When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the feature...When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the features of the dual-mode observation.Due to multipath effect,positioning accuracy of present Kalman filter algorithm is really low.To solve this problem,a chaotic immune-vaccine particle swarm optimization_extended Kalman filter(CIPSO_EKF)algorithm is proposed to improve the output accuracy of the Kalman filter.By chaotic mapping and immunization,the particle swarm algorithm is first optimized,and then the optimized particle swarm algorithm is used to optimize the observation error covariance matrix.The optimal parameters are provided to the EKF,which can effectively reduce the impact of the observation value oscillation caused by multipath effect on positioning accuracy.At the same time,the train positioning results of EKF and CIPSO_EKF algorithms are compared.The eastward position errors and velocity errors show that CIPSO_EKF algorithm has faster convergence speed and higher real-time performance,which can effectively suppress interference and improve positioning accuracy.展开更多
A novel series of Mn^(4+)and Eu^(3+)co-doped double-perovskite Ca_(2)ScNbO_(6)(CSNO)phosphor was synthesized in this work.The phase structure and photoluminescence properties were systematically researched.Due to the ...A novel series of Mn^(4+)and Eu^(3+)co-doped double-perovskite Ca_(2)ScNbO_(6)(CSNO)phosphor was synthesized in this work.The phase structure and photoluminescence properties were systematically researched.Due to the different thermal quenching properties of Mn^(4+)and Eu^(3+)ions,a dual-mode temperature measurement technique over a wide temperature range was established.The CSNO phosphor co-doped with Mn^(4+)and Eu^(3+)ions has a self-calibrated effect due to the different thermal quenching effects of Mn^(4+)and Eu^(3+)ions.The maximum relative sensitivity(S_(R1,R2))values of the CSNO:0.1 mol%Mn^(4+)/0.5 mol%Eu^(3+)phosphor are determined to be 1.92%/K and 1.76%/K at 523 K,under excitation at 296 and 396 nm,respectively.Additionally,the temperature-dependent lifetime of Mn^(4+)indicates that the maximum S_(R3,R4) values for the synthesized phosphors are 1.669%/K(λ_(ex)=296 nm)and1.664%/K(λ_(ex)=396 nm),re spectively.It is interesting to note that different SRcan be obtained by varying the excitation wavelength to the CSNO:0.1 mol%Mn^(4+)/0.5 mol%Eu^(3+)phosphor.Ultimately,this work provides a reference for the development of highly sensitive fluorescent materials based on dualemitting centers of double-perovskite.展开更多
Photothermoelectric(PTE)photodetectors with selfpowered and uncooled advantages have attracted much interest due to the wide application prospects in the military and civilian fields.However,traditional PTE photodetec...Photothermoelectric(PTE)photodetectors with selfpowered and uncooled advantages have attracted much interest due to the wide application prospects in the military and civilian fields.However,traditional PTE photodetectors lack of mechanical flexibility and cannot operate independently without the test instrument.Herein,we present a flexible PTE photodetector capable of dual-mode output,combining electrical and optical signal generation for enhanced functionality.Using solution processing,high-quality MXene thin films are assembled on asymmetric electrodes as the photosensitive layer.The geometrically asymmetric electrode design significantly enhances the responsivity,achieving 0.33 m A W^(-1)under infrared illumination,twice that of the symmetrical configuration.This improvement stems from optimized photothermal conversion and an expanded temperature gradient.The PTE device maintains stable performance after 300 bending cycles,demonstrating excellent flexibility.A new energy conversion pathway has been established by coupling the photothermal conversion of MXene with thermochromic composite materials,leading to a real-time visualization of invisible infrared radiation.Leveraging this functionality,we demonstrate the first human-machine collaborative infrared imaging system,wherein the dual-mode photodetector arrays synchronously generate human-readable pattern and machine-readable pattern.Our study not only provides a new solution for functional integration of flexible photodetectors,but also sets a new benchmark for human-machine collaborative optoelectronics.展开更多
Micro RNA-133a(mi RNA-133a) and cardiac troponin I(c Tn I) are different-type crucial biomarkers of acute myocardial infarction(AMI), whose levels are great significance for AMI diagnosis and treatment. Herein,a novel...Micro RNA-133a(mi RNA-133a) and cardiac troponin I(c Tn I) are different-type crucial biomarkers of acute myocardial infarction(AMI), whose levels are great significance for AMI diagnosis and treatment. Herein,a novel photoelectrochemical-electrochemical(PEC-EC) dual-mode biosensing platform for dual-target assays of mi RNA-133a and c Tn I was developed. In which, a PEC-EC dual-mode sensing platform for mi RNA-133a was constructed based on the changes of the photocurrent inhibition effect and the electrochemical signal of Fc on the Fc-hairpin DNA probe(Fc-HP)/Zn Cd S-quantum dots(QDs)/ITO electrode. Furthermore, under magnetic separation and the specific interaction between c Tn I and its aptamer, the N-doped porous carbon-Zn O polyhedra(NPC-Zn O)-hemin-capture DNA probe hybrid(NH-CP) was obtained and introduced to the Fc-HP/Zn Cd S-QDs/ITO electrode via hybridization between NH-CP and Fc-HP. The hemin molecules encapsulated in NH-CP could effectively induce the photocurrent-polarity-switching of the FcHP/Zn Cd S-QDs/ITO electrode and generate a new electrochemical signal originating from hemin. Thus,c Tn I was assayed sensitively and selectively by the PEC-EC dual-mode biosensing platform. Here, Fc and hemin not only serve as the electrochemical indicators, but also respectively inhibit the photocurrent and switch the photocurrent polarity of Zn Cd S-QDs. Furthermore, the proposed biosensing platform could be easily expanded to the detection of other multiplex-type biomarkers via the change of the sequences of the related DNA probes, implying its significant potential in clinical diagnosis and biological analysis.展开更多
This paper describes an experimental study investigating the effects of sinusoidal pulsed injection on the combustion mode transition in a dual-mode supersonic combustor.The results are obtained under inflow condition...This paper describes an experimental study investigating the effects of sinusoidal pulsed injection on the combustion mode transition in a dual-mode supersonic combustor.The results are obtained under inflow conditions of 2.9 MPa stagnation pressure,1900 K stagnation temperature,and Mach number of 3.0.It has been observed that,at the same equivalence ratio,the combustion mode and flow field structure undergo irreversible changes from a weak combustion state to a strong combustion state at a specific pulsed jet frequency compared to steady jet.For steady jet,the combustion mode is dual-mode.As the frequency of the unsteady jet changes,the combustion mode also changes:it becomes a transition mode at frequencies of 171 Hz and 260 Hz,and a ramjet mode at 216 Hz.Combustion instability under steady jet manifests as a transition in flame stabilization mode.In contrast,under pulsed jet,combustion instability appears either as a transition in flame stabilization mode or as flame blow-off and flashback.The flow field oscillation frequency in the non-reacting flow is 171 Hz,which may resonate with the 171 Hz pulsed jet frequency,making the combustion oscillations most pronounced at this frequency.When the jet frequency is increased to 216 Hz,the combustion intensity significantly increases,and the combustion mode transfers to the ramjet mode.However,further increasing the frequency to 260 Hz results in a decrease in combustion intensity,returning to the transition mode.The frequency of the flow field oscillations varies with the coupling of the pulsed injection frequency,shock wave,and flame,and if the system reaches an unstable state,that is,pre-combustion shock train moves far upstream of the isolator during the pulsed jet period,strong combustion state can be achieved,and this process is irreversible.展开更多
Four-level pulse amplitude modulation(PAM4)signals,recognized for enhanced energy efficiency and spectral utilization compared with non-return-to-zero(NRZ)counterparts,have been adopted in multiple high-speed serializ...Four-level pulse amplitude modulation(PAM4)signals,recognized for enhanced energy efficiency and spectral utilization compared with non-return-to-zero(NRZ)counterparts,have been adopted in multiple high-speed serializer/deserializer(SerDes)standards,but NRZ modulation remains predominant in industrial applications.This paper introduces a UMC 28 nm CMOS-based parallel configurable forward feedback equalization(FFE)dual-mode high-speed SerDes transmitter supporting 7-bit resolution with data rates of 56 Gb∙s^(-1)NRZ and 112 Gb∙s^(-1)PAM4,utilizing a hybrid architecture that integrates digital signal processing(DSP)with digital-to-analog conversion(DAC).The design processes parallel input signals and eight stored 8-bit tap coefficients through a configurable FFE multiplier module and parallel carry adder module,while achieving low-power serialization via low-speed 16∶4 multiplexers(MUXs)with two different 2∶1 MUXs and high-speed 4∶1 MUXs.A source series termination(SST)output network structure enhances lower power dissipation and higher output swing.Simulation results show that,under a 1.05 V supply voltage and a channel loss of 19.21 dB at 28 GHz,the output 56 Gb∙s^(-1)NRZ eye diagram has an eye height of 70.11 mV and an eye width of 12.16 ps(0.68 UI).The output 112 Gb∙s^(-1)PAM4 eye diagram has an eye height of 20.07 mV and an eye width of 7.49 ps(0.42 UI).The layout area of the dual-mode transmitter is 0.079 mm^(2),and the total circuit power consumption is 74.48 mW(energy efficiency is 1.33/0.67 pJ∙bit-1).展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
Evolutionary multi-task optimization(EMTO)presents an efficient way to solve multiple tasks simultaneously.However,difficulties they face in curbing the performance degradation caused by unmatched knowledge transfer a...Evolutionary multi-task optimization(EMTO)presents an efficient way to solve multiple tasks simultaneously.However,difficulties they face in curbing the performance degradation caused by unmatched knowledge transfer and inefficient evolutionary strategies become more severe as the number of iterations increases.Motivated by this,a novel self-adjusting dualmode evolutionary framework,which integrates variable classification evolution and knowledge dynamic transfer strategies,is designed to compensate for this deficiency.First,a dual-mode evolutionary framework is designed to meet the needs of evolution in different states.Then,a self-adjusting strategy based on spatial-temporal information is adopted to guide the selection of evolutionary modes.Second,a classification mechanism for decision variables is proposed to achieve the grouping of variables with different attributes.Then,the evolutionary algorithm with a multi-operator mechanism is employed to conduct classified evolution of decision variables.Third,an evolutionary strategy based on multi-source knowledge sharing is presented to realize the cross-domain transfer of knowledge.Then,a dynamic weighting strategy is developed for efficient utilization of knowledge.Finally,by conducting experiments and comparing the designed method with several existing algorithms,the empirical results confirm that it significantly outperforms its peers in tackling benchmark instances.展开更多
Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting...Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious an...Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.展开更多
The microstrip dual-mode filter （DMF） with conventional coupling structure has some limitations in- eluding the port coupling strength limited by fabrication tolerance and the existence of serious second order spuri...The microstrip dual-mode filter （DMF） with conventional coupling structure has some limitations in- eluding the port coupling strength limited by fabrication tolerance and the existence of serious second order spuri- ous band. Therefore, a novel DMF with a offset-feed bended coupling structure and a stepped-impedance dual- mode resonator is proposed for coupling enhancement and spurious response suppression. Based on the analysis of the change of spur frequencies and the current distribution of spur resonant modes, all spurs near passband of the cascaded DMF can be fully suppressed by optimizing the structure parameters of parasite resonators, which bene- fits from the inherent well-controlled transmission zeros. Experimental results show that the proposed DMF ex- hibits lower insertion loss ,much sharper rate of cutoff and wider spur-free stop band compared with conventional DMF. This design is applicable for spur suppression in wideband communication.展开更多
An improved target tracking information differentiating system using the neural network to substitute for fuzzy rules is presented for the infrared-radar dual-mode guidance system. Since the neural network training ba...An improved target tracking information differentiating system using the neural network to substitute for fuzzy rules is presented for the infrared-radar dual-mode guidance system. Since the neural network training based on the expert knowledge database is conducted off-line, the benefits for developing real-time tracking capabilities can be obtained. The network outputs the confidence degree denoted by the weight value of target information in the data fusion center according to two input variables of the measurement noise covariance and the tracking filter covariance. Simulation results show that the improved system can differentiate the target tracking information from the seeker fast and accurately.展开更多
An all-digital hybrid current regulation scheme for the single-phase shunt active power filter （APF） is presented. The proposed hybrid current control scheme integrates the deadbeat control and the dual-mode structu...An all-digital hybrid current regulation scheme for the single-phase shunt active power filter （APF） is presented. The proposed hybrid current control scheme integrates the deadbeat control and the dual-mode structure repetitive control （DMRC） so that it can offer superior steady-state performance and good transient features. Unlike the conventional schemes, the proposed scheme-based APF can compensate both the odd and the even order harmonics in grid. The detailed design criteria and the stability analysis of the proposed hybrid current controller are presented. Moreover, an improved structure which incorporates the proposed hybrid controller and the resonant controller for tracking specific order harmonics is given. The relationships between the resonant controller and different repetitive control schemes are discussed. Experimental results verify the effectiveness and advantages of the proposed hybrid control scheme.展开更多
Automotive industry,as an important pillar of the national economy,has been rapidly developing in recent years.But proplems such as energy comsumption and environmental pollution are posed at the same time.Electro-mec...Automotive industry,as an important pillar of the national economy,has been rapidly developing in recent years.But proplems such as energy comsumption and environmental pollution are posed at the same time.Electro-mechanical variable transmission system is considered one of avilable workarounds.It is brought forward a kind of design methods of dual-mode electro-mechanical variable transmission system rotational speed characteristics and dual-mode drive diagrams.With the motor operating behavior of running in four quadrants and the speed characteristics of the simple internal and external meshing single planetary gear train,four kinds of dual-mode electro-mechanical transmission system scheme are designed.And the velocity,torque and power characteristics of one of the programs are analyzed.The magnitude of the electric split-flow power is an important factor which influences the system performance,so in the parameters matching design,it needs to reduce the power needs under the first mode of the motor.The motor,output rotational speed range and the position of the mode switching point have relationships with the characteristics design of the planetary gear set.The analysis method is to provide a reference for hybrid vehicles＇ design.As the involved rotational speed and torque relationships are the natural contact of every part of transmission system,a theory basis of system program and performance analysis is provided.展开更多
Near-infrared(NIR),particularly NIR-containing dual-/multimode afterglow,is very attractive in many fields of application,but it is still a great challenge to achieve such property of materials. Herein,we report a fac...Near-infrared(NIR),particularly NIR-containing dual-/multimode afterglow,is very attractive in many fields of application,but it is still a great challenge to achieve such property of materials. Herein,we report a facile method to prepare green and NIR dual-mode afterglow of carbon dots(CDs) through in situ embedding o-CDs(being prepared from o-phenylenediamine) into cyanuric acid(CA) matrix(named o-CDs@CA). Further studies reveal that the green and NIR afterglows of o-CDs@CA originate from thermal activated delayed fluorescence(TADF) and room temperature phosphorescence(RTP) of o-CDs,respectively. In addition,the formation of covalent bonds between o-CDs and CA,and the presence of multiple fixation and rigid e ects to the triplet states of o-CDs are confirmed to be critical for activating the observed dual-mode afterglow. Due to the shorter lifetime and insensitiveness to human vision of the NIR RTP of o-CDs@CA,it is completely covered by the green TADF during directly observing. The NIR RTP signal,however,can be readily captured if an optical filter(cut-o wavelength of 600 nm) being used. By utilizing these unique features,the applications of o-CDs@CA in anti-counterfeiting and information encryption have been demonstrated with great confidentiality. Finally,the as-developed method was confirmed to be applicable to many other kinds of CDs for achieving or enhancing their afterglow performances.展开更多
Combustion mode transition is a valuable and challenging research area in dual-mode scramjet engines.The thermal behavior of an isolator with mode transition inducing backpressure is investigated by direct-connect dua...Combustion mode transition is a valuable and challenging research area in dual-mode scramjet engines.The thermal behavior of an isolator with mode transition inducing backpressure is investigated by direct-connect dual-mode scramjet experiments and theoretical analysis.Combustion experiments are conducted under the incoming airflow conditions of total temperature1270 K and Mach 2.A small increment of the fuel equivalence ratio is scheduled to trigger mode transition.Correspondingly,the variation of the coolant flow rate is very small.Based on the measured wall pressures,the heat-transfer model can quantify the thermal state variation of the engine with active cooling.Compared with the combustor,mode transition has a greater effect on the isolator thermal behavior,and it significantly changes the isolator heat-flux and wall temperature.To further study the isolator thermal behavior from flight Mach 4 to Mach 7,a theoretical analysis is carried out.Around the critical point of combustion mode transition,sudden changes of the isolator flowfield and thermal state are discussed.展开更多
基金National Natural Science Foundation of China(Nos.61662070,61363059)Youth Science Fund Project of Lanzhou Jiaotong University(No.2018036)。
文摘When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the features of the dual-mode observation.Due to multipath effect,positioning accuracy of present Kalman filter algorithm is really low.To solve this problem,a chaotic immune-vaccine particle swarm optimization_extended Kalman filter(CIPSO_EKF)algorithm is proposed to improve the output accuracy of the Kalman filter.By chaotic mapping and immunization,the particle swarm algorithm is first optimized,and then the optimized particle swarm algorithm is used to optimize the observation error covariance matrix.The optimal parameters are provided to the EKF,which can effectively reduce the impact of the observation value oscillation caused by multipath effect on positioning accuracy.At the same time,the train positioning results of EKF and CIPSO_EKF algorithms are compared.The eastward position errors and velocity errors show that CIPSO_EKF algorithm has faster convergence speed and higher real-time performance,which can effectively suppress interference and improve positioning accuracy.
基金Project supported by National Natural Science Foundation of China(12004062)Natural Science Foundation of Chongqing(CSTB2024NSCQLZX0030)+1 种基金the Science and Technology Research Program of Chongqing Municipal Education Commission(KJZD-M202300601,KJZD-K202300612,KJQN202300613)Venture and Innovation Support Program for Chongqing Overseas Returnees(CX2019085,CX2022024)。
文摘A novel series of Mn^(4+)and Eu^(3+)co-doped double-perovskite Ca_(2)ScNbO_(6)(CSNO)phosphor was synthesized in this work.The phase structure and photoluminescence properties were systematically researched.Due to the different thermal quenching properties of Mn^(4+)and Eu^(3+)ions,a dual-mode temperature measurement technique over a wide temperature range was established.The CSNO phosphor co-doped with Mn^(4+)and Eu^(3+)ions has a self-calibrated effect due to the different thermal quenching effects of Mn^(4+)and Eu^(3+)ions.The maximum relative sensitivity(S_(R1,R2))values of the CSNO:0.1 mol%Mn^(4+)/0.5 mol%Eu^(3+)phosphor are determined to be 1.92%/K and 1.76%/K at 523 K,under excitation at 296 and 396 nm,respectively.Additionally,the temperature-dependent lifetime of Mn^(4+)indicates that the maximum S_(R3,R4) values for the synthesized phosphors are 1.669%/K(λ_(ex)=296 nm)and1.664%/K(λ_(ex)=396 nm),re spectively.It is interesting to note that different SRcan be obtained by varying the excitation wavelength to the CSNO:0.1 mol%Mn^(4+)/0.5 mol%Eu^(3+)phosphor.Ultimately,this work provides a reference for the development of highly sensitive fluorescent materials based on dualemitting centers of double-perovskite.
基金supported by the Fundamental Research Funds for the Central Universities(xxj022019009)。
文摘Photothermoelectric(PTE)photodetectors with selfpowered and uncooled advantages have attracted much interest due to the wide application prospects in the military and civilian fields.However,traditional PTE photodetectors lack of mechanical flexibility and cannot operate independently without the test instrument.Herein,we present a flexible PTE photodetector capable of dual-mode output,combining electrical and optical signal generation for enhanced functionality.Using solution processing,high-quality MXene thin films are assembled on asymmetric electrodes as the photosensitive layer.The geometrically asymmetric electrode design significantly enhances the responsivity,achieving 0.33 m A W^(-1)under infrared illumination,twice that of the symmetrical configuration.This improvement stems from optimized photothermal conversion and an expanded temperature gradient.The PTE device maintains stable performance after 300 bending cycles,demonstrating excellent flexibility.A new energy conversion pathway has been established by coupling the photothermal conversion of MXene with thermochromic composite materials,leading to a real-time visualization of invisible infrared radiation.Leveraging this functionality,we demonstrate the first human-machine collaborative infrared imaging system,wherein the dual-mode photodetector arrays synchronously generate human-readable pattern and machine-readable pattern.Our study not only provides a new solution for functional integration of flexible photodetectors,but also sets a new benchmark for human-machine collaborative optoelectronics.
基金financially supported by National Natural Science Foundation of China (Nos. 22074033, 22374035)。
文摘Micro RNA-133a(mi RNA-133a) and cardiac troponin I(c Tn I) are different-type crucial biomarkers of acute myocardial infarction(AMI), whose levels are great significance for AMI diagnosis and treatment. Herein,a novel photoelectrochemical-electrochemical(PEC-EC) dual-mode biosensing platform for dual-target assays of mi RNA-133a and c Tn I was developed. In which, a PEC-EC dual-mode sensing platform for mi RNA-133a was constructed based on the changes of the photocurrent inhibition effect and the electrochemical signal of Fc on the Fc-hairpin DNA probe(Fc-HP)/Zn Cd S-quantum dots(QDs)/ITO electrode. Furthermore, under magnetic separation and the specific interaction between c Tn I and its aptamer, the N-doped porous carbon-Zn O polyhedra(NPC-Zn O)-hemin-capture DNA probe hybrid(NH-CP) was obtained and introduced to the Fc-HP/Zn Cd S-QDs/ITO electrode via hybridization between NH-CP and Fc-HP. The hemin molecules encapsulated in NH-CP could effectively induce the photocurrent-polarity-switching of the FcHP/Zn Cd S-QDs/ITO electrode and generate a new electrochemical signal originating from hemin. Thus,c Tn I was assayed sensitively and selectively by the PEC-EC dual-mode biosensing platform. Here, Fc and hemin not only serve as the electrochemical indicators, but also respectively inhibit the photocurrent and switch the photocurrent polarity of Zn Cd S-QDs. Furthermore, the proposed biosensing platform could be easily expanded to the detection of other multiplex-type biomarkers via the change of the sequences of the related DNA probes, implying its significant potential in clinical diagnosis and biological analysis.
基金supported by the Program of Key Laboratory of Cross-Domain Flight Interdisciplinary Technology,China(No.2023-ZY0205)。
文摘This paper describes an experimental study investigating the effects of sinusoidal pulsed injection on the combustion mode transition in a dual-mode supersonic combustor.The results are obtained under inflow conditions of 2.9 MPa stagnation pressure,1900 K stagnation temperature,and Mach number of 3.0.It has been observed that,at the same equivalence ratio,the combustion mode and flow field structure undergo irreversible changes from a weak combustion state to a strong combustion state at a specific pulsed jet frequency compared to steady jet.For steady jet,the combustion mode is dual-mode.As the frequency of the unsteady jet changes,the combustion mode also changes:it becomes a transition mode at frequencies of 171 Hz and 260 Hz,and a ramjet mode at 216 Hz.Combustion instability under steady jet manifests as a transition in flame stabilization mode.In contrast,under pulsed jet,combustion instability appears either as a transition in flame stabilization mode or as flame blow-off and flashback.The flow field oscillation frequency in the non-reacting flow is 171 Hz,which may resonate with the 171 Hz pulsed jet frequency,making the combustion oscillations most pronounced at this frequency.When the jet frequency is increased to 216 Hz,the combustion intensity significantly increases,and the combustion mode transfers to the ramjet mode.However,further increasing the frequency to 260 Hz results in a decrease in combustion intensity,returning to the transition mode.The frequency of the flow field oscillations varies with the coupling of the pulsed injection frequency,shock wave,and flame,and if the system reaches an unstable state,that is,pre-combustion shock train moves far upstream of the isolator during the pulsed jet period,strong combustion state can be achieved,and this process is irreversible.
基金Supported by the National Key R&D Program Broadband Communications and New Network Key Special Project(No.2019YFB1803600).
文摘Four-level pulse amplitude modulation(PAM4)signals,recognized for enhanced energy efficiency and spectral utilization compared with non-return-to-zero(NRZ)counterparts,have been adopted in multiple high-speed serializer/deserializer(SerDes)standards,but NRZ modulation remains predominant in industrial applications.This paper introduces a UMC 28 nm CMOS-based parallel configurable forward feedback equalization(FFE)dual-mode high-speed SerDes transmitter supporting 7-bit resolution with data rates of 56 Gb∙s^(-1)NRZ and 112 Gb∙s^(-1)PAM4,utilizing a hybrid architecture that integrates digital signal processing(DSP)with digital-to-analog conversion(DAC).The design processes parallel input signals and eight stored 8-bit tap coefficients through a configurable FFE multiplier module and parallel carry adder module,while achieving low-power serialization via low-speed 16∶4 multiplexers(MUXs)with two different 2∶1 MUXs and high-speed 4∶1 MUXs.A source series termination(SST)output network structure enhances lower power dissipation and higher output swing.Simulation results show that,under a 1.05 V supply voltage and a channel loss of 19.21 dB at 28 GHz,the output 56 Gb∙s^(-1)NRZ eye diagram has an eye height of 70.11 mV and an eye width of 12.16 ps(0.68 UI).The output 112 Gb∙s^(-1)PAM4 eye diagram has an eye height of 20.07 mV and an eye width of 7.49 ps(0.42 UI).The layout area of the dual-mode transmitter is 0.079 mm^(2),and the total circuit power consumption is 74.48 mW(energy efficiency is 1.33/0.67 pJ∙bit-1).
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金supported in part by the Plan of Key Scientific Research Projects of Colleges and Universities in Henan Province(25A413005,24A120005)the National Science and Technology Major Project(2021ZD0112302)the National Natural Science Foundation of China(62222301,61890930-5,62021003).
文摘Evolutionary multi-task optimization(EMTO)presents an efficient way to solve multiple tasks simultaneously.However,difficulties they face in curbing the performance degradation caused by unmatched knowledge transfer and inefficient evolutionary strategies become more severe as the number of iterations increases.Motivated by this,a novel self-adjusting dualmode evolutionary framework,which integrates variable classification evolution and knowledge dynamic transfer strategies,is designed to compensate for this deficiency.First,a dual-mode evolutionary framework is designed to meet the needs of evolution in different states.Then,a self-adjusting strategy based on spatial-temporal information is adopted to guide the selection of evolutionary modes.Second,a classification mechanism for decision variables is proposed to achieve the grouping of variables with different attributes.Then,the evolutionary algorithm with a multi-operator mechanism is employed to conduct classified evolution of decision variables.Third,an evolutionary strategy based on multi-source knowledge sharing is presented to realize the cross-domain transfer of knowledge.Then,a dynamic weighting strategy is developed for efficient utilization of knowledge.Finally,by conducting experiments and comparing the designed method with several existing algorithms,the empirical results confirm that it significantly outperforms its peers in tackling benchmark instances.
基金National Key Research and Development Program of China,No.2023YFC3006704National Natural Science Foundation of China,No.42171047CAS-CSIRO Partnership Joint Project of 2024,No.177GJHZ2023097MI。
文摘Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金the National Key Research and Development Program of China(Grant No.2022YFF0711400)which provided valuable financial support and resources for my research and made it possible for me to deeply explore the unknown mysteries in the field of lunar geologythe National Space Science Data Center Youth Open Project(Grant No.NSSDC2302001),which has not only facilitated the smooth progress of my research,but has also built a platform for me to communicate and cooperate with experts in the field.
文摘Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.
基金Supported by the National Natural Science Foundation of China under Grant(60921063)the National Program on Key Basic Research Project(973Program)(2010CB327400)the National Science and Technology Major Project(2010ZX03007-002-01)~~
文摘The microstrip dual-mode filter （DMF） with conventional coupling structure has some limitations in- eluding the port coupling strength limited by fabrication tolerance and the existence of serious second order spuri- ous band. Therefore, a novel DMF with a offset-feed bended coupling structure and a stepped-impedance dual- mode resonator is proposed for coupling enhancement and spurious response suppression. Based on the analysis of the change of spur frequencies and the current distribution of spur resonant modes, all spurs near passband of the cascaded DMF can be fully suppressed by optimizing the structure parameters of parasite resonators, which bene- fits from the inherent well-controlled transmission zeros. Experimental results show that the proposed DMF ex- hibits lower insertion loss ,much sharper rate of cutoff and wider spur-free stop band compared with conventional DMF. This design is applicable for spur suppression in wideband communication.
文摘An improved target tracking information differentiating system using the neural network to substitute for fuzzy rules is presented for the infrared-radar dual-mode guidance system. Since the neural network training based on the expert knowledge database is conducted off-line, the benefits for developing real-time tracking capabilities can be obtained. The network outputs the confidence degree denoted by the weight value of target information in the data fusion center according to two input variables of the measurement noise covariance and the tracking filter covariance. Simulation results show that the improved system can differentiate the target tracking information from the seeker fast and accurately.
基金The National Basic Research Program of China(973 Program)(No.2013CB035603)the National Natural Science Foundation of China(No.51007008,51137001)+1 种基金the Ph.D.Programs Foundation of Ministry of Education of China(No.20100092120043)the Fundamental Research Funds for the Central Universities
文摘An all-digital hybrid current regulation scheme for the single-phase shunt active power filter （APF） is presented. The proposed hybrid current control scheme integrates the deadbeat control and the dual-mode structure repetitive control （DMRC） so that it can offer superior steady-state performance and good transient features. Unlike the conventional schemes, the proposed scheme-based APF can compensate both the odd and the even order harmonics in grid. The detailed design criteria and the stability analysis of the proposed hybrid current controller are presented. Moreover, an improved structure which incorporates the proposed hybrid controller and the resonant controller for tracking specific order harmonics is given. The relationships between the resonant controller and different repetitive control schemes are discussed. Experimental results verify the effectiveness and advantages of the proposed hybrid control scheme.
基金supported by Foundation of National Key Lab of Vehicular Transmission of China
文摘Automotive industry,as an important pillar of the national economy,has been rapidly developing in recent years.But proplems such as energy comsumption and environmental pollution are posed at the same time.Electro-mechanical variable transmission system is considered one of avilable workarounds.It is brought forward a kind of design methods of dual-mode electro-mechanical variable transmission system rotational speed characteristics and dual-mode drive diagrams.With the motor operating behavior of running in four quadrants and the speed characteristics of the simple internal and external meshing single planetary gear train,four kinds of dual-mode electro-mechanical transmission system scheme are designed.And the velocity,torque and power characteristics of one of the programs are analyzed.The magnitude of the electric split-flow power is an important factor which influences the system performance,so in the parameters matching design,it needs to reduce the power needs under the first mode of the motor.The motor,output rotational speed range and the position of the mode switching point have relationships with the characteristics design of the planetary gear set.The analysis method is to provide a reference for hybrid vehicles＇ design.As the involved rotational speed and torque relationships are the natural contact of every part of transmission system,a theory basis of system program and performance analysis is provided.
基金the National Natural Science Foundation of China (52003284,51872300 and U1832110)the China Postdoctoral Science Foundation (BX20190338)S&T Innovation 2025 Major Special Program of Ningbo (2018B10054) for financially supporting this work。
文摘Near-infrared(NIR),particularly NIR-containing dual-/multimode afterglow,is very attractive in many fields of application,but it is still a great challenge to achieve such property of materials. Herein,we report a facile method to prepare green and NIR dual-mode afterglow of carbon dots(CDs) through in situ embedding o-CDs(being prepared from o-phenylenediamine) into cyanuric acid(CA) matrix(named o-CDs@CA). Further studies reveal that the green and NIR afterglows of o-CDs@CA originate from thermal activated delayed fluorescence(TADF) and room temperature phosphorescence(RTP) of o-CDs,respectively. In addition,the formation of covalent bonds between o-CDs and CA,and the presence of multiple fixation and rigid e ects to the triplet states of o-CDs are confirmed to be critical for activating the observed dual-mode afterglow. Due to the shorter lifetime and insensitiveness to human vision of the NIR RTP of o-CDs@CA,it is completely covered by the green TADF during directly observing. The NIR RTP signal,however,can be readily captured if an optical filter(cut-o wavelength of 600 nm) being used. By utilizing these unique features,the applications of o-CDs@CA in anti-counterfeiting and information encryption have been demonstrated with great confidentiality. Finally,the as-developed method was confirmed to be applicable to many other kinds of CDs for achieving or enhancing their afterglow performances.
文摘Combustion mode transition is a valuable and challenging research area in dual-mode scramjet engines.The thermal behavior of an isolator with mode transition inducing backpressure is investigated by direct-connect dual-mode scramjet experiments and theoretical analysis.Combustion experiments are conducted under the incoming airflow conditions of total temperature1270 K and Mach 2.A small increment of the fuel equivalence ratio is scheduled to trigger mode transition.Correspondingly,the variation of the coolant flow rate is very small.Based on the measured wall pressures,the heat-transfer model can quantify the thermal state variation of the engine with active cooling.Compared with the combustor,mode transition has a greater effect on the isolator thermal behavior,and it significantly changes the isolator heat-flux and wall temperature.To further study the isolator thermal behavior from flight Mach 4 to Mach 7,a theoretical analysis is carried out.Around the critical point of combustion mode transition,sudden changes of the isolator flowfield and thermal state are discussed.
