Nanodendritic structures have gained increasing popularity in electrochemical sensors. However, it is still rare to generate a 3-D model in a short period of time to understand the structure-function relationship of t...
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This article discusses the importance of cloud-based multi-tenancy in private–public-private secure cloud environments, which is achieved through the isolation of end-user data and resources into tenants to ensure da...
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Human activity recognition involves identifying the daily living activities of an individual through the utilization of sensor attributes and intelligent learning algorithms. The identification of intricate human acti...
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In sensorless motor drive applications, the rotor and the speed of the rotor are usually estimated through state observer algorithms. A key part of such algorithm is the computation of the derivative of the rotor posi...
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This paper proposes a RISC-V extension, named SigWavy, meant to optimize the PWM control for general purpose or application specific designs. The RISC-V extension named above is a PWM control Unit with a dedicated ISA...
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To estimate the uncertainty of measurement, analytical methods are widely used, a review and comparative analysis of which is given in the work. Among the existing methods for estimating the uncertainty in measurement...
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Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming ...
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Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power *** improve efficiency of predetermination,this paper proposes a framework of knowledge fusion-based deep reinforcement learning(KF-DRL)for intelligent predetermination of ***,the Markov Decision Process(MDP)for GTS problem is formulated based on transient instability ***,linear action space is developed to reduce dimensionality of action space for multiple controllable ***,KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making *** can enhance the efficiency and learning ***,the graph convolutional network(GCN)is introduced to the policy network for enhanced learning *** simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.
The use of semiconductor devices in safety-critical scenarios is increasing in both quantity and complexity. This paper presents a novel approach to support safety requirements from RTL exploration through to implemen...
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With Industry 5.0, prioritizing worker well-being, the integration of human-related data into production processes poses challenges related to data privacy and compliance with regulations such as GDPR. This paper pres...
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The research proposes the application of Digital Intelligent Assistants (DIAs) as proactive agents that can support employees in dealing with cybersecurity issues in sustainable industrial processes underlying the imp...
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