The Industrial Internet of Things(IIoT)is increasingly vulnerable to sophisticated cyber threats,particularly zero-day attacks that exploit unknown vulnerabilities and evade traditional security measures.To address th...The Industrial Internet of Things(IIoT)is increasingly vulnerable to sophisticated cyber threats,particularly zero-day attacks that exploit unknown vulnerabilities and evade traditional security measures.To address this critical challenge,this paper proposes a dynamic defense framework named Zero-day-aware Stackelberg Game-based Multi-Agent Distributed Deep Deterministic Policy Gradient(ZSG-MAD3PG).The framework integrates Stackelberg game modeling with the Multi-Agent Distributed Deep Deterministic Policy Gradient(MAD3PG)algorithm and incorporates defensive deception(DD)strategies to achieve adaptive and efficient protection.While conventional methods typically incur considerable resource overhead and exhibit higher latency due to static or rigid defensive mechanisms,the proposed ZSG-MAD3PG framework mitigates these limitations through multi-stage game modeling and adaptive learning,enabling more efficient resource utilization and faster response times.The Stackelberg-based architecture allows defenders to dynamically optimize packet sampling strategies,while attackers adjust their tactics to reach rapid equilibrium.Furthermore,dynamic deception techniques reduce the time required for the concealment of attacks and the overall system burden.A lightweight behavioral fingerprinting detection mechanism further enhances real-time zero-day attack identification within industrial device clusters.ZSG-MAD3PG demonstrates higher true positive rates(TPR)and lower false alarm rates(FAR)compared to existing methods,while also achieving improved latency,resource efficiency,and stealth adaptability in IIoT zero-day defense scenarios.展开更多
GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieve...GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.展开更多
The rise in construction activities within mountainous regions has significantly increased the frequency of rockfalls.Statistical models for rockfall hazard assessment often struggle to achieve high precision on a lar...The rise in construction activities within mountainous regions has significantly increased the frequency of rockfalls.Statistical models for rockfall hazard assessment often struggle to achieve high precision on a large scale.This limitation arises primarily from the scarcity of historical rockfall data and the inadequacy of conventional assessment indicators in capturing the physical and structural characteristics of rockfalls.This study proposes a physically based deterministic model designed to accurately quantify rockfall hazards at a large scale.The model accounts for multiple rockfall failure modes and incorporates the key physical and structural parameters of the rock mass.Rockfall hazard is defined as the product of three factors:the rockfall failure probability,the probability of reaching a specific position,and the corresponding impact intensity.The failure probability includes probabilities of formation and instability of rock blocks under different failure modes,modeled based on the combination patterns of slope surfaces and rock discontinuities.The Monte Carlo method is employed to account for the randomness of mechanical and geometric parameters when quantifying instability probabilities.Additionally,the rock trajectories and impact energies simulated using Flow-R software are combined with rockfall failure probability to enable regional rockfall hazard zoning.A case study was conducted in Tiefeng,Chongqing,China,considering four types of rockfall failure modes.Hazard zoning results identified the steep and elevated terrains of the northern and southern anaclinal slopes as areas of highest rockfall hazard.These findings align with observed conditions,providing detailed hazard zoning and validating the effectiveness and potential of the proposed model.展开更多
Background:Combined knee valgus and tibial internal rotation(VL+IR)moments have been shown to stress the anterior cruciate ligament(ACL)in several in vitro cadaveric studies.To utilize this knowledge for non-contact A...Background:Combined knee valgus and tibial internal rotation(VL+IR)moments have been shown to stress the anterior cruciate ligament(ACL)in several in vitro cadaveric studies.To utilize this knowledge for non-contact ACL injury prevention in sports,it is necessary to elucidate how the ground reaction force(GRF)acting point(center of pressure(CoP))in the stance foot produces combined knee VL+IR moments in risky maneuvers,such as cuttings.However,the effects of the GRF acting point on the development of the combined knee VL+IR moment in cutting are still unknown.Methods:We first established the deterministic mechanical condition that the CoP position relative to the tibial rotational axis differentiates the GRF vector’s directional probability for developing the combined knee VL+IR moment,and theoretically predicted that when the CoP is posterior to the tibial rotational axis,the GRF vector is more likely to produce the combined knee VL+IR moment than when the CoP is anterior to the tibial rotational axis.Then,we tested a stochastic aspect of our theory in a lab-controlled in vivo experiment.Fourteen females performed 60˚cutting under forefoot/rearfoot strike conditions(10 trials each).The positions of lower limb markers and GRF data were measured,and the knee moment due to GRF vector was calculated.The trials were divided into anterior-and posterior-CoP groups depending on the CoP position relative to the tibial rotational axis at each 10 ms interval from 0 to 100 ms after foot strike,and the occurrence rate of the combined knee VL+IR moment was compared between trial groups.Results:The posterior-CoP group showed significantly higher occurrence rates of the combined knee VL+IR moment(maximum of 82.8%)at every time point than those of the anterior-CoP trials,as theoretically predicted by the deterministic mechanical condition.Conclusion:The rearfoot strikes inducing the posterior CoP should be avoided to reduce the risk of non-contact ACL injury associated with the combined knee VL+IR stress.展开更多
Emerging long-range industrial IoT applications(e.g.,remote patient monitoring)have increasingly higher requirements for global deterministic delay.Although many existing methods have built deterministic networks in s...Emerging long-range industrial IoT applications(e.g.,remote patient monitoring)have increasingly higher requirements for global deterministic delay.Although many existing methods have built deterministic networks in small-scale networks through centralized computing and resource reservation,they cannot be applied on a global scale.The emerging mega-constellations enable new opportunities for realizing deterministic delay globally.As one constellation(e.g.,Starlink)might be managed by a single operator(e.g.,SpaceX),packets can be routed within deterministic number of hops.Moreover,the path diversity brought by the highly symmetrical network structure in mega-constellations can help to construct a congestion free network by routing.This paper leverages these unique characteristics of mega-constellations to avoid the traditional network congestion caused by multiple inputs and single output,and to determine the routing hops,and thus realizing a global deterministic network(DETSPACE).The model based on the 2D Markov chain theoretically verifies the correctness of DETSPACE.The effectiveness of DETSPACE in different traffic load con-ditions is also verified by extensive simulations.展开更多
Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical challenge.In particular,traffic roundabouts bring a set of challenges to autonom...Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical challenge.In particular,traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles,susceptibility to traffic flow bottlenecks,and imperfect data in perceiving environmental information,rendering them a vital issue in the practical application of autonomous driving.To address the traffic challenges,this work focused on complex roundabouts with multi-lane and proposed a Perception EnhancedDeepDeterministic Policy Gradient(PE-DDPG)for AutonomousDriving in the Roundabouts.Specifically,themodel incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework,enhancing the vehicle’s capability to comprehend complex roundabout environments and make decisions.Furthermore,the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios,effectively mitigating traffic bottlenecks and augmenting throughput efficiency.Extensive experiments were conducted with the collaborative simulation platform of CARLA and SUMO,and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process,the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles(AVs).Generally,the proposed PE-DDPGmodel could be employed for autonomous driving in complex scenarios with imperfect data.展开更多
Naturally fractured rocks contain most of the world's petroleum reserves.This significant amount of oil can be recovered efficiently by gas assisted gravity drainage(GAGD).Although,GAGD is known as one of the most...Naturally fractured rocks contain most of the world's petroleum reserves.This significant amount of oil can be recovered efficiently by gas assisted gravity drainage(GAGD).Although,GAGD is known as one of the most effective recovery methods in reservoir engineering,the lack of available simulation and mathematical models is considerable in these kinds of reservoirs.The main goal of this study is to provide efficient and accurate methods for predicting the GAGD recovery factor using data driven techniques.The proposed models are developed to relate GAGD recovery factor to the various parameters including model height,matrix porosity and permeability,fracture porosity and permeability,dip angle,viscosity and density of wet and non-wet phases,injection rate,and production time.In this investigation,by considering the effective parameters on GAGD recovery factor,three different efficient,smart,and fast models including artificial neural network(ANN),least square support vector machine(LSSVM),and multi-gene genetic programming(MGGP)are developed and compared in both fractured and homogenous porous media.Buckinghamπtheorem is also used to generate dimensionless numbers to reduce the number of input and output parameters.The efficiency of the proposed models is examined through statistical analysis of R-squared,RMSE,MSE,ARE,and AARE.Moreover,the performance of the generated MGGP correlation is compared to the traditional models.Results demonstrate that the ANN model predicts the GAGD recovery factor more accurately than the LSSVM and MGGP models.The maximum R^(2)of 0.9677 and minimum RMSE of 0.0520 values are obtained by the ANN model.Although the MGGP model has the lowest performance among the other used models(the R2 of 0.896 and the RMSE of 0.0846),the proposed MGGP correlation can predict the GAGD recovery factor in fractured and homogenous reservoirs with high accuracy and reliability compared to the traditional models.Results reveal that the employed models can easily predict GAGD recovery factor without requiring complicate governing equations or running complex and time-consuming simulation models.The approach of this research work improves our understanding about the most significant parameters on GAGD recovery and helps to optimize the stages of the process,and make appropriate economic decisions.展开更多
Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary a...Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.展开更多
The large-photon-number quantum state is a fundamental but nonresolved request for practical quantum information applications.We propose an N-photon state generation scheme that is feasible and scalable,using lithium ...The large-photon-number quantum state is a fundamental but nonresolved request for practical quantum information applications.We propose an N-photon state generation scheme that is feasible and scalable,using lithium niobate on insulator circuits.Such a scheme is based on the integration of a common building block called photon-number doubling unit(PDU)for deterministic single-photon parametric downconversion and upconversion.The PDU relies on a 107-optical-quality-factor resonator and mW-level on-chip power,which is within the current fabrication and experimental limits.N-photon state generation schemes,with cluster and Greenberger–Horne–Zeilinger state as examples,are shown for different quantum tasks.展开更多
The separation and detection of particles in suspension are essential for a wide spectrum of applications including medical diagnostics.In this field,microfluidic deterministic lateral displacement(DLD)holds a promise...The separation and detection of particles in suspension are essential for a wide spectrum of applications including medical diagnostics.In this field,microfluidic deterministic lateral displacement(DLD)holds a promise due to the ability of continuous separation of particles by size,shape,deformability,and electrical properties with high resolution.DLD is a passive microfluidic separation technique that has been widely implemented for various bioparticle separations from blood cells to exosomes.DLD techniques have been previously reviewed in 2014.Since then,the field has matured as several physics of DLD have been updated,new phenomena have been discovered,and various designs have been presented to achieve a higher separation performance and throughput.Furthermore,some recent progress has shown new clinical applications and ability to use the DLD arrays as a platform for biomolecules detection.This review provides a thorough discussion on the recent progress in DLD with the topics based on the fundamental studies on DLD models and applications for particle separation and detection.Furthermore,current challenges and potential solutions of DLD are also discussed.We believe that a comprehensive understanding on DLD techniques could significantly contribute toward the advancements in the field for various applications.In particular,the rapid,low-cost,and high-throughput particle separation and detection with DLD have a tremendous impact for point-of-care diagnostics.展开更多
A novel efficient deterministic secure quantum communication scheme based on four-qubit cluster states and single-photon identity authentication is proposed. In this scheme, the two authenticated users can transmit tw...A novel efficient deterministic secure quantum communication scheme based on four-qubit cluster states and single-photon identity authentication is proposed. In this scheme, the two authenticated users can transmit two bits of classical information per cluster state, and its efficiency of the quantum communication is 1/3, which is approximately 1.67 times that of the previous protocol presented by Wang et al [Chin. Phys. Lett. 23 （2006） 2658]. Security analysis shows the present scheme is secure against intercept-resend attack and the impersonator＇s attack. Furthermore, it is more economic with present-day techniques and easily processed by a one-way quantum computer.展开更多
The average-passage equation system （APES） provides a rigorous mathematical framework for account- ing for the unsteady blade row interaction through multistage compressors in steady state environment by introducing...The average-passage equation system （APES） provides a rigorous mathematical framework for account- ing for the unsteady blade row interaction through multistage compressors in steady state environment by introducing de- terministic correlations （DC） that need to be modeled to close the equation system. The primary purpose of this study was to provide insight into the DC characteristics and the in- fluence of DC on the time-averaged flow field of the APES. In Part 2 of this two-part paper, the influence of DC on the time-averaged flow field was systematically studied; Several time-averaging computations boundary conditions and DC were conducted with various for the downstream stator in a transonic compressor stage, by employing the CFD solver developed in Part 1 of this two-part paper. These results were compared with the time-averaged unsteady flow field and the steady one. The study indicat;d that the circumferential- averaged DC can take into account major part of the unsteady effects on spanwise redistribution of flow fields in compres- sors. Furthermore, it demonstrated that both deterministic stresses and deterministic enthalpy fluxes are necessary to reproduce the time-averaged flow field.展开更多
A method for electrocardiogram （ECG） pattern modeling and recognition via deterministic learning theory is presented in this paper. Instead of recognizing ECG signals beat-to-beat, each ECG signal which contains a n...A method for electrocardiogram （ECG） pattern modeling and recognition via deterministic learning theory is presented in this paper. Instead of recognizing ECG signals beat-to-beat, each ECG signal which contains a number of heartbeats is recognized. The method is based entirely on the temporal features （i.e., the dynamics） of ECG patterns, which contains complete information of ECG patterns. A dynamical model is employed to demonstrate the method, which is capable of generating synthetic ECG signals. Based on the dynamical model, the method is shown in the following two phases： the identification （training） phase and the recognition （test） phase. In the identification phase, the dynamics of ECG patterns is accurately modeled and expressed as constant RBF neural weights through the deterministic learning. In the recognition phase, the modeling results are used for ECG pattern recognition. The main feature of the proposed method is that the dynamics of ECG patterns is accurately modeled and is used for ECG pattern recognition. Experimental studies using the Physikalisch-Technische Bundesanstalt （PTB） database are included to demonstrate the effectiveness of the approach.展开更多
The average-passage equation system （APES） provides a rigorous mathematical framework for account- ing for the unsteady blade row interaction through multi- stage compressors in steady state environment by introduc-...The average-passage equation system （APES） provides a rigorous mathematical framework for account- ing for the unsteady blade row interaction through multi- stage compressors in steady state environment by introduc- ing deterministic correlations （DC） that need to be modeled to close the equation system. The primary purpose of this study is to provide insight into the DC characteristics and the influence of DC on the time-averaged flow field of the APES. In Part 1 of this two-part paper, firstly a 3D viscous unsteady and time-averaging flow CFD solver is developed to investi- gate the APES technique. Then steady and unsteady simu- lations are conducted in a transonic compressor stage. The results from both simulations are compared to highlight the significance of the unsteady interactions. Furthermore, the distribution characteristics of DC are studied and the DC at the rotor/stator interface are compared with their spatial cor- relations （SC）. Lastly, steady and time-averaging （employing APES with DC） simulations for the downstream stator alone are conducted employing DC derived from the unsteady re- suits. The results from steady and time-averaging simula- tions are compared with the time-averaged unsteady results. The comparisons demonstrate that the simulation employing APES with DC can reproduce the time-averaged field and the 3D viscous time-averaging flow solver is validated.展开更多
Community resilience is becoming a growing concern for authorities and decision makers.This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework.PEOPLES...Community resilience is becoming a growing concern for authorities and decision makers.This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework.PEOPLES is a multi-layered framework that defines community resilience using seven dimensions.Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator’s performance.The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community.The second method exploits a knowledge-based fuzzy modeling for its implementation.This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis.The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community.The paper also introduces an open source online tool in which the first method is implemented.A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.展开更多
We present a novel protocol for deterministic secure quantum communication by using the lour-qubit cluster state as quantum channel. It is shown that two legitimate users can directly transmit the secret messages base...We present a novel protocol for deterministic secure quantum communication by using the lour-qubit cluster state as quantum channel. It is shown that two legitimate users can directly transmit the secret messages based on Bellbasis measurements and classical communication. The present protocol makes use of the ideas of block transmission and decoy particle checking technique. It has a high capacity as each cluster state can carry two 5its of information, and has a high intrinsic efficieney 5ecause almost all the instances except the decoy checking particles （its numSer is negligible） are useful. Furthermore, this protocol is feasible with present-day technique.展开更多
The deterministic lateral displacement (DLD) is an important method used to sort particles and cells of different sizes. In this paper, the flexible cell sorting with the DLD method is studied by using a numerical mod...The deterministic lateral displacement (DLD) is an important method used to sort particles and cells of different sizes. In this paper, the flexible cell sorting with the DLD method is studied by using a numerical model based on the immersed boundary-lattice Boltzmann method (IB-LBM). In this model, the fluid motion is solved by the LBM, and the cell membrane-fluid interaction is modeled with the LBM. The proposed model is validated by simulating the rigid particle sorted with the DLD method, and the results are found in good agreement with those measured in experiments. We first study the effect of flexibility on a single cell and multiple cells continuously going through a DLD device. It is found that the cell flexibility can significantly affect the cell path, which means the flexibility could have significant effects on the continuous cell sorting by the DLD method. The sorting characteristics of white blood cells and red blood cells are further studied by varying the spatial distribution of cylinder arrays and the initial cell-cell distance. The numerical results indicate that a well concentrated cell sorting can be obtained under a proper arrangement of cylinder arrays and a large enough initial cell-cell distance.展开更多
The results of an accident analysis for the loss of offsite power(LOOP)scenario in a reference Bushehr-1 VVER-1000/V446 nuclear power plant(NPP)are presented in this paper.This study attempted to provide a better anal...The results of an accident analysis for the loss of offsite power(LOOP)scenario in a reference Bushehr-1 VVER-1000/V446 nuclear power plant(NPP)are presented in this paper.This study attempted to provide a better analysis of LOOP accident management by integrating deterministic and probabilistic approaches.The RELAP5 code was used to investigate the occurrence of specific thermal–hydraulic phenomena.The probabilistic safety assessment of the LOOP accident is presented using the SAPHIRE software.LOOP accident data were extracted from the Bushehr NPP final safety analysis reports and probabilistic safety analysis reports.A deterministic approach was used to reduce the core damage frequency in the probabilistic analysis of LOOP accidents.The probabilistic approach was used to better observe the philosophy of defense in depth and safety margins in the deterministic analysis of the LOOP accident.The results show that the integration of the two approaches in LOOP accident investigations improved accident control.展开更多
We propose two schemes for quantum secure direct communication (QSDC) and deterministic securequantum communication (DSQC) over collective dephasing noisy channel.In our schemes,four special two-qubit statesare used a...We propose two schemes for quantum secure direct communication (QSDC) and deterministic securequantum communication (DSQC) over collective dephasing noisy channel.In our schemes,four special two-qubit statesare used as the quantum channel.Since these states are unchanged through the collective dephasing noisy channel,the effect of the channel noise can be perfectly overcome.Simultaneously,the security against some usual attacks canbe ensured by utilizing the various checking procedures.Furthermore,these two schemes are feasible with present-daytechnique.展开更多
Recently, an approach for the rapid detection of small oscillation faults based on deterministic learning theory was proposed for continuous-time systems. In this paper, a fault detection scheme is proposed for a clas...Recently, an approach for the rapid detection of small oscillation faults based on deterministic learning theory was proposed for continuous-time systems. In this paper, a fault detection scheme is proposed for a class of nonlinear discrete-time systems via deterministic learning. By using a discrete-time extension of deterministic learning algorithm, the general fault functions （i.e., the internal dynamics） underlying normal and fault modes of nonlinear discrete-time systems are locally-accurately approximated by discrete-time dynamical radial basis function （RBF） networks. Then, a bank of estimators with the obtained knowledge of system dynamics embedded is constructed, and a set of residuals are obtained and used to measure the differences between the dynamics of the monitored system and the dynamics of the trained systems. A fault detection decision scheme is presented according to the smallest residual principle, i.e., the occurrence of a fault can be detected in a discrete-time setting by comparing the magnitude of residuals. The fault detectability analysis is carried out and the upper bound of detection time is derived. A simulation example is given to illustrate the effectiveness of the proposed scheme.展开更多
基金funded in part by the Humanities and Social Sciences Planning Foundation of Ministry of Education of China under Grant No.24YJAZH123National Undergraduate Innovation and Entrepreneurship Training Program of China under Grant No.202510347069the Huzhou Science and Technology Planning Foundation under Grant No.2023GZ04.
文摘The Industrial Internet of Things(IIoT)is increasingly vulnerable to sophisticated cyber threats,particularly zero-day attacks that exploit unknown vulnerabilities and evade traditional security measures.To address this critical challenge,this paper proposes a dynamic defense framework named Zero-day-aware Stackelberg Game-based Multi-Agent Distributed Deep Deterministic Policy Gradient(ZSG-MAD3PG).The framework integrates Stackelberg game modeling with the Multi-Agent Distributed Deep Deterministic Policy Gradient(MAD3PG)algorithm and incorporates defensive deception(DD)strategies to achieve adaptive and efficient protection.While conventional methods typically incur considerable resource overhead and exhibit higher latency due to static or rigid defensive mechanisms,the proposed ZSG-MAD3PG framework mitigates these limitations through multi-stage game modeling and adaptive learning,enabling more efficient resource utilization and faster response times.The Stackelberg-based architecture allows defenders to dynamically optimize packet sampling strategies,while attackers adjust their tactics to reach rapid equilibrium.Furthermore,dynamic deception techniques reduce the time required for the concealment of attacks and the overall system burden.A lightweight behavioral fingerprinting detection mechanism further enhances real-time zero-day attack identification within industrial device clusters.ZSG-MAD3PG demonstrates higher true positive rates(TPR)and lower false alarm rates(FAR)compared to existing methods,while also achieving improved latency,resource efficiency,and stealth adaptability in IIoT zero-day defense scenarios.
基金supported by the National Natural Science Foundation of China(Grant Nos.42404017,42122025 and 42174030).
文摘GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.
基金supported by the National Natural Science Foundation of China(Grant Nos.42172318 and 42377186)the National Key R&D Program of China(Grant No.2023YFC3007201).
文摘The rise in construction activities within mountainous regions has significantly increased the frequency of rockfalls.Statistical models for rockfall hazard assessment often struggle to achieve high precision on a large scale.This limitation arises primarily from the scarcity of historical rockfall data and the inadequacy of conventional assessment indicators in capturing the physical and structural characteristics of rockfalls.This study proposes a physically based deterministic model designed to accurately quantify rockfall hazards at a large scale.The model accounts for multiple rockfall failure modes and incorporates the key physical and structural parameters of the rock mass.Rockfall hazard is defined as the product of three factors:the rockfall failure probability,the probability of reaching a specific position,and the corresponding impact intensity.The failure probability includes probabilities of formation and instability of rock blocks under different failure modes,modeled based on the combination patterns of slope surfaces and rock discontinuities.The Monte Carlo method is employed to account for the randomness of mechanical and geometric parameters when quantifying instability probabilities.Additionally,the rock trajectories and impact energies simulated using Flow-R software are combined with rockfall failure probability to enable regional rockfall hazard zoning.A case study was conducted in Tiefeng,Chongqing,China,considering four types of rockfall failure modes.Hazard zoning results identified the steep and elevated terrains of the northern and southern anaclinal slopes as areas of highest rockfall hazard.These findings align with observed conditions,providing detailed hazard zoning and validating the effectiveness and potential of the proposed model.
基金supported by the Grant-in-Aid for Young Scientists(B)Project(Grant No.24700716)funded by the Ministry of Education,Culture,Sports,Science and Technology,Japan.
文摘Background:Combined knee valgus and tibial internal rotation(VL+IR)moments have been shown to stress the anterior cruciate ligament(ACL)in several in vitro cadaveric studies.To utilize this knowledge for non-contact ACL injury prevention in sports,it is necessary to elucidate how the ground reaction force(GRF)acting point(center of pressure(CoP))in the stance foot produces combined knee VL+IR moments in risky maneuvers,such as cuttings.However,the effects of the GRF acting point on the development of the combined knee VL+IR moment in cutting are still unknown.Methods:We first established the deterministic mechanical condition that the CoP position relative to the tibial rotational axis differentiates the GRF vector’s directional probability for developing the combined knee VL+IR moment,and theoretically predicted that when the CoP is posterior to the tibial rotational axis,the GRF vector is more likely to produce the combined knee VL+IR moment than when the CoP is anterior to the tibial rotational axis.Then,we tested a stochastic aspect of our theory in a lab-controlled in vivo experiment.Fourteen females performed 60˚cutting under forefoot/rearfoot strike conditions(10 trials each).The positions of lower limb markers and GRF data were measured,and the knee moment due to GRF vector was calculated.The trials were divided into anterior-and posterior-CoP groups depending on the CoP position relative to the tibial rotational axis at each 10 ms interval from 0 to 100 ms after foot strike,and the occurrence rate of the combined knee VL+IR moment was compared between trial groups.Results:The posterior-CoP group showed significantly higher occurrence rates of the combined knee VL+IR moment(maximum of 82.8%)at every time point than those of the anterior-CoP trials,as theoretically predicted by the deterministic mechanical condition.Conclusion:The rearfoot strikes inducing the posterior CoP should be avoided to reduce the risk of non-contact ACL injury associated with the combined knee VL+IR stress.
基金This work is supported by National Key Research and Development Plan of China(2022YFB3105204).
文摘Emerging long-range industrial IoT applications(e.g.,remote patient monitoring)have increasingly higher requirements for global deterministic delay.Although many existing methods have built deterministic networks in small-scale networks through centralized computing and resource reservation,they cannot be applied on a global scale.The emerging mega-constellations enable new opportunities for realizing deterministic delay globally.As one constellation(e.g.,Starlink)might be managed by a single operator(e.g.,SpaceX),packets can be routed within deterministic number of hops.Moreover,the path diversity brought by the highly symmetrical network structure in mega-constellations can help to construct a congestion free network by routing.This paper leverages these unique characteristics of mega-constellations to avoid the traditional network congestion caused by multiple inputs and single output,and to determine the routing hops,and thus realizing a global deterministic network(DETSPACE).The model based on the 2D Markov chain theoretically verifies the correctness of DETSPACE.The effectiveness of DETSPACE in different traffic load con-ditions is also verified by extensive simulations.
基金supported in part by the projects of the National Natural Science Foundation of China(62376059,41971340)Fujian Provincial Department of Science and Technology(2023XQ008,2023I0024,2021Y4019),Fujian Provincial Department of Finance(GY-Z230007,GYZ23012)Fujian Key Laboratory of Automotive Electronics and Electric Drive(KF-19-22001).
文摘Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical challenge.In particular,traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles,susceptibility to traffic flow bottlenecks,and imperfect data in perceiving environmental information,rendering them a vital issue in the practical application of autonomous driving.To address the traffic challenges,this work focused on complex roundabouts with multi-lane and proposed a Perception EnhancedDeepDeterministic Policy Gradient(PE-DDPG)for AutonomousDriving in the Roundabouts.Specifically,themodel incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework,enhancing the vehicle’s capability to comprehend complex roundabout environments and make decisions.Furthermore,the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios,effectively mitigating traffic bottlenecks and augmenting throughput efficiency.Extensive experiments were conducted with the collaborative simulation platform of CARLA and SUMO,and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process,the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles(AVs).Generally,the proposed PE-DDPGmodel could be employed for autonomous driving in complex scenarios with imperfect data.
文摘Naturally fractured rocks contain most of the world's petroleum reserves.This significant amount of oil can be recovered efficiently by gas assisted gravity drainage(GAGD).Although,GAGD is known as one of the most effective recovery methods in reservoir engineering,the lack of available simulation and mathematical models is considerable in these kinds of reservoirs.The main goal of this study is to provide efficient and accurate methods for predicting the GAGD recovery factor using data driven techniques.The proposed models are developed to relate GAGD recovery factor to the various parameters including model height,matrix porosity and permeability,fracture porosity and permeability,dip angle,viscosity and density of wet and non-wet phases,injection rate,and production time.In this investigation,by considering the effective parameters on GAGD recovery factor,three different efficient,smart,and fast models including artificial neural network(ANN),least square support vector machine(LSSVM),and multi-gene genetic programming(MGGP)are developed and compared in both fractured and homogenous porous media.Buckinghamπtheorem is also used to generate dimensionless numbers to reduce the number of input and output parameters.The efficiency of the proposed models is examined through statistical analysis of R-squared,RMSE,MSE,ARE,and AARE.Moreover,the performance of the generated MGGP correlation is compared to the traditional models.Results demonstrate that the ANN model predicts the GAGD recovery factor more accurately than the LSSVM and MGGP models.The maximum R^(2)of 0.9677 and minimum RMSE of 0.0520 values are obtained by the ANN model.Although the MGGP model has the lowest performance among the other used models(the R2 of 0.896 and the RMSE of 0.0846),the proposed MGGP correlation can predict the GAGD recovery factor in fractured and homogenous reservoirs with high accuracy and reliability compared to the traditional models.Results reveal that the employed models can easily predict GAGD recovery factor without requiring complicate governing equations or running complex and time-consuming simulation models.The approach of this research work improves our understanding about the most significant parameters on GAGD recovery and helps to optimize the stages of the process,and make appropriate economic decisions.
文摘Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.
基金supported by the National Key R&D Program of China(No.2019YFA0705000)the Key R&D Program of Guangdong Province(No.2018B030329001)+4 种基金the Leading-edge Technology Program of Jiangsu Natural Science Foundation(No.BK20192001)the National Natural Science Foundation of China(Nos.51890861,11690033,and 11974178)the Excellent Research Program of Nanjing University(No.ZYJH002)the support of the National Postdoctoral Program for Innovative Talents(No.BX2021122)China Postdoctoral Science Foundation(No.2022M711570).
文摘The large-photon-number quantum state is a fundamental but nonresolved request for practical quantum information applications.We propose an N-photon state generation scheme that is feasible and scalable,using lithium niobate on insulator circuits.Such a scheme is based on the integration of a common building block called photon-number doubling unit(PDU)for deterministic single-photon parametric downconversion and upconversion.The PDU relies on a 107-optical-quality-factor resonator and mW-level on-chip power,which is within the current fabrication and experimental limits.N-photon state generation schemes,with cluster and Greenberger–Horne–Zeilinger state as examples,are shown for different quantum tasks.
基金the scholarship from NUS Graduate School for integrative science and engineering and funding support from Ministry of Education Academic Research Fund,Singapore(AcRF:R-397-000-270-114,R-397-000-183-112).
文摘The separation and detection of particles in suspension are essential for a wide spectrum of applications including medical diagnostics.In this field,microfluidic deterministic lateral displacement(DLD)holds a promise due to the ability of continuous separation of particles by size,shape,deformability,and electrical properties with high resolution.DLD is a passive microfluidic separation technique that has been widely implemented for various bioparticle separations from blood cells to exosomes.DLD techniques have been previously reviewed in 2014.Since then,the field has matured as several physics of DLD have been updated,new phenomena have been discovered,and various designs have been presented to achieve a higher separation performance and throughput.Furthermore,some recent progress has shown new clinical applications and ability to use the DLD arrays as a platform for biomolecules detection.This review provides a thorough discussion on the recent progress in DLD with the topics based on the fundamental studies on DLD models and applications for particle separation and detection.Furthermore,current challenges and potential solutions of DLD are also discussed.We believe that a comprehensive understanding on DLD techniques could significantly contribute toward the advancements in the field for various applications.In particular,the rapid,low-cost,and high-throughput particle separation and detection with DLD have a tremendous impact for point-of-care diagnostics.
基金Project supported by the National Natural Science Foundation of China (Grant Nos 60572071 and 60873101)Natural Science Foundation of Jiangsu Province (Grant Nos BM2006504, BK2007104 and BK2008209)College Natural Science Foundation of Jiangsu Province (Grant No 06KJB520137)
文摘A novel efficient deterministic secure quantum communication scheme based on four-qubit cluster states and single-photon identity authentication is proposed. In this scheme, the two authenticated users can transmit two bits of classical information per cluster state, and its efficiency of the quantum communication is 1/3, which is approximately 1.67 times that of the previous protocol presented by Wang et al [Chin. Phys. Lett. 23 （2006） 2658]. Security analysis shows the present scheme is secure against intercept-resend attack and the impersonator＇s attack. Furthermore, it is more economic with present-day techniques and easily processed by a one-way quantum computer.
基金supported by the National Natural Science Foundation of China (51006006,51136003,50976010,50976009)the National Basic Research Program of China (2012CB72 0205)+2 种基金the Aeronautical Science Foundation of China (2010ZB51)the 111 Project (B08009)the National Science Special Foundation for Post-doctoral Scientists of China (201104049)
文摘The average-passage equation system （APES） provides a rigorous mathematical framework for account- ing for the unsteady blade row interaction through multistage compressors in steady state environment by introducing de- terministic correlations （DC） that need to be modeled to close the equation system. The primary purpose of this study was to provide insight into the DC characteristics and the in- fluence of DC on the time-averaged flow field of the APES. In Part 2 of this two-part paper, the influence of DC on the time-averaged flow field was systematically studied; Several time-averaging computations boundary conditions and DC were conducted with various for the downstream stator in a transonic compressor stage, by employing the CFD solver developed in Part 1 of this two-part paper. These results were compared with the time-averaged unsteady flow field and the steady one. The study indicat;d that the circumferential- averaged DC can take into account major part of the unsteady effects on spanwise redistribution of flow fields in compres- sors. Furthermore, it demonstrated that both deterministic stresses and deterministic enthalpy fluxes are necessary to reproduce the time-averaged flow field.
基金supported by the National Science Fund for Distinguished Young Scholars of China(No.61225014)
文摘A method for electrocardiogram （ECG） pattern modeling and recognition via deterministic learning theory is presented in this paper. Instead of recognizing ECG signals beat-to-beat, each ECG signal which contains a number of heartbeats is recognized. The method is based entirely on the temporal features （i.e., the dynamics） of ECG patterns, which contains complete information of ECG patterns. A dynamical model is employed to demonstrate the method, which is capable of generating synthetic ECG signals. Based on the dynamical model, the method is shown in the following two phases： the identification （training） phase and the recognition （test） phase. In the identification phase, the dynamics of ECG patterns is accurately modeled and expressed as constant RBF neural weights through the deterministic learning. In the recognition phase, the modeling results are used for ECG pattern recognition. The main feature of the proposed method is that the dynamics of ECG patterns is accurately modeled and is used for ECG pattern recognition. Experimental studies using the Physikalisch-Technische Bundesanstalt （PTB） database are included to demonstrate the effectiveness of the approach.
基金supported by the National Natural Science Foundation of China (51006006,51136003,50976010,50976009)the National Basic Research Program of China (2012CB720205)+2 种基金the Aeronautical Science Foundation of China (2010ZB51)the 111 Project (B08009)the National Science Special Foundation for Post-doctoral Scientists of China (201104049)
文摘The average-passage equation system （APES） provides a rigorous mathematical framework for account- ing for the unsteady blade row interaction through multi- stage compressors in steady state environment by introduc- ing deterministic correlations （DC） that need to be modeled to close the equation system. The primary purpose of this study is to provide insight into the DC characteristics and the influence of DC on the time-averaged flow field of the APES. In Part 1 of this two-part paper, firstly a 3D viscous unsteady and time-averaging flow CFD solver is developed to investi- gate the APES technique. Then steady and unsteady simu- lations are conducted in a transonic compressor stage. The results from both simulations are compared to highlight the significance of the unsteady interactions. Furthermore, the distribution characteristics of DC are studied and the DC at the rotor/stator interface are compared with their spatial cor- relations （SC）. Lastly, steady and time-averaging （employing APES with DC） simulations for the downstream stator alone are conducted employing DC derived from the unsteady re- suits. The results from steady and time-averaging simula- tions are compared with the time-averaged unsteady results. The comparisons demonstrate that the simulation employing APES with DC can reproduce the time-averaged field and the 3D viscous time-averaging flow solver is validated.
基金European Research Council under Grant Agreement No.ERC_IDEAL RESCUE_637842 of the project IDEAL RESCUE-Integrated Design and Control of Sustainable Communities during Emergencies
文摘Community resilience is becoming a growing concern for authorities and decision makers.This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework.PEOPLES is a multi-layered framework that defines community resilience using seven dimensions.Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator’s performance.The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community.The second method exploits a knowledge-based fuzzy modeling for its implementation.This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis.The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community.The paper also introduces an open source online tool in which the first method is implemented.A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.
基金supported by the Postgraduate Innovation Research Plan from Anhui University under Grant No.20073039
文摘We present a novel protocol for deterministic secure quantum communication by using the lour-qubit cluster state as quantum channel. It is shown that two legitimate users can directly transmit the secret messages based on Bellbasis measurements and classical communication. The present protocol makes use of the ideas of block transmission and decoy particle checking technique. It has a high capacity as each cluster state can carry two 5its of information, and has a high intrinsic efficieney 5ecause almost all the instances except the decoy checking particles （its numSer is negligible） are useful. Furthermore, this protocol is feasible with present-day technique.
基金supported by the National Natural Science Foundation of China (Grant 81301291)the Beijing Higher Education Young Elite Teacher Project (Grant YETP1208)UNSW Special Research Grants Program
文摘The deterministic lateral displacement (DLD) is an important method used to sort particles and cells of different sizes. In this paper, the flexible cell sorting with the DLD method is studied by using a numerical model based on the immersed boundary-lattice Boltzmann method (IB-LBM). In this model, the fluid motion is solved by the LBM, and the cell membrane-fluid interaction is modeled with the LBM. The proposed model is validated by simulating the rigid particle sorted with the DLD method, and the results are found in good agreement with those measured in experiments. We first study the effect of flexibility on a single cell and multiple cells continuously going through a DLD device. It is found that the cell flexibility can significantly affect the cell path, which means the flexibility could have significant effects on the continuous cell sorting by the DLD method. The sorting characteristics of white blood cells and red blood cells are further studied by varying the spatial distribution of cylinder arrays and the initial cell-cell distance. The numerical results indicate that a well concentrated cell sorting can be obtained under a proper arrangement of cylinder arrays and a large enough initial cell-cell distance.
文摘The results of an accident analysis for the loss of offsite power(LOOP)scenario in a reference Bushehr-1 VVER-1000/V446 nuclear power plant(NPP)are presented in this paper.This study attempted to provide a better analysis of LOOP accident management by integrating deterministic and probabilistic approaches.The RELAP5 code was used to investigate the occurrence of specific thermal–hydraulic phenomena.The probabilistic safety assessment of the LOOP accident is presented using the SAPHIRE software.LOOP accident data were extracted from the Bushehr NPP final safety analysis reports and probabilistic safety analysis reports.A deterministic approach was used to reduce the core damage frequency in the probabilistic analysis of LOOP accidents.The probabilistic approach was used to better observe the philosophy of defense in depth and safety margins in the deterministic analysis of the LOOP accident.The results show that the integration of the two approaches in LOOP accident investigations improved accident control.
文摘We propose two schemes for quantum secure direct communication (QSDC) and deterministic securequantum communication (DSQC) over collective dephasing noisy channel.In our schemes,four special two-qubit statesare used as the quantum channel.Since these states are unchanged through the collective dephasing noisy channel,the effect of the channel noise can be perfectly overcome.Simultaneously,the security against some usual attacks canbe ensured by utilizing the various checking procedures.Furthermore,these two schemes are feasible with present-daytechnique.
基金This work was supported by the National Science Fund for Distinguished Young Scholars （No. 61225014）, the National Major Scientific Instruments Development Project （No. 61527811）, the National Natural Science Foundation of China （Nos. 61304084, 61374119）, the Guangdong Natural Science Foundation （No. 2014A030312005）, and the Space Intelligent Control Key Laboratory of Science and Technology for National Defense.
文摘Recently, an approach for the rapid detection of small oscillation faults based on deterministic learning theory was proposed for continuous-time systems. In this paper, a fault detection scheme is proposed for a class of nonlinear discrete-time systems via deterministic learning. By using a discrete-time extension of deterministic learning algorithm, the general fault functions （i.e., the internal dynamics） underlying normal and fault modes of nonlinear discrete-time systems are locally-accurately approximated by discrete-time dynamical radial basis function （RBF） networks. Then, a bank of estimators with the obtained knowledge of system dynamics embedded is constructed, and a set of residuals are obtained and used to measure the differences between the dynamics of the monitored system and the dynamics of the trained systems. A fault detection decision scheme is presented according to the smallest residual principle, i.e., the occurrence of a fault can be detected in a discrete-time setting by comparing the magnitude of residuals. The fault detectability analysis is carried out and the upper bound of detection time is derived. A simulation example is given to illustrate the effectiveness of the proposed scheme.
