With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenu...With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.展开更多
Digital Twin (DT) technology is revolutionizing the railway sector by providing a virtual replica of physical systems, enabling real-time monitoring, predictive maintenance, and enhanced decision-making. This systemat...Digital Twin (DT) technology is revolutionizing the railway sector by providing a virtual replica of physical systems, enabling real-time monitoring, predictive maintenance, and enhanced decision-making. This systematic literature review examines the status, enabling technologies, case studies, and frameworks for DT applications in railway systems with 91 selected papers from Scopus, Web of Science, IEEE, and the Snowballing Technique. The review focuses on four primary subsystems: tracks, civil structures, vehicles, and overhead contact line structures. Key findings reveal that DT has successfully optimized maintenance strategies, improved operational efficiency, and enhanced system safety. Internet of Things (IoT) devices, Artificial Intelligence (AI), machine learning, and cloud computing are critical in implementing DT models. However, challenges like data integration, high implementation costs, and cybersecurity risks remain, necessitating the discussed implications. Future research should focus on improving data interoperability, reducing costs through scalable cloud-based solutions, and addressing cybersecurity vulnerabilities. DT technology has the potential to revolutionize railway infrastructure management, ensuring greater efficiency, safety, and sustainability.展开更多
Traditional Chinese medicine(TCM)auscultation has a long history,and with advancements in equipment and analytical methods,the quantitative analysis of auscultation parameters has determined.However,the complexity and...Traditional Chinese medicine(TCM)auscultation has a long history,and with advancements in equipment and analytical methods,the quantitative analysis of auscultation parameters has determined.However,the complexity and diversity of auscultation,along with variations in devices,analytical methods,and applications,bring challenges to its standardization and deeper application.This review presents the advancements in auscultation equipment and systems,auscultation characteristic parameters,and their application in the diagnosis of pulmonary diseases and syndromes over the past 10 years,while also exploring the progress and challenges of current digital research of auscultation.This review also proposes the establishment of standardized protocols for the collection and analysis of auscultation data,the incorporation of advanced artificial intelligence(AI)auscultation analysis methods,and an exploration of the diagnostic utility of auscultatory features in pulmonary diseases and syndromes,so as to provide more precise decision support for intelligent diagnosis of pulmonary diseases and syndromes.展开更多
This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as ru...This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.展开更多
In the contemporary era,characterized by the Internet and digitalization as fundamental features,the operation and application of digital currency have gradually developed into a comprehensive structural system.This s...In the contemporary era,characterized by the Internet and digitalization as fundamental features,the operation and application of digital currency have gradually developed into a comprehensive structural system.This system restores the essential characteristics of currency while providing auxiliary services related to the formation,circulation,storage,application,and promotion of digital currency.Compared to traditional currency management technologies,big data analysis technology,which is primarily embedded in digital currency systems,enables the rapid acquisition of information.This facilitates the identification of standard associations within currency data and provides technical support for the operational framework of digital currency.展开更多
To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase n...To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.展开更多
The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,...The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,General technical requirements for food digital factory,the first general technical national standard for food digital factory,was released recently.It bridges the gap in the industry,serving as the technical support and implementation framework for the intelligent and digital transformation of enterprises in the food industry.展开更多
Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,...Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.展开更多
Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate...Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.展开更多
With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies ...With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.展开更多
Despite broad consensus on the importance of enterprise digital transformation,significant discrepancies persist regarding its actual effects.This divergence stems primarily from two key measurement challenges:(1)a la...Despite broad consensus on the importance of enterprise digital transformation,significant discrepancies persist regarding its actual effects.This divergence stems primarily from two key measurement challenges:(1)a lack of clear and consistent definitions of enterprise digital transformation,and(2)a lack of rigorous and accurate measurement methodologies.These shortcomings lead to research findings that are incomparable,difficult to replicate,and often conflicting.To effectively address the aforementioned challenges,this paper employs machine learning and large language models(LLMs)to construct a novel set of indicators for enterprise digital transformation.The work begins by manually annotating sentences from annual reports of listed companies in China from 2006 to 2020.These labeled sentences are then used to train and fine-tune several machine learning models,including LLMs.The ERNIE model,demonstrating the best classification performance among the models tested,is selected as the sentence classifier to predict sentence labels across the full text of the annual reports,ultimately constructing the enterprise digital transformation metrics.Both theoretical analysis and multiple data cross-validations demonstrate that the metrics developed in this paper are more accurate than existing approaches.Based on these metrics,the paper empirically examines the impact of enterprise digital transformation on financial performance.Our findings reveal three key points:(1)enterprise digital transformation significantly enhances financial performance,with big data,AI,mobile internet,cloud computing,and the Internet of Things(IoT)all playing a significant role;however,blockchain technology does not show a significant effect;(2)the significant positive effect of digital transformation on financial performance is primarily observed in firms with weaker initial financial performance;and(3)enterprise digital transformation improves financial performance mainly through enhancing efficiency and reducing costs.This research has practical implications for promoting enterprise digital transformation and fostering high-quality economic development.展开更多
The right to digital development,rooted in the fundamental right to development,emerges in response to the transformations of our era and serves as a catalyst for Chinese modernization.Building upon the traditional ri...The right to digital development,rooted in the fundamental right to development,emerges in response to the transformations of our era and serves as a catalyst for Chinese modernization.Building upon the traditional right to development,the right to digital development aims to meet the people’s aspirations for a better life in the context of digital development.By integrating a technological perspective,this concept advances the theoretical evolution of the right to development in line with contemporary realities.In terms of generation logic,the right to digital development is grounded in policies supporting Chinese modernization,guided by the development of new quality productive forces,and oriented toward addressing the people’s aspirations for a better life and society’s sustainable digital transformation.Ultimately,this framework constructs a normative structure encompassing the right to digital development opportunity,the right to digital development condition,and the right to digital development realization as a cohesive whole.From a value-oriented perspective,the right to digital development adheres to a people-centered philosophy of development,grounded in practical considerations.It addresses the digital divide as a focal point,gradually mitigating digital exclusion and circumventing digital malpractices,thereby fostering digital sharing.Integrating the right to digital development into the conceptual framework of the right to development can complete the institutional construction of digital development through the theoretical architecture of“condition-opportunity-realization.”This integration helps to better safeguard people’s rights and interests in digital development and promotes the free and comprehensive development of individuals.展开更多
Digital transformation,as a recent trend in socioeconomic development,is considered as a critical pathway for urban carbon reduction because of its potential to increase productivity and energy efficiency.However,few ...Digital transformation,as a recent trend in socioeconomic development,is considered as a critical pathway for urban carbon reduction because of its potential to increase productivity and energy efficiency.However,few studies have explored the relationship between urban digitalization and carbon emissions(CE).Therefore,this study systematically analyzed the spatiotemporal distribution and interaction mechanism between digitalization and CE in the Yangtze River Delta(YRD)urban agglomerations of China during 2006-2020 based on a multidimensional indicator system,including digitalization industry level,digitalization application level,and urban green digitalization willingness.The findings revealed that both digitalization and CE in the YRD exhibit a significant and synchronously evolving“core-periphery”spatial pattern.Core cities generated substantial positive spillover effect on periphery cities through technology diffusion and policy demonstration,advancing both regional digitalization and the collaborative governance of CE.However,digitalization had dual impact on CE.On the one hand,it promoted the reduction of CE by enhancing energy efficiency,optimizing industrial structures,and promoting the application of green technologies.On the other hand,the expansion of digital infrastructure introduced a potential risk of increased energy consumption.Therefore,targeted policy recommendations are proposed to facilitate the coordination of environmental sustainability and digitalization in the YRD.This study provides empirical support and policy insights for advancing the coordinated development of regional digital transformation and green low-carbon initiatives.展开更多
This article is excerpted from a speech titled“Bridging Innovation:Advancing China-ASEAN Digital Technology Collaboration”delivered at the Shanghai Forum 2025 by Koh King Kee,president of the Centre for New Inclusiv...This article is excerpted from a speech titled“Bridging Innovation:Advancing China-ASEAN Digital Technology Collaboration”delivered at the Shanghai Forum 2025 by Koh King Kee,president of the Centre for New Inclusive Asia and president of the ASEAN Research Center for a Community with Shared Future,Malaysia.The text has been edited for length and clarity.展开更多
In this paper,we present a novel first-order digitalΣΔconverter tailored for digital-to-analog applications,focusing on achieving both high yield and reduced silicon estate.Our approach incorporates a substantial le...In this paper,we present a novel first-order digitalΣΔconverter tailored for digital-to-analog applications,focusing on achieving both high yield and reduced silicon estate.Our approach incorporates a substantial level of dithering noise into the input signal,strategically aimed at mitigating the spurious frequencies commonly encountered in such converters.Validation of our design is performed through simulations using a high-level simulator specialized in mixed-signal circuit analysis.The results underscore the enhanced performance of our circuit,especially in reducing spurious frequencies,highlighting its efficiency and effectiveness.The final circuit exhibits an effective number of bits of 13.展开更多
To investigate the application of virtual digital technology in landscape engineering design,the study adopted the enu-meration survey method and observation method.It conducted a comprehensive analysis of the current...To investigate the application of virtual digital technology in landscape engineering design,the study adopted the enu-meration survey method and observation method.It conducted a comprehensive analysis of the current status and existing chal-lenges of virtual digital technology in landscape engineering design.Additionally,the study provided a detailed description and explanation of the integration between virtual digital technology and landscape engineering design,while exploring its charac-teristics and application prospects.The findings revealed:(1)In the early design stage,technological integration enhanced design efficiency.The collaborative use of BIM,GIS,and parametric tools enabled a fully digital workflow from conceptual design to construction drawings,reducing design errors and shortening project timelines.(2)After implementation,interactive experiences revolutionized public engagement.AR/VR technologies introduced dynamic interactivity to landscapes,while metaverse plat-forms expanded the presentation dimensions of virtual landscapes.(3)Smart maintenance promoted sustainability.IoT sensors and AI analytics facilitated real-time plant health monitoring and precise resource management,demonstrating significant advan-tages.The study identified existing limitations and proposed future directions,aiming to provide new theoretical and practical insights for the research and application of digital technology in landscape engineering design.展开更多
The standards system for cultural heritage digitalization aims to build a clear and logically rigorous framework to guide the development and revision of relevant standards.This system enhances the scientific,systemat...The standards system for cultural heritage digitalization aims to build a clear and logically rigorous framework to guide the development and revision of relevant standards.This system enhances the scientific,systematic,and practical aspects of cultural heritage digitalization.This paper comprehensively analyzes the current status and needs of cultural heritage digitalization and standardization.It further examines the methods used to construct the standards system.Through comparative analysis,it establishes a lifecycle-based framework for cultural heritage.This framework accounts for the unique characteristics of cultural heritage and systematically integrates key processes such as collection,processing,storage,transmission,and utilization of data.The standards system is divided into six sections:general,data,information,knowledge,intelligence,and application.Based on the current digitalization efforts,this paper proposes key standardization directions for each section.This framework ensures the integrity and consistency of data throughout the digitalization process.It also supports the application of intelligent technologies in cultural heritage conservation,contributing to the sustainable preservation and utilization of cultural heritage data.展开更多
Quantum digital signature(QDS)can guarantee the information-theoretical security of a signature with the fundamental laws of quantum physics.However,most current QDS protocols do not take source security into account,...Quantum digital signature(QDS)can guarantee the information-theoretical security of a signature with the fundamental laws of quantum physics.However,most current QDS protocols do not take source security into account,leading to an overestimation of the signature rate.In this paper,we propose to utilize Hong–Ou–Mandel interference to characterize the upper bound of the source imperfections,and further to quantify information leakage from potential side-channels.Additionally,we combine decoy-state methods and finite-size analysis in analyzing the signature rate.Simulation results demonstrate the performance and feasibility of our approach.Our current work can improve the practical security of QDS systems,thereby promoting their further networked applications.展开更多
基金Supported by Beijing Municipal Natural Science Foundation of China(Grant No.24JL002)China Postdoctoral Science Foundation(Grant No.2024M754054)+2 种基金National Natural Science Foundation of China(Grant No.52120105008)Beijing Municipal Outstanding Young Scientis Program of Chinathe New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.
文摘Digital Twin (DT) technology is revolutionizing the railway sector by providing a virtual replica of physical systems, enabling real-time monitoring, predictive maintenance, and enhanced decision-making. This systematic literature review examines the status, enabling technologies, case studies, and frameworks for DT applications in railway systems with 91 selected papers from Scopus, Web of Science, IEEE, and the Snowballing Technique. The review focuses on four primary subsystems: tracks, civil structures, vehicles, and overhead contact line structures. Key findings reveal that DT has successfully optimized maintenance strategies, improved operational efficiency, and enhanced system safety. Internet of Things (IoT) devices, Artificial Intelligence (AI), machine learning, and cloud computing are critical in implementing DT models. However, challenges like data integration, high implementation costs, and cybersecurity risks remain, necessitating the discussed implications. Future research should focus on improving data interoperability, reducing costs through scalable cloud-based solutions, and addressing cybersecurity vulnerabilities. DT technology has the potential to revolutionize railway infrastructure management, ensuring greater efficiency, safety, and sustainability.
基金National Natural Science Foundation of China(82104738)National Administration of Traditional Chinese Medicine(TCM)High-level Key Discipline Construction Project:TCM Diagnostics(ZYYZDXK-2023069).
文摘Traditional Chinese medicine(TCM)auscultation has a long history,and with advancements in equipment and analytical methods,the quantitative analysis of auscultation parameters has determined.However,the complexity and diversity of auscultation,along with variations in devices,analytical methods,and applications,bring challenges to its standardization and deeper application.This review presents the advancements in auscultation equipment and systems,auscultation characteristic parameters,and their application in the diagnosis of pulmonary diseases and syndromes over the past 10 years,while also exploring the progress and challenges of current digital research of auscultation.This review also proposes the establishment of standardized protocols for the collection and analysis of auscultation data,the incorporation of advanced artificial intelligence(AI)auscultation analysis methods,and an exploration of the diagnostic utility of auscultatory features in pulmonary diseases and syndromes,so as to provide more precise decision support for intelligent diagnosis of pulmonary diseases and syndromes.
文摘This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.
文摘In the contemporary era,characterized by the Internet and digitalization as fundamental features,the operation and application of digital currency have gradually developed into a comprehensive structural system.This system restores the essential characteristics of currency while providing auxiliary services related to the formation,circulation,storage,application,and promotion of digital currency.Compared to traditional currency management technologies,big data analysis technology,which is primarily embedded in digital currency systems,enables the rapid acquisition of information.This facilitates the identification of standard associations within currency data and provides technical support for the operational framework of digital currency.
基金supported in part by National Natural Science Foundation of China(No.62271080)in part by Fund of State Key Laboratory of IPOC(BUPT)(No.IPOC2022ZT06)in part by BUPT Excellent Ph.D Students Foundation(No.CX2022102).
文摘To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.
文摘The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,General technical requirements for food digital factory,the first general technical national standard for food digital factory,was released recently.It bridges the gap in the industry,serving as the technical support and implementation framework for the intelligent and digital transformation of enterprises in the food industry.
基金supported by the Natural Science Foundation of Shanghai(No.23ZR1429300)Innovation Funds of CNNC(Lingchuang Fund,Contract No.CNNC-LCKY-202234)the Project of the Nuclear Power Technology Innovation Center of Science Technology and Industry(No.HDLCXZX-2023-HD-039-02)。
文摘Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.
基金Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDB0740000National Key Research and Development Program of China,No.2022YFB3904200,No.2022YFF0711601+1 种基金Key Project of Innovation LREIS,No.PI009National Natural Science Foundation of China,No.42471503。
文摘Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.
基金supported in part by Shenzhen Key Laboratory of Control Theory and Intelligent Systems (ZDSYS20220330161800001)the National Natural Science Foundation of China (62173255, 62188101)。
文摘With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.
基金supported by the Fundamental Research Funds for the Central Universitiesfollowing projects:the Major Project of the National Social Science Fund of China(NSSFC)“Research on the Synergistic Mechanisms of Innovation and Governance for High-Quality Development of the Digital Economy”(Grant No.22&ZD070)+1 种基金the Youth Project of the National Natural Science Foundation of China(NSFC)“Research on Risk-Taking of Zombie Enterprises from a Government-Enterprise Interaction Perspective:Tendency,Behavioral Patterns,and Economic Consequences”(Grant No.72002213)the General Program of the National Natural Science Foundation of China(NSFC)“Reshaping Enterprise Nature,Boundaries,and Internal Organization in the Digital Economy”(Grant No.72273144).
文摘Despite broad consensus on the importance of enterprise digital transformation,significant discrepancies persist regarding its actual effects.This divergence stems primarily from two key measurement challenges:(1)a lack of clear and consistent definitions of enterprise digital transformation,and(2)a lack of rigorous and accurate measurement methodologies.These shortcomings lead to research findings that are incomparable,difficult to replicate,and often conflicting.To effectively address the aforementioned challenges,this paper employs machine learning and large language models(LLMs)to construct a novel set of indicators for enterprise digital transformation.The work begins by manually annotating sentences from annual reports of listed companies in China from 2006 to 2020.These labeled sentences are then used to train and fine-tune several machine learning models,including LLMs.The ERNIE model,demonstrating the best classification performance among the models tested,is selected as the sentence classifier to predict sentence labels across the full text of the annual reports,ultimately constructing the enterprise digital transformation metrics.Both theoretical analysis and multiple data cross-validations demonstrate that the metrics developed in this paper are more accurate than existing approaches.Based on these metrics,the paper empirically examines the impact of enterprise digital transformation on financial performance.Our findings reveal three key points:(1)enterprise digital transformation significantly enhances financial performance,with big data,AI,mobile internet,cloud computing,and the Internet of Things(IoT)all playing a significant role;however,blockchain technology does not show a significant effect;(2)the significant positive effect of digital transformation on financial performance is primarily observed in firms with weaker initial financial performance;and(3)enterprise digital transformation improves financial performance mainly through enhancing efficiency and reducing costs.This research has practical implications for promoting enterprise digital transformation and fostering high-quality economic development.
基金the National Social Science Fund’s major project“Research on the Generation Background,Construction Logic,and Value Orientation of China’s Human Rights Knowledge System”(Project Approval Number 24&ZD129).
文摘The right to digital development,rooted in the fundamental right to development,emerges in response to the transformations of our era and serves as a catalyst for Chinese modernization.Building upon the traditional right to development,the right to digital development aims to meet the people’s aspirations for a better life in the context of digital development.By integrating a technological perspective,this concept advances the theoretical evolution of the right to development in line with contemporary realities.In terms of generation logic,the right to digital development is grounded in policies supporting Chinese modernization,guided by the development of new quality productive forces,and oriented toward addressing the people’s aspirations for a better life and society’s sustainable digital transformation.Ultimately,this framework constructs a normative structure encompassing the right to digital development opportunity,the right to digital development condition,and the right to digital development realization as a cohesive whole.From a value-oriented perspective,the right to digital development adheres to a people-centered philosophy of development,grounded in practical considerations.It addresses the digital divide as a focal point,gradually mitigating digital exclusion and circumventing digital malpractices,thereby fostering digital sharing.Integrating the right to digital development into the conceptual framework of the right to development can complete the institutional construction of digital development through the theoretical architecture of“condition-opportunity-realization.”This integration helps to better safeguard people’s rights and interests in digital development and promotes the free and comprehensive development of individuals.
文摘Digital transformation,as a recent trend in socioeconomic development,is considered as a critical pathway for urban carbon reduction because of its potential to increase productivity and energy efficiency.However,few studies have explored the relationship between urban digitalization and carbon emissions(CE).Therefore,this study systematically analyzed the spatiotemporal distribution and interaction mechanism between digitalization and CE in the Yangtze River Delta(YRD)urban agglomerations of China during 2006-2020 based on a multidimensional indicator system,including digitalization industry level,digitalization application level,and urban green digitalization willingness.The findings revealed that both digitalization and CE in the YRD exhibit a significant and synchronously evolving“core-periphery”spatial pattern.Core cities generated substantial positive spillover effect on periphery cities through technology diffusion and policy demonstration,advancing both regional digitalization and the collaborative governance of CE.However,digitalization had dual impact on CE.On the one hand,it promoted the reduction of CE by enhancing energy efficiency,optimizing industrial structures,and promoting the application of green technologies.On the other hand,the expansion of digital infrastructure introduced a potential risk of increased energy consumption.Therefore,targeted policy recommendations are proposed to facilitate the coordination of environmental sustainability and digitalization in the YRD.This study provides empirical support and policy insights for advancing the coordinated development of regional digital transformation and green low-carbon initiatives.
文摘This article is excerpted from a speech titled“Bridging Innovation:Advancing China-ASEAN Digital Technology Collaboration”delivered at the Shanghai Forum 2025 by Koh King Kee,president of the Centre for New Inclusive Asia and president of the ASEAN Research Center for a Community with Shared Future,Malaysia.The text has been edited for length and clarity.
文摘In this paper,we present a novel first-order digitalΣΔconverter tailored for digital-to-analog applications,focusing on achieving both high yield and reduced silicon estate.Our approach incorporates a substantial level of dithering noise into the input signal,strategically aimed at mitigating the spurious frequencies commonly encountered in such converters.Validation of our design is performed through simulations using a high-level simulator specialized in mixed-signal circuit analysis.The results underscore the enhanced performance of our circuit,especially in reducing spurious frequencies,highlighting its efficiency and effectiveness.The final circuit exhibits an effective number of bits of 13.
基金Basic scientific research business expenses of universities directly under Inner Mongolia Autonomous Region,Key project of Philosophy and Social Science Foundation of Inner Mongolia Agricultural University(BR220603)Special project for improving scientific research ability of young teachers of Inner Mongolia Agricultural University(BR230218).
文摘To investigate the application of virtual digital technology in landscape engineering design,the study adopted the enu-meration survey method and observation method.It conducted a comprehensive analysis of the current status and existing chal-lenges of virtual digital technology in landscape engineering design.Additionally,the study provided a detailed description and explanation of the integration between virtual digital technology and landscape engineering design,while exploring its charac-teristics and application prospects.The findings revealed:(1)In the early design stage,technological integration enhanced design efficiency.The collaborative use of BIM,GIS,and parametric tools enabled a fully digital workflow from conceptual design to construction drawings,reducing design errors and shortening project timelines.(2)After implementation,interactive experiences revolutionized public engagement.AR/VR technologies introduced dynamic interactivity to landscapes,while metaverse plat-forms expanded the presentation dimensions of virtual landscapes.(3)Smart maintenance promoted sustainability.IoT sensors and AI analytics facilitated real-time plant health monitoring and precise resource management,demonstrating significant advan-tages.The study identified existing limitations and proposed future directions,aiming to provide new theoretical and practical insights for the research and application of digital technology in landscape engineering design.
基金supported by“The Palace Museum Talent Program”.The Palace Museum Talent Program is supported by The Hong Kong Jockey Club,exclusively sponsored by the Institute of Philanthropy.
文摘The standards system for cultural heritage digitalization aims to build a clear and logically rigorous framework to guide the development and revision of relevant standards.This system enhances the scientific,systematic,and practical aspects of cultural heritage digitalization.This paper comprehensively analyzes the current status and needs of cultural heritage digitalization and standardization.It further examines the methods used to construct the standards system.Through comparative analysis,it establishes a lifecycle-based framework for cultural heritage.This framework accounts for the unique characteristics of cultural heritage and systematically integrates key processes such as collection,processing,storage,transmission,and utilization of data.The standards system is divided into six sections:general,data,information,knowledge,intelligence,and application.Based on the current digitalization efforts,this paper proposes key standardization directions for each section.This framework ensures the integrity and consistency of data throughout the digitalization process.It also supports the application of intelligent technologies in cultural heritage conservation,contributing to the sustainable preservation and utilization of cultural heritage data.
基金the financial support from the Natural Science Foundation of Jiangsu Province(Grant Nos.BE2022071 and BK20192001)the National Natural Science Foundation of China(Grant Nos.12074194,62471248,12104240,and 62101285)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX220954)。
文摘Quantum digital signature(QDS)can guarantee the information-theoretical security of a signature with the fundamental laws of quantum physics.However,most current QDS protocols do not take source security into account,leading to an overestimation of the signature rate.In this paper,we propose to utilize Hong–Ou–Mandel interference to characterize the upper bound of the source imperfections,and further to quantify information leakage from potential side-channels.Additionally,we combine decoy-state methods and finite-size analysis in analyzing the signature rate.Simulation results demonstrate the performance and feasibility of our approach.Our current work can improve the practical security of QDS systems,thereby promoting their further networked applications.
