The accurate prediction and analysis of emergencies in Urban Rail Transit Systems(URTS)are essential for the development of effective early warning and prevention mechanisms.This study presents an integrated perceptio...The accurate prediction and analysis of emergencies in Urban Rail Transit Systems(URTS)are essential for the development of effective early warning and prevention mechanisms.This study presents an integrated perception model designed to predict emergencies and analyze their causes based on historical unstructured emergency data.To address issues related to data structuredness and missing values,we employed label encoding and an Elastic Net Regularization-based Generative Adversarial Interpolation Network(ER-GAIN)for data structuring and imputation.Additionally,to mitigate the impact of imbalanced data on the predictive performance of emergencies,we introduced an Adaptive Boosting Ensemble Model(AdaBoost)to forecast the key features of emergencies,including event types and levels.We also utilized Information Gain(IG)to analyze and rank the causes of various significant emergencies.Experimental results indicate that,compared to baseline data imputation models,ER-GAIN improved the prediction accuracy of key emergency features by 3.67%and 3.78%,respectively.Furthermore,AdaBoost enhanced the accuracy by over 4.34%and 3.25%compared to baseline predictivemodels.Through causation analysis,we identified the critical causes of train operation and fire incidents.The findings of this research will contribute to the establishment of early warning and prevention mechanisms for emergencies in URTS,potentially leading to safer and more reliable URTS operations.展开更多
This paper gives an introduction to the essential challenges of software engineering and requirements that software has to fulfill in the domain of automation. Besides, the functional characteristics, specific constra...This paper gives an introduction to the essential challenges of software engineering and requirements that software has to fulfill in the domain of automation. Besides, the functional characteristics, specific constraints and circumstances are considered for deriving requirements concerning usability, the technical process, the automation functions, used platform and the well-established models, which are described in detail. On the other hand, challenges result from the circumstances at different points in the single phases of the life cycle of the automated system. The requirements for life-cycle-management, tools and the changeability during runtime are described in detail.展开更多
Currently,distributed routing protocols are constrained by offering a single path between any pair of nodes,thereby limiting the potential throughput and overall network performance.This approach not only restricts th...Currently,distributed routing protocols are constrained by offering a single path between any pair of nodes,thereby limiting the potential throughput and overall network performance.This approach not only restricts the flow of data but also makes the network susceptible to failures in case the primary path is disrupted.In contrast,routing protocols that leverage multiple paths within the network offer a more resilient and efficient solution.Multipath routing,as a fundamental concept,surpasses the limitations of traditional shortest path first protocols.It not only redirects traffic to unused resources,effectively mitigating network congestion,but also ensures load balancing across the network.This optimization significantly improves network utilization and boosts the overall performance,making it a widely recognized efficient method for enhancing network reliability.To further strengthen network resilience against failures,we introduce a routing scheme known as Multiple Nodes with at least Two Choices(MNTC).This innovative approach aims to significantly enhance network availability by providing each node with at least two routing choices.By doing so,it not only reduces the dependency on a single path but also creates redundant paths that can be utilized in case of failures,thereby enhancing the overall resilience of the network.To ensure the optimal placement of nodes,we propose three incremental deployment algorithms.These algorithms carefully select the most suitable set of nodes for deployment,taking into account various factors such as node connectivity,traffic patterns,and network topology.By deployingMNTCon a carefully chosen set of nodes,we can significantly enhance network reliability without the need for a complete overhaul of the existing infrastructure.We have conducted extensive evaluations of MNTC in diverse topological spaces,demonstrating its effectiveness in maintaining high network availability with minimal path stretch.The results are impressive,showing that even when implemented on just 60%of nodes,our incremental deployment method significantly boosts network availability.This underscores the potential of MNTC in enhancing network resilience and performance,making it a viable solution for modern networks facing increasing demands and complexities.The algorithms OSPF,TBFH,DC and LFC perform fast rerouting based on strict conditions,while MNTC is not restricted by these conditions.In five real network topologies,the average network availability ofMNTCis improved by 14.68%,6.28%,4.76%and 2.84%,respectively,compared with OSPF,TBFH,DC and LFC.展开更多
The(3+1)-dimensional Boiti-Leon-Manna-Pempinelli(BLMP)equation serves as a crucial nonlinear evolution equation in mathematical physics,capable of characterizing complex nonlinear dynamic phenomena in three-dimensiona...The(3+1)-dimensional Boiti-Leon-Manna-Pempinelli(BLMP)equation serves as a crucial nonlinear evolution equation in mathematical physics,capable of characterizing complex nonlinear dynamic phenomena in three-dimensional space and one-dimensional time.With broad applications spanning fluid dynamics,shallow water waves,plasma physics,and condensed matter physics,the investigation of its solutions holds significant importance.Traditional analytical methods face limitations due to their dependence on bilinear forms.To overcome this constraint,this letter proposes a novel multi-modal neurosymbolic reasoning intelligent algorithm(MMNRIA)that achieves 100%accurate solutions for nonlinear partial differential equations without requiring bilinear transformations.By synergistically integrating neural networks with symbolic computation,this approach establishes a new paradigm for universal analytical solutions of nonlinear partial differential equations.As a practical demonstration,we successfully derive several exact analytical solutions for the(3+1)-dimensional BLMP equation using MMNRIA.These solutions provide a powerful theoretical framework for studying intricate wave phenomena governed by nonlinearity and dispersion effects in three-dimensional physical space.展开更多
The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach ...The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach facilitates the rapid collection of complete knowledge and rules to form effective decisions.However,the current structured degree of the URT emergency knowledge base remains low,and the domain questions lack labeled datasets,resulting in a large deviation between the consultation outcomes and the intended objectives.To address this issue,this paper proposes a question intention recognition model for the URT emergency domain,leveraging knowledge graph(KG)and data enhancement technology.First,a structured storage of emergency cases and emergency plans is realized based on KG.Subsequently,a comprehensive question template is developed,and the labeled dataset of emergency domain questions in URT is generated through the KG.Lastly,data enhancement is applied by prompt learning and the NLP Chinese Data Augmentation(NLPCDA)tool,and the intention recognition model combining Generalized Auto-regression Pre-training for Language Understanding(XLNet)and Recurrent Convolutional Neural Network for Text Classification(TextRCNN)is constructed.Word embeddings are generated by XLNet,context information is further captured using Bidirectional Long Short-Term Memory Neural Network(BiLSTM),and salient features are extracted with Convolutional Neural Network(CNN).Experimental results demonstrate that the proposed model can enhance the clarity of classification and the identification of domain questions,thereby providing supportive knowledge for emergency decision-making in URT.展开更多
The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation met...The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation method is developed in this study.Firstly,a shift model is established based on computational fluid dynamics and motion simulation to predict the movement of the ceramic core in investment casting process.Subsequently,utilizing this model,an optimization method for fixturing layout inside the refractory ceramic shell is devised for the ceramic core.The casting experiment demonstrates that by utilizing the optimized fixture layout,not only can core shift during the investment casting pouring process be effectively controlled,but also the maximum wall thickness error of the blade can be reduced by 42.02%.In addition,the core shift prediction is also validated,with a prediction error of less than 26.9%.展开更多
Optical reservoir computing(ORC)offers advantages,such as high computational speed,low power consumption,and high training speed,so it has become a competitive candidate for time series analysis in recent years.The cu...Optical reservoir computing(ORC)offers advantages,such as high computational speed,low power consumption,and high training speed,so it has become a competitive candidate for time series analysis in recent years.The current ORC employs single-dimensional encoding for computation,which limits input resolution and introduces extraneous information due to interactions between optical dimensions during propagation,thus constraining performance.Here,we propose complex-value encoding-based optoelectronic reservoir computing(CE-ORC),in which the amplitude and phase of the input optical field are both modulated to improve the input resolution and prevent the influence of extraneous information on computation.In addition,scale factors in the amplitude encoding can fine-tune the optical reservoir dynamics for better performance.We built a CE-ORC processing unit with an iteration rate of up to∼1.2 kHz using high-speed communication interfaces and field programmable gate arrays(FPGAs)and demonstrated the excellent performance of CE-ORC in two time series prediction tasks.In comparison with the conventional ORC for the Mackey–Glass task,CE-ORC showed a decrease in normalized mean square error by∼75%.Furthermore,we applied this method in a weather time series analysis and effectively predicted the temperature and humidity within a range of 24 h.展开更多
Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective fun...Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective functions of all clusters.A novel piecewise power-law control protocol with cooperative-competition relations is proposed.Furthermore,a sufficient condition is obtained to ensure that the FOMASs achieve the cluster consensus within an FXT.展开更多
Dear Editor,This letter deals with the structural controller design problem of interconnected systems with unknown feedback topology.Firstly,under a cardinality constraint on the directed communication links among sub...Dear Editor,This letter deals with the structural controller design problem of interconnected systems with unknown feedback topology.Firstly,under a cardinality constraint on the directed communication links among sub-controllers,a distributed controller’s feedback gain and feedback topology are incorporated in a unified co-design framework.Secondly,the cardinality constraint introduced in the distributed control is represented by a binary integer programming.To deal with the complementary constraint,a nonlinear programming(NLP)is proposed to relax the binary integer programming.Finally,incorporating the NLP into the standard distributed event-triggered control method,an algorithm is developed for interconnected systems to simultaneously design the feedback topology and controller gain.An interconnected system is composed of several coupling subsystems,which usually coordinate with each other to accomplish a common task.展开更多
Network failures are unavoidable and occur frequently.When the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence process.During this period,a large number of mes...Network failures are unavoidable and occur frequently.When the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence process.During this period,a large number of messages are discarded,which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers(ISP).Therefore,improving the availability of intra-domain routing is a trending research question to be solved.Industry usually employs routing protection algorithms to improve intra-domain routing availability.However,existing routing protection schemes compute as many backup paths as possible to reduce message loss due to network failures,which increases the cost of the network and impedes the methods deployed in practice.To address the issues,this study proposes an efficient routing protection algorithm based on optimized network topology(ERPBONT).ERPBONT adopts the optimized network topology to calculate a backup path with the minimum path coincidence degree with the shortest path for all source purposes.Firstly,the backup path with the minimum path coincidence with the shortest path is described as an integer programming problem.Then the simulated annealing algorithm ERPBONT is used to find the optimal solution.Finally,the algorithm is tested on the simulated topology and the real topology.The experimental results show that ERPBONT effectively reduces the path coincidence between the shortest path and the backup path,and significantly improves the routing availability.展开更多
Membership inference(MI)attacks mainly aim to infer whether a data record was used to train a target model or not.Due to the serious privacy risks,MI attacks have been attracting a tremendous amount of attention in th...Membership inference(MI)attacks mainly aim to infer whether a data record was used to train a target model or not.Due to the serious privacy risks,MI attacks have been attracting a tremendous amount of attention in the research community.One existing work conducted-to our best knowledge the first dedicated survey study in this specific area:The survey provides a comprehensive review of the literature during the period of 2017~2021(e.g.,over 100 papers).However,due to the tremendous amount of progress(i.e.,176 papers)made in this area since 2021,the survey conducted by the one existing work has unfortunately already become very limited in the following two aspects:(1)Although the entire literature from 2017~2021 covers 18 ways to categorize(all the proposed)MI attacks,the literature during the period of 2017~2021,which was reviewed in the one existing work,only covered 5 ways to categorize MI attacks.With 13 ways missing,the survey conducted by the one existing work only covers 27%of the landscape(in terms of how to categorize MI attacks)if a retrospective view is taken.(2)Since the literature during the period of 2017~2021 only covers 27%of the landscape(in terms of how to categorize),the number of new insights(i.e.,why an MI attack could succeed)behind all the proposed MI attacks has been significantly increasing since year 2021.As a result,although none of the previous work has made the insights as a main focus of their studies,we found that the various insights leveraged in the literature can be broken down into 10 groups.Without making the insights as a main focus,a survey study could fail to help researchers gain adequate intellectual depth in this area of research.In this work,we conduct a systematic study to address these limitations.In particular,in order to address the first limitation,we make the 13 newly emerged ways to categorize MI attacks as a main focus on the study.In order to address the second limitation,we provide-to our best knowledge-the first review of the various insights leveraged in the entire literature.We found that the various insights leveraged in the literature can be broken down into 10 groups.Moreover,our survey also provides a comprehensive review of the existing defenses against MI attacks,the existing applications of MI attacks,the widely used datasets(e.g.,107 new datasets),and the eva luation metrics(e.g.,20 new evaluation metrics).展开更多
Numerous complex nonlinear systems in the real-world constantly suffer from random noises,which contribute to the enormous challenge of system control.Additionally,unknown powers in nonlinear systems always lead to th...Numerous complex nonlinear systems in the real-world constantly suffer from random noises,which contribute to the enormous challenge of system control.Additionally,unknown powers in nonlinear systems always lead to the inapplicability of many reported control methods.This article investigates the control issue of stochastic systems which contain complicated nonlinearities and unknown system powers.With the newly constructed Lyapunov function,as well as the control algorithm presented in this work,the authors successfully obtain a controller so that the closed-loop system is semiglobally finite-time stable in probability(SGFSP).Besides,the system output can trackthe reference signal fast.The presented method significantly enlarges the range of application for nonlinear systems.The presented strategy is successfully applied to the liquid-level system.展开更多
The long-term monitoring of respiratory status is crucial for the prevention and diagnosis of respiratory diseases.However,existing continuous respiratory monitoring devices are typically bulky and require either ches...The long-term monitoring of respiratory status is crucial for the prevention and diagnosis of respiratory diseases.However,existing continuous respiratory monitoring devices are typically bulky and require either chest strapping or proximity to the nasal area,which compromises user comfort and may disrupt the monitoring process.To overcome these challenges,we have developed a flexible,attachable,lightweight,and miniaturized system designed for extended wear on the wrist.This system incorporates signal acquisition circuitry,a mobile client,and a deep neural network,facilitating long-term respiratory monitoring.Specifically,we fabricated a highly sensitive(11,847.24 kPa^(−1))flexible pressure sensor using a screen printing process,which is capable of functioning beyond 70,000 cycles.Additionally,we engineered a bidirectional long short-term memory(BiLSTM)neural network,enhanced with a residual module,to classify various respiratory states including slow,normal,fast,and simulated breathing.The system achieved a dataset classification accuracy exceeding 99.5%.We have successfully demonstrated a stable,cost-effective,and durable respiratory sensor system that can quantitatively collect and store respiratory data for individuals and groups.This system holds potential for everyday monitoring of physiological signals and healthcare applications.展开更多
Recently,flexible iontronic pressure sensors(FIPSs)with higher sensitivities and wider sensing ranges than conventional capacitive sensors have been widely investigated.Due to the difficulty of fabricating the nanostr...Recently,flexible iontronic pressure sensors(FIPSs)with higher sensitivities and wider sensing ranges than conventional capacitive sensors have been widely investigated.Due to the difficulty of fabricating the nanostructures that are commonly used on electrodes and ionic layers by screen printing techniques,strategies for fabricating such devices using these techniques to drive their mass production have rarely been reported.Herein,for the first time,we employed a 2-dimensional(2D)hexagonal boron nitride(h-BN)as both an additive and an ionic liquid reservoir in an ionic film,making the sensor printable and significantly improving its sensitivity and sensing range through screen printing.The engineered sensor exhibited high sensitivity(S_(min)>261.4 kPa^(−1))and a broad sensing range(0.05-450 kPa),and it was capable of stable operation at a high pressure(400 kPa)for more than 5000 cycles.In addition,the integrated sensor array system allowed accurate monitoring of wrist pressure and showed great potential for health care systems.We believe that using h-BN as an additive in an ionic material for screen-printed FIPS could greatly inspire research on 2D materials for similar systems and other types of sensors.展开更多
This work studies the tracking issue of uncertain nonlinear systems.The existence of odd rational powers,multiple unknown parameters and the dead-zone input add many difficulties for control design.During procedures o...This work studies the tracking issue of uncertain nonlinear systems.The existence of odd rational powers,multiple unknown parameters and the dead-zone input add many difficulties for control design.During procedures of the control design,by introducing an appropriate Lyapunov function,utilizing recursive control method and the inequality technique,some appropriate intermediate auxiliary control laws are designed under the hypothesis that nonlinear terms in the system are known.When those nonlinear terms are unknown,by employing the powerful approximation ability of fuzzy systems,the intermediate auxiliary control laws are approximated recursively and used to construct the virtual control.Finally,a new fuzzy adaptive tracking controller is constructed to ensure a small tracking error and the boundedness of all states.In this paper,the overparameterization problem is significantly avoided since only two adaptive laws are adopted.Numerical and practical examples are used to verify the raised theory.展开更多
Accurately measuring the complex transmission matrix(CTM) of the scattering medium(SM) holds critical significance for applications in anti-scattering optical imaging, phototherapy, and optical neural networks. Nonint...Accurately measuring the complex transmission matrix(CTM) of the scattering medium(SM) holds critical significance for applications in anti-scattering optical imaging, phototherapy, and optical neural networks. Noninterferometric approaches, utilizing phase retrieval algorithms, can robustly extract the CTM from the speckle patterns formed by multiple probing fields traversing the SM. However, in cases where an amplitude-type spatial light modulator is employed for probing field modulation, the absence of phase control frequently results in the convergence towards a local optimum, undermining the measurement accuracy. Here, we propose a high-accuracy CTM retrieval(CTMR) approach based on regional phase differentiation(RPD). It incorporates a sequence of additional phase masks into the probing fields, imposing a priori constraints on the phase retrieval algorithms. By distinguishing the variance of speckle patterns produced by different phase masks, the RPD-CTMR can effectively direct the algorithm towards a solution that closely approximates the CTM of the SM. We built a prototype of a digital micromirror device modulated RPD-CTMR. By accurately measuring the CTM of diffusers, we achieved an enhancement in the peak-to-background ratio of anti-scattering focusing by a factor of 3.6, alongside a reduction in the bit error rate of anti-scattering image transmission by a factor of 24. Our proposed approach aims to facilitate precise modulation of scattered optical fields, thereby fostering advancements in diverse fields including high-resolution microscopy, biomedical optical imaging, and optical communications.展开更多
With the modernization of traditional Chinese medicine(TCM),creating devices to digitalize aspects of pulse diagnosis has proved to be challenging.The currently available pulse detection devices usually rely on extern...With the modernization of traditional Chinese medicine(TCM),creating devices to digitalize aspects of pulse diagnosis has proved to be challenging.The currently available pulse detection devices usually rely on external pressure devices,which are either bulky or poorly integrated,hindering their practical application.In this work,we propose an innovative wearable active pressure three-channel pulse monitoring device based on TCM pulse diagnosis methods.It combines a flexible pressure sensor array,flexible airbag array,active pressure control unit,advanced machine learning approach,and a companion mobile application for human–computer interaction.Due to the high sensitivity(460.1 kPa^(−1)),high linearity(R^(2)>0.999)and flexibility of the flexible pressure sensors,the device can accurately simulate finger pressure to collect pulse waves(Cun,Guan,and Chi)at different external pressures on the wrist.In addition,by measuring the change in pulse wave amplitude at different pressures,an individual’s blood pressure status can be successfully predicted.This enables truly wearable,actively pressurized,continuous wireless dynamic monitoring of wrist pulse health.The innovative and integrated design of this pulse monitoring platform could provide a new paradigm for digitizing aspects of TCM and other smart healthcare systems.展开更多
The Shack-Hartmann wavefront sensor(SHWS)is widely used for high-speed,precise,and stable wavefront measurements.However,conventional SHWSs encounter a limitation in that the focused spot from each microlens is restri...The Shack-Hartmann wavefront sensor(SHWS)is widely used for high-speed,precise,and stable wavefront measurements.However,conventional SHWSs encounter a limitation in that the focused spot from each microlens is restricted to a single microlens,leading to a limited dynamic range.Herein,we propose an adaptive spot matching(ASM)-based SHWS to extend the dynamic range.This approach involves seeking an incident wavefront that best matches the detected spot distribution by employing a Hausdorff-distance-based nearest-distance matching strategy.The ASM-SHWS enables comprehensive spot matching across the entire imaging plane without requiring initial spot correspondences.Furthermore,due to its global matching capability,ASM-SHWS can maintain its capacity even if a portion of the spots are missing.Experiments showed that the ASM-SHWS could measure a high-curvature spherical wavefront with a local slope of 204.97 mrad,despite a 12.5%absence of spots.This value exceeds that of the conventional SHWS by a factor of 14.81.展开更多
The exact physical modeling for scattered light modulation is critical in phototherapy,biomedical imaging,and free-space optical communications.In particular,the angular spectrum modeling of scattered light has attrac...The exact physical modeling for scattered light modulation is critical in phototherapy,biomedical imaging,and free-space optical communications.In particular,the angular spectrum modeling of scattered light has attracted considerable attention,but the existing angular spectrum models neglect the polarization of photons,degrading their performance.Here,we propose a full-polarization angular spectrum model(fpASM)to take the polarization into account.This model involves a combination of the optical field changes and free-space angular spectrum diffraction,and enables an investigation of the influence of polarization-related factors on the performance of scattered light modulation.By establishing the relationship between various model parameters and macroscopic scattering properties,our model can effectively characterize various depolarization conditions.As a demonstration,we apply the model in the time-reversal data transmission and anti-scattering light focusing.Our method allows the analysis of various depolarization scattering events and benefits applications related to scattered light modulation.展开更多
Speed and enhancement are the two most important metrics for anti-scattering light focusing by wavefront shaping(WS),which requires a spatial light modulator with a large number of modulation modes and a fast speed of...Speed and enhancement are the two most important metrics for anti-scattering light focusing by wavefront shaping(WS),which requires a spatial light modulator with a large number of modulation modes and a fast speed of response.Among the commercial modulators,the digital-micromirror device(DMD)is the sole solution providing millions of modulation modes and a pattern rate higher than 20 kHz.Thus,it has the potential to accelerate the process of anti-scattering light focusing with a high enhancement.Nevertheless,modulating light in a binary mode by the DMD restricts both the speed and enhancement seriously.Here,we propose a multi-pixel encoded DMD-based WS method by combining multiple micromirrors into a single modulation unit to overcome the drawbacks of binary modulation.In addition,to efficiently optimize the wavefront,we adopted separable natural evolution strategies(SNES),which could carry out a global search against a noisy environment.Compared with the state-of-the-art DMD-based WS method,the proposed method increased the speed of optimization and enhancement of focus by a factor of 179 and 16,respectively.In our demonstration,we achieved 10 foci with homogeneous brightness at a high speed and formed W-and S-shape patterns against the scattering medium.The experimental results suggest that the proposed method will pave a new avenue for WS in the applications of biomedical imaging,photon therapy,optogenetics,dynamic holographic display,etc.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(grant number 2024YJS096)National Natural Science Foundation of China(grant numbers 62433005,62272036,62173167).
文摘The accurate prediction and analysis of emergencies in Urban Rail Transit Systems(URTS)are essential for the development of effective early warning and prevention mechanisms.This study presents an integrated perception model designed to predict emergencies and analyze their causes based on historical unstructured emergency data.To address issues related to data structuredness and missing values,we employed label encoding and an Elastic Net Regularization-based Generative Adversarial Interpolation Network(ER-GAIN)for data structuring and imputation.Additionally,to mitigate the impact of imbalanced data on the predictive performance of emergencies,we introduced an Adaptive Boosting Ensemble Model(AdaBoost)to forecast the key features of emergencies,including event types and levels.We also utilized Information Gain(IG)to analyze and rank the causes of various significant emergencies.Experimental results indicate that,compared to baseline data imputation models,ER-GAIN improved the prediction accuracy of key emergency features by 3.67%and 3.78%,respectively.Furthermore,AdaBoost enhanced the accuracy by over 4.34%and 3.25%compared to baseline predictivemodels.Through causation analysis,we identified the critical causes of train operation and fire incidents.The findings of this research will contribute to the establishment of early warning and prevention mechanisms for emergencies in URTS,potentially leading to safer and more reliable URTS operations.
文摘This paper gives an introduction to the essential challenges of software engineering and requirements that software has to fulfill in the domain of automation. Besides, the functional characteristics, specific constraints and circumstances are considered for deriving requirements concerning usability, the technical process, the automation functions, used platform and the well-established models, which are described in detail. On the other hand, challenges result from the circumstances at different points in the single phases of the life cycle of the automated system. The requirements for life-cycle-management, tools and the changeability during runtime are described in detail.
基金supported by Fundamental Research Program of Shanxi Province(No.20210302123444)the Research Project at the College Level of China Institute of Labor Relations(No.23XYJS018)+2 种基金the ICH Digitalization and Multi-Source Information Fusion Fujian Provincial University Engineering Research Center 2022 Open Fund Project(G3-KF2207)the China University Industry University Research Innovation Fund(No.2021FNA02009)the Key R&D Program(International Science and Technology Cooperation Project)of Shanxi Province China(No.201903D421003).
文摘Currently,distributed routing protocols are constrained by offering a single path between any pair of nodes,thereby limiting the potential throughput and overall network performance.This approach not only restricts the flow of data but also makes the network susceptible to failures in case the primary path is disrupted.In contrast,routing protocols that leverage multiple paths within the network offer a more resilient and efficient solution.Multipath routing,as a fundamental concept,surpasses the limitations of traditional shortest path first protocols.It not only redirects traffic to unused resources,effectively mitigating network congestion,but also ensures load balancing across the network.This optimization significantly improves network utilization and boosts the overall performance,making it a widely recognized efficient method for enhancing network reliability.To further strengthen network resilience against failures,we introduce a routing scheme known as Multiple Nodes with at least Two Choices(MNTC).This innovative approach aims to significantly enhance network availability by providing each node with at least two routing choices.By doing so,it not only reduces the dependency on a single path but also creates redundant paths that can be utilized in case of failures,thereby enhancing the overall resilience of the network.To ensure the optimal placement of nodes,we propose three incremental deployment algorithms.These algorithms carefully select the most suitable set of nodes for deployment,taking into account various factors such as node connectivity,traffic patterns,and network topology.By deployingMNTCon a carefully chosen set of nodes,we can significantly enhance network reliability without the need for a complete overhaul of the existing infrastructure.We have conducted extensive evaluations of MNTC in diverse topological spaces,demonstrating its effectiveness in maintaining high network availability with minimal path stretch.The results are impressive,showing that even when implemented on just 60%of nodes,our incremental deployment method significantly boosts network availability.This underscores the potential of MNTC in enhancing network resilience and performance,making it a viable solution for modern networks facing increasing demands and complexities.The algorithms OSPF,TBFH,DC and LFC perform fast rerouting based on strict conditions,while MNTC is not restricted by these conditions.In five real network topologies,the average network availability ofMNTCis improved by 14.68%,6.28%,4.76%and 2.84%,respectively,compared with OSPF,TBFH,DC and LFC.
基金supported by the National Natural Science Foundation of China(Grant No.62303289)Tianyuan Fund for Mathematics of the National Natural Science Foundation of China(Grant No.12426105)+3 种基金the Scientific and Technological Innovation Programs(STIP)of Higher Education Institutions in Shanxi(Grant No.2024L022)Fundamental Research Program of Shanxi Province(Grant Nos.202403021222001 and 202203021222003)the“Wen Ying Young Scholars”Talent Project of Shanxi University(Grant Nos.138541088,138541090,and 138541127)Funded by Open Foundation of Hubei Key Laboratory of Applied Mathematics(Hubei University)(Grant No.HBAM202401).
文摘The(3+1)-dimensional Boiti-Leon-Manna-Pempinelli(BLMP)equation serves as a crucial nonlinear evolution equation in mathematical physics,capable of characterizing complex nonlinear dynamic phenomena in three-dimensional space and one-dimensional time.With broad applications spanning fluid dynamics,shallow water waves,plasma physics,and condensed matter physics,the investigation of its solutions holds significant importance.Traditional analytical methods face limitations due to their dependence on bilinear forms.To overcome this constraint,this letter proposes a novel multi-modal neurosymbolic reasoning intelligent algorithm(MMNRIA)that achieves 100%accurate solutions for nonlinear partial differential equations without requiring bilinear transformations.By synergistically integrating neural networks with symbolic computation,this approach establishes a new paradigm for universal analytical solutions of nonlinear partial differential equations.As a practical demonstration,we successfully derive several exact analytical solutions for the(3+1)-dimensional BLMP equation using MMNRIA.These solutions provide a powerful theoretical framework for studying intricate wave phenomena governed by nonlinearity and dispersion effects in three-dimensional physical space.
基金supported in part by the National Natural Science Foundation of China.The funding numbers 62433005,62272036,62132003,and 62173167.
文摘The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach facilitates the rapid collection of complete knowledge and rules to form effective decisions.However,the current structured degree of the URT emergency knowledge base remains low,and the domain questions lack labeled datasets,resulting in a large deviation between the consultation outcomes and the intended objectives.To address this issue,this paper proposes a question intention recognition model for the URT emergency domain,leveraging knowledge graph(KG)and data enhancement technology.First,a structured storage of emergency cases and emergency plans is realized based on KG.Subsequently,a comprehensive question template is developed,and the labeled dataset of emergency domain questions in URT is generated through the KG.Lastly,data enhancement is applied by prompt learning and the NLP Chinese Data Augmentation(NLPCDA)tool,and the intention recognition model combining Generalized Auto-regression Pre-training for Language Understanding(XLNet)and Recurrent Convolutional Neural Network for Text Classification(TextRCNN)is constructed.Word embeddings are generated by XLNet,context information is further captured using Bidirectional Long Short-Term Memory Neural Network(BiLSTM),and salient features are extracted with Convolutional Neural Network(CNN).Experimental results demonstrate that the proposed model can enhance the clarity of classification and the identification of domain questions,thereby providing supportive knowledge for emergency decision-making in URT.
基金the National Natural Science Foundation of China(Grant No.52005311)the Scientific and the National Science and Technology Major Project(Grant No.J2019-VII-0013-0153)Research Project Supported by Shanxi Scholarship Council of China(Grant No.2023-003).
文摘The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation method is developed in this study.Firstly,a shift model is established based on computational fluid dynamics and motion simulation to predict the movement of the ceramic core in investment casting process.Subsequently,utilizing this model,an optimization method for fixturing layout inside the refractory ceramic shell is devised for the ceramic core.The casting experiment demonstrates that by utilizing the optimized fixture layout,not only can core shift during the investment casting pouring process be effectively controlled,but also the maximum wall thickness error of the blade can be reduced by 42.02%.In addition,the core shift prediction is also validated,with a prediction error of less than 26.9%.
基金the National Natural Science Foundation of China(Grant Nos.62375171,62305208,62205189,62105203,and 62405182)the Shanghai Pujiang Program(Grant No.22PJ1407500)+4 种基金the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SJTU)(Grant No.SL2022ZD205)the National Key Research and Development Program of China(Grant No.2022YFC2806600)the Science Foundation of Donghai Laboratory(Grant Nos.DH-2022KF01001 and DH-2022KF01005)the Startup Fund for Young Faculty at SJTU(Grant No.24X010500120)the Science and Technology Commission of Shanghai Municipality(Grant No.20DZ2220400).
文摘Optical reservoir computing(ORC)offers advantages,such as high computational speed,low power consumption,and high training speed,so it has become a competitive candidate for time series analysis in recent years.The current ORC employs single-dimensional encoding for computation,which limits input resolution and introduces extraneous information due to interactions between optical dimensions during propagation,thus constraining performance.Here,we propose complex-value encoding-based optoelectronic reservoir computing(CE-ORC),in which the amplitude and phase of the input optical field are both modulated to improve the input resolution and prevent the influence of extraneous information on computation.In addition,scale factors in the amplitude encoding can fine-tune the optical reservoir dynamics for better performance.We built a CE-ORC processing unit with an iteration rate of up to∼1.2 kHz using high-speed communication interfaces and field programmable gate arrays(FPGAs)and demonstrated the excellent performance of CE-ORC in two time series prediction tasks.In comparison with the conventional ORC for the Mackey–Glass task,CE-ORC showed a decrease in normalized mean square error by∼75%.Furthermore,we applied this method in a weather time series analysis and effectively predicted the temperature and humidity within a range of 24 h.
基金supported in part by the National Natural Science Foundation of China(62373231,61973201)the Fundamental Research Program of Shanxi Province(202203021211297)Shanxi Scholarship Council of China(2023-002)。
文摘Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective functions of all clusters.A novel piecewise power-law control protocol with cooperative-competition relations is proposed.Furthermore,a sufficient condition is obtained to ensure that the FOMASs achieve the cluster consensus within an FXT.
基金This work was supported by the National Natural Science Foundation of China(61973201)the Fundamental Research Program of Shanxi Province(20210302124030).
文摘Dear Editor,This letter deals with the structural controller design problem of interconnected systems with unknown feedback topology.Firstly,under a cardinality constraint on the directed communication links among sub-controllers,a distributed controller’s feedback gain and feedback topology are incorporated in a unified co-design framework.Secondly,the cardinality constraint introduced in the distributed control is represented by a binary integer programming.To deal with the complementary constraint,a nonlinear programming(NLP)is proposed to relax the binary integer programming.Finally,incorporating the NLP into the standard distributed event-triggered control method,an algorithm is developed for interconnected systems to simultaneously design the feedback topology and controller gain.An interconnected system is composed of several coupling subsystems,which usually coordinate with each other to accomplish a common task.
基金This work is supported by the Hainan Provincial Natural Science Foundation of China(620RC562)the Natural Science Foundation of Shanxi Province(Grant Nos.20210302123444,20210302123455)+5 种基金the China University industry university research innovation fund(No.2021FNA02009)the Open Project Program of the Key Laboratory of Embedded System and Service Computing of Ministry of Education(Tongji University)ESSCKF 2021-04the National Natural Science Foundation of China(Grant Nos.61702315,61802092)the Applied Basic Research Plan of Shanxi Province(No.201901D211168)the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation(QCXM201910)the Key R&D Program(International Science and Technology Cooperation Project)of Shanxi Province China(No.201903D421003).
文摘Network failures are unavoidable and occur frequently.When the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence process.During this period,a large number of messages are discarded,which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers(ISP).Therefore,improving the availability of intra-domain routing is a trending research question to be solved.Industry usually employs routing protection algorithms to improve intra-domain routing availability.However,existing routing protection schemes compute as many backup paths as possible to reduce message loss due to network failures,which increases the cost of the network and impedes the methods deployed in practice.To address the issues,this study proposes an efficient routing protection algorithm based on optimized network topology(ERPBONT).ERPBONT adopts the optimized network topology to calculate a backup path with the minimum path coincidence degree with the shortest path for all source purposes.Firstly,the backup path with the minimum path coincidence with the shortest path is described as an integer programming problem.Then the simulated annealing algorithm ERPBONT is used to find the optimal solution.Finally,the algorithm is tested on the simulated topology and the real topology.The experimental results show that ERPBONT effectively reduces the path coincidence between the shortest path and the backup path,and significantly improves the routing availability.
基金supported by National Natural Science Foundation of China(61941105,61772406,and U2336203)National Key Research and Development Program of China(2023QY1202)Beijing Natural Science Foundation(4242031).
文摘Membership inference(MI)attacks mainly aim to infer whether a data record was used to train a target model or not.Due to the serious privacy risks,MI attacks have been attracting a tremendous amount of attention in the research community.One existing work conducted-to our best knowledge the first dedicated survey study in this specific area:The survey provides a comprehensive review of the literature during the period of 2017~2021(e.g.,over 100 papers).However,due to the tremendous amount of progress(i.e.,176 papers)made in this area since 2021,the survey conducted by the one existing work has unfortunately already become very limited in the following two aspects:(1)Although the entire literature from 2017~2021 covers 18 ways to categorize(all the proposed)MI attacks,the literature during the period of 2017~2021,which was reviewed in the one existing work,only covered 5 ways to categorize MI attacks.With 13 ways missing,the survey conducted by the one existing work only covers 27%of the landscape(in terms of how to categorize MI attacks)if a retrospective view is taken.(2)Since the literature during the period of 2017~2021 only covers 27%of the landscape(in terms of how to categorize),the number of new insights(i.e.,why an MI attack could succeed)behind all the proposed MI attacks has been significantly increasing since year 2021.As a result,although none of the previous work has made the insights as a main focus of their studies,we found that the various insights leveraged in the literature can be broken down into 10 groups.Without making the insights as a main focus,a survey study could fail to help researchers gain adequate intellectual depth in this area of research.In this work,we conduct a systematic study to address these limitations.In particular,in order to address the first limitation,we make the 13 newly emerged ways to categorize MI attacks as a main focus on the study.In order to address the second limitation,we provide-to our best knowledge-the first review of the various insights leveraged in the entire literature.We found that the various insights leveraged in the literature can be broken down into 10 groups.Moreover,our survey also provides a comprehensive review of the existing defenses against MI attacks,the existing applications of MI attacks,the widely used datasets(e.g.,107 new datasets),and the eva luation metrics(e.g.,20 new evaluation metrics).
基金supported by the Fundamental Research Program of Shanxi Province under Grant Nos.202203021221004 and 202303021221185。
文摘Numerous complex nonlinear systems in the real-world constantly suffer from random noises,which contribute to the enormous challenge of system control.Additionally,unknown powers in nonlinear systems always lead to the inapplicability of many reported control methods.This article investigates the control issue of stochastic systems which contain complicated nonlinearities and unknown system powers.With the newly constructed Lyapunov function,as well as the control algorithm presented in this work,the authors successfully obtain a controller so that the closed-loop system is semiglobally finite-time stable in probability(SGFSP).Besides,the system output can trackthe reference signal fast.The presented method significantly enlarges the range of application for nonlinear systems.The presented strategy is successfully applied to the liquid-level system.
基金supported by the National Key Research and Development Program of China(2023YFB3208600)the National Natural Science Foundation of China(No.62274140)+3 种基金Key Program of the National Natural Science Foundation of China(62433017)the Science and Technology on Vacuum Technology and Physics Laboratory Fund(HTKJ2023KL510008)the Fundamental Research Funds for the Central Universities(20720230030)the Xiaomi Young Talents Program/Xiaomi Foundation,Shenzhen Science and Technology Program(JCYJ20230807091401003).
文摘The long-term monitoring of respiratory status is crucial for the prevention and diagnosis of respiratory diseases.However,existing continuous respiratory monitoring devices are typically bulky and require either chest strapping or proximity to the nasal area,which compromises user comfort and may disrupt the monitoring process.To overcome these challenges,we have developed a flexible,attachable,lightweight,and miniaturized system designed for extended wear on the wrist.This system incorporates signal acquisition circuitry,a mobile client,and a deep neural network,facilitating long-term respiratory monitoring.Specifically,we fabricated a highly sensitive(11,847.24 kPa^(−1))flexible pressure sensor using a screen printing process,which is capable of functioning beyond 70,000 cycles.Additionally,we engineered a bidirectional long short-term memory(BiLSTM)neural network,enhanced with a residual module,to classify various respiratory states including slow,normal,fast,and simulated breathing.The system achieved a dataset classification accuracy exceeding 99.5%.We have successfully demonstrated a stable,cost-effective,and durable respiratory sensor system that can quantitatively collect and store respiratory data for individuals and groups.This system holds potential for everyday monitoring of physiological signals and healthcare applications.
基金The authors would like to acknowledge the financial support of the project from the National Natural Science Foundation of China(No.62274140 and 61804090)the Key R&D Program of Shanxi Province(No.202102020101010).
文摘Recently,flexible iontronic pressure sensors(FIPSs)with higher sensitivities and wider sensing ranges than conventional capacitive sensors have been widely investigated.Due to the difficulty of fabricating the nanostructures that are commonly used on electrodes and ionic layers by screen printing techniques,strategies for fabricating such devices using these techniques to drive their mass production have rarely been reported.Herein,for the first time,we employed a 2-dimensional(2D)hexagonal boron nitride(h-BN)as both an additive and an ionic liquid reservoir in an ionic film,making the sensor printable and significantly improving its sensitivity and sensing range through screen printing.The engineered sensor exhibited high sensitivity(S_(min)>261.4 kPa^(−1))and a broad sensing range(0.05-450 kPa),and it was capable of stable operation at a high pressure(400 kPa)for more than 5000 cycles.In addition,the integrated sensor array system allowed accurate monitoring of wrist pressure and showed great potential for health care systems.We believe that using h-BN as an additive in an ionic material for screen-printed FIPS could greatly inspire research on 2D materials for similar systems and other types of sensors.
基金supported by Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(STIP)under Grant No.2019L0011the Major Scientific and Technological Innovation Project in Shandong Province under Grant No.2019JZZY011111。
文摘This work studies the tracking issue of uncertain nonlinear systems.The existence of odd rational powers,multiple unknown parameters and the dead-zone input add many difficulties for control design.During procedures of the control design,by introducing an appropriate Lyapunov function,utilizing recursive control method and the inequality technique,some appropriate intermediate auxiliary control laws are designed under the hypothesis that nonlinear terms in the system are known.When those nonlinear terms are unknown,by employing the powerful approximation ability of fuzzy systems,the intermediate auxiliary control laws are approximated recursively and used to construct the virtual control.Finally,a new fuzzy adaptive tracking controller is constructed to ensure a small tracking error and the boundedness of all states.In this paper,the overparameterization problem is significantly avoided since only two adaptive laws are adopted.Numerical and practical examples are used to verify the raised theory.
基金National Natural Science Foundation of China(62305208,62375171)Shanghai Pujiang Program(22PJ1407500)+2 种基金Shanghai Jiao Tong University 2030 Initiative(WH510363001-10)Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SL2022ZD205)Science Foundation of Donghai Laboratory(DH-2022KF01001)。
文摘Accurately measuring the complex transmission matrix(CTM) of the scattering medium(SM) holds critical significance for applications in anti-scattering optical imaging, phototherapy, and optical neural networks. Noninterferometric approaches, utilizing phase retrieval algorithms, can robustly extract the CTM from the speckle patterns formed by multiple probing fields traversing the SM. However, in cases where an amplitude-type spatial light modulator is employed for probing field modulation, the absence of phase control frequently results in the convergence towards a local optimum, undermining the measurement accuracy. Here, we propose a high-accuracy CTM retrieval(CTMR) approach based on regional phase differentiation(RPD). It incorporates a sequence of additional phase masks into the probing fields, imposing a priori constraints on the phase retrieval algorithms. By distinguishing the variance of speckle patterns produced by different phase masks, the RPD-CTMR can effectively direct the algorithm towards a solution that closely approximates the CTM of the SM. We built a prototype of a digital micromirror device modulated RPD-CTMR. By accurately measuring the CTM of diffusers, we achieved an enhancement in the peak-to-background ratio of anti-scattering focusing by a factor of 3.6, alongside a reduction in the bit error rate of anti-scattering image transmission by a factor of 24. Our proposed approach aims to facilitate precise modulation of scattered optical fields, thereby fostering advancements in diverse fields including high-resolution microscopy, biomedical optical imaging, and optical communications.
基金support provided by the National Natural Science Foundation of China(Nos.62274140,42004157,62201537)the Fundamental Research Funds for the Central Universities(No.20720230030)+2 种基金the Xiaomi Young Talents Program/Xiaomi Foundation,the Youth Talent Promotion Project of Gansu Province(No.GXH20210611-05)the Youth Talent Promotion Project of Chinathe funding of the Natural Science Foundation of Shandong Province(No.ZR2022QF008).
文摘With the modernization of traditional Chinese medicine(TCM),creating devices to digitalize aspects of pulse diagnosis has proved to be challenging.The currently available pulse detection devices usually rely on external pressure devices,which are either bulky or poorly integrated,hindering their practical application.In this work,we propose an innovative wearable active pressure three-channel pulse monitoring device based on TCM pulse diagnosis methods.It combines a flexible pressure sensor array,flexible airbag array,active pressure control unit,advanced machine learning approach,and a companion mobile application for human–computer interaction.Due to the high sensitivity(460.1 kPa^(−1)),high linearity(R^(2)>0.999)and flexibility of the flexible pressure sensors,the device can accurately simulate finger pressure to collect pulse waves(Cun,Guan,and Chi)at different external pressures on the wrist.In addition,by measuring the change in pulse wave amplitude at different pressures,an individual’s blood pressure status can be successfully predicted.This enables truly wearable,actively pressurized,continuous wireless dynamic monitoring of wrist pulse health.The innovative and integrated design of this pulse monitoring platform could provide a new paradigm for digitizing aspects of TCM and other smart healthcare systems.
基金supported by the Fundamental Research Funds for the Central Universities of Shanghai Jiao Tong University and the Shanghai Jiao Tong University 2030 Initiative(No.WH510363001-10)the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(No.SL2022ZD205)+1 种基金the Science Foundation of the Donghai Laboratory(No.DH-2022KF01001)National Natural Science Foundation of China(No.62205189).
文摘The Shack-Hartmann wavefront sensor(SHWS)is widely used for high-speed,precise,and stable wavefront measurements.However,conventional SHWSs encounter a limitation in that the focused spot from each microlens is restricted to a single microlens,leading to a limited dynamic range.Herein,we propose an adaptive spot matching(ASM)-based SHWS to extend the dynamic range.This approach involves seeking an incident wavefront that best matches the detected spot distribution by employing a Hausdorff-distance-based nearest-distance matching strategy.The ASM-SHWS enables comprehensive spot matching across the entire imaging plane without requiring initial spot correspondences.Furthermore,due to its global matching capability,ASM-SHWS can maintain its capacity even if a portion of the spots are missing.Experiments showed that the ASM-SHWS could measure a high-curvature spherical wavefront with a local slope of 204.97 mrad,despite a 12.5%absence of spots.This value exceeds that of the conventional SHWS by a factor of 14.81.
基金National Natural Science Foundation of China(62205189,62375171)Fundamental Research Funds for the Central Universities+3 种基金Shanghai Pujiang Program(22PJ1407500)Shanghai Jiao Tong University 2030Initiative(WH510363001-10)Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SL2022ZD205)Science Foundation of Donghai Laboratory(DH-2022KF01001)。
文摘The exact physical modeling for scattered light modulation is critical in phototherapy,biomedical imaging,and free-space optical communications.In particular,the angular spectrum modeling of scattered light has attracted considerable attention,but the existing angular spectrum models neglect the polarization of photons,degrading their performance.Here,we propose a full-polarization angular spectrum model(fpASM)to take the polarization into account.This model involves a combination of the optical field changes and free-space angular spectrum diffraction,and enables an investigation of the influence of polarization-related factors on the performance of scattered light modulation.By establishing the relationship between various model parameters and macroscopic scattering properties,our model can effectively characterize various depolarization conditions.As a demonstration,we apply the model in the time-reversal data transmission and anti-scattering light focusing.Our method allows the analysis of various depolarization scattering events and benefits applications related to scattered light modulation.
基金Shanghai Municipal of Science and Technology Project(No.20JC1419500)Foundation of National Facility for Translational Medicine(Shanghai)(No.TMSK-2020-129)+2 种基金Shanghai Pujiang Program(NO.20PJ 1408700)National Natural Science Foundation of China(No.62005007)the Fundamental Research Funds for the Central Universities(Beihang University).
文摘Speed and enhancement are the two most important metrics for anti-scattering light focusing by wavefront shaping(WS),which requires a spatial light modulator with a large number of modulation modes and a fast speed of response.Among the commercial modulators,the digital-micromirror device(DMD)is the sole solution providing millions of modulation modes and a pattern rate higher than 20 kHz.Thus,it has the potential to accelerate the process of anti-scattering light focusing with a high enhancement.Nevertheless,modulating light in a binary mode by the DMD restricts both the speed and enhancement seriously.Here,we propose a multi-pixel encoded DMD-based WS method by combining multiple micromirrors into a single modulation unit to overcome the drawbacks of binary modulation.In addition,to efficiently optimize the wavefront,we adopted separable natural evolution strategies(SNES),which could carry out a global search against a noisy environment.Compared with the state-of-the-art DMD-based WS method,the proposed method increased the speed of optimization and enhancement of focus by a factor of 179 and 16,respectively.In our demonstration,we achieved 10 foci with homogeneous brightness at a high speed and formed W-and S-shape patterns against the scattering medium.The experimental results suggest that the proposed method will pave a new avenue for WS in the applications of biomedical imaging,photon therapy,optogenetics,dynamic holographic display,etc.
