Background:Based on the principle of“joint consultation,co-building,and sharing”,with the aim of creating an energetic new model of economic growth,the Belt and Road Initiative achieves connectivity and mutual benef...Background:Based on the principle of“joint consultation,co-building,and sharing”,with the aim of creating an energetic new model of economic growth,the Belt and Road Initiative achieves connectivity and mutual benefit.However,the degree of coordinated development of innovation subjects directly affects the improvement and optimization of the Belt and Road Initiative’s strategy implementation environment,and technology efficiency needs improvement.Methods:In this study,a data envelopment analysis model based on the environmental noise elimination algorithm(traditional Chinese medicine-Belt and Road Initiative)was used to identify the technical efficiency of the traditional Chinese medicine industry of Belt and Road Initiative by eliminating the impact of environmental factors.Results:Pure technical ineffectiveness,regional impact,and environmental factors represented by policy responses have a non-linear impact on technical efficiency.The overall technical efficiency of the traditional Chinese medicine industry in the countries along the route shows a trend of annual increases,technical efficiency and scale efficiency are relatively high,and operational efficiency is influenced by the degree of response of the countries along the route and its supporting policies.Conclusion:Pure technical inefficiency is the main factor affecting total technical loss.Geographical advantage is the key factor in operational efficiency.External environmental factors have a significant influence on the operational efficiency of the traditional Chinese medicine industry.展开更多
With the continuous development of drone technology,rapid exploration strategies are of significant importance for tasks such as search and rescue and surveying.Current autonomous exploration systems often face issues...With the continuous development of drone technology,rapid exploration strategies are of significant importance for tasks such as search and rescue and surveying.Current autonomous exploration systems often face issues of partial small-area information omission in cluttered environments,leading to repeated visits by drones.This paper proposes an improved multi-drone autonomous exploration system,which introduces a novel mode-switching mechanism based on a rapid autonomous exploration framework.This mechanism dynamically adjusts the exploration mode of the drones using the density information of surrounding obstacles.By doing so,drones can avoid missing small pieces of information that result in repeated visits in complex environments,while maintaining high exploration efficiency in simpler environments.This flexible exploration planning approach effectively addresses varying levels of environmental complexity.Evaluations conducted in three different environments of varying complexity demonstrate that the proposed method achieves higher exploration efficiency and reconstruction quality.展开更多
Solar-driven interfacial desalination(SID)offers a sustainable route for freshwater production,yet its long-term performance is compromised by salt crystallization and microbial fouling under complex marine conditions...Solar-driven interfacial desalination(SID)offers a sustainable route for freshwater production,yet its long-term performance is compromised by salt crystallization and microbial fouling under complex marine conditions.Zwitterionic polymers offer promising nonfouling capabilities,but current zwitterionic hydrogel-based solar evaporators(HSEs)suffer from inadequate hydration and salt vulnerability.Inspired by the natural marine environmental adaptive characteristics of saltwater fish,we report a superhydrated zwitterionic poly(trimethylamine N-oxide,PTMAO)/polyacrylamide(PAAm)/polypyrrole(PPy)hydrogel(PTAP)with dedicated water channels for efficient,durable,and nonfouling SID.The directly linked N⁺and O⁻groups in PTMAO establish a robust hydration shell that facilitates rapid water transport while resisting salt and microbial adhesion.Integrated PAAm and PPy networks enhance mechanical strength and photothermal conversion.PTAP achieves a high evaporation rate of 2.35 kg m^(−2)h^(−1)under 1 kW m^(–2)in 10 wt%NaCl solution,maintaining stable operation over 100 h without salt accumulation.Furthermore,PTAP effectively resists various foulants including proteins,bacterial,and algal adhesion.Molecular dynamics simulations reveal that the exceptional hydration capacity supports its nonfouling properties.This work advances the development of nonfouling HSEs for sustainable solar desalination in real-world marine environments.展开更多
This paper presents a 3D path planning algorithm for an unmanned aerial vehicle （UAV） in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the...This paper presents a 3D path planning algorithm for an unmanned aerial vehicle （UAV） in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, free space is represented by free voxels, which have enough space margin for the UAV to pass through. A bounding box array is created in the whole 3D space to evaluate the free voxel connectivity. The probabilistic roadmap method （PRM） is improved by random sampling in the bounding box array to ensure a more efficient distribution of roadmap nodes in 3D space. According to the connectivity evaluation, the roadmap is used to plan a feasible path by using A＊ algorithm. Experimental results indicate that the proposed algorithm is valid in complex 3D environments.展开更多
In recent decades,path planning for unmanned surface vehicles(USVs)in complex environments,such as harbours and coastlines,has become an important concern.The existing algorithms for real-time path planning for USVs a...In recent decades,path planning for unmanned surface vehicles(USVs)in complex environments,such as harbours and coastlines,has become an important concern.The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with multiple dynamic obstacles.In this study,we developed a novel path planning method based on the D^(*) lite algorithm for real-time path planning of USVs in complex environments.The proposed method has the following advantages:(1)the computational time for replanning is reduced significantly owing to the use of an incremental algorithm and a new method for modelling dynamic obstacles;(2)a constrained artificial potential field method is employed to enhance the safety of the planned paths;and(3)the method is practical in terms of vehicle performance.The performance of the proposed method was evaluated through simulations and compared with those of existing algorithms.The simulation results confirmed the efficiency of the method for real-time path planning of USVs in complex environments.展开更多
Studying and analyzing the dynamic behavior of offshore wind turbines are of great importance to ensure the safety and improve the efficiency of such expensive equipments.In this work,a tapered beam model is proposed ...Studying and analyzing the dynamic behavior of offshore wind turbines are of great importance to ensure the safety and improve the efficiency of such expensive equipments.In this work,a tapered beam model is proposed to investigate the dynamic response of an offshore wind turbine tower on the monopile foundation assembled with rotating blades in the complex ocean environment.Several environment factors like wind,wave,current,and soil resistance are taken into account.The proposed model is ana-lytically solved with the Galerkin method.Based on the numerical results,the effects of various structure parameters including the taper angle,the height and thickness of the tower,the depth,and the diameter and the cement filler of the monopile on the funda-mental natural frequency of the wind turbine tower system are investigated in detail.It is found that the fundamental natural frequency decreases with the increase in the taper angle and the height and thickness of the tower,and increases with the increase in the diameter of the monopile.Moreover,filling cement into the monopile can effectively im-prove the fundamental natural frequency of the wind turbine tower system,but there is a critical value of the amount of cement maximizing the property of the monopile.This research may be helpful in the design and safety evaluation of offshore wind turbines.展开更多
In virtue of effect of N-S intensive ground stress and mining disturbance to +579E2EB_(1+2) mining site at Weihuliang Mine,the dip angle and section height is 65° and 52 m,respectively,the collapses happed freque...In virtue of effect of N-S intensive ground stress and mining disturbance to +579E2EB_(1+2) mining site at Weihuliang Mine,the dip angle and section height is 65° and 52 m,respectively,the collapses happed frequently during mining.Firstly,mining condi- tions,spatial structure and parameters were investigated.Then physical simulation and dynamic numerical tracing and elaborate simulation relating roof and top-coal were ap- plied based on 2D-Block Program and quantitative regularity of stress at variable depths had been estimated.Furthermore,it was manifested that effective measures,i.e.,fast mining,control symmetrical top-coal-caving at dip and strike directions,optimizing ventila- tion system,active-stereo preventing gas were performed successfully in mining practice. Ultimately,the derived dynamic hazard were prevented so as to safety mining.展开更多
With the increasing global demand for renewable energy,the application of photovoltaic power generation in mountainous areas is gradually increasing.However,the complex wind environment in mountainous areas poses seve...With the increasing global demand for renewable energy,the application of photovoltaic power generation in mountainous areas is gradually increasing.However,the complex wind environment in mountainous areas poses severe challenges to the design and optimization of solar photovoltaic brackets.Traditional design methods are difficult to cope with the changeable wind speed and direction in mountainous areas,resulting in structural instability or material waste.Researchers have identified the key factors affecting wind response through parametric research and dynamic wind response analysis,so as to optimize the brackets design and improve its adaptability and stability in complex wind environments.In this paper,the complexity of wind speed,wind direction and turbulence characteristics in mountainous areas and their influence on brackets design are explored.Through static and dynamic wind load analysis,the geometrical shape and material selection of the bracket are optimized to enhance its wind resistance.The application of multi-objective optimization model and intelligent optimization algorithm provides an effective solution for the design of solar photovoltaic brackets,ensuring their safety and reliability in complex wind environments.展开更多
Recycled aggregate concrete refers to a new type of concrete material made by processing waste concrete materials through grading,crushing,and cleaning,and then mixing them with cement,water,and other materials in a c...Recycled aggregate concrete refers to a new type of concrete material made by processing waste concrete materials through grading,crushing,and cleaning,and then mixing them with cement,water,and other materials in a certain gradation or proportion.This type of concrete is highly suitable for modern construction waste disposal and reuse and has been widely used in various construction projects.It can also be used as an environmentally friendly permeable brick material to promote the development of modern green buildings.However,practical applications have found that compared to ordinary concrete,the durability of this type of concrete is more susceptible to high-temperature and complex environments.Based on this,this paper conducts theoretical research on its durability in high-temperature and complex environments,including the current research status,existing problems,and application prospects of recycled aggregate concrete’s durability in such environments.It is hoped that this analysis can provide some reference for studying the influence of high-temperature and complex environments on recycled aggregate concrete and its subsequent application strategies.展开更多
Shield tunneling is an important link in the current subway construction. It has a high level of automation, which greatly improves the construction efficiency. At the same time, subway shield construction can also re...Shield tunneling is an important link in the current subway construction. It has a high level of automation, which greatly improves the construction efficiency. At the same time, subway shield construction can also reduce the impact of urban ground traffic, so it has been widely used in the construction of subway projects. In this paper, the technology and construction technology of shield tunneling under complex environment are studied and analyzed for reference.展开更多
With China and Africa having worked hand in hand for mutual benefits for a long time,China-Africa economic and trade cooperation has developed steadily,achieving significant progress in many fields.However,at the same...With China and Africa having worked hand in hand for mutual benefits for a long time,China-Africa economic and trade cooperation has developed steadily,achieving significant progress in many fields.However,at the same time,the environment in which China-Africa economic and trade cooperation operates is becoming increasingly complex.Risks and challenges from different levels are worth noticing.展开更多
Detecting individuals wearing safety helmets in complex environments faces several challenges.These factors include limited detection accuracy and frequent missed or false detections.Additionally,existing algorithms o...Detecting individuals wearing safety helmets in complex environments faces several challenges.These factors include limited detection accuracy and frequent missed or false detections.Additionally,existing algorithms often have excessive parameter counts,complex network structures,and high computational demands.These challenges make it difficult to deploy such models efficiently on resource-constrained devices like embedded systems.Aiming at this problem,this research proposes an optimized and lightweight solution called FGP-YOLOv8,an improved version of YOLOv8n.The YOLOv8 backbone network is replaced with the FasterNet model to reduce parameters and computational demands while local convolution layers are added.This modification minimizes computational costs with only a minor impact on accuracy.A new GSTA(GSConv-Triplet Attention)module is introduced to enhance feature fusion and reduce computational complexity.This is achieved using attention weights generated from dimensional interactions within the feature map.Additionally,the ParNet-C2f module replaces the original C2f(CSP Bottleneck with 2 Convolutions)module,improving feature extraction for safety helmets of various shapes and sizes.The CIoU(Complete-IoU)is replaced with the WIoU(Wise-IoU)to boost performance further,enhancing detection accuracy and generalization capabilities.Experimental results validate the improvements.The proposedmodel reduces the parameter count by 19.9% and the computational load by 18.5%.At the same time,mAP(mean average precision)increases by 2.3%,and precision improves by 1.2%.These results demonstrate the model’s robust performance in detecting safety helmets across diverse environments.展开更多
This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated ...This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments.Initially,a collaborative planning cost function for the multi-UAV system is formulated,thereby converting the trajectory planning challenge into an optimization problem.Building on the foundational dung beetle optimization(DBO)algorithm,BFDBO incorporates three significant innovations:a boundary reflection mechanism,an adaptive mixed exploration strategy,and a dynamic multi-scale mutation strategy.These enhancements are intended to optimize the equilibrium between local exploration and global exploitation,facilitating the discovery of globally optimal trajectories thatminimize the cost function.Numerical simulations utilizing the CEC2022 benchmark function indicate that all three enhancements of BFDBOpositively influence its performance,resulting in accelerated convergence and improved optimization accuracy relative to leading optimization algorithms.In two battlefield scenarios of varying complexities,BFDBO achieved a minimum of a 39% reduction in total trajectory planning costs when compared to DBO and three other highperformance variants,while also demonstrating superior average runtime.This evidence underscores the effectiveness and applicability of BFDBO in practical,real-world contexts.展开更多
In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.Ho...In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.展开更多
In response to the problems of low sampling efficiency,strong randomness of sampling points,and the tortuous shape of the planned path in the traditional rapidly-exploring random tree(RRT)algorithm and bidirectional R...In response to the problems of low sampling efficiency,strong randomness of sampling points,and the tortuous shape of the planned path in the traditional rapidly-exploring random tree(RRT)algorithm and bidirectional RRT algorithm used for unmanned aerial vehicle(UAV)path planning in complex environments,an improved bidirectional RRT algorithm was proposed.The algorithm firstly adopted a goal-oriented strategy to guide the sampling points towards the target point,and then the artificial potential field acted on the random tree nodes to avoid collision with obstacles and reduced the length of the search path,and the random tree node growth also combined the UAV’s own flight constraints,and by combining the triangulation method to remove the redundant node strategy and the third-order B-spline curve for the smoothing of the trajectory,the planned path was better.The planned paths were more optimized.Finally,the simulation experiments in complex and dynamic environments showed that the algorithm effectively improved the speed of trajectory planning and shortened the length of the trajectory,and could generate a safe,smooth and fast trajectory in complex environments,which could be applied to online trajectory planning.展开更多
Underwater imaging is frequently influenced by factors such as illumination,scattering,and refraction,which can result in low image contrast and blurriness.Moreover,the presence of numerous small,overlapping targets r...Underwater imaging is frequently influenced by factors such as illumination,scattering,and refraction,which can result in low image contrast and blurriness.Moreover,the presence of numerous small,overlapping targets reduces detection accuracy.To address these challenges,first,green channel images are preprocessed to rectify color bias while improving contrast and clarity.Se-cond,the YOLO-DBS network that employs deformable convolution is proposed to enhance feature learning from underwater blurry images.The ECA attention mechanism is also introduced to strengthen feature focus.Moreover,a bidirectional feature pyramid net-work is utilized for efficient multilayer feature fusion while removing nodes that contribute minimally to detection performance.In addition,the SIoU loss function that considers factors such as angular error and distance deviation is incorporated into the network.Validation on the RUOD dataset demonstrates that YOLO-DBS achieves approximately 3.1%improvement in mAP@0.5 compared with YOLOv8n and surpasses YOLOv9-tiny by 1.3%.YOLO-DBS reduces parameter count by 32%relative to YOLOv8n,thereby demonstrating superior performance in real-time detection on underwater observation platforms.展开更多
Mid-Year Marine Economy Report Developing the marine economy and building China into a maritime powerhouse are of great significance for China’s socio-economic sustainable development,as well as for advancing its mod...Mid-Year Marine Economy Report Developing the marine economy and building China into a maritime powerhouse are of great significance for China’s socio-economic sustainable development,as well as for advancing its modernization drive.Recently released data from the Ministry of Natural Resources shows that during the first half of 2025,despite a complex and volatile external environment,China’s marine economy withstood the pressure and maintained a steady and positive development trend.展开更多
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.展开更多
A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homo...A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching- CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.展开更多
文摘Background:Based on the principle of“joint consultation,co-building,and sharing”,with the aim of creating an energetic new model of economic growth,the Belt and Road Initiative achieves connectivity and mutual benefit.However,the degree of coordinated development of innovation subjects directly affects the improvement and optimization of the Belt and Road Initiative’s strategy implementation environment,and technology efficiency needs improvement.Methods:In this study,a data envelopment analysis model based on the environmental noise elimination algorithm(traditional Chinese medicine-Belt and Road Initiative)was used to identify the technical efficiency of the traditional Chinese medicine industry of Belt and Road Initiative by eliminating the impact of environmental factors.Results:Pure technical ineffectiveness,regional impact,and environmental factors represented by policy responses have a non-linear impact on technical efficiency.The overall technical efficiency of the traditional Chinese medicine industry in the countries along the route shows a trend of annual increases,technical efficiency and scale efficiency are relatively high,and operational efficiency is influenced by the degree of response of the countries along the route and its supporting policies.Conclusion:Pure technical inefficiency is the main factor affecting total technical loss.Geographical advantage is the key factor in operational efficiency.External environmental factors have a significant influence on the operational efficiency of the traditional Chinese medicine industry.
文摘With the continuous development of drone technology,rapid exploration strategies are of significant importance for tasks such as search and rescue and surveying.Current autonomous exploration systems often face issues of partial small-area information omission in cluttered environments,leading to repeated visits by drones.This paper proposes an improved multi-drone autonomous exploration system,which introduces a novel mode-switching mechanism based on a rapid autonomous exploration framework.This mechanism dynamically adjusts the exploration mode of the drones using the density information of surrounding obstacles.By doing so,drones can avoid missing small pieces of information that result in repeated visits in complex environments,while maintaining high exploration efficiency in simpler environments.This flexible exploration planning approach effectively addresses varying levels of environmental complexity.Evaluations conducted in three different environments of varying complexity demonstrate that the proposed method achieves higher exploration efficiency and reconstruction quality.
基金supported by National Natural Science Foundation of China(22209036,U23A20119)Hebei Provincial Natural Science Foundation,Excellent Youth Project(E2023202069)+1 种基金National Key R&D Program of China(2024YFF0506000,2024YFB4609100)Fundamental Research Foundation from Hebei University of Technology(424132016,282021485).
文摘Solar-driven interfacial desalination(SID)offers a sustainable route for freshwater production,yet its long-term performance is compromised by salt crystallization and microbial fouling under complex marine conditions.Zwitterionic polymers offer promising nonfouling capabilities,but current zwitterionic hydrogel-based solar evaporators(HSEs)suffer from inadequate hydration and salt vulnerability.Inspired by the natural marine environmental adaptive characteristics of saltwater fish,we report a superhydrated zwitterionic poly(trimethylamine N-oxide,PTMAO)/polyacrylamide(PAAm)/polypyrrole(PPy)hydrogel(PTAP)with dedicated water channels for efficient,durable,and nonfouling SID.The directly linked N⁺and O⁻groups in PTMAO establish a robust hydration shell that facilitates rapid water transport while resisting salt and microbial adhesion.Integrated PAAm and PPy networks enhance mechanical strength and photothermal conversion.PTAP achieves a high evaporation rate of 2.35 kg m^(−2)h^(−1)under 1 kW m^(–2)in 10 wt%NaCl solution,maintaining stable operation over 100 h without salt accumulation.Furthermore,PTAP effectively resists various foulants including proteins,bacterial,and algal adhesion.Molecular dynamics simulations reveal that the exceptional hydration capacity supports its nonfouling properties.This work advances the development of nonfouling HSEs for sustainable solar desalination in real-world marine environments.
基金supported by National Natural Science Foundation of China(No.61305128)Fundamental Research Funds for the Central Universities,and U.S.Army Research Ofce(No.W911NF-091-0565)
文摘This paper presents a 3D path planning algorithm for an unmanned aerial vehicle （UAV） in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, free space is represented by free voxels, which have enough space margin for the UAV to pass through. A bounding box array is created in the whole 3D space to evaluate the free voxel connectivity. The probabilistic roadmap method （PRM） is improved by random sampling in the bounding box array to ensure a more efficient distribution of roadmap nodes in 3D space. According to the connectivity evaluation, the roadmap is used to plan a feasible path by using A＊ algorithm. Experimental results indicate that the proposed algorithm is valid in complex 3D environments.
基金financially supported by the Cultivation of Scientific Research Ability of Young Talents of Shanghai Jiao Tong University(Grant No.19X100040072)the Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education(Grant No.MIES-2020-07)。
文摘In recent decades,path planning for unmanned surface vehicles(USVs)in complex environments,such as harbours and coastlines,has become an important concern.The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with multiple dynamic obstacles.In this study,we developed a novel path planning method based on the D^(*) lite algorithm for real-time path planning of USVs in complex environments.The proposed method has the following advantages:(1)the computational time for replanning is reduced significantly owing to the use of an incremental algorithm and a new method for modelling dynamic obstacles;(2)a constrained artificial potential field method is employed to enhance the safety of the planned paths;and(3)the method is practical in terms of vehicle performance.The performance of the proposed method was evaluated through simulations and compared with those of existing algorithms.The simulation results confirmed the efficiency of the method for real-time path planning of USVs in complex environments.
基金Project supported by the National Natural Science Foundation of China(Nos.11872233,11727804,and 11472163)the National Key Basic Research Project of China(No.2014CB046203)the Innovation Program of Shanghai Municipal Education Commission(No.2017-01-07-00-09-E00019)。
文摘Studying and analyzing the dynamic behavior of offshore wind turbines are of great importance to ensure the safety and improve the efficiency of such expensive equipments.In this work,a tapered beam model is proposed to investigate the dynamic response of an offshore wind turbine tower on the monopile foundation assembled with rotating blades in the complex ocean environment.Several environment factors like wind,wave,current,and soil resistance are taken into account.The proposed model is ana-lytically solved with the Galerkin method.Based on the numerical results,the effects of various structure parameters including the taper angle,the height and thickness of the tower,the depth,and the diameter and the cement filler of the monopile on the funda-mental natural frequency of the wind turbine tower system are investigated in detail.It is found that the fundamental natural frequency decreases with the increase in the taper angle and the height and thickness of the tower,and increases with the increase in the diameter of the monopile.Moreover,filling cement into the monopile can effectively im-prove the fundamental natural frequency of the wind turbine tower system,but there is a critical value of the amount of cement maximizing the property of the monopile.This research may be helpful in the design and safety evaluation of offshore wind turbines.
基金the National Natural Science Foundation of China(10402033,10772144)
文摘In virtue of effect of N-S intensive ground stress and mining disturbance to +579E2EB_(1+2) mining site at Weihuliang Mine,the dip angle and section height is 65° and 52 m,respectively,the collapses happed frequently during mining.Firstly,mining condi- tions,spatial structure and parameters were investigated.Then physical simulation and dynamic numerical tracing and elaborate simulation relating roof and top-coal were ap- plied based on 2D-Block Program and quantitative regularity of stress at variable depths had been estimated.Furthermore,it was manifested that effective measures,i.e.,fast mining,control symmetrical top-coal-caving at dip and strike directions,optimizing ventila- tion system,active-stereo preventing gas were performed successfully in mining practice. Ultimately,the derived dynamic hazard were prevented so as to safety mining.
文摘With the increasing global demand for renewable energy,the application of photovoltaic power generation in mountainous areas is gradually increasing.However,the complex wind environment in mountainous areas poses severe challenges to the design and optimization of solar photovoltaic brackets.Traditional design methods are difficult to cope with the changeable wind speed and direction in mountainous areas,resulting in structural instability or material waste.Researchers have identified the key factors affecting wind response through parametric research and dynamic wind response analysis,so as to optimize the brackets design and improve its adaptability and stability in complex wind environments.In this paper,the complexity of wind speed,wind direction and turbulence characteristics in mountainous areas and their influence on brackets design are explored.Through static and dynamic wind load analysis,the geometrical shape and material selection of the bracket are optimized to enhance its wind resistance.The application of multi-objective optimization model and intelligent optimization algorithm provides an effective solution for the design of solar photovoltaic brackets,ensuring their safety and reliability in complex wind environments.
基金Chongqing Municipal Education Commission Science and Technology Research Project(Project No.KJQN202301910).
文摘Recycled aggregate concrete refers to a new type of concrete material made by processing waste concrete materials through grading,crushing,and cleaning,and then mixing them with cement,water,and other materials in a certain gradation or proportion.This type of concrete is highly suitable for modern construction waste disposal and reuse and has been widely used in various construction projects.It can also be used as an environmentally friendly permeable brick material to promote the development of modern green buildings.However,practical applications have found that compared to ordinary concrete,the durability of this type of concrete is more susceptible to high-temperature and complex environments.Based on this,this paper conducts theoretical research on its durability in high-temperature and complex environments,including the current research status,existing problems,and application prospects of recycled aggregate concrete’s durability in such environments.It is hoped that this analysis can provide some reference for studying the influence of high-temperature and complex environments on recycled aggregate concrete and its subsequent application strategies.
文摘Shield tunneling is an important link in the current subway construction. It has a high level of automation, which greatly improves the construction efficiency. At the same time, subway shield construction can also reduce the impact of urban ground traffic, so it has been widely used in the construction of subway projects. In this paper, the technology and construction technology of shield tunneling under complex environment are studied and analyzed for reference.
文摘With China and Africa having worked hand in hand for mutual benefits for a long time,China-Africa economic and trade cooperation has developed steadily,achieving significant progress in many fields.However,at the same time,the environment in which China-Africa economic and trade cooperation operates is becoming increasingly complex.Risks and challenges from different levels are worth noticing.
基金funded by National Natural Science Foundation of China(61741303)the Foundation Project of Guangxi Key Laboratory of Spatial Information andMapping(No.21-238-21-16).
文摘Detecting individuals wearing safety helmets in complex environments faces several challenges.These factors include limited detection accuracy and frequent missed or false detections.Additionally,existing algorithms often have excessive parameter counts,complex network structures,and high computational demands.These challenges make it difficult to deploy such models efficiently on resource-constrained devices like embedded systems.Aiming at this problem,this research proposes an optimized and lightweight solution called FGP-YOLOv8,an improved version of YOLOv8n.The YOLOv8 backbone network is replaced with the FasterNet model to reduce parameters and computational demands while local convolution layers are added.This modification minimizes computational costs with only a minor impact on accuracy.A new GSTA(GSConv-Triplet Attention)module is introduced to enhance feature fusion and reduce computational complexity.This is achieved using attention weights generated from dimensional interactions within the feature map.Additionally,the ParNet-C2f module replaces the original C2f(CSP Bottleneck with 2 Convolutions)module,improving feature extraction for safety helmets of various shapes and sizes.The CIoU(Complete-IoU)is replaced with the WIoU(Wise-IoU)to boost performance further,enhancing detection accuracy and generalization capabilities.Experimental results validate the improvements.The proposedmodel reduces the parameter count by 19.9% and the computational load by 18.5%.At the same time,mAP(mean average precision)increases by 2.3%,and precision improves by 1.2%.These results demonstrate the model’s robust performance in detecting safety helmets across diverse environments.
基金funded by the National Defense Science and Technology Innovation project,grant number ZZKY20223103the Basic Frontier InnovationProject at the Engineering University of PAP,grant number WJY202429+2 种基金the Basic Frontier lnnovation Project at the Engineering University of PAP,grant number WJY202408the Graduate Student Funding Priority Project,grant number JYWJ2024B006Key project of National Social Science Foundation,grant number 2023-SKJJ-A-116.
文摘This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization andmulti-strategy fusion(BFDBO),which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments.Initially,a collaborative planning cost function for the multi-UAV system is formulated,thereby converting the trajectory planning challenge into an optimization problem.Building on the foundational dung beetle optimization(DBO)algorithm,BFDBO incorporates three significant innovations:a boundary reflection mechanism,an adaptive mixed exploration strategy,and a dynamic multi-scale mutation strategy.These enhancements are intended to optimize the equilibrium between local exploration and global exploitation,facilitating the discovery of globally optimal trajectories thatminimize the cost function.Numerical simulations utilizing the CEC2022 benchmark function indicate that all three enhancements of BFDBOpositively influence its performance,resulting in accelerated convergence and improved optimization accuracy relative to leading optimization algorithms.In two battlefield scenarios of varying complexities,BFDBO achieved a minimum of a 39% reduction in total trajectory planning costs when compared to DBO and three other highperformance variants,while also demonstrating superior average runtime.This evidence underscores the effectiveness and applicability of BFDBO in practical,real-world contexts.
基金supported in part by STI 2030-Major Projects(2022ZD0209200)in part by National Natural Science Foundation of China(62374099)+2 种基金in part by Beijing Natural Science Foundation−Xiaomi Innovation Joint Fund(L233009)Beijing Natural Science Foundation(L248104)in part by Independent Research Program of School of Integrated Circuits,Tsinghua University,in part by Tsinghua University Fuzhou Data Technology Joint Research Institute.
文摘In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.
基金supported by Gansu Provincial Science and Technology Program Project(No.23JRRA868)Lanzhou Municipal Talent Innovation and Entrepreneurship Project(No.2019-RC-103)。
文摘In response to the problems of low sampling efficiency,strong randomness of sampling points,and the tortuous shape of the planned path in the traditional rapidly-exploring random tree(RRT)algorithm and bidirectional RRT algorithm used for unmanned aerial vehicle(UAV)path planning in complex environments,an improved bidirectional RRT algorithm was proposed.The algorithm firstly adopted a goal-oriented strategy to guide the sampling points towards the target point,and then the artificial potential field acted on the random tree nodes to avoid collision with obstacles and reduced the length of the search path,and the random tree node growth also combined the UAV’s own flight constraints,and by combining the triangulation method to remove the redundant node strategy and the third-order B-spline curve for the smoothing of the trajectory,the planned path was better.The planned paths were more optimized.Finally,the simulation experiments in complex and dynamic environments showed that the algorithm effectively improved the speed of trajectory planning and shortened the length of the trajectory,and could generate a safe,smooth and fast trajectory in complex environments,which could be applied to online trajectory planning.
基金funded by the Jilin City Science and Technology Innovation Development Plan Project(No.20240302014)the Jilin Provincial Department of Educa-tion Science and Technology Research Project(No.JJKH 20250879KJ)the Jilin Province Science and Tech-nology Development Plan Project(No.YDZJ202401640 ZYTS).
文摘Underwater imaging is frequently influenced by factors such as illumination,scattering,and refraction,which can result in low image contrast and blurriness.Moreover,the presence of numerous small,overlapping targets reduces detection accuracy.To address these challenges,first,green channel images are preprocessed to rectify color bias while improving contrast and clarity.Se-cond,the YOLO-DBS network that employs deformable convolution is proposed to enhance feature learning from underwater blurry images.The ECA attention mechanism is also introduced to strengthen feature focus.Moreover,a bidirectional feature pyramid net-work is utilized for efficient multilayer feature fusion while removing nodes that contribute minimally to detection performance.In addition,the SIoU loss function that considers factors such as angular error and distance deviation is incorporated into the network.Validation on the RUOD dataset demonstrates that YOLO-DBS achieves approximately 3.1%improvement in mAP@0.5 compared with YOLOv8n and surpasses YOLOv9-tiny by 1.3%.YOLO-DBS reduces parameter count by 32%relative to YOLOv8n,thereby demonstrating superior performance in real-time detection on underwater observation platforms.
文摘Mid-Year Marine Economy Report Developing the marine economy and building China into a maritime powerhouse are of great significance for China’s socio-economic sustainable development,as well as for advancing its modernization drive.Recently released data from the Ministry of Natural Resources shows that during the first half of 2025,despite a complex and volatile external environment,China’s marine economy withstood the pressure and maintained a steady and positive development trend.
基金supported in part by the National Natural Science Foundation of China(62222301, 62073085, 62073158, 61890930-5, 62021003)the National Key Research and Development Program of China (2021ZD0112302, 2021ZD0112301, 2018YFC1900800-5)Beijing Natural Science Foundation (JQ19013)。
文摘Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
基金supported by the National Natural Science Foundation of China(61102158)the China Postdoctoral Science Foundation(2011M500667)
文摘A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching- CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.
