Compared to conventional single-rotor permanent magnet synchronous machines (PMSMs), the distributed magnetic pole permanent magnet planetary machine (DMPPMPM) consists of several small-radius rotors, allowing for hig...
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Home automation is growing rapidly in the Fourth Industrial Revolution (4IR), providing users with unwavering convenience and enhanced security. This paper presents a comprehensive Internet of Things (IoT) smart home ...
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Increasing the semantic understanding and contextual awareness of machine learning models is important for improving robustness and reducing susceptibility to data shifts. In this work, we leverage contextual awarenes...
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ISBN:
(数字)9781665490429
ISBN:
(纸本)9781665490429
Increasing the semantic understanding and contextual awareness of machine learning models is important for improving robustness and reducing susceptibility to data shifts. In this work, we leverage contextual awareness for the anomaly detection problem. Although graphed-based anomaly detection has been widely studied, context-dependent anomaly detection is an open problem and without much current research. We develop a general framework for converting a context-dependent anomaly detection problem to a link prediction problem, allowing well-established techniques from this domain to be applied. We implement a system based on our framework that utilizes knowledge graph embedding models and demonstrates the ability to detect outliers using context provided by a semantic knowledge base. We show that our method can detect context-dependent anomalies with a high degree of accuracy and show that current object detectors can detect enough classes to provide the needed context to show good performance within our example domain.
With the increasing focus on flexible automation, which emphasizes systems capable of adapting to varied tasks and conditions, exploring future deployments of cloud and edge-based network infrastructures in robotic sy...
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Linear motors are widely used in automation industry where both the tracking performance and the productivity are of importance. The inevitable uncertainties in system parameters and process nonlinearities and the exi...
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ISBN:
(数字)9781665490429
ISBN:
(纸本)9781665490429
Linear motors are widely used in automation industry where both the tracking performance and the productivity are of importance. The inevitable uncertainties in system parameters and process nonlinearities and the existence of hard constraints due to physical limitations of control input and system states often makes the simultaneous improvement of the tracking accuracy and the time efficiency a daunting theoretical problem to solve. In this paper, the constrained time-optimal tracking control problem of the linear motors under uncertainties and hard constraints is addressed through a seamless integration of the constrained optimization methods and the adaptive robust controls. Specifically, the demand for high productivity under state and input constraints is met by solving a constrained time-optimal trajectory replanning problem using the Pontryagin maximum principle (indirect method). The resulting replanned trajectories are then fed into the low-level adaptive robust controller that effectively deals with the parametric uncertainties and uncertain nonlinearities for high tracking performance. Comparative experiments have been carried out and validated the superiority of the proposed method over existing ones.
In order to better train shooters of different levels, this paper focuses on path planning and evaluation of mobile target robots. Given the global map, multiple random points are generated in the accessible area of t...
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Electrochemical impedance spectroscopy (EIS) plays a crucial role in fuel cells (FCS) and can reflect the health status of fuel cells. The measurement of fuel cell EIS can apply ripple modulation on the control side o...
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FGVC plays a major role in the field of robotic vision, which has a significant impact, for example, on the conservation of endangered and rare birds, It aims to distinguish similar subcategories. In this paper, we pr...
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Aiming at the low efficiency of gesture interaction in the command and control system, this paper proposes a gesture interaction optimization method based on gesture complexity. Ten joint points are selected to model ...
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With the development of Marine technology, the importance of Marine environment exploration is increasing day by day. Imaging sonar is the most effective means in ocean exploration and forward sonar is one of the most...
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