Nonstationary time series are ubiquitous in almost all natural and engineering *** the time-varying signatures from nonstationary time series is still a challenging problem for data *** Time-Frequency Distribution(TFD...
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Nonstationary time series are ubiquitous in almost all natural and engineering *** the time-varying signatures from nonstationary time series is still a challenging problem for data *** Time-Frequency Distribution(TFD)provides a powerful tool to analyze these ***,they suffer from Cross-Term(CT)issues that impair the readability of ***,to achieve high-resolution and CT-free TFDs,an end-to-end architecture termed Quadratic TF-Net(QTFN)is proposed in this *** by classic TFD theory,the design of this deep learning architecture is heuristic,which firstly generates various basis functions through ***,more comprehensive TF features can be extracted by these basis ***,to balance the results of various basis functions adaptively,the Efficient Channel Attention(ECA)block is also embedded into ***,a new structure called Muti-scale Residual Encoder-Decoder(MRED)is also proposed to improve the learning ability of the model by highly integrating the multi-scale learning and encoder-decoder ***,although the model is only trained by synthetic signals,both synthetic and real-world signals are tested to validate the generalization capability and superiority of the proposed QTFN.
This article introduces a novel model for low-quality pedestrian trajectory prediction, the social nonstationary transformers (NSTransformers), that merges the strengths of NSTransformers and spatiotemporal graph tran...
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This letter presents a human-to-robot handover design for an Autonomous Mobile Robot (AMR). The developed control system enables the AMR to navigate to a specific person and grasp the object that the person wants to h...
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A multi-level regional project management system is considered, in which targets and policy indicators for implementing a set of works implemented at the lower management level (production) are set at the upper level ...
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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 ...
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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.
In this paper,we propose a game theory framework to solve advanced persistent threat problems,especially considering two types of insider threats:malicious and *** this framework,we establish a unified three-player ga...
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In this paper,we propose a game theory framework to solve advanced persistent threat problems,especially considering two types of insider threats:malicious and *** this framework,we establish a unified three-player game model and derive Nash equilibria in response to different types of insider *** analyzing these Nash equilibria,we provide quantitative solutions to advanced persistent threat problems pertaining to insider ***,we have conducted a comparative assessment of the optimal defense strategy and corresponding defender's costs between two types of insider ***,our findings advocate a more proactive defense strategy against inadvertent insider threats in contrast to malicious ones,despite the latter imposing a higher burden on the *** theoretical results are substantiated by numerical results,which additionally include a detailed exploration of the conditions under which different insiders adopt risky *** conditions can serve as guiding indicators for the defender when calibrating their monitoring intensities and devising defensive strategies.
This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the co...
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This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the control objective. The DF mapping refers to the fact that the system state and input of each robot can be derived algebraically from the flat outputs of the leaders and the cooperative errors and their finite order derivatives. Based on the proposed swarm DF mapping, a distributed controller is designed. The distributed implementation of swarm DF mapping is achieved through observer design. The effectiveness of the proposed method is validated through a numerical simulation of quadrotor swarm synchronization.
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.
Being able to safely land on the surface is one of the primary challenges when a probe exploring an asteroid. In order to ensure landing safety, the landing location planning needs to comprehensively consider the terr...
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Automatic path planning is very important for many applications such as robots exploring unknown environments and logistics delivery. In this paper, we propose a discrete multi-population fruit fly optimization algori...
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