu,in part by the China Postdoctoral Science Foundation under Grant Nos.2020M671596 and 2021M692369+2 种基金in part by the Suzhou Science and Technology Development Plan Project(Key Industry Technology Innovation)under Grant No.SYG202114in part by the Natural Science Foundation of Jiangsu Province under Grant No.BK20200989Postdoctoral Research Funding Program of Jiangsu Province.
文摘Discrete Tomography(DT)is a technology that uses image projection to reconstruct images.Its reconstruction problem,especially the binary image(0–1matrix)has attracted strong attention.In this study,a fixed point iterative method of integer programming based on intelligent optimization is proposed to optimize the reconstructedmodel.The solution process can be divided into two procedures.First,the DT problem is reformulated into a polyhedron judgment problembased on lattice basis reduction.Second,the fixed-point iterativemethod of Dang and Ye is used to judge whether an integer point exists in the polyhedron of the previous program.All the programs involved in this study are written in MATLAB.The final experimental data show that this method is obviously better than the branch and bound method in terms of computational efficiency,especially in the case of high dimension.The branch and bound method requires more branch operations and takes a long time.It also needs to store a large number of leaf node boundaries and the corresponding consumptionmatrix,which occupies a largememory space.
基金funded by Nature Science Foundation of China(51878556)the Key Scientific Research Projects of Shaanxi Provincial Department of Education(20JY049)+1 种基金Key Research and Development Program of Shaanxi Province(2019TD-014)State Key Laboratory of Rail Transit Engineering Informatization(FSDI)(SKLKZ21-03).
文摘To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction.As one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction phase.Excessive cutting waste increases construction costs and generates a considerable amount of CO_(2)emission.This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction.In the proposed algorithm,the integer linear programming algorithm was applied to solve the problem.It was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation.The proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction costs.As the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation efficiency.When the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.
文摘In this paper,the intelligent construction of prefabricated components is analyzed based on building information modeling(BIM).It includes an overview of BIM-based prefabricated components and intelligent construction,intelligent production lines in BIM-based intelligent construction systems,and analysis of the application of intelligent manufacturing in BIM-based prefabricated components.It was found that the determination of construction goals,the establishment of intelligent construction systems,and the application of intelligent construction systems are all areas that need to be emphasized in producing prefabricated building components through intelligent construction.It is hoped that this analysis can provide some reference for the application of intelligent construction and the improvement of the quality of prefabricated building components.
基金Chongqing Municipal Education Science Planning ProjectEducational Reform Special ProjectPractice Research on Integrated Teaching Reform of“Post Course Competition Certificate”for BIM Intelligent Construction Major in Vocational Schools(K23ZG3250169)。
文摘Cultivating application-oriented talents have become essential in vocational and higher education.This concept also applies to BIM intelligent construction programs.Based on literature review and general observations,we analyzed the connotation,key points,and value of developing a BIM intelligent construction program based on application-oriented talent cultivation.We also identified problems in the development of the program such as lack of comprehensive planning and the school being the sole authority in program development.Therefore,we proposed several strategies to address these problems,including systematic program development planning and fostering a multi-faceted partnership between schools and the industry.The goal is to provide valuable insights for the development of relevant programs in the new era.
文摘In view of the problems such as backward production mode,poor quality stability,high safety risk and incomplete control system during erection of the reinforcement framework of simply-supported box girders for high-speed railway(HSR),and in combination with the key points and main challenges in the reinforcement framework construction of Guangzhou-Zhanjiang HSR,the overall technical route for the intelligent manufacturing of reinforcement framework of simply-supported box girders is put forward.The component design of reinforcement framework of simply supported box girder is carried out based on BIM,and the feasibility of the scheme is verified through segment assembly test.The assembly techniques are studied in combination with the mesh design scheme to achieve rapid forming of the reinforcement framework.R&D of automatic processing equipment for components,material transshipment equipment,automatic hoisting equipment and technological equipment for assembly clamping fixture are carried out to realize the overall design of equipment production line.An intelligent control system is developed for the whole-process intelligent construction of reinforcement framework to realize the full life-cycle applications for the workshop production and visual management including intelligent layout and quality traceability.The research results systematically optimize and innovate the assembly and forming technologies of reinforcement framework in the prefabrication beam yard of high-speed railway,realize the component processing,automatic assembly and information technology management,improve the construction quality,efficiency and information technology level of intelligent manufacturing of reinforcement framework of railway prefabricated beam as a whole,and reduce the construction cost of the project.The research has realized a major breakthrough in the construction technology of railway prefabricated box girders,which has the extensive technical and market promotion values.
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.
基金supported by the National Key R&D Program of China under Grant 2020YFB1807900the National Natural Science Foundation of China (NSFC) under Grant 61931005Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.
基金supported by the Natural Science Foundation of Heilongjiang Province(Grant Number:LH2021F002).
文摘With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.
基金supported by the National Natural Science Foundation of China(41871184)the National Social Science Fund of China(21ZDA056)the Scientific and Technological Innovation Project of the Chinese Academy of Agricultural Sciences(10-IAED-ZT-01-2023and 10-IAED-RC-07-2023)。
文摘Food security is a strategic priority for a country’s economic development.In China,high-standard farmland construction(HSFC)is an important initiative to stabilize grain production and increase grain production capacity.Based on panel data from 31 sample provinces,autonomous regions,and municipalities in China from 2005–2017,this study explored the impact of HSFC on grain yield using the difference-in-differences(DID)method.The results showed that HSFC significantly increased total grain production,which is robust to various checks.HSFC increased grain yield through three potential mechanisms.First,it could increase the grain replanting index.Second,it could effectively reduce yield loss due to droughts and floods.Last,HSFC could strengthen the cultivated land by renovating the low-and medium-yielding fields.Heterogeneity analysis found that the HSFC farmland showed a significant increase in grain yield only in the main grain-producing areas and balanced areas.In addition,HSFC significantly increased the yields of rice,wheat,and maize while leading to a reduction in soybean yields.The findings suggest the government should continue to promote HSFC,improve construction standards,and strictly control the“non-agriculturalization”and“non-coordination”of farmland to increase grain production further.At the same time,market mechanisms should be used to incentivize soybean farming,improve returns and stabilize soybean yields.
基金supported by the National Key R&D Program of China under Grant 2021YFB1407001the National Natural Science Foundation of China (NSFC) under Grants 62001269 and 61960206006+2 种基金the State Key Laboratory of Rail Traffic Control and Safety (under Grants RCS2022K009)Beijing Jiaotong University, the Future Plan Program for Young Scholars of Shandong Universitythe EU H2020 RISE TESTBED2 project under Grant 872172
文摘A large amount of mobile data from growing high-speed train(HST)users makes intelligent HST communications enter the era of big data.The corresponding artificial intelligence(AI)based HST channel modeling becomes a trend.This paper provides AI based channel characteristic prediction and scenario classification model for millimeter wave(mmWave)HST communications.Firstly,the ray tracing method verified by measurement data is applied to reconstruct four representative HST scenarios.By setting the positions of transmitter(Tx),receiver(Rx),and other parameters,the multi-scenarios wireless channel big data is acquired.Then,based on the obtained channel database,radial basis function neural network(RBF-NN)and back propagation neural network(BP-NN)are trained for channel characteristic prediction and scenario classification.Finally,the channel characteristic prediction and scenario classification capabilities of the network are evaluated by calculating the root mean square error(RMSE).The results show that RBF-NN can generally achieve better performance than BP-NN,and is more applicable to prediction of HST scenarios.
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.
基金supported by a grant from the National Natural Science Foundations of China(No.52171282)supported by Taishan Scholars Program of Shandong Province,China(No.tsqn202306098)the Shandong Provincial Key Research and Development Plan,China(No.2021ZLGX04).
文摘Structure-soil interface friction characteristics is of importance to investigate the interaction between engineering structures and soils,especially for offshore structures.The interface friction behavior between marine clay and structural materials with different roughness was studied in this paper by using 3D optical scanning tests,a modified direct shear device and numerical simulation.Relationships between the surface roughness of structures,water content and interface friction angle were presented by model tests.The increase of water contents decreased the interface friction angles.For interfaces with different roughness,the interface friction angles will be smaller than that of the soil when the water content exceeds a certain value.The roughness of the interface and the water content of the soil are mutually coupled to influence the coefficient of friction(COF).This paper proposed a Finite Element Method(FEM)to simulate the interface direct shear tests of structures with different roughness.The surface models with different roughness are established based on the structure data obtained by 3D scanning.The Coupled Eulerian-Lagrangian(CEL)approach was employed to analyse soils sheared by irregular surfaces.The interface behavior for interfaces with different roughness under cyclic shear stresses was analyzed by FEM.
基金the National Natural Science Foundation of China(Grant No.52072041)the Beijing Natural Science Foundation(Grant No.JQ21007)+2 种基金the University of Chinese Academy of Sciences(Grant No.Y8540XX2D2)the Robotics Rhino-Bird Focused Research Project(No.2020-01-002)the Tencent Robotics X Laboratory.
文摘Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.
基金Supported by Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties(No.SZGSP014)Sanming Project of Medicine in Shenzhen(No.SZSM202011015)Shenzhen Science and Technology Planning Project(No.KCXFZ20211020163813019).
文摘AIM:To develop an artificial intelligence(AI)diagnosis model based on deep learning(DL)algorithm to diagnose different types of retinal vein occlusion(RVO)by recognizing color fundus photographs(CFPs).METHODS:Totally 914 CFPs of healthy people and patients with RVO were collected as experimental data sets,and used to train,verify and test the diagnostic model of RVO.All the images were divided into four categories[normal,central retinal vein occlusion(CRVO),branch retinal vein occlusion(BRVO),and macular retinal vein occlusion(MRVO)]by three fundus disease experts.Swin Transformer was used to build the RVO diagnosis model,and different types of RVO diagnosis experiments were conducted.The model’s performance was compared to that of the experts.RESULTS:The accuracy of the model in the diagnosis of normal,CRVO,BRVO,and MRVO reached 1.000,0.978,0.957,and 0.978;the specificity reached 1.000,0.986,0.982,and 0.976;the sensitivity reached 1.000,0.955,0.917,and 1.000;the F1-Sore reached 1.000,0.9550.943,and 0.887 respectively.In addition,the area under curve of normal,CRVO,BRVO,and MRVO diagnosed by the diagnostic model were 1.000,0.900,0.959 and 0.970,respectively.The diagnostic results were highly consistent with those of fundus disease experts,and the diagnostic performance was superior.CONCLUSION:The diagnostic model developed in this study can well diagnose different types of RVO,effectively relieve the work pressure of clinicians,and provide help for the follow-up clinical diagnosis and treatment of RVO patients.
文摘Taking the changes of construction land in Wan’an County over the years as the research object,the quantity and spatial characteristics of construction land in Wan’an County were analyzed,and the overall situation and regional differences of construction land utilization in Wan’an County were revealed.From the aspects of main influencing factors such as land use structure,land use intensity,land input intensity and output benefit,an evaluation indicator system was established to evaluate the economical and intensive use level of construction land in Wan’an County.The results show that the score of the economical and intensive use level of construction land in Wan’an County was 56.92,which was the lowest among all the districts and counties in Ji’an City.Based on the evaluation results,the corresponding economizing and intensive strategies were put forward,and the safeguard measures for its implementation were explored.The purpose is to provide some support for the preparation of territorial spatial planning,the delineation of urban development boundaries,and the potential exploitation of construction land stock,hoping to improve the utilization efficiency and benefit of construction land in Wan’an County,and promote the economic growth of Wan’an County to the stage of high-quality development.
基金National Natural Science Foundation of China under Grand No.51808190the Central Government Guides Local Science and Technology Development Fund Projects under Grand No.XZ202301YD0019C+2 种基金the Foundation of Key Laboratory of Soft Soils and Geoenvironmental Engineering(Zhejiang University)Ministry of Education under Grand No.2022P04the Central University Basic Research Fund of China under Grand No.B220202017。
文摘This research is concentrated on the longitudinal vibration of a tapered pipe pile considering the vertical support of the surrounding soil and construction disturbance.First,the pile-soil system is partitioned into finite segments in the vertical direction and the Voigt model is applied to simulate the vertical support of the surrounding soil acting on the pile segment.The surrounding soil is divided into finite ring-shaped zones in the radial direction to consider the construction disturbance.Then,the shear complex stiffness at the pile-soil interface is derived by solving the dynamic equilibrium equation for the soil from the outermost to innermost zone.The displacement impedance at the top of an arbitrary pile segment is obtained by solving the dynamic equilibrium equation for the pile and is combined with the vertical support of the surrounding soil to derive the displacement impedance at the bottom of the upper adjacent segment.Further,the displacement impedance at the pile head is obtained based on the impedance function transfer technique.Finally,the reliability of the proposed solution is verified,followed by a sensitivity analysis concerning the coupling effect of the pile parameters,construction disturbance and the vertical support of the surrounding soil on the displacement impedance of the pile.
