Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal...
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Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal graph association rules(TGARs)that extend traditional graph-pattern association rules in a static graph by incorporating the unique temporal information and *** introduce quality measures(e.g.,support,confidence,and diversification)to characterize meaningful TGARs that are useful and *** addition,the proposed support metric is an upper bound for alternative metrics,allowing us to guarantee a superset of *** extend conventional confidence measures in terms of maximal occurrences of *** diversification score strikes a balance between interestingness and *** the problem is NP-hard,we develop an effective discovery algorithm for TGARs that integrates TGARs generation and TGARs selection and shows that mining TGARs is feasible over a temporal *** propose pruning strategies to filter TGARs that have low support or cannot make top-k as early as ***,we design an auxiliary data structure to prune the TGARs that do not meet the constraints during the TGARs generation process to avoid conducting repeated subgraph matching for each extension in the search *** experimentally verify the effectiveness,efficiency,and scalability of our algorithms in discovering diversified top-k TGARs from temporal graphs in real-life applications.
This article develops a novel data-driven safe Q-learning method to design the safe optimal controller which can guarantee constrained states of nonlinear systems always stay in the safe region while providing an opti...
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This article develops a novel data-driven safe Q-learning method to design the safe optimal controller which can guarantee constrained states of nonlinear systems always stay in the safe region while providing an optimal ***,we design an augmented utility function consisting of an adjustable positive definite control obstacle function and a quadratic form of the next state to ensure the safety and ***,by exploiting a pre-designed admissible policy for initialization,an off-policy stabilizing value iteration Q-learning(SVIQL)algorithm is presented to seek the safe optimal policy by using offline data within the safe region rather than the mathematical ***,the monotonicity,safety,and optimality of the SVIQL algorithm are theoretically *** obtain the initial admissible policy for SVIQL,an offline VIQL algorithm with zero initialization is constructed and a new admissibility criterion is established for immature iterative ***,the critic and action networks with precise approximation ability are established to promote the operation of VIQL and SVIQL ***,three simulation experiments are conducted to demonstrate the virtue and superiority of the developed safe Q-learning method.
In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem(CTSP). When solving large-scale CTSP with a scale of more than 1000d...
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In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem(CTSP). When solving large-scale CTSP with a scale of more than 1000dimensions, their convergence speed and the quality of their solutions are limited. This paper proposes a new hybrid IT?(HIT?) algorithm, which integrates two new strategies, crossover operator and mutation strategy, into the standard IT?. In the iteration process of HIT?, the feasible solution of CTSP is represented by the double chromosome coding, and the random drift and wave operators are used to explore and develop new unknown regions. In this process, the drift operator is executed by the improved crossover operator, and the wave operator is performed by the optimized mutation strategy. Experiments show that HIT? is superior to the known comparison algorithms in terms of the quality solution.
Data migration strategies (DMSs) improve the overall performance of hybrid memory systems by migrating frequently accessed (hot) data to faster memory. However, designing an efficient DMS is challenging since the key ...
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This paper proposes a novel method for early action prediction based on 3D skeleton data. Our method combines the advantages of graph convolutional networks (GCNs) and adversarial learning to avoid the problems of ins...
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This paper proposes a novel method for early action prediction based on 3D skeleton data. Our method combines the advantages of graph convolutional networks (GCNs) and adversarial learning to avoid the problems of insufficient spatio-temporal feature extraction and difficulty in predicting actions in the early execution stage of actions. In our method, GCNs, which have outstanding performance in the field of action recognition, are used to extract the spatio-temporal features of the skeleton. The model learns how to optimize the feature distribution of partial videos from the features of full videos through adversarial learning. Experiments on two challenging action prediction datasets show that our method performs well on skeleton-based early action prediction. State-of-the-art performance is reported in some observation ratios.
With the proposal of a“smart battery,”real-time sensing by rechargeable batteries has become progressively more important in both fundamental research and practical ***,many traditional sensing technologies suffer f...
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With the proposal of a“smart battery,”real-time sensing by rechargeable batteries has become progressively more important in both fundamental research and practical ***,many traditional sensing technologies suffer from low sensitivity,large size,and electromagnetic interference problems,rendering them unusable in the harsh and complicated electrochemical environments of *** optical sensor is an alternative approach to realize multiple-parameter,multiple-point measurements ***,it has garnered significant *** analyzing these measured parameters,the state of interest can be decoded to monitor a battery's *** review summarizes current progress in optical sensing techniques for batteries with respect to various sensing parameters,discussing the current limitations of optical fiber sensors as well as directions for their future development.
The traditional telecommunications band performs poorly in harsh weather conditions due to atmospheric absorption. In recent years, researchers have begun to study optical communication through atmospheric windows, an...
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The traditional telecommunications band performs poorly in harsh weather conditions due to atmospheric absorption. In recent years, researchers have begun to study optical communication through atmospheric windows, and optical switches are an essential component of optical communication. A broadband atmospheric window optical switch was proposed based on Vanadium dioxide and magnetic polaritons(MP). It is formed by the stacking of two metal-dielectric-metal structures. The simulation results show that the modulation depth can reach 98.38%, and the extinction ratio is 17.93 dB. By calculating the magnetic field, we confirmed that the reason for the “off” mode is the coupling between the different MP modes, while the “on”mode is the excitation of MP. The optical switch we proposed may be applied to radiation cooling and optical satellite communication.
Mid-infrared wavelength switchable and dual-wavelength random laser output has many potential applications.A polarization-maintaining random fiber Bragg grating(PMRFBG)array based on the photonic localization effect o...
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Mid-infrared wavelength switchable and dual-wavelength random laser output has many potential applications.A polarization-maintaining random fiber Bragg grating(PMRFBG)array based on the photonic localization effect of longitudinal invariant transverse disorder in fiber structure is proposed,which can be used as random feedback of dual-wavelength and wavelength switchable output of random fiber laser(RFL).The random fiber Bragg grating(RFBG)array was designed on the panda-type polarization-maintaining fiber(PMF),and the two center wavelengths were 2151.60 nm and 2152.22 nm,*** RFBG array was designed on the bow tie-type PMF,and the two center wavelengths were obtained,which were 2153.08 nm and 2153.96 nm,*** RFBG array with a center wavelength of 2139.27 nm was designed on single-mode fiber(SMF).The length of individual fiber Bragg grating(FBG)and PMRFBG,the refractive index modulation depth,the number of cascaded gratings,and the distance between gratings have different effects on the full width at half maximum(FWHM)and reflectance of the RFBG and PMRFBG array,but not on the central wavelength,as obtained by simulation using the transmission matrix *** designed PMRFBG array provides theoretical support for the design of the feedback mechanism of RFL.
Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors (SPMSMs) due to its strong robustness against measurement and system noise. However, conventional meth...
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When humanoid robots attempt to walk on terrain such as shaking platforms,time-varying disturbances are introduced to the support *** abrupt changes of inclination angle can cause the robot to lose balance upon landin...
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When humanoid robots attempt to walk on terrain such as shaking platforms,time-varying disturbances are introduced to the support *** abrupt changes of inclination angle can cause the robot to lose balance upon landing,presenting significant challenges for balance control *** address this issue,we propose a novel divergent component of motion(DCM)-based time-varying disturbance walking(DCM-TVDW)*** method allows the robot to walk on rugged surfaces and helps to maintain dynamic balance when subjected to large time-varying *** the DCM-TVDW control method,we first adjust the robot's center of mass and stride height to adapt to transitions between different terrain types via a variable height stabilization method,and hold these quantities constant as base *** then combine DCM with the N-step capturability *** combination allows for dynamic balance through multi-step adjustments from the initially unstable region,thereby extending the robots stability *** and experimental results demonstrate that the DCM-TVDW method enables the SJ-Bruce robot to traverse a dynamically shaking platform with an inclination angle of approximately 22°.
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