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
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
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
The Internet of Things(IoT)has become an integral part of various industries,from smart cities to healthcare,driving the need for energy-efficient and stable devices,especially in complex and unpredictable environment...The Internet of Things(IoT)has become an integral part of various industries,from smart cities to healthcare,driving the need for energy-efficient and stable devices,especially in complex and unpredictable environments.This research investigates the optimization of energy consumption and the enhancement of stability in IoT devices operating in such environments.The study addresses key challenges,including resource constraints,fluctuating environmental conditions,and the increasing complexity of IoT networks.It explores various energy optimization techniques,such as low-power communication protocols,edge and cloud computing,and machine learning models,that help reduce energy usage while maintaining performance.Furthermore,it examines stability enhancement strategies,including fault-tolerant mechanisms,resilient network architectures,and real-time monitoring and adaptive control,that ensure the continuous and reliable operation of IoT devices despite external disruptions.The findings of this research contribute to the development of next-generation IoT systems that are both energy-efficient and resilient,thereby promoting sustainable deployment in real-world applications.展开更多
Complex environments featuring variable lighting and backgrounds similar in color to the target objects present challenges for the rapid and accurate detection of tobacco leaves,which is critical for the development o...Complex environments featuring variable lighting and backgrounds similar in color to the target objects present challenges for the rapid and accurate detection of tobacco leaves,which is critical for the development of automated tobacco leaf harvesting robots.This study introduces a depth filtering approach to filter out complex regions based on distance information,thereby simplifying the detection task,and proposes a lightweight detection method based on an enhanced YOLOv5s model.Initially,the YOLOv5s backbone network is substituted with a more lightweight MobileNetV2 to reduce the model size.Subsequently,sparse model training combined with the scaling factor distribution rules of batch normalization layers is utilized to identify and eliminate inconsequential neural network channels.Finally,fine-tuning and knowledge distillation techniques are employed to achieve a model accuracy close to the YOLOv5s baseline.Experimental results indicate that the depth filtering method can improve the model’s precision,recall,and mean Average Precision(mAP)by 11.2%,29.6%,and 17.1%,respectively.The optimized lightweight model achieves a precision of 91.1%,a recall of 90.8%,and an mAP of 91.6%,with a memory footprint of only 1.4MB.It delivers a detection frame rate of 112 fps on desktop computers and 21 fps on mobile devices,which is approximately 3.5 and 4 times faster,respectively,compared to the baseline YOLOv5s tobacco leaf detection model.The precision,recall,and mAP experience a marginal decrease of 3.8,1.6,and 2.8 percentage points,respectively,while the memory consumption is merely 10%of the pre-optimization amount.In summary,the proposed method enables the accurate detection of tobacco leaves against near-color backgrounds.Simultaneously,it achieves effective lightweighting of the model without compromising its performance,thereby providing technical support for deploying tobacco leaf detection on mobile platforms.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
To realize the visual navigation of agricultural robots in the complex environment of orchards,this study proposed a method for fruit tree recognition and navigation based on YOLOv5.The YOLOv5s model was selected and ...To realize the visual navigation of agricultural robots in the complex environment of orchards,this study proposed a method for fruit tree recognition and navigation based on YOLOv5.The YOLOv5s model was selected and trained to identify the trunks of the left and right rows of fruit trees;the quadratic curve was fitted to the bottom center of the fruit tree recognition box,and the identified fruit trees were divided into left and right columns by using the extreme value point of the quadratic curve to obtain the left and right rows of fruit trees;the straight-line equation of the left and right fruit tree rows was further solved,the median line of the two straight lines was taken as the expected navigation path of the robot,and the path tracing navigation experiment was carried out by using the improved LQR control algorithm.The experimental results show that under the guidance of the machine vision system and guided by the improved LQR control algorithm,the lateral error and heading error can converge quickly to the desired navigation path in the four initial states of[0 m,−0.34 rad],[0.10 m,0.34 rad],[0.15 m,0 rad]and[0.20 m,−0.34 rad].When the initial speed was 0.5 m/s,the average lateral error was 0.059 m and the average heading error was 0.2787 rad for the navigation trials in the four different initial states.Its average driving was 5.3 m into the steady state,the average value of steady state lateral error was 0.0102 m,the average value of steady state heading error was 0.0253 rad,and the average relative error of the robot driving along the desired navigation path was 4.6%.The results indicate that the navigation algorithm proposed in this study has good robustness,meets the operational requirements of robot autonomous navigation in orchard environment,and improves the reliability of robot driving in orchard.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
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 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
This study is the first of a series of a project on the development and implementation of environmental protection policies, before<span style="font-family:Verdana;">,</span><span style="...This study is the first of a series of a project on the development and implementation of environmental protection policies, before<span style="font-family:Verdana;">,</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> during and after the construction of the </span><i><span style="font-family:Verdana;">Kribi</span></i> <i><span style="font-family:Verdana;">Industrial</span></i> <i><span style="font-family:Verdana;">and</span></i> <i><span style="font-family:Verdana;">Urban</span></i> <i><span style="font-family:Verdana;">Port</span></i> <i><span style="font-family:Verdana;">Complex</span></i><span style="font-family:Verdana;"> (</span><i><span style="font-family:Verdana;">KIPC</span></i><span style="font-family:Verdana;">). The results will equip the State and scientific structures concerned with the protection of people, water resources and the environment as a whole. This includes reference data on the state of marine pollution in the region dating from the end of realization of the first phase of KIPC known as </span><i><span style="font-family:Verdana;">Kribi</span></i> <i><span style="font-family:Verdana;">Deep-Water</span></i> <i><span style="font-family:Verdana;">Harbor</span></i><span style="font-family:Verdana;"> (</span><i><span style="font-family:Verdana;">KDWH</span></i><span style="font-family:Verdana;">). Accordingly, the aim of this work is to assess the current state of KIPC and its surrounding by quantifying the preliminary parameters of suspended matter (SM);to analyze the physical and chemical parameters, chemical pollution indicators for anions and major cations and organic pollution indicators of four water samples taken from four different sites in the project area by filtration and weighing, pH meter, turbid meter, titration, colorimetry and titrimetric methods. The analysis of these samples and these parameters provide</span></span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> results which are slightly similar to international standards. This suggests that the environment remains relatively healthy. Hence, continuous management and monitoring of the parameters and pollution factors is strongly recommended.</span>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 complexity we take into account when dealing with complex issues and the way we deal with that complexity is not given or self-evident, it is framed and negotiated. Based on two environmental health decision suppo...The complexity we take into account when dealing with complex issues and the way we deal with that complexity is not given or self-evident, it is framed and negotiated. Based on two environmental health decision support case studies we address a set of key methodological choices, crucial in shaping the multi-criteria decision support and illuminate how they followed from transdisciplinary collaboration and negotiation: diversity tolerance, dealing with uncertainty and difference of opinion, weight of information and the epistemological divide between traditional closed and alternative open paradigms. The case studies exemplify the growing conviction amongst methodologists that, especially regarding complex issues, best methods do not exist as such: methods are chosen and tailored in practice and the quality to a large extent is dependent on the process in which methodological development is embedded. We hope to contribute to making explicit the importance of methodological decision making regarding environmental health complexity.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
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
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The Internet of Things(IoT)has become an integral part of various industries,from smart cities to healthcare,driving the need for energy-efficient and stable devices,especially in complex and unpredictable environments.This research investigates the optimization of energy consumption and the enhancement of stability in IoT devices operating in such environments.The study addresses key challenges,including resource constraints,fluctuating environmental conditions,and the increasing complexity of IoT networks.It explores various energy optimization techniques,such as low-power communication protocols,edge and cloud computing,and machine learning models,that help reduce energy usage while maintaining performance.Furthermore,it examines stability enhancement strategies,including fault-tolerant mechanisms,resilient network architectures,and real-time monitoring and adaptive control,that ensure the continuous and reliable operation of IoT devices despite external disruptions.The findings of this research contribute to the development of next-generation IoT systems that are both energy-efficient and resilient,thereby promoting sustainable deployment in real-world applications.
基金supported by the Horizontal Research Project of China Agricultural University(Project No.202405410711069).
文摘Complex environments featuring variable lighting and backgrounds similar in color to the target objects present challenges for the rapid and accurate detection of tobacco leaves,which is critical for the development of automated tobacco leaf harvesting robots.This study introduces a depth filtering approach to filter out complex regions based on distance information,thereby simplifying the detection task,and proposes a lightweight detection method based on an enhanced YOLOv5s model.Initially,the YOLOv5s backbone network is substituted with a more lightweight MobileNetV2 to reduce the model size.Subsequently,sparse model training combined with the scaling factor distribution rules of batch normalization layers is utilized to identify and eliminate inconsequential neural network channels.Finally,fine-tuning and knowledge distillation techniques are employed to achieve a model accuracy close to the YOLOv5s baseline.Experimental results indicate that the depth filtering method can improve the model’s precision,recall,and mean Average Precision(mAP)by 11.2%,29.6%,and 17.1%,respectively.The optimized lightweight model achieves a precision of 91.1%,a recall of 90.8%,and an mAP of 91.6%,with a memory footprint of only 1.4MB.It delivers a detection frame rate of 112 fps on desktop computers and 21 fps on mobile devices,which is approximately 3.5 and 4 times faster,respectively,compared to the baseline YOLOv5s tobacco leaf detection model.The precision,recall,and mAP experience a marginal decrease of 3.8,1.6,and 2.8 percentage points,respectively,while the memory consumption is merely 10%of the pre-optimization amount.In summary,the proposed method enables the accurate detection of tobacco leaves against near-color backgrounds.Simultaneously,it achieves effective lightweighting of the model without compromising its performance,thereby providing technical support for deploying tobacco leaf detection on mobile platforms.
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funded by the National Key Research and Development Program of China Project(Grant No.2021YFD2000700)the National Natural Science Funds for Young Scholars of China(Grant No.51905154)the Luoyang Public Welfare Special Project(Grant No.2302031A).
文摘To realize the visual navigation of agricultural robots in the complex environment of orchards,this study proposed a method for fruit tree recognition and navigation based on YOLOv5.The YOLOv5s model was selected and trained to identify the trunks of the left and right rows of fruit trees;the quadratic curve was fitted to the bottom center of the fruit tree recognition box,and the identified fruit trees were divided into left and right columns by using the extreme value point of the quadratic curve to obtain the left and right rows of fruit trees;the straight-line equation of the left and right fruit tree rows was further solved,the median line of the two straight lines was taken as the expected navigation path of the robot,and the path tracing navigation experiment was carried out by using the improved LQR control algorithm.The experimental results show that under the guidance of the machine vision system and guided by the improved LQR control algorithm,the lateral error and heading error can converge quickly to the desired navigation path in the four initial states of[0 m,−0.34 rad],[0.10 m,0.34 rad],[0.15 m,0 rad]and[0.20 m,−0.34 rad].When the initial speed was 0.5 m/s,the average lateral error was 0.059 m and the average heading error was 0.2787 rad for the navigation trials in the four different initial states.Its average driving was 5.3 m into the steady state,the average value of steady state lateral error was 0.0102 m,the average value of steady state heading error was 0.0253 rad,and the average relative error of the robot driving along the desired navigation path was 4.6%.The results indicate that the navigation algorithm proposed in this study has good robustness,meets the operational requirements of robot autonomous navigation in orchard environment,and improves the reliability of robot driving in orchard.
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 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.
文摘This study is the first of a series of a project on the development and implementation of environmental protection policies, before<span style="font-family:Verdana;">,</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> during and after the construction of the </span><i><span style="font-family:Verdana;">Kribi</span></i> <i><span style="font-family:Verdana;">Industrial</span></i> <i><span style="font-family:Verdana;">and</span></i> <i><span style="font-family:Verdana;">Urban</span></i> <i><span style="font-family:Verdana;">Port</span></i> <i><span style="font-family:Verdana;">Complex</span></i><span style="font-family:Verdana;"> (</span><i><span style="font-family:Verdana;">KIPC</span></i><span style="font-family:Verdana;">). The results will equip the State and scientific structures concerned with the protection of people, water resources and the environment as a whole. This includes reference data on the state of marine pollution in the region dating from the end of realization of the first phase of KIPC known as </span><i><span style="font-family:Verdana;">Kribi</span></i> <i><span style="font-family:Verdana;">Deep-Water</span></i> <i><span style="font-family:Verdana;">Harbor</span></i><span style="font-family:Verdana;"> (</span><i><span style="font-family:Verdana;">KDWH</span></i><span style="font-family:Verdana;">). Accordingly, the aim of this work is to assess the current state of KIPC and its surrounding by quantifying the preliminary parameters of suspended matter (SM);to analyze the physical and chemical parameters, chemical pollution indicators for anions and major cations and organic pollution indicators of four water samples taken from four different sites in the project area by filtration and weighing, pH meter, turbid meter, titration, colorimetry and titrimetric methods. The analysis of these samples and these parameters provide</span></span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> results which are slightly similar to international standards. This suggests that the environment remains relatively healthy. Hence, continuous management and monitoring of the parameters and pollution factors is strongly recommended.</span>
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 complexity we take into account when dealing with complex issues and the way we deal with that complexity is not given or self-evident, it is framed and negotiated. Based on two environmental health decision support case studies we address a set of key methodological choices, crucial in shaping the multi-criteria decision support and illuminate how they followed from transdisciplinary collaboration and negotiation: diversity tolerance, dealing with uncertainty and difference of opinion, weight of information and the epistemological divide between traditional closed and alternative open paradigms. The case studies exemplify the growing conviction amongst methodologists that, especially regarding complex issues, best methods do not exist as such: methods are chosen and tailored in practice and the quality to a large extent is dependent on the process in which methodological development is embedded. We hope to contribute to making explicit the importance of methodological decision making regarding environmental health complexity.
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 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.
