Flow dynamics of binary particles are investigated to realize the monitoring and optimization of fluidized *** is a challenge to accurately classify the mass fraction of mixed biomass,considering the limitations of ex...
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Flow dynamics of binary particles are investigated to realize the monitoring and optimization of fluidized *** is a challenge to accurately classify the mass fraction of mixed biomass,considering the limitations of existing *** data collected from an electrostatic sensor array is *** correlation,empirical mode decomposition(EMD),Hilbert-Huang transform(HHT)are applied to process the *** a higher mass fraction of the wood sawdust,the segregation behavior occurs,and the high energy region of HHT spectrum ***,two data-driven models are trained based on a hybrid wavelet scattering transform and bidirectional long short-term memory(ST-BiLSTM)network and a EMD and BiLSTM(EMD-BiLSTM)network to identify the mass fractions of the mixed biomass,with accuracies of 92%and 99%.The electrostatic sensing combined with the EMD-BiLSTM model is effective to classify the mass fraction of the mixed biomass.
This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance ru...
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This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.
This paper focuses on the effective utilization of data augmentation techniques for 3Dlidar point clouds to enhance the performance of neural network *** point clouds,which represent spatial information through a coll...
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This paper focuses on the effective utilization of data augmentation techniques for 3Dlidar point clouds to enhance the performance of neural network *** point clouds,which represent spatial information through a collection of 3D coordinates,have found wide-ranging *** augmentation has emerged as a potent solution to the challenges posed by limited labeled data and the need to enhance model generalization *** of the existing research is devoted to crafting novel data augmentation methods specifically for 3D lidar point ***,there has been a lack of focus on making the most of the numerous existing augmentation *** this deficiency,this research investigates the possibility of combining two fundamental data augmentation *** paper introduces PolarMix andMix3D,two commonly employed augmentation techniques,and presents a new approach,named *** of using a fixed or predetermined combination of augmentation methods,RandomFusion randomly chooses one method from a pool of options for each instance or *** innovative data augmentation technique randomly augments each point in the point cloud with either PolarMix or *** crux of this strategy is the random choice between PolarMix and Mix3Dfor the augmentation of each point within the point cloud data *** results of the experiments conducted validate the efficacy of the RandomFusion strategy in enhancing the performance of neural network models for 3D lidar point cloud semantic segmentation *** is achieved without compromising computational *** examining the potential of merging different augmentation techniques,the research contributes significantly to a more comprehensive understanding of how to utilize existing augmentation methods for 3D lidar point *** data augmentation technique offers a simple yet effective method to leverage the diversity of augmentation techniques and boost the ro
Synthesizing garment dynamics according to body motions is a vital technique in computer ***-based simulation depends on an accurate model of the law of kinetics of cloth,which is time-consuming,hard to implement,and ...
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Synthesizing garment dynamics according to body motions is a vital technique in computer ***-based simulation depends on an accurate model of the law of kinetics of cloth,which is time-consuming,hard to implement,and complex to *** data-driven approaches either lack temporal consistency,or fail to handle garments that are different from body *** this paper,we present a motion-inspired real-time garment synthesis workflow that enables high-level control of garment *** a sequence of body motions,our workflow is able to gen-erate corresponding garment dynamics with both spatial and temporal *** that end,we develop a transformer-based garment synthesis network to learn the mapping from body motions to garment ***-level attention is employed to capture the dependency of garments and body ***,a post-processing procedure is further tak-en to perform penetration removal and ***,textured clothing animation that is collision-free and tempo-rally-consistent is *** quantitatively and qualitatively evaluated our proposed workflow from different *** experiments demonstrate that our network is able to deliver clothing dynamics which retain the wrinkles from the physics-based simulation,while running 1000 times ***,our workflow achieved superior synthesis perfor-mance compared with alternative *** stimulate further research in this direction,our code will be publicly available soon.
The distributed active power control problem is explored by equating wind turbines to multi-agent systems in this *** time delays and unknown topological relations are considered in the proposed *** the graph discover...
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The distributed active power control problem is explored by equating wind turbines to multi-agent systems in this *** time delays and unknown topological relations are considered in the proposed *** the graph discovery algorithm,the algebraic connectivity of the graph is found in ***,a proportional control protocol is proposed based on the adjustable margin of different wind ***,the proposed distributed controller not only handles the problem of supply-demand balance between the wind farm and power grid but also regulates the output power of individual wind turbines based on their ***,simulations are performed on the wind turbines to illustrate the validity of the proposed method.
Grasp detection is a visual recognition task where the robot makes use of its sensors to detect graspable objects in its *** the steady progress in robotic grasping,it is still difficult to achieve both real-time and ...
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Grasp detection is a visual recognition task where the robot makes use of its sensors to detect graspable objects in its *** the steady progress in robotic grasping,it is still difficult to achieve both real-time and high accuracy grasping *** this paper,we propose a real-time robotic grasp detection method,which can accurately predict potential grasp for parallel-plate robotic grippers using RGB *** work employs an end-to-end convolutional neural network which consists of a feature descriptor and a grasp *** for the first time,we add an attention mechanism to the grasp detection task,which enables the network to focus on grasp regions rather than ***,we present an angular label smoothing strategy in our grasp detection method to enhance the fault tolerance of the *** quantitatively and qualitatively evaluate our grasp detection method from different aspects on the public Cornell dataset and Jacquard *** experiments demonstrate that our grasp detection method achieves superior performance to the state-of-the-art *** particular,our grasp detection method ranked first on both the Cornell dataset and the Jacquard dataset,giving rise to the accuracy of 98.9%and 95.6%,respectively at realtime calculation speed.
Due to the complex flow state of pneumatically conveyed particles and the influence of the conveying conditions, existing measurement techniques have limitations in detecting the dynamic parameters of full-sections pa...
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Querying power big data across multiple sections plays an important role in achieving efficient power data sharing and emergent accident handling. However, power big data often suffers from the issues of data sparsity...
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In order to address the issue of low segmentation accuracy in the weak flame region of waste incineration flame images and the potential loss of texture details at the flame edge, this study proposes an algorithm for ...
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This paper is concerned with the multi-agent systems with both packet dropout and input delay.A novel receding horizon control(RHC)based consensus protocol is proposed by solving a distributed RHC based optimization *...
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This paper is concerned with the multi-agent systems with both packet dropout and input delay.A novel receding horizon control(RHC)based consensus protocol is proposed by solving a distributed RHC based optimization *** novelty of the optimization problem lines in the involvement of the neighbours’predictor information in the cost *** on the derived RHC based consensus protocol,the necessary and sufficient condition for the mean-square consensus is *** addition,the authors give a specific sufficient condition to guarantee the mean-square consensus.
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