As smart manufacturing and Industry 4.0 continue to evolve,fault diagnosis of mechanical equipment has become crucial for ensuring production safety and optimizing equipment utilization.To address the challenge of cro...As smart manufacturing and Industry 4.0 continue to evolve,fault diagnosis of mechanical equipment has become crucial for ensuring production safety and optimizing equipment utilization.To address the challenge of cross-domain adaptation in intelligent diagnostic models under varying operational conditions,this paper introduces the CNN-1D-KAN model,which combines a 1D Convolutional Neural Network(1D-CNN)with a Kolmogorov–Arnold Network(KAN).The novelty of this approach lies in replacing the traditional 1D-CNN’s final fully connected layer with a KANLinear layer,leveraging KAN’s advanced nonlinear processing and function approximation capabilities while maintaining the simplicity of linear transformations.Experimental results on the CWRU dataset demonstrate that,under stable load conditions,the CNN-1D-KAN model achieves high accuracy,averaging 96.67%.Furthermore,the model exhibits strong transfer generalization and robustness across varying load conditions,sustaining an average accuracy of 90.21%.When compared to traditional neural networks(e.g.,1D-CNN and Multi-Layer Perceptron)and other domain adaptation models(e.g.,KAN Convolutions and KAN),the CNN-1D-KAN consistently outperforms in both accuracy and F1 scores across diverse load scenarios.Particularly in handling complex cross-domain data,it excels in diagnostic performance.This study provides an effective solution for cross-domain fault diagnosis in Industrial Internet systems,offering a theoretical foundation to enhance the reliability and stability of intelligent manufacturing processes,thus supporting the future advancement of industrial IoT applications.展开更多
In this paper we propose an Ising model on an infinite ladder lattice, which is made of two infinite Ising spin chains with interactions. It is essentially a quasi-one-dimessional Ising model because the length of the...In this paper we propose an Ising model on an infinite ladder lattice, which is made of two infinite Ising spin chains with interactions. It is essentially a quasi-one-dimessional Ising model because the length of the ladder lattice is infinite, while its width is finite. We investigate the phase transition and dynamic behavior of Ising model on this quasi-one-dimessional system. We use the generalized transfer matrix method to investigate the phase transition of the system. It is found that there is no nonzero temperature phase transition in this system. At the same time, we are interested in Glauber dynamics. Based on that, we obtain the time evolution of the local spin magnetization by exactly solving a set of master equations.展开更多
Secure multi-party computation(MPC)allows a set of parties to jointly compute a function on their private inputs,and reveals nothing but the output of the function.In the last decade,MPC has rapidly moved from a purel...Secure multi-party computation(MPC)allows a set of parties to jointly compute a function on their private inputs,and reveals nothing but the output of the function.In the last decade,MPC has rapidly moved from a purely theoretical study to an object of practical interest,with a growing interest in practical applications such as privacy-preserving machine learning(PPML).In this paper,we comprehensively survey existing work on concretely ecient MPC protocols with both semi-honest and malicious security,in both dishonest-majority and honest-majority settings.We focus on considering the notion of security with abort,meaning that corrupted parties could prevent honest parties from receiving output after they receive output.We present high-level ideas of the basic and key approaches for designing di erent styles of MPC protocols and the crucial building blocks of MPC.For MPC applications,we compare the known PPML protocols built on MPC,and describe the eciency of private inference and training for the state-of-the-art PPML protocols.Further-more,we summarize several challenges and open problems to break though the eciency of MPC protocols as well as some interesting future work that is worth being addressed.This survey aims to provide the recent development and key approaches of MPC to researchers,who are interested in knowing,improving,and applying concretely ecient MPC protocols.展开更多
基金supported by the Science and Technology Research Program of Chongqing Municipal Education Commission(Grant Nos.KJQN202100812,KJQN202215901,KJQN202400812).
文摘As smart manufacturing and Industry 4.0 continue to evolve,fault diagnosis of mechanical equipment has become crucial for ensuring production safety and optimizing equipment utilization.To address the challenge of cross-domain adaptation in intelligent diagnostic models under varying operational conditions,this paper introduces the CNN-1D-KAN model,which combines a 1D Convolutional Neural Network(1D-CNN)with a Kolmogorov–Arnold Network(KAN).The novelty of this approach lies in replacing the traditional 1D-CNN’s final fully connected layer with a KANLinear layer,leveraging KAN’s advanced nonlinear processing and function approximation capabilities while maintaining the simplicity of linear transformations.Experimental results on the CWRU dataset demonstrate that,under stable load conditions,the CNN-1D-KAN model achieves high accuracy,averaging 96.67%.Furthermore,the model exhibits strong transfer generalization and robustness across varying load conditions,sustaining an average accuracy of 90.21%.When compared to traditional neural networks(e.g.,1D-CNN and Multi-Layer Perceptron)and other domain adaptation models(e.g.,KAN Convolutions and KAN),the CNN-1D-KAN consistently outperforms in both accuracy and F1 scores across diverse load scenarios.Particularly in handling complex cross-domain data,it excels in diagnostic performance.This study provides an effective solution for cross-domain fault diagnosis in Industrial Internet systems,offering a theoretical foundation to enhance the reliability and stability of intelligent manufacturing processes,thus supporting the future advancement of industrial IoT applications.
文摘In this paper we propose an Ising model on an infinite ladder lattice, which is made of two infinite Ising spin chains with interactions. It is essentially a quasi-one-dimessional Ising model because the length of the ladder lattice is infinite, while its width is finite. We investigate the phase transition and dynamic behavior of Ising model on this quasi-one-dimessional system. We use the generalized transfer matrix method to investigate the phase transition of the system. It is found that there is no nonzero temperature phase transition in this system. At the same time, we are interested in Glauber dynamics. Based on that, we obtain the time evolution of the local spin magnetization by exactly solving a set of master equations.
基金the National Key Research and Development Program of China(Grant No.2018YFB0804105)in part by the National Natural Science Foundation of China(Grant Nos.62102037,61932019).
文摘Secure multi-party computation(MPC)allows a set of parties to jointly compute a function on their private inputs,and reveals nothing but the output of the function.In the last decade,MPC has rapidly moved from a purely theoretical study to an object of practical interest,with a growing interest in practical applications such as privacy-preserving machine learning(PPML).In this paper,we comprehensively survey existing work on concretely ecient MPC protocols with both semi-honest and malicious security,in both dishonest-majority and honest-majority settings.We focus on considering the notion of security with abort,meaning that corrupted parties could prevent honest parties from receiving output after they receive output.We present high-level ideas of the basic and key approaches for designing di erent styles of MPC protocols and the crucial building blocks of MPC.For MPC applications,we compare the known PPML protocols built on MPC,and describe the eciency of private inference and training for the state-of-the-art PPML protocols.Further-more,we summarize several challenges and open problems to break though the eciency of MPC protocols as well as some interesting future work that is worth being addressed.This survey aims to provide the recent development and key approaches of MPC to researchers,who are interested in knowing,improving,and applying concretely ecient MPC protocols.
