This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramia...This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.展开更多
《智能系统学报》(CAAI Transactions on Intelligent Systems)2006年创刊,双月刊,为中国人工智能学会会刊,由哈尔滨工程大学和中国人工智能学会联合主办,由中国人工智能学会名誉理事长李德毅院士担任名誉主编,中国人工智能学会理事长...《智能系统学报》(CAAI Transactions on Intelligent Systems)2006年创刊,双月刊,为中国人工智能学会会刊,由哈尔滨工程大学和中国人工智能学会联合主办,由中国人工智能学会名誉理事长李德毅院士担任名誉主编,中国人工智能学会理事长戴琼海院士担任主编。展开更多
《系统工程与电子技术(英文)》(《Journal of Systems Engineering and Electronics》)是由中国航天科工防御技术研究院、中国宇航学会、中国系统工程学会和北京航天情报与信息研究所联合主办的学术期刊,创刊于1990年,现为双月刊。本刊...《系统工程与电子技术(英文)》(《Journal of Systems Engineering and Electronics》)是由中国航天科工防御技术研究院、中国宇航学会、中国系统工程学会和北京航天情报与信息研究所联合主办的学术期刊,创刊于1990年,现为双月刊。本刊栏目主要包括:电子技术,防御电子技术,系统工程,控制理论与实践等。投稿要求如下:1.投稿时请作者提供本单位保密部门出具的保密审查证明,证明不涉及国家秘密和内部敏感信息。展开更多
《系统工程与电子技术(英文)》(《Journal of Systems Engineering and Electronics》)是由中国航天科工防御技术研究院、中国宇航学会、中国系统工程学会和北京航天情报与信息研究所联合主办的学术期刊,创刊于1990年,现为双月刊。本刊...《系统工程与电子技术(英文)》(《Journal of Systems Engineering and Electronics》)是由中国航天科工防御技术研究院、中国宇航学会、中国系统工程学会和北京航天情报与信息研究所联合主办的学术期刊,创刊于1990年,现为双月刊。本刊栏目主要包括:电子技术,防御电子技术,系统工程,控制理论与实践等。投稿要求如下:1.投稿时请作者提供本单位保密部门出具的保密审查证明,证明不涉及国家秘密和内部敏感信息。切勿投寄涉密稿件,否则后果自负。展开更多
Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest developments and achievements in both theoretical and pra...Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest developments and achievements in both theoretical and practical aspects of systems engineering,electronics and related research areas.The journal welcomes high quality original papers from a wide range of countries.The scope of the journal includes systems engineering,military systems,electronic technology,defense electronic technology,control theory and practice,software algorithm and simulation,reliability,computer development and application,and other topics in all related fields.展开更多
Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third ...Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third most common cancer worldwide and ranks second in mortality among all malignancies.Currently,it has become one of the most severe challenges faced by healthcare systems in many countries[2].A previous study has found that patients with psoriasis have a significantly increased risk of developing CRC[3].展开更多
Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the ...Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the emerging artificial intelligence and machine learning,traditional modeling techniques in these energy systems have met challenges in still leveraging physics model and first principle-based approaches.Moreover,with the rapid development of hardware and computing techniques,new modeling approaches for energy systems have become more and more important for system design,integration,analysis,control,and management.展开更多
This paper develops an advanced framework for the operational optimization of integrated multi-energy systems that encompass electricity,gas,and heating networks.Introducing a cutting-edge stochastic gradient-enhanced...This paper develops an advanced framework for the operational optimization of integrated multi-energy systems that encompass electricity,gas,and heating networks.Introducing a cutting-edge stochastic gradient-enhanced distributionally robust optimization approach,this study integrates deep learning models,especially generative adversarial networks,to adeptly handle the inherent variability and uncertainties of renewable energy and fluctuating consumer demands.The effectiveness of this framework is rigorously tested through detailed simulations mirroring real-world urban energy consumption,renewable energy production,and market price fluctuations over an annual period.The results reveal substantial improvements in the resilience and efficiency of the grid,achieving a reduction in power distribution losses by 15%and enhancing voltage stability by 20%,markedly outperforming conventional systems.Additionally,the framework facilitates up to 25%in cost reductions during peak demand periods,significantly lowering operational costs.The adoption of stochastic gradients further refines the framework’s ability to continually adjust to real-time changes in environmental and market conditions,ensuring stable grid operations and fostering active consumer engagement in demand-side management.This strategy not only aligns with contem-porary sustainable energy practices but also provides scalable and robust solutions to pressing challenges in modern power network management.展开更多
This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on th...This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.展开更多
This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to es...This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to estimate higher-order synchronization errors,enabling the controller to rely solely on relative output measurements.This approach significantly reduces the dependence on full-state information,which is often infeasible or costly in practical engineering applications.An output feedback control strategy is developed to overcome these limitations while ensuring robust and effective synchronization.Simulation results are provided to demonstrate the effectiveness of the proposed approach and validate the theoretical findings.展开更多
Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contempo...Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contemporary enterprises typically operate 200+interconnected systems,with research indicating that 52% of organizations manage three or more enterprise content management systems,creating information silos that reduce operational efficiency by up to 35%.While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision,their systematic application to business information systems remains largely unexplored.This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System(HABIS)framework that applies multi-level attention mechanisms to enterprise environments.We provide a comprehensive mathematical formulation of the framework,analyze its computational complexity,and present a proof-of-concept implementation with simulation-based validation that demonstrates a 42% reduction in crosssystem query latency compared to legacy ERP modules and 70% improvement in prediction accuracy over baseline methods.The theoretical framework introduces four hierarchical attention levels:system-level attention for dynamic weighting of business systems,process-level attention for business process prioritization,data-level attention for critical information selection,and temporal attention for time-sensitive pattern recognition.Our complexity analysis demonstrates that the framework achieves O(n log n)computational complexity for attention computation,making it scalable to large enterprise environments including retail supply chains with 200+system-scale deployments.The proof-of-concept implementation validates the theoretical framework’s feasibility withMSE loss of 0.439 and response times of 0.000120 s per query,demonstrating its potential for addressing key challenges in business information systems.This work establishes a foundation for future empirical research and practical implementation of attention-driven enterprise systems.展开更多
As an Indian journalist who has lived and worked in China for more than a decade,I have witnessed firsthand the astounding pace of China’s urban transformation-high-speed rail networks linking megacities,digital paym...As an Indian journalist who has lived and worked in China for more than a decade,I have witnessed firsthand the astounding pace of China’s urban transformation-high-speed rail networks linking megacities,digital payment systems reshaping daily life,smart manufacturing emerging across industrial zones,and modern infrastructure spreading nationwide.Yet,my recent eight-day media tour to Zhejiang Province o!ered a new and deeply thought-provoking perspective.展开更多
AIM:To evaluate the predictive value of pan-immuneinflammation value(PIV)in the diagnosis of proliferative diabetic retinopathy(PDR)and its association with the stage of PDR.METHODS:This observational case-control stu...AIM:To evaluate the predictive value of pan-immuneinflammation value(PIV)in the diagnosis of proliferative diabetic retinopathy(PDR)and its association with the stage of PDR.METHODS:This observational case-control study included participants who underwent routine complete blood count testing.Inflammation-related indices,including neutrophil-to-lymphocyte ratio,systemic immune-inflammation index(SII),and PIV,were derived and analyzed.Receiver operating characteristic curve(ROC)analysis was applied to assess the diagnostic performance of these indices in distinguishing patients with PDR,with sensitivity,specificity,area under ROC,and optimal threshold values calculated.In addition,binary logistic regression analysis was performed to evaluate the association between inflammatory indices and PDR stage.RESULTS:This study included 205 patients:60 with diabetes without retinopathy(mean age:61.81±10.76y),80 with PDR(mean age:61.63±10.03y)and 65 healthy controls(mean age:59.52±5.88y).The PDR group had significantly higher white blood cell(WBC,P<0.001),monocyte(MONO,P=0.009)and neutrophil(NEU)counts(P<0.001).SII and PIV had the highest sensitivity and area under ROC for predicting patients with PDR(0.822,0.846,respectively).The optimal cut-off values for discriminating patients with PDR were determined to be>527.12 and>299.08 for SII and PIV,respectively.The logistic regression analysis demonstrated that a decrease in lymphocyte(LYM)count and an increase in platelet count(PLT),glycated haemoglobin(HbA1c),SII,and PIV were all significantly associated with the development of high-risk PDR(all P<0.05).PIV was more stable than independent MONO,LYM,PLT and NEU levels in predicting both the diagnosis and stage of PDR.The optimal cut-off value for PIV to discriminate patients with high-risk PDR was found to be>345.87 area under ROC=0.871,with sensitivity of 0.827 and specificity of 0.812.CONCLUSION:PIV is a reliable,valuable,and inexpensive blood index that can be used for early detection and staging of PDR.PIV may therefore be essential to be used for the follow-up of diabetic patients.展开更多
This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing th...This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.展开更多
Networked predictive control(NPC) has gained significant attention in recent years for its ability to effectively and actively address communication constraints in networked control systems(NCSs),such as network-induc...Networked predictive control(NPC) has gained significant attention in recent years for its ability to effectively and actively address communication constraints in networked control systems(NCSs),such as network-induced delays,packet dropouts,and packet disorders.Despite significant advancements,the increasing complexity and dynamism of network environments,along with the growing complexity of systems,pose new challenges for NPC.These challenges include difficulties in system modeling,cyber attacks,component faults,limited network bandwidth,and the necessity for distributed collaboration.This survey aims to provide a comprehensive review of NPC strategies.It begins with a summary of the primary challenges faced by NCSs,followed by an introduction to the control structure and core concepts of NPC.The survey then discusses several typical NPC schemes and examines their extensions in the areas of secure control,fault-tolerant control,distributed coordinated control,and event-triggered control.Moreover,it reviews notable works that have implemented these schemes.Finally,the survey concludes by exploring typical applications of NPC schemes and highlighting several challenging issues that could guide future research efforts.展开更多
April 14-16,Manchester,United KingdomThe Global Age Assurance Standards Summit2026 brings together the international age assurance community for three days of practical insight,shared learning and real-world experienc...April 14-16,Manchester,United KingdomThe Global Age Assurance Standards Summit2026 brings together the international age assurance community for three days of practical insight,shared learning and real-world experience focused on implementing age assurance systems in live environments.展开更多
The poultry gut microbiome plays a key role in nutrient digestion,immune function,and overall health.Differences among various farming systems,including conventional,antibiotic-free,free-range,and organic systems,infl...The poultry gut microbiome plays a key role in nutrient digestion,immune function,and overall health.Differences among various farming systems,including conventional,antibiotic-free,free-range,and organic systems,influence microbial composition and function through variations in diet,genetic selection,environmental exposure,and antibiotic use.Conventional systems typically rely on formulated diets and controlled housing conditions,often with routine antimicrobial use.In contrast,organic systems emphasize natural feed ingredients,including roughage,outdoor access,and strict limitations on the use of antibiotics.These divergent practices shape the gut microbiota differently,with organic systems generally associated with greater exposure to environmental microbes and,consequently,greater microbial diversity.However,the implications of this increased diversity for poultry health and performance are complex,as organic systems may also carry a higher risk of pathogen exposure.This review summarizes current findings on the chicken gut microbiome across conventional and alternative production systems(antibiotic-free,freerange,and organic),focusing on microbial diversity,functional potential,and disease resilience.The need for standardized methodologies and consistent nomenclature in microbiome research is also discussed to improve comparability across studies.Understanding how production systems influence the gut microbiota is essential for improving poultry health and productivity while addressing challenges related to antimicrobial resistance and sustainable farming practices.展开更多
The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review exa...The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector,highlighting their transformative impact on Intelligent Transportation Systems(ITS)operations.It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation,highlighting their roles in enhancing efficiency,safety,and sustainability.A systematic framework is proposed for developing,implementing,and managing these technologies in the transportation industry.Moreover,the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration.Lastly,it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.展开更多
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
文摘This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
文摘This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.
文摘《系统工程与电子技术(英文)》(《Journal of Systems Engineering and Electronics》)是由中国航天科工防御技术研究院、中国宇航学会、中国系统工程学会和北京航天情报与信息研究所联合主办的学术期刊,创刊于1990年,现为双月刊。本刊栏目主要包括:电子技术,防御电子技术,系统工程,控制理论与实践等。投稿要求如下:1.投稿时请作者提供本单位保密部门出具的保密审查证明,证明不涉及国家秘密和内部敏感信息。
文摘《系统工程与电子技术(英文)》(《Journal of Systems Engineering and Electronics》)是由中国航天科工防御技术研究院、中国宇航学会、中国系统工程学会和北京航天情报与信息研究所联合主办的学术期刊,创刊于1990年,现为双月刊。本刊栏目主要包括:电子技术,防御电子技术,系统工程,控制理论与实践等。投稿要求如下:1.投稿时请作者提供本单位保密部门出具的保密审查证明,证明不涉及国家秘密和内部敏感信息。切勿投寄涉密稿件,否则后果自负。
文摘Aims and scope Journal of Systems Engineering and Electronics,keeping abreast with the development trend of science and technology worldwide,reports the latest developments and achievements in both theoretical and practical aspects of systems engineering,electronics and related research areas.The journal welcomes high quality original papers from a wide range of countries.The scope of the journal includes systems engineering,military systems,electronic technology,defense electronic technology,control theory and practice,software algorithm and simulation,reliability,computer development and application,and other topics in all related fields.
基金supported by the National Natural Science Foundation of China(Grant No.82373475).
文摘Dear Editor,Psoriasis is increasingly recognized as a systemic inflammatory disease associated with several comorbidities,including metabolic syndrome,depression,and malignancies[1].Colorectal cancer(CRC)is the third most common cancer worldwide and ranks second in mortality among all malignancies.Currently,it has become one of the most severe challenges faced by healthcare systems in many countries[2].A previous study has found that patients with psoriasis have a significantly increased risk of developing CRC[3].
基金supported by the Ministry of Industry and Information Technology,China,the Science Foundation of the Ministry of Education of China(No.21YJC630072)the Key Talent Project of the Yan Zhao Golden Platform for Talent Attraction in Hebei Province,China(No.HJYB202528).
文摘Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the emerging artificial intelligence and machine learning,traditional modeling techniques in these energy systems have met challenges in still leveraging physics model and first principle-based approaches.Moreover,with the rapid development of hardware and computing techniques,new modeling approaches for energy systems have become more and more important for system design,integration,analysis,control,and management.
基金supported by the National Key R&D Program of China(No.2021ZD0112700).
文摘This paper develops an advanced framework for the operational optimization of integrated multi-energy systems that encompass electricity,gas,and heating networks.Introducing a cutting-edge stochastic gradient-enhanced distributionally robust optimization approach,this study integrates deep learning models,especially generative adversarial networks,to adeptly handle the inherent variability and uncertainties of renewable energy and fluctuating consumer demands.The effectiveness of this framework is rigorously tested through detailed simulations mirroring real-world urban energy consumption,renewable energy production,and market price fluctuations over an annual period.The results reveal substantial improvements in the resilience and efficiency of the grid,achieving a reduction in power distribution losses by 15%and enhancing voltage stability by 20%,markedly outperforming conventional systems.Additionally,the framework facilitates up to 25%in cost reductions during peak demand periods,significantly lowering operational costs.The adoption of stochastic gradients further refines the framework’s ability to continually adjust to real-time changes in environmental and market conditions,ensuring stable grid operations and fostering active consumer engagement in demand-side management.This strategy not only aligns with contem-porary sustainable energy practices but also provides scalable and robust solutions to pressing challenges in modern power network management.
文摘This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.
文摘This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to estimate higher-order synchronization errors,enabling the controller to rely solely on relative output measurements.This approach significantly reduces the dependence on full-state information,which is often infeasible or costly in practical engineering applications.An output feedback control strategy is developed to overcome these limitations while ensuring robust and effective synchronization.Simulation results are provided to demonstrate the effectiveness of the proposed approach and validate the theoretical findings.
文摘Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contemporary enterprises typically operate 200+interconnected systems,with research indicating that 52% of organizations manage three or more enterprise content management systems,creating information silos that reduce operational efficiency by up to 35%.While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision,their systematic application to business information systems remains largely unexplored.This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System(HABIS)framework that applies multi-level attention mechanisms to enterprise environments.We provide a comprehensive mathematical formulation of the framework,analyze its computational complexity,and present a proof-of-concept implementation with simulation-based validation that demonstrates a 42% reduction in crosssystem query latency compared to legacy ERP modules and 70% improvement in prediction accuracy over baseline methods.The theoretical framework introduces four hierarchical attention levels:system-level attention for dynamic weighting of business systems,process-level attention for business process prioritization,data-level attention for critical information selection,and temporal attention for time-sensitive pattern recognition.Our complexity analysis demonstrates that the framework achieves O(n log n)computational complexity for attention computation,making it scalable to large enterprise environments including retail supply chains with 200+system-scale deployments.The proof-of-concept implementation validates the theoretical framework’s feasibility withMSE loss of 0.439 and response times of 0.000120 s per query,demonstrating its potential for addressing key challenges in business information systems.This work establishes a foundation for future empirical research and practical implementation of attention-driven enterprise systems.
文摘As an Indian journalist who has lived and worked in China for more than a decade,I have witnessed firsthand the astounding pace of China’s urban transformation-high-speed rail networks linking megacities,digital payment systems reshaping daily life,smart manufacturing emerging across industrial zones,and modern infrastructure spreading nationwide.Yet,my recent eight-day media tour to Zhejiang Province o!ered a new and deeply thought-provoking perspective.
文摘AIM:To evaluate the predictive value of pan-immuneinflammation value(PIV)in the diagnosis of proliferative diabetic retinopathy(PDR)and its association with the stage of PDR.METHODS:This observational case-control study included participants who underwent routine complete blood count testing.Inflammation-related indices,including neutrophil-to-lymphocyte ratio,systemic immune-inflammation index(SII),and PIV,were derived and analyzed.Receiver operating characteristic curve(ROC)analysis was applied to assess the diagnostic performance of these indices in distinguishing patients with PDR,with sensitivity,specificity,area under ROC,and optimal threshold values calculated.In addition,binary logistic regression analysis was performed to evaluate the association between inflammatory indices and PDR stage.RESULTS:This study included 205 patients:60 with diabetes without retinopathy(mean age:61.81±10.76y),80 with PDR(mean age:61.63±10.03y)and 65 healthy controls(mean age:59.52±5.88y).The PDR group had significantly higher white blood cell(WBC,P<0.001),monocyte(MONO,P=0.009)and neutrophil(NEU)counts(P<0.001).SII and PIV had the highest sensitivity and area under ROC for predicting patients with PDR(0.822,0.846,respectively).The optimal cut-off values for discriminating patients with PDR were determined to be>527.12 and>299.08 for SII and PIV,respectively.The logistic regression analysis demonstrated that a decrease in lymphocyte(LYM)count and an increase in platelet count(PLT),glycated haemoglobin(HbA1c),SII,and PIV were all significantly associated with the development of high-risk PDR(all P<0.05).PIV was more stable than independent MONO,LYM,PLT and NEU levels in predicting both the diagnosis and stage of PDR.The optimal cut-off value for PIV to discriminate patients with high-risk PDR was found to be>345.87 area under ROC=0.871,with sensitivity of 0.827 and specificity of 0.812.CONCLUSION:PIV is a reliable,valuable,and inexpensive blood index that can be used for early detection and staging of PDR.PIV may therefore be essential to be used for the follow-up of diabetic patients.
基金supported in part by the National Natural Science Foundation of China under Grants 62073124 and U1804150.
文摘This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.
基金supported by the National Natural Science Foundation of China(62173002,62403235,62403010,52301408,62173255)the Beijing Natural Science Foundation(L241015,4222045)+2 种基金the Yuxiu Innovation Project of NCUT(2024NCUTYXCX111)the China Postdoctoral Science Foundation(2025T180466)the Beijing Postdoctoral Research Foundation(2025-ZZ-70)。
文摘Networked predictive control(NPC) has gained significant attention in recent years for its ability to effectively and actively address communication constraints in networked control systems(NCSs),such as network-induced delays,packet dropouts,and packet disorders.Despite significant advancements,the increasing complexity and dynamism of network environments,along with the growing complexity of systems,pose new challenges for NPC.These challenges include difficulties in system modeling,cyber attacks,component faults,limited network bandwidth,and the necessity for distributed collaboration.This survey aims to provide a comprehensive review of NPC strategies.It begins with a summary of the primary challenges faced by NCSs,followed by an introduction to the control structure and core concepts of NPC.The survey then discusses several typical NPC schemes and examines their extensions in the areas of secure control,fault-tolerant control,distributed coordinated control,and event-triggered control.Moreover,it reviews notable works that have implemented these schemes.Finally,the survey concludes by exploring typical applications of NPC schemes and highlighting several challenging issues that could guide future research efforts.
文摘April 14-16,Manchester,United KingdomThe Global Age Assurance Standards Summit2026 brings together the international age assurance community for three days of practical insight,shared learning and real-world experience focused on implementing age assurance systems in live environments.
基金supported by funds of the Federal Ministry of Agriculture,Food and Regional Identity(BMLEH)based on a decision of the parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food(BLE)under the Federal Programme for Ecological Farming and Other Forms of Sustainable Agriculture(FKZ 2821OE034)。
文摘The poultry gut microbiome plays a key role in nutrient digestion,immune function,and overall health.Differences among various farming systems,including conventional,antibiotic-free,free-range,and organic systems,influence microbial composition and function through variations in diet,genetic selection,environmental exposure,and antibiotic use.Conventional systems typically rely on formulated diets and controlled housing conditions,often with routine antimicrobial use.In contrast,organic systems emphasize natural feed ingredients,including roughage,outdoor access,and strict limitations on the use of antibiotics.These divergent practices shape the gut microbiota differently,with organic systems generally associated with greater exposure to environmental microbes and,consequently,greater microbial diversity.However,the implications of this increased diversity for poultry health and performance are complex,as organic systems may also carry a higher risk of pathogen exposure.This review summarizes current findings on the chicken gut microbiome across conventional and alternative production systems(antibiotic-free,freerange,and organic),focusing on microbial diversity,functional potential,and disease resilience.The need for standardized methodologies and consistent nomenclature in microbiome research is also discussed to improve comparability across studies.Understanding how production systems influence the gut microbiota is essential for improving poultry health and productivity while addressing challenges related to antimicrobial resistance and sustainable farming practices.
文摘The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector,highlighting their transformative impact on Intelligent Transportation Systems(ITS)operations.It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation,highlighting their roles in enhancing efficiency,safety,and sustainability.A systematic framework is proposed for developing,implementing,and managing these technologies in the transportation industry.Moreover,the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration.Lastly,it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.
