Many industrial companies and researchers are looking for more efficient model driven engineering approaches (MDE) in software engineering of manufacturing automation systems (MS) especially for logic control programm...Many industrial companies and researchers are looking for more efficient model driven engineering approaches (MDE) in software engineering of manufacturing automation systems (MS) especially for logic control programming, but are uncertain about the applicability and effort needed to implement those approaches in comparison to classical Programmable Logic Controller?(PLC) programming with IEC 61131-3. The paper summarizes results of usability experiments evaluating UML and SysML as software engineering notations for a MDE applied in the domain of manufacturing systems. Modeling MS needs to cover the domain specific characteristics,?i.e.?hybrid process, real time requirements and communication requirements. In addition the paper presents factors, constraint and practical experience for the development of further usability experiments. The paper gives examples of notational expressiveness and weaknesses of UML and SysML. The appendix delivers detailed master models, representing the correct best suited model, and evaluation schemes of the experiment, which is helpful if setting up own empirical experiments.展开更多
Co-based alloy coating was prepared on Zr alloy using laser melting and cladding technique to study the difference in the high-temperature oxidation behavior between pure metal Co coatings and Co-T800 alloy coatings,a...Co-based alloy coating was prepared on Zr alloy using laser melting and cladding technique to study the difference in the high-temperature oxidation behavior between pure metal Co coatings and Co-T800 alloy coatings,as well as the wear resistance of the coatings.Besides,the effect of changing the laser melting process on the coatings was also investigated.The oxidation mass gain at 800–1200℃and the high-temperature oxidation behavior during high-temperature treatment for 1 h of two coated Zr alloy samples were studied.Results show that the Co coating and the Co-T800 coating have better resistance against high-temperature oxidation.After oxidizing at 1000℃for 1 h,the thickness of the oxide layer of the uncoated sample was 241.0μm,whereas that of the sample with Co-based coating is only 11.8–35.5μm.The friction wear test shows that the depth of the abrasion mark of the coated sample is only 1/2 of that of the substrate,indicating that the hardness and wear resistance of the Zr substrate are greatly improved.The disadvantage of Co-based coatings is the inferior corrosion resistance in 3.5wt%NaCl solution.展开更多
Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-...Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.展开更多
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
As production automation systems have been and are becoming more and more complex, the task of quality assurance is increasingly challenging. Model-based testing is a research field addressing this challenge and many ...As production automation systems have been and are becoming more and more complex, the task of quality assurance is increasingly challenging. Model-based testing is a research field addressing this challenge and many approaches have been suggested for different applications. The goal of this paper is to review these approaches regarding their suitability for the domain of production automation in order to identify current trends and research gaps. The different approaches are classified and clustered according to their main focus which is either testing and test case generation from some form of model automatons, test case generation from models used within the development process of production automation systems, test case generation from fault models or test case selection and regression testing.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
To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explo...To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explores the feasibility of adaptive-signal-decomposition-based denoising methods to improve THz spectral quality.THz time-domain spectroscopy(THz-TDS)combined with an attenuated total reflection(ATR)accessory was used to collect THz absorbance spectra from 48 peanut samples.Taking the quantitative prediction model of peanut moisture content based on THz-ATR as an example,wavelet transform(WT),empirical mode decomposition(EMD),local mean decomposition(LMD),and its improved methods-segmented local mean decomposition(SLMD)and piecewise mirror extension local mean decomposition(PME-LMD)-were employed for spectral denoising.The applicability of different denoising methods was evaluated using a support vector regression(SVR)model.Experimental results show that the peanut moisture content prediction model constructed after PME-LMD denoising achieved the best performance,with a root mean square error(RMSE),coefficient of determination(R^(2)),and mean absolute percentage error(MAPE)of 0.010,0.912,and 0.040,respectively.Compared with traditional methods,PME-LMD significantly improved spectral quality and model prediction performance.The PME-LMD denoising strategy proposed in this study effectively suppresses non-uniform noise interference in THz spectral signals,providing an efficient and accurate preprocessing method for THz spectral analysis of agricultural products.This research provides theoretical support and technical guidance for the application of THz technology for detecting agricultural product quality.展开更多
High-temperature piezoelectric sen-sors are very important in severe environments such as fire safety,aerospace and oil drills,however,most current sensors are not heat res-istant(<300℃)and are fragile,which limit...High-temperature piezoelectric sen-sors are very important in severe environments such as fire safety,aerospace and oil drills,however,most current sensors are not heat res-istant(<300℃)and are fragile,which limits their use,especially in high-temperature environ-ments.A high-temperature resistant flexible piezoelectric film based on graphene oxide(GO)/polyacrylonitrile(PAN)composites was prepared by electrospinning and thermal treat-ment.It was packed into a micro-device,which could work continuously at 500℃.The intro-duction of GO significantly increased the mechanical properties of the PAN nanofibers because the oxygen-containing func-tional groups(electronegative groups)on the surface of the GO initiated a nucleophilic attack on the PAN molecule during heat treatment,enabling the GO to initiate the cyclization of the PAN at lower heat-treatment temperatures.In addition,the abund-ant oxygen-containing functional groups on GO acted as pro-oxidants to hasten the oxidation of PAN during heat treatment.The effects of GO content and heat treatment temperature on the properties of the nanofiber films were investigated.A GO/PAN nanofiber piezoelectric sensor heat-treated at 300℃had a 9.10 V and 2.25μA peak output,which are respectively 101.3%and 78.6%higher than those of the untreated films.Cyclic testing over 5000 cycles at 350℃confirmed the stable out-put performance of the GO/PAN nanofiber piezoelectric sensor.Furthermore,a sensor heat-treated at 400℃had a sensitivity of 1.7 V/N,which is 83.5%higher than that of an untreated one.The results show that the prepared GO/PAN nanofiber piezo-electric sensor combines high temperature resistance,high flexibility,stability and high sensitivity,and may have broad applic-ations in high temperature environments such as the aerospace and petroleum industries.展开更多
In its 2023 global health statistics,the World Health Organization noted that noncommunicable diseases(NCDs)remain the leading cause of disease burden worldwide,with cardiovascular diseases(CVDs)resulting in more deat...In its 2023 global health statistics,the World Health Organization noted that noncommunicable diseases(NCDs)remain the leading cause of disease burden worldwide,with cardiovascular diseases(CVDs)resulting in more deaths than the three other major NCDs combined.In this study,we developed a method that can comprehensively detect which CVDs are present in a patient.Specifically,we propose a multi-label classification method that utilizes photoplethysmography(PPG)signals and physiological characteristics from public datasets to classify four types of CVDs and related conditions:hypertension,diabetes,cerebral infarction,and cerebrovascular disease.Our approach to multi-disease classification of cardiovascular diseases(CVDs)using PPG signals achieves the highest classification performance when encompassing the broadest range of disease categories,thereby offering a more comprehensive assessment of human health.We employ a multi-label classification strategy to simultaneously predict the presence or absence of multiple diseases.Specifically,we first apply the Savitzky-Golay(S-G)filter to the PPG signals to reduce noise and then transform into statistical features.We integrate processed PPG signals with individual physiological features as a multimodal input,thereby expanding the learned feature space.Notably,even with a simple machine learning method,this approach can achieve relatively high accuracy.The proposed method achieved a maximum F1-score of 0.91,minimum Hamming loss of 0.04,and an accuracy of 0.95.Thus,our method represents an effective and rapid solution for detecting multiple diseases simultaneously,which is beneficial for comprehensively managing CVDs.展开更多
An innovative design method is outlined in this paper for the pointing control mechanism of large space flexible antennas.This method focuses on enhancing the accuracy and stability that are crucial for large spacecra...An innovative design method is outlined in this paper for the pointing control mechanism of large space flexible antennas.This method focuses on enhancing the accuracy and stability that are crucial for large spacecraft applications,such as space solar power stations.Utilizing potential energy function analysis,the dynamics of the antenna are modeled,treating it as an equivalent n-joint robotic arm.This approach simulates the rigid-flexible coupling effect through joint angle manipulations.The proposed HJI(Hamilton-Jacobi-Inequality)sliding mode robust control integrates HJI principle,dissipative system theory,and sliding mode control,offering improved pointing accuracy and robustness.Simulation results underscore the superiority of HJI sliding mode robust control over traditional PD(proportional-derivative)control in initial response,precision,and control smoothness,albeit at the cost of higher control torque requirements.This research underscores the potential of HJI sliding mode robust control in facilitating precise pointing control for future large space structures,enabling efficient space missions and reliable energy transmission.展开更多
Flexible electronic technology has laid the foundation for complex human-computer interaction system,and has attracted great attention in the field of human motion detection and soft robotics.Graphene has received an ...Flexible electronic technology has laid the foundation for complex human-computer interaction system,and has attracted great attention in the field of human motion detection and soft robotics.Graphene has received an extensive attention due to its excellent electrical conductivity;however,how to use it to fabricate wearable flexible sensors with complex structures remains challenging.In this study,we studied the rheological behavior of graphene/polydimethylsiloxane ink and proposed an optimal graphene ratio,which makes the ink have an good printability and conductivity at the same time.Then,based on the theory of Peano fractal layout,we proposed a two-dimensional structure that can withstand multi-directional tension by replacing the traditional arris structure with the arc structure.After that,we manufactured circular arc fractal structure sensor by adjusting ink composition and printing structure through direct ink writing method.Finally,we evaluated the detection performance and repeatability of the sensor.This method provides a simple and effective solution for fabricating wearable flexible sensors and exhibits the potential to fabricate 3D complex flexible electronic devices.展开更多
The propulsion mechanisms of biomimetic underwater vehicles using bionic undulatory fins have been extensively studied for their potential to enhance efficiency and maneuverability in underwater environments.However,t...The propulsion mechanisms of biomimetic underwater vehicles using bionic undulatory fins have been extensively studied for their potential to enhance efficiency and maneuverability in underwater environments.However,the hydrodynamic interactions between the vehicle body,robotic manipulator,and fluctuating motion remain less explored,particularly in turbulent conditions.In this work,a Biomimetic Underwater Vehicle-Manipulator System(BUVMS)propelled using bionic undulatory fins is considered.The propulsion mechanism and hydrodynamic performance of fluctuating motion are analyzed by numerical simulation.The drag coefficients of the BUVMS at different Reynolds numbers are calculated,and the investigation of vortex generation during the motion of the BUVMS reveals that vortex binding and shedding are the key factors for propulsion generation.Various moving modes of the BUVMS are developed in conjunction with the pro-pulsion mechanism.The hydrodynamic loads during the motion of the underwater robotic arm in a turbulent environment are analyzed.A simple motion strategy is proposed to reduce the effect of water drag on the manipulation of the robotic arm and on the overall stability of the BUVMS.The results of the hydrodynamic analysis offer systematic guidance for controlling underwater operations of the BUVMS.展开更多
In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, differen...In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, different from that in the 4G LTE system, the cyclic redundancy check(CRC) in polar decoding plays both error correction and error detection roles. Consequently, the false alarm rates(FAR) may not meet the system requirements(FAR<1.52 × 10^(−5)). In this paper, to mitigate the FAR in polar code blind detection, we attach a binary classifier after the polar decoder to further remove the false alarm results and meanwhile retain the correct DCI. This classifier works by tracking the squared Euclidean distance ratio(SEDR) between the received signal and hypothesis. We derive an analytical method to fast compute proper classification threshold that is implementation-friendly in practical use. Combining the well-designed classifier, we show that some very short CRC sequences can even be used to meet the FAR requirements. This consequently reduces the CRC overhead and contributes to the system error performance improvements.展开更多
Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative char...Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative characterization of interface debonding mechanisms and the challenge of identifying key factors have made precise control of process variables difficult,resulting in unpredictable failure risks.This paper presents an improved fuzzy failure probability evaluation method that combines fuzzy fault tree analysis with expert knowledge,transforming process data into fuzzy failure probability to accurately assess debonding probabilities.The predictive model is constructed through a general regression neural network and optimized using the particle swarm optimization algorithm.Sensitivity analysis is conducted to identify key decision variables,including normal force,grain rotation speed,and adhesive weight,which are verified experimentally.Compared with classical models,the maximum error margin of the constructed reliability prediction model is only 0.02%,and it has high stability.The experimental results indicate that the main factors affecting debonding are processing roughness and coating uniformity.Controlling the key decision variable as the median resulted in a maximum increase of 200.7%in bonding strength.The feasibility of the improved method has been verified,confirming that identifying key decision variables has the ability to improve bonding reliability.The proposed method simplifies the evaluation of propellant interface bonding reliability under complex conditions by quantifying the relationship between process parameters and failure risk,enabling targeted management of key decision variables.展开更多
Metal–organic frameworks(MOFs)hold great potential for gas separation and storage,and graph neural networks have proven to be a powerful tool for exploring material structure–property relationships and discovering n...Metal–organic frameworks(MOFs)hold great potential for gas separation and storage,and graph neural networks have proven to be a powerful tool for exploring material structure–property relationships and discovering new materials.Unlike traditional molecular graphs,crystal graphs require consideration of periodic invariance and modes.In addition,MOF structures such as covalent bonds,functional groups,and global structures impact adsorption performance in different ways.However,redundant atomic interactions can disrupt training accuracy,potentially leading to overfitting.In this paper,we propose a multi-scale crystal graph for describing periodic crystal structures,modeling interatomic interactions at different scales while preserving periodicity invariance.We also propose a multi-head attention crystal graph network in multi-scale graphs(MHACGN-MS),which learns structural characteristics by focusing on interatomic interactions at different scales,thereby reducing interference from redundant interactions.Using MOF adsorption for gases as an example,we demonstrate that MHACGN-MS outperforms traditional graph neural networks in predicting multi-component gas adsorption.We also visualize attention scores to validate effective learning and demonstrate the model’s interpretability.展开更多
Digital light processing(DLP)is a crucial additive manufacturing(AM)technique for producing high-precision ceramic com-ponents.This study aims to optimize the formulation of Si_(3)N_(4)slurry to enhance both its perfo...Digital light processing(DLP)is a crucial additive manufacturing(AM)technique for producing high-precision ceramic com-ponents.This study aims to optimize the formulation of Si_(3)N_(4)slurry to enhance both its performance and manufacturability in the DLP process,and investigate key factors such as particle size distribution,photopolymer resin monomer ratios,and dispersant types to im-prove the slurry’s rheological properties.Through these optimizations,a photosensitive Si_(3)N_(4)slurry with 50vol%solid content was de-veloped,exhibiting excellent stability,and low viscosity(2.48 Pa·s at a shear rate of 12.8 s^(-1)).The effects of gas-pressure sintering on the material’s phase composition,microstructure,and mechanical properties were further explored,revealing that this technique significantly increases the flexural strength of the green sample from(109±10.24)to(618±42.15)MPa.The sintered ceramics exhibited high hard-ness((16.59±0.05)GPa)and improved fracture toughness((4.45±0.03)MPa·m^(1/2)).Crack trajectory analysis revealed that crack deflec-tion,crack bridging,and the pull-out of rod-likeβ-Si_(3)N_(4)grains,are the main toughening mechanisms,which could effectively mitigate crack propagation.Among these mechanisms,crack deflection and bridging were particularly influential,significantly enhancing the frac-ture toughness of the Si_(3)N_(4)matrix.Overall,this research highlights how monomer formulation and gas-pressure sintering strengthen the performance of Si_(3)N_(4)slurry in the DLP three-dimensional printing technique.This work is expected to provide new insights for fabricat-ing complex Si_(3)N_(4)ceramic components with superior mechanical properties.展开更多
The microstructure,mechanical properties,and corrosion resistance of as-cast Zr–Sn–Co ternary alloys have been investigated in this experiment.The properties of as-cast Zr–1.5Sn–xCo(x=0,2.5,5,7.5,and 10 at.%)terna...The microstructure,mechanical properties,and corrosion resistance of as-cast Zr–Sn–Co ternary alloys have been investigated in this experiment.The properties of as-cast Zr–1.5Sn–xCo(x=0,2.5,5,7.5,and 10 at.%)ternary alloys were investigated,and the alloy composition exhibiting the best comprehensive performance was identified.Subsequently,the chosen alloys were subjected to hot rolling treatment.The microstructure of the alloys in the rolled state was analyzed using the optical microscope,X-ray diffractometer,and scanning electron microscope.The mechanical properties of the alloys were analyzed using room temperature compression tests and microhardness tests,while the corrosion properties of the alloy were investigated through electrochemical testing.The results show that the strength of as-cast Zr–1.5Sn–Co ternary alloy increases significantly with the increase in Co content.The incorporation of Co element makes the corrosion resistance of as-cast Zr–1.5Sn–Co alloy increase significantly.The hot rolling treatment has minimal effect on enhancing the corrosion resistance of Zr–1.5Sn–2.5Co alloy.However,the mechanical properties of Zr–1.5Sn–2.5Co alloy after rolling treatment are significantly enhanced.The alloy exhibits the highest strength and hardness at a rolling temperature of 600℃ and exhibits the best plasticity at a rolling temperature of 800℃.展开更多
In engineering practice,there are many factors causing the vibration to which rods are usually subjected.Generally,the vibration of elastic rods motivated by determined vibration excitations can be controlled effectiv...In engineering practice,there are many factors causing the vibration to which rods are usually subjected.Generally,the vibration of elastic rods motivated by determined vibration excitations can be controlled effectively.However,the working frequency of vibration excitation may vary due to environmental changes,the working conditions of equipment,and other factors.Consequently,it remains a challenge to restrict the longitudinal vibration of elastic rods within a wide frequency band.In order to meet the relevant engineering requirements and address the existing limitations,the longitudinal vibration control of an elastic rod within a wide frequency band is explored in this study through an adjustable stiffness internal support.To achieve this purpose,the variable stiffness longitudinal vibration control theory of the elastic rod is validated.The model of an adjustable stiffness internal support is designed,constructed,and tested,demonstrating that the stiffness coefficients of the adjustable stiffness internal support can be effectively controlled.Through the adjustable stiffness internal support,the experiment on longitudinal vibration control of the elastic rod is designed and performed.It leads to the conclusion that the adjustable stiffness internal support within the adjustable working region is effective in restricting the longitudinal vibration within a wide frequency band of the elastic rod.Furthermore,the existence of the adjustable working region in the experiment demonstrates the effectiveness of the adjustable stiffness internal support intended for the variable stiffness longitudinal vibration control of an elastic rod.To sum up,this study provides insights into an adjustable stiffness mechanism for applying the theory of variable stiffness longitudinal vibration control on an elastic rod in engineering practice.展开更多
Dear Editor,Transcranial Magnetic Stimulation(TMS)has emerged as a promising therapeutic tool for various neurological and psychiatric conditions[1-3].However,despite its potential benefits,TMS is not without its disc...Dear Editor,Transcranial Magnetic Stimulation(TMS)has emerged as a promising therapeutic tool for various neurological and psychiatric conditions[1-3].However,despite its potential benefits,TMS is not without its discomfort issues[4,5],which are mainly related to target location,stimulus intensity,and treatment duration.The discomfort associated with TMS arises from several factors,including the physical sensations experienced during the procedure and potential adverse effects on the scalp and surrounding tissues.展开更多
One of the core works of analyzing Electrochemical Impedance Spectroscopy(EIS)data is to select an appropriate equivalent circuit model to quantify the parameters of the electrochemical reaction process.However,this p...One of the core works of analyzing Electrochemical Impedance Spectroscopy(EIS)data is to select an appropriate equivalent circuit model to quantify the parameters of the electrochemical reaction process.However,this process often relies on human experience and judgment,which will introduce subjectivity and error.In this paper,an intelligent approach is proposed for matching EIS data to their equivalent circuits based on the Random Forest algorithm.It can automatically select the most suitable equivalent circuit model based on the characteristics and patterns of EIS data.Addressing the typical scenario of metal corrosion,an atmospheric corrosion EIS dataset of low-carbon steel is constructed in this paper,which includes five different corrosion scenarios.This dataset was used to validate and evaluate the pro-posed method in this paper.The contributions of this paper can be summarized in three aspects:(1)This paper proposes a method for selecting equivalent circuit models for EIS data based on the Random Forest algorithm.(2)Using authentic EIS data collected from metal atmospheric corrosion,the paper es-tablishes a dataset encompassing five categories of metal corrosion scenarios.(3)The superiority of the proposed method is validated through the utilization of the established authentic EIS dataset.The ex-periment results demonstrate that,in terms of equivalent circuit matching,this method surpasses other machine learning algorithms in both precision and robustness.Furthermore,it shows strong applicability in the analysis of EIS data.展开更多
文摘Many industrial companies and researchers are looking for more efficient model driven engineering approaches (MDE) in software engineering of manufacturing automation systems (MS) especially for logic control programming, but are uncertain about the applicability and effort needed to implement those approaches in comparison to classical Programmable Logic Controller?(PLC) programming with IEC 61131-3. The paper summarizes results of usability experiments evaluating UML and SysML as software engineering notations for a MDE applied in the domain of manufacturing systems. Modeling MS needs to cover the domain specific characteristics,?i.e.?hybrid process, real time requirements and communication requirements. In addition the paper presents factors, constraint and practical experience for the development of further usability experiments. The paper gives examples of notational expressiveness and weaknesses of UML and SysML. The appendix delivers detailed master models, representing the correct best suited model, and evaluation schemes of the experiment, which is helpful if setting up own empirical experiments.
基金National Natural Science Foundation of China(52071126)Natural Science Foundation of Tianjin City,China(22JCQNJC01240)+2 种基金Central Guidance on Local Science and Technology Development Fund of Hebei Province(226Z1009G)Special Funds for Science and Technology Innovation in Hebei(2022X19)Anhui Provincial Natural Science Foundation(2308085ME135)。
文摘Co-based alloy coating was prepared on Zr alloy using laser melting and cladding technique to study the difference in the high-temperature oxidation behavior between pure metal Co coatings and Co-T800 alloy coatings,as well as the wear resistance of the coatings.Besides,the effect of changing the laser melting process on the coatings was also investigated.The oxidation mass gain at 800–1200℃and the high-temperature oxidation behavior during high-temperature treatment for 1 h of two coated Zr alloy samples were studied.Results show that the Co coating and the Co-T800 coating have better resistance against high-temperature oxidation.After oxidizing at 1000℃for 1 h,the thickness of the oxide layer of the uncoated sample was 241.0μm,whereas that of the sample with Co-based coating is only 11.8–35.5μm.The friction wear test shows that the depth of the abrasion mark of the coated sample is only 1/2 of that of the substrate,indicating that the hardness and wear resistance of the Zr substrate are greatly improved.The disadvantage of Co-based coatings is the inferior corrosion resistance in 3.5wt%NaCl solution.
基金The National Natural Science Foundation of China(62136008,62293541)The Beijing Natural Science Foundation(4232056)The Beijing Nova Program(20240484514).
文摘Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
文摘As production automation systems have been and are becoming more and more complex, the task of quality assurance is increasingly challenging. Model-based testing is a research field addressing this challenge and many approaches have been suggested for different applications. The goal of this paper is to review these approaches regarding their suitability for the domain of production automation in order to identify current trends and research gaps. The different approaches are classified and clustered according to their main focus which is either testing and test case generation from some form of model automatons, test case generation from models used within the development process of production automation systems, test case generation from fault models or test case selection and regression testing.
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 the National Key R&D Program of China(2023YFD2101001)National Natural Science Foundation of China(32202144,61807001)。
文摘To address the issues of peak overlap caused by complex matrices in agricultural product terahertz(THz)spectral signals and the dynamic,nonlinear interference induced by environmental and system noise,this study explores the feasibility of adaptive-signal-decomposition-based denoising methods to improve THz spectral quality.THz time-domain spectroscopy(THz-TDS)combined with an attenuated total reflection(ATR)accessory was used to collect THz absorbance spectra from 48 peanut samples.Taking the quantitative prediction model of peanut moisture content based on THz-ATR as an example,wavelet transform(WT),empirical mode decomposition(EMD),local mean decomposition(LMD),and its improved methods-segmented local mean decomposition(SLMD)and piecewise mirror extension local mean decomposition(PME-LMD)-were employed for spectral denoising.The applicability of different denoising methods was evaluated using a support vector regression(SVR)model.Experimental results show that the peanut moisture content prediction model constructed after PME-LMD denoising achieved the best performance,with a root mean square error(RMSE),coefficient of determination(R^(2)),and mean absolute percentage error(MAPE)of 0.010,0.912,and 0.040,respectively.Compared with traditional methods,PME-LMD significantly improved spectral quality and model prediction performance.The PME-LMD denoising strategy proposed in this study effectively suppresses non-uniform noise interference in THz spectral signals,providing an efficient and accurate preprocessing method for THz spectral analysis of agricultural products.This research provides theoretical support and technical guidance for the application of THz technology for detecting agricultural product quality.
文摘High-temperature piezoelectric sen-sors are very important in severe environments such as fire safety,aerospace and oil drills,however,most current sensors are not heat res-istant(<300℃)and are fragile,which limits their use,especially in high-temperature environ-ments.A high-temperature resistant flexible piezoelectric film based on graphene oxide(GO)/polyacrylonitrile(PAN)composites was prepared by electrospinning and thermal treat-ment.It was packed into a micro-device,which could work continuously at 500℃.The intro-duction of GO significantly increased the mechanical properties of the PAN nanofibers because the oxygen-containing func-tional groups(electronegative groups)on the surface of the GO initiated a nucleophilic attack on the PAN molecule during heat treatment,enabling the GO to initiate the cyclization of the PAN at lower heat-treatment temperatures.In addition,the abund-ant oxygen-containing functional groups on GO acted as pro-oxidants to hasten the oxidation of PAN during heat treatment.The effects of GO content and heat treatment temperature on the properties of the nanofiber films were investigated.A GO/PAN nanofiber piezoelectric sensor heat-treated at 300℃had a 9.10 V and 2.25μA peak output,which are respectively 101.3%and 78.6%higher than those of the untreated films.Cyclic testing over 5000 cycles at 350℃confirmed the stable out-put performance of the GO/PAN nanofiber piezoelectric sensor.Furthermore,a sensor heat-treated at 400℃had a sensitivity of 1.7 V/N,which is 83.5%higher than that of an untreated one.The results show that the prepared GO/PAN nanofiber piezo-electric sensor combines high temperature resistance,high flexibility,stability and high sensitivity,and may have broad applic-ations in high temperature environments such as the aerospace and petroleum industries.
基金supporting of the National Science and Technology Council NSTC(grant nos.NSTC 112-2221-E-019-023,NSTC 113-2221-E-019-039)Taiwan University of Science and Technology.
文摘In its 2023 global health statistics,the World Health Organization noted that noncommunicable diseases(NCDs)remain the leading cause of disease burden worldwide,with cardiovascular diseases(CVDs)resulting in more deaths than the three other major NCDs combined.In this study,we developed a method that can comprehensively detect which CVDs are present in a patient.Specifically,we propose a multi-label classification method that utilizes photoplethysmography(PPG)signals and physiological characteristics from public datasets to classify four types of CVDs and related conditions:hypertension,diabetes,cerebral infarction,and cerebrovascular disease.Our approach to multi-disease classification of cardiovascular diseases(CVDs)using PPG signals achieves the highest classification performance when encompassing the broadest range of disease categories,thereby offering a more comprehensive assessment of human health.We employ a multi-label classification strategy to simultaneously predict the presence or absence of multiple diseases.Specifically,we first apply the Savitzky-Golay(S-G)filter to the PPG signals to reduce noise and then transform into statistical features.We integrate processed PPG signals with individual physiological features as a multimodal input,thereby expanding the learned feature space.Notably,even with a simple machine learning method,this approach can achieve relatively high accuracy.The proposed method achieved a maximum F1-score of 0.91,minimum Hamming loss of 0.04,and an accuracy of 0.95.Thus,our method represents an effective and rapid solution for detecting multiple diseases simultaneously,which is beneficial for comprehensively managing CVDs.
基金Sponsored by Strategic Priority Research Program on Space Science,Chinese Academy of Sciences(Grant No.XDA1502030505).
文摘An innovative design method is outlined in this paper for the pointing control mechanism of large space flexible antennas.This method focuses on enhancing the accuracy and stability that are crucial for large spacecraft applications,such as space solar power stations.Utilizing potential energy function analysis,the dynamics of the antenna are modeled,treating it as an equivalent n-joint robotic arm.This approach simulates the rigid-flexible coupling effect through joint angle manipulations.The proposed HJI(Hamilton-Jacobi-Inequality)sliding mode robust control integrates HJI principle,dissipative system theory,and sliding mode control,offering improved pointing accuracy and robustness.Simulation results underscore the superiority of HJI sliding mode robust control over traditional PD(proportional-derivative)control in initial response,precision,and control smoothness,albeit at the cost of higher control torque requirements.This research underscores the potential of HJI sliding mode robust control in facilitating precise pointing control for future large space structures,enabling efficient space missions and reliable energy transmission.
基金the National Key Research and Development Program of China(No.2020YFB1313100)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA16020803)+2 种基金the National Natural Science Foundation of China(Nos.51875557 and 52205319)the Research Equipment Development Program of the Chinese Academy of Sciences(No.YJKYYQ20190045)the Foundation of State Key Laboratory of Robotics(Nos.2021-Z01,2022-Z04 and 2023-Z01)。
文摘Flexible electronic technology has laid the foundation for complex human-computer interaction system,and has attracted great attention in the field of human motion detection and soft robotics.Graphene has received an extensive attention due to its excellent electrical conductivity;however,how to use it to fabricate wearable flexible sensors with complex structures remains challenging.In this study,we studied the rheological behavior of graphene/polydimethylsiloxane ink and proposed an optimal graphene ratio,which makes the ink have an good printability and conductivity at the same time.Then,based on the theory of Peano fractal layout,we proposed a two-dimensional structure that can withstand multi-directional tension by replacing the traditional arris structure with the arc structure.After that,we manufactured circular arc fractal structure sensor by adjusting ink composition and printing structure through direct ink writing method.Finally,we evaluated the detection performance and repeatability of the sensor.This method provides a simple and effective solution for fabricating wearable flexible sensors and exhibits the potential to fabricate 3D complex flexible electronic devices.
基金supported in part by the National Key Research and Development Program of China under Grant 2023YFB4707000,in part by the National Natural Science Foundation of China under Grant U24A20282,Grant U24A20281,Grant U23A20343,Grant U23B2038in part by the Youth Innovation Promotion Association CAS under Grant Y2022053in part by Beijing Natural Science Foundation under Grant 4222055。
文摘The propulsion mechanisms of biomimetic underwater vehicles using bionic undulatory fins have been extensively studied for their potential to enhance efficiency and maneuverability in underwater environments.However,the hydrodynamic interactions between the vehicle body,robotic manipulator,and fluctuating motion remain less explored,particularly in turbulent conditions.In this work,a Biomimetic Underwater Vehicle-Manipulator System(BUVMS)propelled using bionic undulatory fins is considered.The propulsion mechanism and hydrodynamic performance of fluctuating motion are analyzed by numerical simulation.The drag coefficients of the BUVMS at different Reynolds numbers are calculated,and the investigation of vortex generation during the motion of the BUVMS reveals that vortex binding and shedding are the key factors for propulsion generation.Various moving modes of the BUVMS are developed in conjunction with the pro-pulsion mechanism.The hydrodynamic loads during the motion of the underwater robotic arm in a turbulent environment are analyzed.A simple motion strategy is proposed to reduce the effect of water drag on the manipulation of the robotic arm and on the overall stability of the BUVMS.The results of the hydrodynamic analysis offer systematic guidance for controlling underwater operations of the BUVMS.
基金supported in part by National Natural Science Foundation of China(No.62471054)in part by National Natural Science Foundation of China(No.92467301)+3 种基金in part by the National Natural Science Foundation of China(No.62201562)in part by the National Natural Science Foundation of China(No.62371063)in part by the National Natural Science Foundation of China(No.62321001)in part by Liaoning Provincial Natural Science Foundation of China(No.2024–BSBA–51).
文摘In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, different from that in the 4G LTE system, the cyclic redundancy check(CRC) in polar decoding plays both error correction and error detection roles. Consequently, the false alarm rates(FAR) may not meet the system requirements(FAR<1.52 × 10^(−5)). In this paper, to mitigate the FAR in polar code blind detection, we attach a binary classifier after the polar decoder to further remove the false alarm results and meanwhile retain the correct DCI. This classifier works by tracking the squared Euclidean distance ratio(SEDR) between the received signal and hypothesis. We derive an analytical method to fast compute proper classification threshold that is implementation-friendly in practical use. Combining the well-designed classifier, we show that some very short CRC sequences can even be used to meet the FAR requirements. This consequently reduces the CRC overhead and contributes to the system error performance improvements.
基金supported in part by the Equipment Development Pre-research Project funded by Equipment Development Department,PRC under Grant No.50923010501Fundamental Research Program of Shenyang Institute of Automation(SIA),Chinese Academy of Sciencess under Grant No.355060201。
文摘Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative characterization of interface debonding mechanisms and the challenge of identifying key factors have made precise control of process variables difficult,resulting in unpredictable failure risks.This paper presents an improved fuzzy failure probability evaluation method that combines fuzzy fault tree analysis with expert knowledge,transforming process data into fuzzy failure probability to accurately assess debonding probabilities.The predictive model is constructed through a general regression neural network and optimized using the particle swarm optimization algorithm.Sensitivity analysis is conducted to identify key decision variables,including normal force,grain rotation speed,and adhesive weight,which are verified experimentally.Compared with classical models,the maximum error margin of the constructed reliability prediction model is only 0.02%,and it has high stability.The experimental results indicate that the main factors affecting debonding are processing roughness and coating uniformity.Controlling the key decision variable as the median resulted in a maximum increase of 200.7%in bonding strength.The feasibility of the improved method has been verified,confirming that identifying key decision variables has the ability to improve bonding reliability.The proposed method simplifies the evaluation of propellant interface bonding reliability under complex conditions by quantifying the relationship between process parameters and failure risk,enabling targeted management of key decision variables.
基金supported by the National Natural Science Foundation of China(NSFC)(61821005).
文摘Metal–organic frameworks(MOFs)hold great potential for gas separation and storage,and graph neural networks have proven to be a powerful tool for exploring material structure–property relationships and discovering new materials.Unlike traditional molecular graphs,crystal graphs require consideration of periodic invariance and modes.In addition,MOF structures such as covalent bonds,functional groups,and global structures impact adsorption performance in different ways.However,redundant atomic interactions can disrupt training accuracy,potentially leading to overfitting.In this paper,we propose a multi-scale crystal graph for describing periodic crystal structures,modeling interatomic interactions at different scales while preserving periodicity invariance.We also propose a multi-head attention crystal graph network in multi-scale graphs(MHACGN-MS),which learns structural characteristics by focusing on interatomic interactions at different scales,thereby reducing interference from redundant interactions.Using MOF adsorption for gases as an example,we demonstrate that MHACGN-MS outperforms traditional graph neural networks in predicting multi-component gas adsorption.We also visualize attention scores to validate effective learning and demonstrate the model’s interpretability.
基金supported in part by the National Natural Science Foundation of China.(Nos.62461160259,92360307 and 92267103).
文摘Digital light processing(DLP)is a crucial additive manufacturing(AM)technique for producing high-precision ceramic com-ponents.This study aims to optimize the formulation of Si_(3)N_(4)slurry to enhance both its performance and manufacturability in the DLP process,and investigate key factors such as particle size distribution,photopolymer resin monomer ratios,and dispersant types to im-prove the slurry’s rheological properties.Through these optimizations,a photosensitive Si_(3)N_(4)slurry with 50vol%solid content was de-veloped,exhibiting excellent stability,and low viscosity(2.48 Pa·s at a shear rate of 12.8 s^(-1)).The effects of gas-pressure sintering on the material’s phase composition,microstructure,and mechanical properties were further explored,revealing that this technique significantly increases the flexural strength of the green sample from(109±10.24)to(618±42.15)MPa.The sintered ceramics exhibited high hard-ness((16.59±0.05)GPa)and improved fracture toughness((4.45±0.03)MPa·m^(1/2)).Crack trajectory analysis revealed that crack deflec-tion,crack bridging,and the pull-out of rod-likeβ-Si_(3)N_(4)grains,are the main toughening mechanisms,which could effectively mitigate crack propagation.Among these mechanisms,crack deflection and bridging were particularly influential,significantly enhancing the frac-ture toughness of the Si_(3)N_(4)matrix.Overall,this research highlights how monomer formulation and gas-pressure sintering strengthen the performance of Si_(3)N_(4)slurry in the DLP three-dimensional printing technique.This work is expected to provide new insights for fabricat-ing complex Si_(3)N_(4)ceramic components with superior mechanical properties.
基金supported by the National Natural Science Foundation of China(Grant No.52071126)the Natural Science Foundation of Tianjin City China(Grant No.22JCQNJC01240)+1 种基金the Central Guidance on Local Science and Technology Development Fund of Hebei Province(226Z1009G)the special funds for science and technology innovation in Hebei(2022X19).
文摘The microstructure,mechanical properties,and corrosion resistance of as-cast Zr–Sn–Co ternary alloys have been investigated in this experiment.The properties of as-cast Zr–1.5Sn–xCo(x=0,2.5,5,7.5,and 10 at.%)ternary alloys were investigated,and the alloy composition exhibiting the best comprehensive performance was identified.Subsequently,the chosen alloys were subjected to hot rolling treatment.The microstructure of the alloys in the rolled state was analyzed using the optical microscope,X-ray diffractometer,and scanning electron microscope.The mechanical properties of the alloys were analyzed using room temperature compression tests and microhardness tests,while the corrosion properties of the alloy were investigated through electrochemical testing.The results show that the strength of as-cast Zr–1.5Sn–Co ternary alloy increases significantly with the increase in Co content.The incorporation of Co element makes the corrosion resistance of as-cast Zr–1.5Sn–Co alloy increase significantly.The hot rolling treatment has minimal effect on enhancing the corrosion resistance of Zr–1.5Sn–2.5Co alloy.However,the mechanical properties of Zr–1.5Sn–2.5Co alloy after rolling treatment are significantly enhanced.The alloy exhibits the highest strength and hardness at a rolling temperature of 600℃ and exhibits the best plasticity at a rolling temperature of 800℃.
基金Supported by the Fundamental Research Project of SIA(Grant No.2022JC1G04)National Natural Science Foundation of China(Grant Nos.52401364 and 52205091)。
文摘In engineering practice,there are many factors causing the vibration to which rods are usually subjected.Generally,the vibration of elastic rods motivated by determined vibration excitations can be controlled effectively.However,the working frequency of vibration excitation may vary due to environmental changes,the working conditions of equipment,and other factors.Consequently,it remains a challenge to restrict the longitudinal vibration of elastic rods within a wide frequency band.In order to meet the relevant engineering requirements and address the existing limitations,the longitudinal vibration control of an elastic rod within a wide frequency band is explored in this study through an adjustable stiffness internal support.To achieve this purpose,the variable stiffness longitudinal vibration control theory of the elastic rod is validated.The model of an adjustable stiffness internal support is designed,constructed,and tested,demonstrating that the stiffness coefficients of the adjustable stiffness internal support can be effectively controlled.Through the adjustable stiffness internal support,the experiment on longitudinal vibration control of the elastic rod is designed and performed.It leads to the conclusion that the adjustable stiffness internal support within the adjustable working region is effective in restricting the longitudinal vibration within a wide frequency band of the elastic rod.Furthermore,the existence of the adjustable working region in the experiment demonstrates the effectiveness of the adjustable stiffness internal support intended for the variable stiffness longitudinal vibration control of an elastic rod.To sum up,this study provides insights into an adjustable stiffness mechanism for applying the theory of variable stiffness longitudinal vibration control on an elastic rod in engineering practice.
基金supported by STI2030-Major Projects(2021ZD0200200)the Key Collaborative Research Program of the Alliance of International Science Organizations(ANSO-CR-KP-2022-10)+1 种基金the Natural Science Foundation of China(82151307,82202253,and 31620103905)the Science Frontier Program of the Chinese Academy of Sciences(QYZDJ-SSW-SMC019).
文摘Dear Editor,Transcranial Magnetic Stimulation(TMS)has emerged as a promising therapeutic tool for various neurological and psychiatric conditions[1-3].However,despite its potential benefits,TMS is not without its discomfort issues[4,5],which are mainly related to target location,stimulus intensity,and treatment duration.The discomfort associated with TMS arises from several factors,including the physical sensations experienced during the procedure and potential adverse effects on the scalp and surrounding tissues.
基金support of the project from the National Key R&D Program of China,Research and Application of Sensing System for Cross-regional Complex Oil&Gas Pipeline Network Safe and Efficiency Operational Status Monitoring(Grant No.2022YFB3207603).
文摘One of the core works of analyzing Electrochemical Impedance Spectroscopy(EIS)data is to select an appropriate equivalent circuit model to quantify the parameters of the electrochemical reaction process.However,this process often relies on human experience and judgment,which will introduce subjectivity and error.In this paper,an intelligent approach is proposed for matching EIS data to their equivalent circuits based on the Random Forest algorithm.It can automatically select the most suitable equivalent circuit model based on the characteristics and patterns of EIS data.Addressing the typical scenario of metal corrosion,an atmospheric corrosion EIS dataset of low-carbon steel is constructed in this paper,which includes five different corrosion scenarios.This dataset was used to validate and evaluate the pro-posed method in this paper.The contributions of this paper can be summarized in three aspects:(1)This paper proposes a method for selecting equivalent circuit models for EIS data based on the Random Forest algorithm.(2)Using authentic EIS data collected from metal atmospheric corrosion,the paper es-tablishes a dataset encompassing five categories of metal corrosion scenarios.(3)The superiority of the proposed method is validated through the utilization of the established authentic EIS dataset.The ex-periment results demonstrate that,in terms of equivalent circuit matching,this method surpasses other machine learning algorithms in both precision and robustness.Furthermore,it shows strong applicability in the analysis of EIS data.
