Medical Visual Question Answering (MedVQA) serves as an automated medical assistant, capable of answering patient queries and aiding physician diagnoses based on medical images and questions. Recent advancements have ...
complexsimulationsystems usually need to satisfy the credibility requirements and the credibility of complexsimulationsystems is inextricably linked to the credibility of simulation sub-systems. Hence, in order to...
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The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to i...
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The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber ***, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.
Machine Learning and Artificial Intelligence technology accelerates technological progress and promotes social development, but also brings many security problems. Machine learning models may be affected, deceived, co...
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The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security *** solve th...
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The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security *** solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the ***,a prediction model of TCAN-BiGRU is established respectively for each *** uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from *** learns the before-after status of situation data to extract more feature information from sequences for ***,IQPSO is proposed to optimize the hyperparameters of ***,the prediction results of the subsequence are superimposed to obtain the final predicted *** the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs *** the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy.
Over the past century,ferroelectricity has offered exciting opportunities for fundamental research and device ***,most of the discovered excellent ferroelectrics are oxide materials with large band gaps,limiting their...
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Over the past century,ferroelectricity has offered exciting opportunities for fundamental research and device ***,most of the discovered excellent ferroelectrics are oxide materials with large band gaps,limiting their potential for optoelectronics *** using first-principles calculations we identify a new narrow-gap ferroelectric beyond oxides,i.e.,ferroelectric perovskite sulphide BaZrS_(3).Under large compressive strains,BaZrS_(3)can be stabilized into a unique supertetragonal phase with an extraordinary polarization of 67.16μC/cm^(2),which is even stronger than that of conventional oxide ***,the supertetragonal BaZrS_(3)exhibits a direct narrow band gap of 1.2 eV and excellent electronic *** on the chemical bonding analysis,we attribute the formation of supertetragonal phase to charge re-ordering in which theπbond overlap along the long〈Zr-S〉bond completely vanishes and the antibonding states of theσbond appear below the Fermi *** work provides a conceptual strategy for designing new ferroelectrics for electronic and photovoltaic applications.
This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state *** this paper, the specific control laws under the three forms are *** is analyz...
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This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state *** this paper, the specific control laws under the three forms are *** is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test *** calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing ***, a unified form of the control laws under the three forms is given.
In this paper,physics-informed liquid networks(PILNs)are proposed based on liquid time-constant networks(LTC)for solving nonlinear partial differential equations(PDEs).In this approach,the network state is controlled ...
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In this paper,physics-informed liquid networks(PILNs)are proposed based on liquid time-constant networks(LTC)for solving nonlinear partial differential equations(PDEs).In this approach,the network state is controlled via ordinary differential equations(ODEs).The significant advantage is that neurons controlled by ODEs are more expressive compared to simple activation *** addition,the PILNs use difference schemes instead of automatic differentiation to construct the residuals of PDEs,which avoid information loss in the neighborhood of sampling *** this method draws on both the traveling wave method and physics-informed neural networks(PINNs),it has a better physical ***,the KdV equation and the nonlinear Schr¨odinger equation are solved to test the generalization ability of the *** the best of the authors’knowledge,this is the first deep learning method that uses ODEs to simulate the numerical solutions of PDEs.
Radio frequency energy harvesting offers a promising solution to provide low power Internet of Things (IoT) devices with convenient and perpetual energy supply. In this work, we investigate the reliable performance of...
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Aiming at the problem of periodic interference in flight simulation turntables, a design method of full-form dynamic linearization model free adaptive control (FFDL-MFAC) is proposed. An equivalent dynamic linearized ...
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