The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this ***,a comprehensive nonlinear mathematical model that encompasses both mat...
详细信息
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this ***,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is *** to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched *** from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output ***,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory *** mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is ***,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact *** analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop ***,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is ***,the algorithm’s efficacy is validated through comparative experiments.
The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear *** a fault occurs,the distribution of fault characteri...
详细信息
The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear *** a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different *** address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault ***,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two *** improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault *** addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test *** proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.
A simplified calculation of the specimen’s stress-strain curve is generally conducted using the two-wave method by the split Hopkinson pressure bar(SHPB),which aligns the onset of the transmitted and reflected ***,th...
详细信息
A simplified calculation of the specimen’s stress-strain curve is generally conducted using the two-wave method by the split Hopkinson pressure bar(SHPB),which aligns the onset of the transmitted and reflected ***,this approach neglects the travel time of elastic waves within the *** the travel time of elastic waves,this study quantitatively investigates the error characteristics and patterns of stress,strain,and strain rate in the specimen under different conditions using the theoretical two-wave method,and compares the results with those obtained using the onset-aligned twowave *** study reveals that the stress-time curves derived from the theoretical two-wave method are lower than the actual stress curves,whereas those obtained from the onset-aligned two-wave method are consistently higher than the actual stress curves,with the stress deviation approximating a constant value when the dimensionless time exceeds *** starting point of the stress-strain curves obtained by the theoretical two-wave method is not zero but a point on the strain axis,whereas the onset-aligned two-wave method always starts at ***,the slopes of the stress-strain curves obtained by both methods differ from the actual Young’s modulus of the material,and functional relationships between the slopes and the actual Young’s modulus are *** research offers theoretical guidance for the refined design of SHPB experiments and the accurate processing of data.
Partial maximum satisfiability(PMS) is a significant generalization of Boolean satisfiability(SAT) and maximum satisfiability(MaxSAT), by introducing hard clauses and soft clauses. Compared with SAT and MaxSAT, the PM...
详细信息
Partial maximum satisfiability(PMS) is a significant generalization of Boolean satisfiability(SAT) and maximum satisfiability(MaxSAT), by introducing hard clauses and soft clauses. Compared with SAT and MaxSAT, the PMS problem has more real-world applications where both hard and soft constraints are involved. Local search is an effective incomplete method for solving PMS and is useful for important domains where good-quality solutions are desired within reasonable *** local search PMS solvers, the approach for initial assignment generation is crucial because its effectiveness significantly affects practical performance. In this study, we propose a novel initial assignment prediction approach, called InitPMS. When predicting an assignment for PMS, InitPMS considers the specific structure of PMS instances, i.e., distinguishing hard and soft clauses. Our experiments on extensive PMS instances from MaxSAT evaluations(MSEs) 2020 and 2021 show that InitPMS significantly boosts the performance of five state-of-the-art local search PMS solvers, demonstrating its generality. In addition,our results indicate that incorporating InitPMS could improve the performance of one of the best incomplete PMS solvers in MaxSAT Evaluation 2021, indicating that InitPMS might help advance the state of the art in PMS solving.
UAV networks often encounter jamming attacks, under which multi-radio protocols have to switch radios to accelerate communication recovery. However, the existing protocols rely on exchange of hello messages to detect ...
详细信息
UAV networks often encounter jamming attacks, under which multi-radio protocols have to switch radios to accelerate communication recovery. However, the existing protocols rely on exchange of hello messages to detect jamming, leading to long sensing time and thus slow routing recovery. To address the issues raised by jamming attacks, we propose a new routing protocol, Electromagnetic Spectrum situation awareness Optimized Link State Routing (ESOLSR) protocol, to improve the existing OLSRv2 protocol. ESOLSR utilizes the spectrum situation awareness capability from the physical layer, and adopts joint-updating of link status, updating of interface functions, and adaptive adjustment of parameters. Our simulation results show that the improved protocol, ESOLSR, can recover routing and resume normal communication 26.6% faster compared to the existing protocols.
Knowledge graphs(KGs) effectively mitigate data sparsity in recommendation systems(RSs) by providing valuable auxiliary information [1]. However, traditional centralized KG-based RSs increase the risk of user privacy ...
Knowledge graphs(KGs) effectively mitigate data sparsity in recommendation systems(RSs) by providing valuable auxiliary information [1]. However, traditional centralized KG-based RSs increase the risk of user privacy *** learning(FL) enhances RS's privacy by enabling model training on decentralized data [2]. Although integrating KG and FL can address both data sparsity and privacy issues in RSs [3], several challenges persist. CH1,Each client's local model relies on a consistent global model from the server, limiting personalized deployment to endusers.
Although ray tracing produces high-fidelity, realistic images, it is considered computationally burdensome when implemented on a high rendering rate system. Perception-driven rendering techniques generate images with ...
详细信息
Although ray tracing produces high-fidelity, realistic images, it is considered computationally burdensome when implemented on a high rendering rate system. Perception-driven rendering techniques generate images with minimal noise and distortion that are generally acceptable to the human visual system, thereby reducing rendering costs. In this paper, we introduce a perception-entropy-driven temporal reusing method to accelerate real-time ray tracing. We first build a just noticeable difference(JND) model to represent the uncertainty of ray samples and image space masking effects. Then, we expand the shading gradient through gradient max-pooling and gradient filtering to enlarge the visual receipt field. Finally, we dynamically optimize reusable time segments to improve the accuracy of temporal reusing. Compared with Monte Carlo ray tracing, our algorithm enhances frames per second(fps) by 1.93× to 2.96× at 8 to 16 samples per pixel, significantly accelerating the Monte Carlo ray tracing process while maintaining visual quality.
Electronic auctions(e-auctions)remove the physical limitations of traditional auctions and bring this mechanism to the general ***,most e-auction schemes involve a trusted auctioneer,which is not always credible in **...
详细信息
Electronic auctions(e-auctions)remove the physical limitations of traditional auctions and bring this mechanism to the general ***,most e-auction schemes involve a trusted auctioneer,which is not always credible in *** studies have applied cryptography tools to solve this problem by distributing trust,but they ignore the existence of *** this paper,a blockchain-based Privacy-Preserving and Collusion-Resistant scheme(PPCR)for double auctions is proposed by employing both cryptography and blockchain technology,which is the first decentralized and collusion-resistant double auction scheme that guarantees bidder anonymity and bid privacy.A two-server-based auction framework is designed to support off-chain allocation with privacy preservation and on-chain dispute resolution for collusion resistance.A Dispute Resolution agreement(DR)is provided to the auctioneer to prove that they have conducted the auction correctly and the result is fair and *** addition,a Concise Dispute Resolution protocol(CDR)is designed to handle situations where the number of accused winners is small,significantly reducing the computation cost of dispute *** experimental results confirm that PPCR can indeed achieve efficient collusion resistance and verifiability of auction results with low on-chain and off-chain computational overhead.
Dialogue-based relation extraction(DialogRE) aims to predict relationships between two entities in dialogue. Current approaches to dialogue relationship extraction grapple with long-distance entity relationships in di...
详细信息
Dialogue-based relation extraction(DialogRE) aims to predict relationships between two entities in dialogue. Current approaches to dialogue relationship extraction grapple with long-distance entity relationships in dialogue data as well as complex entity relationships, such as a single entity with multiple types of connections. To address these issues, this paper presents a novel approach for dialogue relationship extraction termed the hypergraphs and heterogeneous graphs model(HG2G). This model introduces a two-tiered structure, comprising dialogue hypergraphs and dialogue heterogeneous graphs, to address the shortcomings of existing methods. The dialogue hypergraph establishes connections between similar nodes using hyper-edges and utilizes hypergraph convolution to capture multi-level features. Simultaneously, the dialogue heterogeneous graph connects nodes and edges of different types, employing heterogeneous graph convolution to aggregate cross-sentence information. Ultimately, the integrated nodes from both graphs capture the semantic nuances inherent in dialogue. Experimental results on the DialogRE dataset demonstrate that the HG2G model outperforms existing state-of-the-art methods.
As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention...
详细信息
As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.
暂无评论