The rapid pace of urban development has resulted in the widespread presence of construction equipment andincreasingly complex conditions in transmission corridors. These conditions pose a serious threat to the safeope...The rapid pace of urban development has resulted in the widespread presence of construction equipment andincreasingly complex conditions in transmission corridors. These conditions pose a serious threat to the safeoperation of the power grid.Machine vision technology, particularly object recognition technology, has beenwidelyemployed to identify foreign objects in transmission line images. Despite its wide application, the technique faceslimitations due to the complex environmental background and other auxiliary factors. To address these challenges,this study introduces an improved YOLOv8n. The traditional stepwise convolution and pooling layers are replacedwith a spatial-depth convolution (SPD-Conv) module, aiming to improve the algorithm’s efficacy in recognizinglow-resolution and small-size objects. The algorithm’s feature extraction network is improved by using a LargeSelective Kernel (LSK) attention mechanism, which enhances the ability to extract relevant features. Additionally,the SIoU Loss function is used instead of the Complete Intersection over Union (CIoU) Loss to facilitate fasterconvergence of the algorithm. Through experimental verification, the improved YOLOv8n model achieves adetection accuracy of 88.8% on the test set. The recognition accuracy of cranes is improved by 2.9%, which isa significant enhancement compared to the unimproved algorithm. This improvement effectively enhances theaccuracy of recognizing foreign objects on transmission lines and proves the effectiveness of the new algorithm.展开更多
Three-dimensional printing technologies exhibit tremendous potential in the advancing fields of tissue engineering and regenerative medicine due to the precise spatial control over depositing the biomaterial.Despite t...Three-dimensional printing technologies exhibit tremendous potential in the advancing fields of tissue engineering and regenerative medicine due to the precise spatial control over depositing the biomaterial.Despite their widespread utilization and numerous advantages,the development of suitable novel biomaterials for extrusion-based 3D printing of scaffolds that support cell attachment,proliferation,and vascularization remains a challenge.Multi-material composite hydrogels present incredible potential in this field.Thus,in this work,a multi-material composite hydrogel with a promising formulation of chitosan/gelatin functionalized with egg white was developed,which provides good printability and shape fidelity.In addition,a series of comparative analyses of different crosslinking agents and processes based on tripolyphosphate(TPP),genipin(GP),and glutaraldehyde(GTA)were investigated and compared to select the ideal crosslinking strategy to enhance the physicochemical and biological properties of the fabricated scaffolds.All of the results indicate that the composite hydrogel and the resulting scaffolds utilizing TPP crosslinking have great potential in tissue engineering,especially for supporting neo-vessel growth into the scaffold and promoting angiogenesis within engineered tissues.展开更多
The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,th...The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters.To solve the above problem,the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms.Firstly,an integrated energy system consisting of the photovoltaic,wind turbine,electrolysis cell,hydrogen storage tank,and energy storage is established.Meanwhile,the minimum economic cost,the maximum wind and PV power consumption rate,and the minimum load shortage rate are considered to be the objective functions.Then,a hybrid method combined the particle swarm combined with non-dominated sorting genetic algorithms-II is proposed to solve the optimal allocation problem.According to the optimal result,the economic cost is 6.3 million RMB,and the load shortage rate is 9.83%.Finally,four comparative experiments are conducted to verify the superiority-seeking ability of the proposed method.The comparative results indicate that the proposed method possesses a strongermerit-seeking ability,resulting in a solution satisfaction rate of 87.37%,which is higher than that of the unimproved non-dominated sorting genetic algorithms-II.展开更多
In this paper, the models describing the charge transfer between two sand particles due to collisions are reviewed. By comparing the experimental results and the calculated results by the models carried on an individu...In this paper, the models describing the charge transfer between two sand particles due to collisions are reviewed. By comparing the experimental results and the calculated results by the models carried on an individual particle due to a single collision, it indicates the Mosaic model is more reasonable to describe the collision charging mechanism. The Mosaic model cannot only describe the dependence of the collision charges on the relative collision speed and the particle size, but also reveal the relationship between the collision charges with the environmental temperature, the relative humidity and the material parameters, e.g., the absorption energy. Based on the Mosaic model, the model to describe the charges transfer due to multiple collisions is also developed, which can be used to calculate the charges carried by sand particles due to multiple collisions in the wind blown sand flux.展开更多
基金the Natural Science Foundation of Shandong Province(ZR2021QE289)State Key Laboratory of Electrical Insulation and Power Equipment(EIPE22201).
文摘The rapid pace of urban development has resulted in the widespread presence of construction equipment andincreasingly complex conditions in transmission corridors. These conditions pose a serious threat to the safeoperation of the power grid.Machine vision technology, particularly object recognition technology, has beenwidelyemployed to identify foreign objects in transmission line images. Despite its wide application, the technique faceslimitations due to the complex environmental background and other auxiliary factors. To address these challenges,this study introduces an improved YOLOv8n. The traditional stepwise convolution and pooling layers are replacedwith a spatial-depth convolution (SPD-Conv) module, aiming to improve the algorithm’s efficacy in recognizinglow-resolution and small-size objects. The algorithm’s feature extraction network is improved by using a LargeSelective Kernel (LSK) attention mechanism, which enhances the ability to extract relevant features. Additionally,the SIoU Loss function is used instead of the Complete Intersection over Union (CIoU) Loss to facilitate fasterconvergence of the algorithm. Through experimental verification, the improved YOLOv8n model achieves adetection accuracy of 88.8% on the test set. The recognition accuracy of cranes is improved by 2.9%, which isa significant enhancement compared to the unimproved algorithm. This improvement effectively enhances theaccuracy of recognizing foreign objects on transmission lines and proves the effectiveness of the new algorithm.
基金The authors acknowledge the funding support from the National Natural Science Foundation of China(Nos.52175474 and 51775324)the China Scholarship Council(No.202006890054).
文摘Three-dimensional printing technologies exhibit tremendous potential in the advancing fields of tissue engineering and regenerative medicine due to the precise spatial control over depositing the biomaterial.Despite their widespread utilization and numerous advantages,the development of suitable novel biomaterials for extrusion-based 3D printing of scaffolds that support cell attachment,proliferation,and vascularization remains a challenge.Multi-material composite hydrogels present incredible potential in this field.Thus,in this work,a multi-material composite hydrogel with a promising formulation of chitosan/gelatin functionalized with egg white was developed,which provides good printability and shape fidelity.In addition,a series of comparative analyses of different crosslinking agents and processes based on tripolyphosphate(TPP),genipin(GP),and glutaraldehyde(GTA)were investigated and compared to select the ideal crosslinking strategy to enhance the physicochemical and biological properties of the fabricated scaffolds.All of the results indicate that the composite hydrogel and the resulting scaffolds utilizing TPP crosslinking have great potential in tissue engineering,especially for supporting neo-vessel growth into the scaffold and promoting angiogenesis within engineered tissues.
基金supported in part by the Natural Science Foundation of Shandong Province(ZR2021QE289)in part by State Key Laboratory of Electrical Insulation and Power Equipment(EIPE22201).
文摘The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters.To solve the above problem,the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms.Firstly,an integrated energy system consisting of the photovoltaic,wind turbine,electrolysis cell,hydrogen storage tank,and energy storage is established.Meanwhile,the minimum economic cost,the maximum wind and PV power consumption rate,and the minimum load shortage rate are considered to be the objective functions.Then,a hybrid method combined the particle swarm combined with non-dominated sorting genetic algorithms-II is proposed to solve the optimal allocation problem.According to the optimal result,the economic cost is 6.3 million RMB,and the load shortage rate is 9.83%.Finally,four comparative experiments are conducted to verify the superiority-seeking ability of the proposed method.The comparative results indicate that the proposed method possesses a strongermerit-seeking ability,resulting in a solution satisfaction rate of 87.37%,which is higher than that of the unimproved non-dominated sorting genetic algorithms-II.
基金National Natural Science Foundation of China(Grants 51435008,11472122 and 11272139)。
文摘In this paper, the models describing the charge transfer between two sand particles due to collisions are reviewed. By comparing the experimental results and the calculated results by the models carried on an individual particle due to a single collision, it indicates the Mosaic model is more reasonable to describe the collision charging mechanism. The Mosaic model cannot only describe the dependence of the collision charges on the relative collision speed and the particle size, but also reveal the relationship between the collision charges with the environmental temperature, the relative humidity and the material parameters, e.g., the absorption energy. Based on the Mosaic model, the model to describe the charges transfer due to multiple collisions is also developed, which can be used to calculate the charges carried by sand particles due to multiple collisions in the wind blown sand flux.