Following the fundamental characteristics of the porosity windbreak,this study suggests a new numerical investigation method for the wind field of the windbreak based on the porous medium physical model.This method ca...Following the fundamental characteristics of the porosity windbreak,this study suggests a new numerical investigation method for the wind field of the windbreak based on the porous medium physical model.This method can transform the reasonable matching problem of the porosity and windproof performance of the windbreak into a study of the relationship between the resistance coefficient of the porous medium and the aerodynamic load of the train.This study examines the influence of the hole type on the wind field behind the porosity windbreak.Then,the relationship between the resistance coefficient of the porous medium,the porosity of the windbreak,and the aerodynamic loads of the train is investigated.The results show that the porous media physical model can be used instead of the windbreak geometry to study the windbreak-train aerodynamic performance,and the process of using this method is suggested.展开更多
Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.How...Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.However,real battlefield data is limited,and equivalent experiments are costly.Currently,there is a lack of comprehensive physical modeling and numerical simulation methods for SIRD.To this end,this study proposes a SIRD simulation framework incorporating full-link physical response,which is integrated through the radiative transfer layer,the sensor response layer,and the model-driven layer.In the radiative transfer layer,a coupled dynamic detection model is established to describe the external optical channel response of the SIRD system by combining the infrared radiation model and the geometric measurement model.In the sensor response layer,considering photoelectric conversion and signal processing,the internal signal response model of the SIRD system is established by a hybrid mode of parametric modeling and analog circuit analysis.In the model-driven layer,a cosimulation application based on a three-dimensional virtual environment is proposed to drive the full-link physical model,and a parallel ray tracing method is employed for real-time synchronous simulation.The proposed simulation framework can provide pixel-level signal output and is verified by the measured data.The evaluation results of the root mean square error(RMSE)and the Pearson correlation coefficient(PCC)show that the simulated data and the measured data achieve good consistency,and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals.The proposed simulation framework has the potential to acquire large sample datasets of SIRD under various complex battlefield environments and can provide an effective data source for SIRD application research.展开更多
Red mud is a solid waste discharged in the process of alumina production,and how to realize the efficient recovery of its iron is an urgent problem to be solved.In this study,the iron extraction test and mechanism stu...Red mud is a solid waste discharged in the process of alumina production,and how to realize the efficient recovery of its iron is an urgent problem to be solved.In this study,the iron extraction test and mechanism study of high iron red mud were carried out under the coupling conditions of multiple physical field(microwave field,gas-solid flow field and temperature field)with biomass as the reducing agent.The test results showed that under the optimal conditions,an iron concentrate with a yield of 78.4%,an iron grade of 59.23%,and a recovery rate of 86.65%was obtained.The analyses of XRD,XPS,TEM,and SEM-EDS showed that during the roasting process,the hematite in the high-iron red mud was completely converted to magnetite,and the biomass produced the reductant that provided the magnetization reaction;A large number of cracks and pores appeared in the surface of the hematite reduction product particles,which helped to induce iron minerals to undergo effective mineral phase transformation.The above study provides ideas for the phase transformation and efficient recovery of iron minerals in red mud.展开更多
The spin-exchange relaxation-free atomic gyroscope,with its exceptionally high theoretical precision,demonstrates immense potential to become the next-generation strategic-grade gyroscope.However,due to technological ...The spin-exchange relaxation-free atomic gyroscope,with its exceptionally high theoretical precision,demonstrates immense potential to become the next-generation strategic-grade gyroscope.However,due to technological noise,there is still a significant gap between its actual precision and theoretical precision.This study identifies the key factor limiting the precision of the SERF gyroscope as coupling noise.By optimizing the detection loop structure,a distinction between the dual-axis signals'response to optical and magnetic fields was achieved-where the optical errors responded similarly,while the response to magnetic noise was opposite.Based on the differences in the optical-magnetic response of the dual-axis signals,empirical mode decomposition was used to decompose the dual-axis gyroscope signals into multiple intrinsic mode functions,and Allan deviation analysis was applied to analyze the noise characteristics of the intrinsic mode functions over various periods.This study successfully reveals that optical errors caused by thermal-optical coupling and long-period magnetic noise induced by thermal-magnetic coupling are the dominant factors limiting the long-term stability of the SERF gyroscope.Based on these analyses,the study concludes that to achieve strategic-grade precision for the SERF gyroscope,it is essential to effectively address the noise issues caused by multi-physical field couplings.展开更多
Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems...Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.展开更多
A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on ...A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.展开更多
Objective:Existing research shows that psychotherapists may experience secondary trauma and burnout,often neglecting self-care.This study aims to examine the effectiveness of self-care education in enhancing self-care...Objective:Existing research shows that psychotherapists may experience secondary trauma and burnout,often neglecting self-care.This study aims to examine the effectiveness of self-care education in enhancing self-care efficacy among psychotherapists and explore factors affecting improvements in their self-care abilities.Methods:A self-care workshop was conducted for 159 psychotherapists from various fields.Participants’demographic information and self-care ability data were collected.The Exercise of Self-Care Agency Scale(ESCA)was used to assess the participant’s self-care levels before and after the workshop.Results:Post-workshop,ESCA total scores and subscale scores of participants showed significant increases(all P<0.001).Notably,score improvement levels differed by gender and years of practice,with female therapists showing greater improvement than male therapists(t=2.069,P=0.040)and those with longer work experience showing greater improvement than those with shorter experience(F=2.537,P=0.042).Conclusion:Providing self-care education for psychotherapists is essential.Future self care education programs or interventions for psychotherapists should consider gender and work experience factors to better support their self-care enhancement.展开更多
The stratification phenomenon resulting from differences in the physical properties of solid-liquid components seriously affect the final combustion and explosion characteristics of mixed fuel under the action of osci...The stratification phenomenon resulting from differences in the physical properties of solid-liquid components seriously affect the final combustion and explosion characteristics of mixed fuel under the action of oscillation.The effects of oscillation on the physical stability of mixed fuel with two solid-liquid ratios and three liquid component distribution ratios have been investigated using a self-designed experimental system at oscillation frequencies of 60-300 r/min.The explosion characteristics of mixed fuel before and after oscillation are gained from a 20 L spherical explosion container system.When the mass ratio of liquid components is controlled at 66.9%,64.7%,62.6%the final explosion characteristics are stable,with a maximum difference of only 0.71%.The volume of liquid fuel precipitation increases with increasing oscillation frequency when the mass ratio of liquid components reaches 71.7%,69.6%,67.7%.The fuel explosion overpressure after oscillation decreases with increasing liquid precipitation volume,and the repeatability is poor,with a maximum standard deviation of 82.736,which is much higher than the ratio without stratification.Properly controlling the mass ratio of liquid components of the mixed fuel can effectively combat the impact of oscillation on the physical state and maintain the stability of the final explosion characteristics.展开更多
Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The ...Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The performance of existing long-term navigation algorithm is limited by the cumulative error of inertial sensors, disturbed local magnetic field, and complex motion modes of the pedestrian. This paper develops a robust data and physical model dual-driven based trajectory estimation(DPDD-TE) framework, which can be applied for long-term navigation tasks. A Bi-directional Long Short-Term Memory(Bi-LSTM) based quasi-static magnetic field(QSMF) detection algorithm is developed for extracting useful magnetic observation for heading calibration, and another Bi-LSTM is adopted for walking speed estimation by considering hybrid human motion information under a specific time period. In addition, a data and physical model dual-driven based multi-source fusion model is proposed to integrate basic INS mechanization and multi-level constraint and observations for maintaining accuracy under long-term navigation tasks, and enhanced by the magnetic and trajectory features assisted loop detection algorithm. Real-world experiments indicate that the proposed DPDD-TE outperforms than existing algorithms, and final estimated heading and positioning accuracy indexes reaches 5° and less than 2 m under the time period of 30 min, respectively.展开更多
With the rapid development of big data,online education can use big data technology to achieve personalized and intelligent education as well as improve learning effect and user satisfaction.In this study,the users of...With the rapid development of big data,online education can use big data technology to achieve personalized and intelligent education as well as improve learning effect and user satisfaction.In this study,the users of The Open University of China online education platform were taken as the research object,their user behavior data was collected,cleaned,and analyzed with text mining.The RFM model and the improved K-Means algorithm were used to construct the user portrait of the platform group and the needs and preferences of different types of the users were analyzded.Chinese word segmentation was used to show the key words of different types of users and the word cloud of their using frequency.The focus of different user groups was determined to facilitate for the follow-up course recommendation and precision marketing.Experimental results showed that the improved K-Means algorithm can well depict the behavior of group users.The index of silhouette score was improved to 0.811 by the improved K-Means algorithm,from random uncertainty to a fixed value,which can effectively solve the problem of inconsistent results caused by outlier sample points.展开更多
基金Projects(52302447,52388102,52372369)supported by the National Natural Science Foundation of China。
文摘Following the fundamental characteristics of the porosity windbreak,this study suggests a new numerical investigation method for the wind field of the windbreak based on the porous medium physical model.This method can transform the reasonable matching problem of the porosity and windproof performance of the windbreak into a study of the relationship between the resistance coefficient of the porous medium and the aerodynamic load of the train.This study examines the influence of the hole type on the wind field behind the porosity windbreak.Then,the relationship between the resistance coefficient of the porous medium,the porosity of the windbreak,and the aerodynamic loads of the train is investigated.The results show that the porous media physical model can be used instead of the windbreak geometry to study the windbreak-train aerodynamic performance,and the process of using this method is suggested.
基金supported by the Foundation of Equipment Preresearch Area(Grant No.80919010303).
文摘Missile-borne short-range infrared detection(SIRD)technology is commonly used in military ground target detection.In complex battlefield environments,achieving precise strike on ground target is a challenging task.However,real battlefield data is limited,and equivalent experiments are costly.Currently,there is a lack of comprehensive physical modeling and numerical simulation methods for SIRD.To this end,this study proposes a SIRD simulation framework incorporating full-link physical response,which is integrated through the radiative transfer layer,the sensor response layer,and the model-driven layer.In the radiative transfer layer,a coupled dynamic detection model is established to describe the external optical channel response of the SIRD system by combining the infrared radiation model and the geometric measurement model.In the sensor response layer,considering photoelectric conversion and signal processing,the internal signal response model of the SIRD system is established by a hybrid mode of parametric modeling and analog circuit analysis.In the model-driven layer,a cosimulation application based on a three-dimensional virtual environment is proposed to drive the full-link physical model,and a parallel ray tracing method is employed for real-time synchronous simulation.The proposed simulation framework can provide pixel-level signal output and is verified by the measured data.The evaluation results of the root mean square error(RMSE)and the Pearson correlation coefficient(PCC)show that the simulated data and the measured data achieve good consistency,and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals.The proposed simulation framework has the potential to acquire large sample datasets of SIRD under various complex battlefield environments and can provide an effective data source for SIRD application research.
基金Project(MMCS2023OF02)supported by the Open Foundation of State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures,ChinaProject(AA23073018)supported by the Guangxi Science and Technology,ChinaProject(2024M751861)supported by the China Postdoctoral Science Foundation。
文摘Red mud is a solid waste discharged in the process of alumina production,and how to realize the efficient recovery of its iron is an urgent problem to be solved.In this study,the iron extraction test and mechanism study of high iron red mud were carried out under the coupling conditions of multiple physical field(microwave field,gas-solid flow field and temperature field)with biomass as the reducing agent.The test results showed that under the optimal conditions,an iron concentrate with a yield of 78.4%,an iron grade of 59.23%,and a recovery rate of 86.65%was obtained.The analyses of XRD,XPS,TEM,and SEM-EDS showed that during the roasting process,the hematite in the high-iron red mud was completely converted to magnetite,and the biomass produced the reductant that provided the magnetization reaction;A large number of cracks and pores appeared in the surface of the hematite reduction product particles,which helped to induce iron minerals to undergo effective mineral phase transformation.The above study provides ideas for the phase transformation and efficient recovery of iron minerals in red mud.
基金supported by Hefei National Laboratory,Innovation Program for Quantum Science and Technology(2021ZD0300400/2021ZD0300402)the Beijing Natural Science Foundation(3252013)the China Postdoctoral Science Foundation(2024T171116).
文摘The spin-exchange relaxation-free atomic gyroscope,with its exceptionally high theoretical precision,demonstrates immense potential to become the next-generation strategic-grade gyroscope.However,due to technological noise,there is still a significant gap between its actual precision and theoretical precision.This study identifies the key factor limiting the precision of the SERF gyroscope as coupling noise.By optimizing the detection loop structure,a distinction between the dual-axis signals'response to optical and magnetic fields was achieved-where the optical errors responded similarly,while the response to magnetic noise was opposite.Based on the differences in the optical-magnetic response of the dual-axis signals,empirical mode decomposition was used to decompose the dual-axis gyroscope signals into multiple intrinsic mode functions,and Allan deviation analysis was applied to analyze the noise characteristics of the intrinsic mode functions over various periods.This study successfully reveals that optical errors caused by thermal-optical coupling and long-period magnetic noise induced by thermal-magnetic coupling are the dominant factors limiting the long-term stability of the SERF gyroscope.Based on these analyses,the study concludes that to achieve strategic-grade precision for the SERF gyroscope,it is essential to effectively address the noise issues caused by multi-physical field couplings.
基金supported by the National Natural Science Foundation of China(61571149,62001139)the Initiation Fund for Postdoctoral Research in Heilongjiang Province(LBH-Q19098)the Natural Science Foundation of Heilongjiang Province(LH2020F0178).
文摘Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.
文摘A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.
基金supported by the Natural Science Foundation of Hunan Province,China(2023JJ60076).
文摘Objective:Existing research shows that psychotherapists may experience secondary trauma and burnout,often neglecting self-care.This study aims to examine the effectiveness of self-care education in enhancing self-care efficacy among psychotherapists and explore factors affecting improvements in their self-care abilities.Methods:A self-care workshop was conducted for 159 psychotherapists from various fields.Participants’demographic information and self-care ability data were collected.The Exercise of Self-Care Agency Scale(ESCA)was used to assess the participant’s self-care levels before and after the workshop.Results:Post-workshop,ESCA total scores and subscale scores of participants showed significant increases(all P<0.001).Notably,score improvement levels differed by gender and years of practice,with female therapists showing greater improvement than male therapists(t=2.069,P=0.040)and those with longer work experience showing greater improvement than those with shorter experience(F=2.537,P=0.042).Conclusion:Providing self-care education for psychotherapists is essential.Future self care education programs or interventions for psychotherapists should consider gender and work experience factors to better support their self-care enhancement.
文摘The stratification phenomenon resulting from differences in the physical properties of solid-liquid components seriously affect the final combustion and explosion characteristics of mixed fuel under the action of oscillation.The effects of oscillation on the physical stability of mixed fuel with two solid-liquid ratios and three liquid component distribution ratios have been investigated using a self-designed experimental system at oscillation frequencies of 60-300 r/min.The explosion characteristics of mixed fuel before and after oscillation are gained from a 20 L spherical explosion container system.When the mass ratio of liquid components is controlled at 66.9%,64.7%,62.6%the final explosion characteristics are stable,with a maximum difference of only 0.71%.The volume of liquid fuel precipitation increases with increasing oscillation frequency when the mass ratio of liquid components reaches 71.7%,69.6%,67.7%.The fuel explosion overpressure after oscillation decreases with increasing liquid precipitation volume,and the repeatability is poor,with a maximum standard deviation of 82.736,which is much higher than the ratio without stratification.Properly controlling the mass ratio of liquid components of the mixed fuel can effectively combat the impact of oscillation on the physical state and maintain the stability of the final explosion characteristics.
文摘Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The performance of existing long-term navigation algorithm is limited by the cumulative error of inertial sensors, disturbed local magnetic field, and complex motion modes of the pedestrian. This paper develops a robust data and physical model dual-driven based trajectory estimation(DPDD-TE) framework, which can be applied for long-term navigation tasks. A Bi-directional Long Short-Term Memory(Bi-LSTM) based quasi-static magnetic field(QSMF) detection algorithm is developed for extracting useful magnetic observation for heading calibration, and another Bi-LSTM is adopted for walking speed estimation by considering hybrid human motion information under a specific time period. In addition, a data and physical model dual-driven based multi-source fusion model is proposed to integrate basic INS mechanization and multi-level constraint and observations for maintaining accuracy under long-term navigation tasks, and enhanced by the magnetic and trajectory features assisted loop detection algorithm. Real-world experiments indicate that the proposed DPDD-TE outperforms than existing algorithms, and final estimated heading and positioning accuracy indexes reaches 5° and less than 2 m under the time period of 30 min, respectively.
文摘With the rapid development of big data,online education can use big data technology to achieve personalized and intelligent education as well as improve learning effect and user satisfaction.In this study,the users of The Open University of China online education platform were taken as the research object,their user behavior data was collected,cleaned,and analyzed with text mining.The RFM model and the improved K-Means algorithm were used to construct the user portrait of the platform group and the needs and preferences of different types of the users were analyzded.Chinese word segmentation was used to show the key words of different types of users and the word cloud of their using frequency.The focus of different user groups was determined to facilitate for the follow-up course recommendation and precision marketing.Experimental results showed that the improved K-Means algorithm can well depict the behavior of group users.The index of silhouette score was improved to 0.811 by the improved K-Means algorithm,from random uncertainty to a fixed value,which can effectively solve the problem of inconsistent results caused by outlier sample points.
