In this paper, we investigated leader-following consensus control for nonlinear multiagent systems (MASs) experiencing denial-of-service (DoS) attacks. We proposed a distributed control strategy incorporating an adapt...
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SiC-reinforced aluminum matrix(SiCp/Al)composite is widely utilized in the aerospace,automotive,and electronics industries due to the combination of ceramic hardness and metal ***,the significant disparity in properti...
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SiC-reinforced aluminum matrix(SiCp/Al)composite is widely utilized in the aerospace,automotive,and electronics industries due to the combination of ceramic hardness and metal ***,the significant disparity in properties between SiC particles and the aluminum matrix results in severe tool wear and diminished surface quality during conventional *** study proposes an environmentally friendly and clean dry electrical discharge assisted grinding process as an efficient and low-damage machining method for SiCp/*** experimental platform was set up to study the impact of grinding and discharge process parameters on surface *** study compared the chip formation mechanism and surface quality between dry electrical discharge assisted grinding and conventional grinding,revealing relationships between surface roughness,grinding force,grinding temperature,and related *** results indicate that the proposed grinding method leads to smaller chip sizes,lower grinding forces and temperatures,and an average reduction of 19.2%in surface roughness compared to conventional *** axial,tangential,and normal grinding forces were reduced by roughly 10.5%,37.8%,and 23.0%,*** optimized process parameters were determined to be N=2500 r/min,vf=30 mm/min,a=10μm,E=15 V,f=5000 Hz,dc=80%,resulting in a surface roughness of 0.161μm.
Catastrophic and major disasters in real-world systems ranging from financial markets and ecosystems, often show generic early-warning signals that may indicate a collapse. Hence, understanding the collapse mechanism ...
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Catastrophic and major disasters in real-world systems ranging from financial markets and ecosystems, often show generic early-warning signals that may indicate a collapse. Hence, understanding the collapse mechanism of a complex network and predicting its process are of uttermost importance. However, these challenges are often hindered by the extremely high dimensionality of the underlying *** present here the concept of the fractional core(F-core) that considers the contribution of the network topology and dynamics to systematically analyze the collapse process in such networks, and encompass a broad range of dynamical systems, from mutualistic ecosystems to regulatory dynamics. We offer testable predictions on the tipping point, and, in particular, prove that the extinction of the maximum F-core of a network is an efficient indicator of whether a system completely collapses. The results show that the death of species or cells in a low-order F-core may improve the average density and have little influence on the tipping point. Generally, the principle of the F-core demonstrates how complex systems collapse and opens an innovative optimization strategy to uncover the optimal structure of systems.
In order to ensure that the complexity of the model and the physical memory occupied by the model are reduced under the condition of high detection accuracy, an EfficientNetYOLOX object detection algorithm under the f...
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The tool is the executing part of the machine tool processing, and its wear state directly affects the production efficiency and product quality. This paper proposes a tool wear state recognition method based on impro...
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This paper presents a subspace identification method for closed-loop systems with unknown deterministic *** deal with the unknown deterministic disturbances,two strategies are implemented to construct the row space th...
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This paper presents a subspace identification method for closed-loop systems with unknown deterministic *** deal with the unknown deterministic disturbances,two strategies are implemented to construct the row space that can be used to approximately represent the unknown deterministic disturbances using the trigonometric functions or Bernstein polynomials depending on whether the disturbance frequencies are *** closed-loop identification,CCF-N4SID is extended to the case with unknown deterministic disturbances using the oblique *** addition,a proper Bernstein polynomial order can be determined using the Akaike information criterion(AIC)or the Bayesian information criterion(BIC).Numerical simulation results demonstrate the effectiveness of the proposed identification method for both periodic and aperiodic deterministic disturbances.
Planetary craters are natural navigation landmarks that widely exist and are easily *** navigation based on crater landmarks has become an important autonomous navigation method for planetary *** to the increase in ob...
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Planetary craters are natural navigation landmarks that widely exist and are easily *** navigation based on crater landmarks has become an important autonomous navigation method for planetary *** to the increase in observed crater landmarks and the limitation of onboard computation,the selection of good crater landmarks has gradually become a research hotspot in the field of landmark-based optical *** paper designs a fast crater landmark selection method,which not only considers the configuration observability of crater subsets but also focuses on the influence on navigation performance arising from the measurement uncertainty and the matching confidence of craters,which is different from other landmark selection *** factor of measurement uncertainty,which is anisotropic,correlated and nonidentically distributed,is quantified and integrated into selection based on crater pairing detection and localization error *** addition,the concept of the crater matching confidence factor is introduced,which reflects the possibility of 2D projection measurements corresponding to 3D *** with the configuration observability factor,the crater landmark selection indicator is ***,the effectiveness of the proposed method is verified by Monte Carlo simulations.
To address the issues of slow diagnostic speed,low accuracy,and poor generalization performance in traditional rolling bearing fault diagnosis methods,we propose a rolling bearing fault diagnosis method based on Marko...
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To address the issues of slow diagnostic speed,low accuracy,and poor generalization performance in traditional rolling bearing fault diagnosis methods,we propose a rolling bearing fault diagnosis method based on Markov Transition Field(MTF)image encoding combined with a lightweight convolutional neural network that integrates a Convolutional Block Attention Module(CBAM-LCNN).Specifically,we first use the Markov Transition Field to convert the original one-dimensional vibration signals of rolling bearings into two-dimensional ***,we construct a lightweight convolutional neural network incorporating the convolutional attention module(CBAM-LCNN).Finally,the two-dimensional images obtained from MTF mapping are fed into the CBAM-LCNN network for image feature extraction and fault *** validate the effectiveness of the proposed method on the bearing fault datasets from Guangdong University of Petrochemical technology’s multi-stage centrifugal fan and Case Western Reserve *** results show that,compared to other advanced baseline methods,the proposed rolling bearing fault diagnosis method offers faster diagnostic speed and higher diagnostic *** addition,we conducted experiments on the Xi’an Jiaotong University rolling bearing dataset,achieving excellent results in bearing fault *** results validate the strong generalization performance of the proposed *** method presented in this paper not only effectively diagnoses faults in rolling bearings but also serves as a reference for fault diagnosis in other equipment.
With the widespread use of network infrastructures such as 5G and low-power wide-area networks,a large number of the Internet of Things(IoT)device nodes are connected to the network,generating massive amounts of ***,i...
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With the widespread use of network infrastructures such as 5G and low-power wide-area networks,a large number of the Internet of Things(IoT)device nodes are connected to the network,generating massive amounts of ***,it is a great challenge to achieve anonymous authentication of IoT nodes and secure data *** present,blockchain technology is widely used in authentication and s data storage due to its decentralization and ***,Fan et *** a secure and efficient blockchain-based IoT authentication and data sharing *** studied it as one of the state-of-the-art protocols and found that this scheme does not consider the resistance to ephemeral secret compromise attacks and the anonymity of IoT *** overcome these security flaws,this paper proposes an enhanced authentication and data transmission scheme,which is verified by formal security proofs and informal security ***,Scyther is applied to prove the security of the proposed ***,it is demonstrated that the proposed scheme achieves better performance in terms of communication and computational cost compared to other related schemes.
A fault diagnosis method based on improved Pearson correlation algorithm and Convolutional Neural Network (CNN) is proposed to address the issue of high diagnostic speed and high proportion of semiconductor power tran...
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