In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often fa...In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.展开更多
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
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
The year 2025 witnessed the profound evolution of the international landscape,characterized by intensified major-power rivalry,protracted geopolitical conflicts,erosion of multilateral mechanisms,and increasingly obso...The year 2025 witnessed the profound evolution of the international landscape,characterized by intensified major-power rivalry,protracted geopolitical conflicts,erosion of multilateral mechanisms,and increasingly obsolete international rules.The old order is dying,and the new one is yet to be born.The future trajectory of the world hinges largely on whether nations,particularly major powers,can manage differences and seek cooperation through effective communication amidst the complex and volatile environment.展开更多
The continuous decrease in global fishery resources has increased the importance of precise and efficient underwater fish monitoring technology.First,this study proposes an improved underwater target detection framewo...The continuous decrease in global fishery resources has increased the importance of precise and efficient underwater fish monitoring technology.First,this study proposes an improved underwater target detection framework based on YOLOv8,with the aim of enhancing detection accuracy and the ability to recognize multi-scale targets in blurry and complex underwater environments.A streamlined Vision Transformer(ViT)model is used as the feature extraction backbone,which retains global self-attention feature extraction and accelerates training efficiency.In addition,a detection head named Dynamic Head(DyHead)is introduced,which enhances the efficiency of processing various target sizes through multi-scale feature fusion and adaptive attention modules.Furthermore,a dynamic loss function adjustment method called SlideLoss is employed.This method utilizes sliding window technology to adaptively adjust parameters,which optimizes the detection of challenging targets.The experimental results on the RUOD dataset show that the proposed improved model not only significantly enhances the accuracy of target detection but also increases the efficiency of target detection.展开更多
Geological prospecting and the identification of adverse geological features are essential in tunnel construction,providing critical information to ensure safety and guide engineering decisions.As tunnel projects exte...Geological prospecting and the identification of adverse geological features are essential in tunnel construction,providing critical information to ensure safety and guide engineering decisions.As tunnel projects extend into deeper and more mountainous terrains,engineers face increasingly complex geological conditions,including high water pressure,intense geo-stress,elevated geothermal gradients,and active fault zones.These conditions pose substantial risks such as high-pressure water inrush,largescale collapses,and tunnel boring machine(TBM)blockages.Addressing these challenges requires advanced detection technologies capable of long-distance,high-precision,and intelligent assessments of adverse geology.This paper presents a comprehensive review of recent advancements in tunnel geological ahead prospecting methods.It summarizes the fundamental principles,technical maturity,key challenges,development trends,and real-world applications of various detection techniques.Airborne and semi-airborne geophysical methods enable large-scale reconnaissance for initial surveys in complex terrain.Tunnel-and borehole-based approaches offer high-resolution detection during excavation,including seismic ahead prospecting(SAP),TBM rock-breaking source seismic methods,fulltime-domain tunnel induced polarization(TIP),borehole electrical resistivity,and ground penetrating radar(GPR).To address scenarios involving multiple,coexisting adverse geologies,intelligent inversion and geological identification methods have been developed based on multi-source data fusion and artificial intelligence(AI)techniques.Overall,these advances significantly improve detection range,resolution,and geological characterization capabilities.The methods demonstrate strong adaptability to complex environments and provide reliable subsurface information,supporting safer and more efficient tunnel construction.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
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
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
Currently,welding quality detection remains dependent on manual operation,while the increase in the span and intricacy of steel bridges has rendered the conventional method of detection insufficient to fulfill the eng...Currently,welding quality detection remains dependent on manual operation,while the increase in the span and intricacy of steel bridges has rendered the conventional method of detection insufficient to fulfill the engineering requirements.This paper presents a systematic study of welding quality detection of steel bridges based on fusion of point clouds and images in complex construction environments.(1)A welding detection system is developed that could filter out stray light and capture weld images.(2)This paper enhances the centerline extraction method in 3D reconstruction,which could effectively filter out noise interference and precisely reconstruct weld contours.The contour dimensions of both filler and cover welds are identified through feature point extraction,with an estimated detection error under 0.6%.(3)This paper optimizes the feature extraction of the Faster R-CNN network based on the appearance feature and detection need of welding defects,resulting in an improvement of 28.3 in mAP.Experimental results demonstrate that the proposed welding quality detection is both efficient and accurate,and is capable of meeting the requirements of actual steel bridge construction.展开更多
Various imaging techniques have been employed to detect suspicious objects and activities to help preservep eace and order.However,challenges such as illumination changes,occlusion,noise,and low-resolution imagerys ig...Various imaging techniques have been employed to detect suspicious objects and activities to help preservep eace and order.However,challenges such as illumination changes,occlusion,noise,and low-resolution imagerys ignificantly hinder the effectiveness of automated detection methods.To address these issues,machine learningt echniques have been applied,but they often struggle to detect the multiple activities simultaneously,leading to ambiguitya nd reduced accuracy.To mitigate these issues,the proposed methodology presented the YOLOv8 model for detectings uspicious objects and activities in images and video frames.To remove environmental noise,an adaptive sliding windowb ased bilateral filter is used to remove local and global noise from the noisy input images,then YOLOv8 model is trainedt o identify suspicious and non-suspicious objects and activities.The performance was evaluated on suspicious object and activity dataset collected from publicly available resources such as Roboflow.Performance was measured using mean average precision(mAP)and compared to existing state-of-the-art models.The proposed model achieved ana verage mAP of 74.5%,which represents approximately a 13% improvement over current leading methods.Therefore,t he study shows the efficacy of the proposed model in enhancing the surveillance system to handle environmental complexities.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
文摘In modern industrial production,foreign object detection in complex environments is crucial to ensure product quality and production safety.Detection systems based on deep-learning image processing algorithms often face challenges with handling high-resolution images and achieving accurate detection against complex backgrounds.To address these issues,this study employs the PatchCore unsupervised anomaly detection algorithm combined with data augmentation techniques to enhance the system’s generalization capability across varying lighting conditions,viewing angles,and object scales.The proposed method is evaluated in a complex industrial detection scenario involving the bogie of an electric multiple unit(EMU).A dataset consisting of complex backgrounds,diverse lighting conditions,and multiple viewing angles is constructed to validate the performance of the detection system in real industrial environments.Experimental results show that the proposed model achieves an average area under the receiver operating characteristic curve(AUROC)of 0.92 and an average F1 score of 0.85.Combined with data augmentation,the proposed model exhibits improvements in AUROC by 0.06 and F1 score by 0.03,demonstrating enhanced accuracy and robustness for foreign object detection in complex industrial settings.In addition,the effects of key factors on detection performance are systematically analyzed,providing practical guidance for parameter selection in real industrial applications.
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The year 2025 witnessed the profound evolution of the international landscape,characterized by intensified major-power rivalry,protracted geopolitical conflicts,erosion of multilateral mechanisms,and increasingly obsolete international rules.The old order is dying,and the new one is yet to be born.The future trajectory of the world hinges largely on whether nations,particularly major powers,can manage differences and seek cooperation through effective communication amidst the complex and volatile environment.
基金supported by the National Natural Science Foundation of China(No.52106080)the Jilin City Science and Technology Innovation Development Plan Project(No.20240302014)+2 种基金the Jilin Provincial Department of Education Science and Technology Research Project(No.JJKH20230135K)the Jilin Province Science and Technology Development Plan Project(No.YDZJ202401640ZYTS)the Northeast Electric Power University Teaching Reform Research Project(No.J2427)。
文摘The continuous decrease in global fishery resources has increased the importance of precise and efficient underwater fish monitoring technology.First,this study proposes an improved underwater target detection framework based on YOLOv8,with the aim of enhancing detection accuracy and the ability to recognize multi-scale targets in blurry and complex underwater environments.A streamlined Vision Transformer(ViT)model is used as the feature extraction backbone,which retains global self-attention feature extraction and accelerates training efficiency.In addition,a detection head named Dynamic Head(DyHead)is introduced,which enhances the efficiency of processing various target sizes through multi-scale feature fusion and adaptive attention modules.Furthermore,a dynamic loss function adjustment method called SlideLoss is employed.This method utilizes sliding window technology to adaptively adjust parameters,which optimizes the detection of challenging targets.The experimental results on the RUOD dataset show that the proposed improved model not only significantly enhances the accuracy of target detection but also increases the efficiency of target detection.
基金supported by the National Natural Science Foundation of China(Grant Nos.52021005,52325904,and 51991391)。
文摘Geological prospecting and the identification of adverse geological features are essential in tunnel construction,providing critical information to ensure safety and guide engineering decisions.As tunnel projects extend into deeper and more mountainous terrains,engineers face increasingly complex geological conditions,including high water pressure,intense geo-stress,elevated geothermal gradients,and active fault zones.These conditions pose substantial risks such as high-pressure water inrush,largescale collapses,and tunnel boring machine(TBM)blockages.Addressing these challenges requires advanced detection technologies capable of long-distance,high-precision,and intelligent assessments of adverse geology.This paper presents a comprehensive review of recent advancements in tunnel geological ahead prospecting methods.It summarizes the fundamental principles,technical maturity,key challenges,development trends,and real-world applications of various detection techniques.Airborne and semi-airborne geophysical methods enable large-scale reconnaissance for initial surveys in complex terrain.Tunnel-and borehole-based approaches offer high-resolution detection during excavation,including seismic ahead prospecting(SAP),TBM rock-breaking source seismic methods,fulltime-domain tunnel induced polarization(TIP),borehole electrical resistivity,and ground penetrating radar(GPR).To address scenarios involving multiple,coexisting adverse geologies,intelligent inversion and geological identification methods have been developed based on multi-source data fusion and artificial intelligence(AI)techniques.Overall,these advances significantly improve detection range,resolution,and geological characterization capabilities.The methods demonstrate strong adaptability to complex environments and provide reliable subsurface information,supporting safer and more efficient tunnel construction.
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.
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 by the National Natural Science Foundation of China(72071043)the National Key R&D Program of China(2021YFF0500904).
文摘Currently,welding quality detection remains dependent on manual operation,while the increase in the span and intricacy of steel bridges has rendered the conventional method of detection insufficient to fulfill the engineering requirements.This paper presents a systematic study of welding quality detection of steel bridges based on fusion of point clouds and images in complex construction environments.(1)A welding detection system is developed that could filter out stray light and capture weld images.(2)This paper enhances the centerline extraction method in 3D reconstruction,which could effectively filter out noise interference and precisely reconstruct weld contours.The contour dimensions of both filler and cover welds are identified through feature point extraction,with an estimated detection error under 0.6%.(3)This paper optimizes the feature extraction of the Faster R-CNN network based on the appearance feature and detection need of welding defects,resulting in an improvement of 28.3 in mAP.Experimental results demonstrate that the proposed welding quality detection is both efficient and accurate,and is capable of meeting the requirements of actual steel bridge construction.
文摘Various imaging techniques have been employed to detect suspicious objects and activities to help preservep eace and order.However,challenges such as illumination changes,occlusion,noise,and low-resolution imagerys ignificantly hinder the effectiveness of automated detection methods.To address these issues,machine learningt echniques have been applied,but they often struggle to detect the multiple activities simultaneously,leading to ambiguitya nd reduced accuracy.To mitigate these issues,the proposed methodology presented the YOLOv8 model for detectings uspicious objects and activities in images and video frames.To remove environmental noise,an adaptive sliding windowb ased bilateral filter is used to remove local and global noise from the noisy input images,then YOLOv8 model is trainedt o identify suspicious and non-suspicious objects and activities.The performance was evaluated on suspicious object and activity dataset collected from publicly available resources such as Roboflow.Performance was measured using mean average precision(mAP)and compared to existing state-of-the-art models.The proposed model achieved ana verage mAP of 74.5%,which represents approximately a 13% improvement over current leading methods.Therefore,t he study shows the efficacy of the proposed model in enhancing the surveillance system to handle environmental complexities.
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.
