Metallised film capacitors(MFCs)are renowned for their unique self-healing(SH)properties,which bestow them with exceptional reliability and stability in the face of intense electric fields,high voltages,and pulse powe...
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Metallised film capacitors(MFCs)are renowned for their unique self-healing(SH)properties,which bestow them with exceptional reliability and stability in the face of intense electric fields,high voltages,and pulse power ***,the exploration of SH characteristics concerning single-layer dielectric film remains insufficient for advancing MFC reliability *** establish the theoretical correlation of SH characteristics from the device to the film in the MFCs,this work developed a simulation model to analyse the SH dynamic behaviour in the *** effects of coupling capacitors,arc resistance and insulation resistance on the macroscopic characteristics(voltage drop and pulse current)are focused during the SH process in *** results indicate that SH is primarily associated with the voltage drop duration rather than the sampling ***,the SH process in MFC is characterised as an abrupt decrease in voltage to its minimum *** refinement enhances the SH energy dissipation model of *** quantified relationship between the macroscopic characteristics and microstructure evolution(polypropylene decomposition and aluminium electrode vaporisation)is established in MFCs under diverse SH energy *** SH energy and duration increase,the proportion of energy attributed to polypropylene decomposition increases,resulting in multi-layer ablation and adhesion within the metallised film and a pronounced deterioration in MFC electrical *** examination of macro-micro perspectives sheds new light on the intricate mechanisms governing the SH behaviour in MFCs,offering valuable insights for the advancement of their design,reliability evaluation,and performance optimisation in diverse electrical applications.
The key-value separation is renowned for its significant mitigation of the write amplification inherent in traditional LSM trees. However, KV separation potentially increases performance overhead in the management of ...
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INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically loc...
INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.
Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language *** data is the ...
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Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language *** data is the basis for developing detectors;however,the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English *** significantly affects the accuracy of Chinese offensive language detectors in practical applications,especially when dealing with hard cases or out-of-domain *** alleviate the limitations posed by available datasets,we introduce AugCOLD(Augmented Chinese Offensive Language Dataset),a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model ***,we employ a multiteacher distillation framework to enhance detection performance with unsupervised *** is,we build multiple teachers with publicly accessible datasets and use them to assign soft labels to *** soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network,i.e.,the final offensive *** conduct experiments on multiple public test sets and our well-designed hard tests,demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.
To reduce phase errors caused by nonlinear responses in the measurement system, we propose a non-calibration correction method for nonlinear errors in phase-shifting patterns. First, the captured grating fringes are t...
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Traditional path planning approach is generally focused on finding a single one shortest path given the temporal or spatial constraints. However, the strategy of single-one optimal path is unable to adapt to various s...
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As a mature distributed machine learning paradigm,federated learning enables wireless edge devices to collaboratively train a shared AI-model by stochastic gradient descent(SGD).However,devices need to upload high-dim...
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As a mature distributed machine learning paradigm,federated learning enables wireless edge devices to collaboratively train a shared AI-model by stochastic gradient descent(SGD).However,devices need to upload high-dimensional stochastic gradients to edge server in training,which cause severe communication *** address this problem,we compress the communication by sparsifying and quantizing the stochastic gradients of edge *** first derive a closed form of the communication compression in terms of sparsification and quantization ***,the convergence rate of this communicationcompressed system is analyzed and several insights are ***,we formulate and deal with the quantization resource allocation problem for the goal of minimizing the convergence upper bound,under the constraint of multiple-access channel *** show that the proposed scheme outperforms the benchmarks.
This paper studies a finite-time adaptive fractionalorder fault-tolerant control(FTC)scheme for the slave position tracking of the teleoperating cyber physical system(TCPS)with external disturbances and actuator *** o...
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This paper studies a finite-time adaptive fractionalorder fault-tolerant control(FTC)scheme for the slave position tracking of the teleoperating cyber physical system(TCPS)with external disturbances and actuator *** on the fractional Lyapunov stability theory and the finite-time stability theory,a fractional-order nonsingular fast terminal sliding mode(FONFTSM)control law is proposed to promote the tracking and fault tolerance performance of the considered ***,the adaptive fractional-order update laws are designed to cope with the unknown upper bounds of the unknown actuator faults and external ***,the finite-time stability of the closed-loop system is ***,comparison simulation results are also provided to show the validity and the advantages of the proposed techniques.
The increasing dependence on smartphones with advanced sensors has highlighted the imperative of precise transportation mode classification, pivotal for domains like health monitoring and urban planning. This research...
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The increasing dependence on smartphones with advanced sensors has highlighted the imperative of precise transportation mode classification, pivotal for domains like health monitoring and urban planning. This research is motivated by the pressing demand to enhance transportation mode classification, leveraging the potential of smartphone sensors, notably the accelerometer, magnetometer, and gyroscope. In response to this challenge, we present a novel automated classification model rooted in deep reinforcement learning. Our model stands out for its innovative approach of harnessing enhanced features through artificial neural networks (ANNs) and visualizing the classification task as a structured series of decision-making events. Our model adopts an improved differential evolution (DE) algorithm for initializing weights, coupled with a specialized agent-environment relationship. Every correct classification earns the agent a reward, with additional emphasis on the accurate categorization of less frequent modes through a distinct reward strategy. The Upper Confidence Bound (UCB) technique is used for action selection, promoting deep-seated knowledge, and minimizing reliance on chance. A notable innovation in our work is the introduction of a cluster-centric mutation operation within the DE algorithm. This operation strategically identifies optimal clusters in the current DE population and forges potential solutions using a pioneering update mechanism. When assessed on the extensive HTC dataset, which includes 8311 hours of data gathered from 224 participants over two years. Noteworthy results spotlight an accuracy of 0.88±0.03 and an F-measure of 0.87±0.02, underscoring the efficacy of our approach for large-scale transportation mode classification tasks. This work introduces an innovative strategy in the realm of transportation mode classification, emphasizing both precision and reliability, addressing the pressing need for enhanced classification mechanisms in an eve
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