Based on the requirements of local high-quality economic development and addressing the critical task of transformation and upgrading in the tea industry,this paper systematically discusses the necessity and feasibili...Based on the requirements of local high-quality economic development and addressing the critical task of transformation and upgrading in the tea industry,this paper systematically discusses the necessity and feasibility of constructing an optimal industrialization operation system driven by the dual wheels of"branding+standardization".The article first clarifies the connotation of high-quality development and the synergistic mechanism between branding and standardization.It then analyzes the current situation and bottlenecks of China's tea industry development.Subsequently,it proposes a dual-wheel drive strategy where branding enhances value and standardization guarantees quality,and designs a systematic implementation plan involving industrial chain synergy optimization and integrated support from government,industry,academia,research,and application.On this basis,strategies and suggestions are proposed,encompassing the starting point,standard focal points,key effort areas,innovation points,and target achievement points.The aim is to promote the tea industry to break through homogeneous competition,achieve value ascent,and provide important industrial support for regional high-quality development through the construction of the aforementioned system.展开更多
As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds...As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.展开更多
The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has dri...The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has driven a growing need for robust ICS security measures.Among the key defences,intrusion detection technology is critical in identifying threats to ICS networks.This paper provides an overview of the distinctive characteristics of ICS network security,highlighting standard attack methods.It then examines various intrusion detection methods,including those based on misuse detection,anomaly detection,machine learning,and specialised requirements.This paper concludes by exploring future directions for developing intrusion detection systems to advance research and ensure the continued security and reliability of ICS operations.展开更多
At a critical juncture of global industrial transformation and economic recovery,the 2026 China Expo Forum for International Cooperation(CEFCO)recently concluded in Wuhan.Dubbed the“Davos of the exhibition industry”...At a critical juncture of global industrial transformation and economic recovery,the 2026 China Expo Forum for International Cooperation(CEFCO)recently concluded in Wuhan.Dubbed the“Davos of the exhibition industry”,the forum,attracted more than 600 exhibition professionals from over 20 countries and regions.展开更多
THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-...THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-cloud collaborative design.However,the large-scale integration ofdistributed renewable energy resources,coupled with the extensivedeployment of sensing and communication devices,has resulted inthe new-type power system characterized by dynamic complexityand high uncertainty[1]-[4].展开更多
Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e....Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e.,run to failure)or time-based preventive maintenance(i.e.,scheduled servicing),prove ineffective for complex systems with many Internet of Things(IoT)devices and sensors because they fall short in detecting faults at early stages when it is most crucial.This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory(LSTM)Networks and Convolutional Neural Networks(CNNs).The framework integrates spatial feature extraction and temporal sequence modeling to accurately classify the health state of industrial equipment into three categories,including Normal,Require Maintenance,and Failed.The framework uses a modular pipeline that includes IoT-enabled data collection along with secure transmission methods to manage cloud storage and provide real-time fault classification.The FD004 subset of the NASA C-MAPSS dataset,containing multivariate sensor readings from aircraft engines,serves as the training and evaluation data for the model.Experimental results show that the LSTM-CNN model outperforms baseline models such as LSTM-SVM and LSTM-RNN,achieving an overall average accuracy of 86.66%,precision of 86.00%,recall of 86.33%,and F1-score of 86.33%.Contrary to the previous LSTM-CNN-based predictive maintenance models that either provide a binary classification or rely on synthetically balanced data,our paper provides a three-class maintenance state(i.e.,Normal,Require Maintenance,and Failed)along with threshold-based labeling that retains the true nature of the degradation.In addition,our work also provides an IoT-to-cloud-based modular architecture for deployment.It offers Computerized Maintenance Management System(CMMS)integration,making our proposed solution not only technically sound but also practical and innovative.The solution achieves real-world industrial deployment readiness through its reliable performance alongside its scalable system design.展开更多
Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring ...Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.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
Aiming at the issues of poor scalability,single training modes,and missing platform foundation in current parachute training simulation systems,a method for a parachute training simulation system supporting the"1...Aiming at the issues of poor scalability,single training modes,and missing platform foundation in current parachute training simulation systems,a method for a parachute training simulation system supporting the"1+N+N"mode is proposed by building a flexible functional structure design based on four domains and two systems architecture,which can adapt to multiple working modes such as"1+N"and"1+N(*)".This method can effectively save the cost and time of upgrading and expanding system capacity,greatly increasing the lifespan and availability of the system.展开更多
In recent years, the digital economy has become a key driver of deepening China-Thailand cooperation. As trade and industrial digitalization advance, artificial intelligence (AI), an essential force in the new wave of...In recent years, the digital economy has become a key driver of deepening China-Thailand cooperation. As trade and industrial digitalization advance, artificial intelligence (AI), an essential force in the new wave of technological revolution, is increasingly embedded in the bilateral agenda, steering collaboration beyond efficiencydriven “digital coordination” toward more structured and systemic“intelligent co-development.”Building on five decades of mutual trust since the establishment of diplomatic ties, this cooperation not only addresses the practical needs of industrial upgrading and governance transformation but offers a valuable reference for ASEAN countries exploring replicable pathways in the era of digital transformation.展开更多
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings...Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.展开更多
Security and access control for data storage in 5G industrial Internet collaborative systems are facing significant challenges.The characteristics of 5 G networks,such as low latency and high speed,facilitate data tra...Security and access control for data storage in 5G industrial Internet collaborative systems are facing significant challenges.The characteristics of 5 G networks,such as low latency and high speed,facilitate data transmission in the industrial Internet but also increase vulnerability to attacks like theft and tampering.Moreover,in 5G industrial Internet collaborative system environments,data flows across multiple entities and links,which necessitates a flexible access control model to meet specific data access requirements.Traditional role-based and attribute-based access control mechanisms are difficult to apply in such dynamic application scenarios.To address these challenges,we propose a novel data storage solution for 5G industrial Internet collaborative systems.Similar to existing approaches,it provides integrity and confidentiality protection for transmitted data.In terms of security,only authenticated data owners and users can obtain file decryption keys,preventing malicious attackers from data forgery.Regarding access control,decryption is permitted only to authorized data users,safeguarding against unauthorized file access.Furthermore,by introducing an attribute-based encryption mechanism,only data users with specific attributes can decrypt files.In terms of efficiency,our approach utilizes bilinear and modular exponentiation operations solely during the authentication process.For handling substantial data loads,lightweight cryptographic algorithms are employed.Consequently,our solution achieves higher efficiency compared with other known methods.Experimental results demonstrate the feasibility of our approach in real-world applications.展开更多
[Objective] The aim was to study the effects of urbanization and industrialization on farmland system in Shandong Peninsula. [Method] In Shandong Peninsula, the effects were studied and analyzed using remote sensing a...[Objective] The aim was to study the effects of urbanization and industrialization on farmland system in Shandong Peninsula. [Method] In Shandong Peninsula, the effects were studied and analyzed using remote sensing and image interpretation with spatial data analysis and statistic data analysis. [Result] During researching periods in Shandong Peninsula, wasteland area changed from decreasing to increasing; farmland area was declining; orchard and forestry areas were increasing, mainly resulting from political policies and benefits maximization of farmers. Meanwhile, chemical fertilizers and agricultural mechanization are more frequently applied with industrialization and urbanization, leading significant effects on environment, industry and urban. [Conclusion] More policies should be formulated to promote harmonious development of society, economy and environment.展开更多
New industrialization in China, different from its past economic development pattern or patterns in developed nations, is the country’s theoretical innovation based on the positive and negative experiences of industr...New industrialization in China, different from its past economic development pattern or patterns in developed nations, is the country’s theoretical innovation based on the positive and negative experiences of industrialization at home and worldwide. New industrialization has various novel characteristics, including new sources of efficiency, new factors of production, new organizational forms, and new constraints. In addition, it has certain particularities arising from modernization with Chinese characteristics. This article summarizes the characteristics of new industrialization from the perspectives of people-centered approach, quality-first concept, independent innovation, green low-carbon economics, digital-real integration, and open circulation. There are four systems for promoting new industrialization: A self-sustained scientific and technological system, a high-end advanced manufacturing system, a green low-carbon circular system, and a division of labor system with domestic and international circulation. The Chinese new industrialization proposes the pathway and policy measures considering the new global situation and the requirements of new goals of strengthening organization and leadership, reducing factor cost, accelerating independent technological innovation, smoothing domestic and international circulation, and optimizing competition environment.展开更多
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
In this paper draw on the innovative concept of investment in the system of agriculture industrialization, examines the status of the industrialization of agriculture in Anhui Province, the industrialization of agricu...In this paper draw on the innovative concept of investment in the system of agriculture industrialization, examines the status of the industrialization of agriculture in Anhui Province, the industrialization of agriculture investment regime status quo, elaborated on the meaning of investment regimes investment system innovation on innovation and industrialization of agriculture, Anhui should be investment in the industrialization of agriculture system innovation, and promote the development of Anhui Province, rural and agricultural industrialization, specification and guidance, as well as the establishment and improvement investment regime; focuses on the innovative design of the investment regime of the industrialization of agriculture in Anhui Province.展开更多
Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection metho...Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.展开更多
Finger-joint lumber is a sustainable building product commercialized as a structural solution for beams,pillars and other thin flat load-bearing elements.This study aims to study finger-joint lumber and its industry t...Finger-joint lumber is a sustainable building product commercialized as a structural solution for beams,pillars and other thin flat load-bearing elements.This study aims to study finger-joint lumber and its industry to promote this engineered wood product.The first research stage assessed the collection of publications on fingerjoint lumber available globally,in which a structured protocol was developed to prospect studies based on two complementary methodologies:PRISMA 2020 using Scopus and Web of Science databases,and Snowball using both forward and backward models to complete with additional literature.The second research stage assessed finger-joint lumber manufacturers,in which companies were globally prospected using Google search engine and their corporate websites were profoundly analyzed using a structured script to collect information.Literary approaches have provided structural performance and bonding quality of finger-jointing.In the review,we provide a global overview and data regarding the current stage and future directions of finger-joint lumber for industrialized construction.Regarding this structural product,we review the main resources,material preparation and processing,and automated production.Mainly active in Europe and already present in 38 nations across five continents,we survey a finger-joint lumber industry comprising 186 producers controlling 214 manufacturing operations worldwide.The vast majority of this industry has exported linear engineered solutions in different dimensions,certified as to compliance with the origins of their bioresources and the European Union requirements,to markets exposed to 24 languages in order to meet commercial applications such as single-story houses,townhouses,roof structures,and hangars.展开更多
Global sustainable development cannot be achieved by neglecting rural areas.These regions represent vast territorial spaces beyond urban built-up areas,possessing comparative advantages through their distinctive ecolo...Global sustainable development cannot be achieved by neglecting rural areas.These regions represent vast territorial spaces beyond urban built-up areas,possessing comparative advantages through their distinctive ecological resources.The transformation of ecological resources into economic value,commonly referred to as ecological industrialization,enhances rural economic vitality and developmental potential.Comprehensive rural revitalization strengthens regional functionality and development resilience,thereby promoting sustainable rural development.Based on human-earth system science,we theorize ecological industrialization as the PGR model,manifesting the transformation path from“poor mountain”to“green mountain”and then to“rich mountain”.It is noteworthy that in regions endowed with beautiful ecological landscapes,the PGR model prioritizes the transformation of“green mountain”to“rich mountain”.The essence of rural revitalization manifests through areal transformations driven by tripartite forces:the rural internal force,urban peripheral force,and urban-rural interaction force.There is a mutually reinforcing relationship between ecological industrialization and rural revitalization,and the implementation of the two can realize the coordinated development of rural functions.In this process,rural areas have realized the transformation from degraded land system to human-earth coupling system.Furthermore,through the examination of Fuping,Liuba,and Sanming as exemplary case studies,we have distilled three distinct modes of ecological industrialization:the circular industry mode,the ecological tourism mode,and the carbon sink trading mode.It is recommended that rural areas prioritize the coordinated implementation of ecological industrialization and rural revitalization in accordance with regional characteristics,so as to better foster rural sustainable development.展开更多
基金Supported by General Project of Philosophy and Social Sciences Research in Universities of Jiangsu Province,2024(2024SJYB1650).
文摘Based on the requirements of local high-quality economic development and addressing the critical task of transformation and upgrading in the tea industry,this paper systematically discusses the necessity and feasibility of constructing an optimal industrialization operation system driven by the dual wheels of"branding+standardization".The article first clarifies the connotation of high-quality development and the synergistic mechanism between branding and standardization.It then analyzes the current situation and bottlenecks of China's tea industry development.Subsequently,it proposes a dual-wheel drive strategy where branding enhances value and standardization guarantees quality,and designs a systematic implementation plan involving industrial chain synergy optimization and integrated support from government,industry,academia,research,and application.On this basis,strategies and suggestions are proposed,encompassing the starting point,standard focal points,key effort areas,innovation points,and target achievement points.The aim is to promote the tea industry to break through homogeneous competition,achieve value ascent,and provide important industrial support for regional high-quality development through the construction of the aforementioned system.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by the Korea Internet&Security Agency(KISA)through the Information Security Specialized University Support Project(50%).
文摘As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.
文摘The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has driven a growing need for robust ICS security measures.Among the key defences,intrusion detection technology is critical in identifying threats to ICS networks.This paper provides an overview of the distinctive characteristics of ICS network security,highlighting standard attack methods.It then examines various intrusion detection methods,including those based on misuse detection,anomaly detection,machine learning,and specialised requirements.This paper concludes by exploring future directions for developing intrusion detection systems to advance research and ensure the continued security and reliability of ICS operations.
文摘At a critical juncture of global industrial transformation and economic recovery,the 2026 China Expo Forum for International Cooperation(CEFCO)recently concluded in Wuhan.Dubbed the“Davos of the exhibition industry”,the forum,attracted more than 600 exhibition professionals from over 20 countries and regions.
基金partially supported by the National Natural Science Foundation of China(62293500,62293505,62233010,62503240)Natural Science Foundation of Jiangsu Province(BK20250679)。
文摘THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-cloud collaborative design.However,the large-scale integration ofdistributed renewable energy resources,coupled with the extensivedeployment of sensing and communication devices,has resulted inthe new-type power system characterized by dynamic complexityand high uncertainty[1]-[4].
文摘Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e.,run to failure)or time-based preventive maintenance(i.e.,scheduled servicing),prove ineffective for complex systems with many Internet of Things(IoT)devices and sensors because they fall short in detecting faults at early stages when it is most crucial.This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory(LSTM)Networks and Convolutional Neural Networks(CNNs).The framework integrates spatial feature extraction and temporal sequence modeling to accurately classify the health state of industrial equipment into three categories,including Normal,Require Maintenance,and Failed.The framework uses a modular pipeline that includes IoT-enabled data collection along with secure transmission methods to manage cloud storage and provide real-time fault classification.The FD004 subset of the NASA C-MAPSS dataset,containing multivariate sensor readings from aircraft engines,serves as the training and evaluation data for the model.Experimental results show that the LSTM-CNN model outperforms baseline models such as LSTM-SVM and LSTM-RNN,achieving an overall average accuracy of 86.66%,precision of 86.00%,recall of 86.33%,and F1-score of 86.33%.Contrary to the previous LSTM-CNN-based predictive maintenance models that either provide a binary classification or rely on synthetically balanced data,our paper provides a three-class maintenance state(i.e.,Normal,Require Maintenance,and Failed)along with threshold-based labeling that retains the true nature of the degradation.In addition,our work also provides an IoT-to-cloud-based modular architecture for deployment.It offers Computerized Maintenance Management System(CMMS)integration,making our proposed solution not only technically sound but also practical and innovative.The solution achieves real-world industrial deployment readiness through its reliable performance alongside its scalable system design.
文摘Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.
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.
文摘Aiming at the issues of poor scalability,single training modes,and missing platform foundation in current parachute training simulation systems,a method for a parachute training simulation system supporting the"1+N+N"mode is proposed by building a flexible functional structure design based on four domains and two systems architecture,which can adapt to multiple working modes such as"1+N"and"1+N(*)".This method can effectively save the cost and time of upgrading and expanding system capacity,greatly increasing the lifespan and availability of the system.
文摘In recent years, the digital economy has become a key driver of deepening China-Thailand cooperation. As trade and industrial digitalization advance, artificial intelligence (AI), an essential force in the new wave of technological revolution, is increasingly embedded in the bilateral agenda, steering collaboration beyond efficiencydriven “digital coordination” toward more structured and systemic“intelligent co-development.”Building on five decades of mutual trust since the establishment of diplomatic ties, this cooperation not only addresses the practical needs of industrial upgrading and governance transformation but offers a valuable reference for ASEAN countries exploring replicable pathways in the era of digital transformation.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金supported by the Research Funding Project for Graduate Education and Teaching Reform of Beijing University of Posts and Telecommunications(No.2024Y036)the Postgraduate Education and Teaching Reform Research Fund Project of Beijing University of Posts and Telecommunications(No.2024Z007)the Postgraduate Education and Teaching Reform Project of Beijing University of Posts and Telecommunications(2025).
文摘Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20230628015the State Key Laboratory of Particle Detection and Electronics under Grant No.SKLPDE-KF-202314。
文摘Security and access control for data storage in 5G industrial Internet collaborative systems are facing significant challenges.The characteristics of 5 G networks,such as low latency and high speed,facilitate data transmission in the industrial Internet but also increase vulnerability to attacks like theft and tampering.Moreover,in 5G industrial Internet collaborative system environments,data flows across multiple entities and links,which necessitates a flexible access control model to meet specific data access requirements.Traditional role-based and attribute-based access control mechanisms are difficult to apply in such dynamic application scenarios.To address these challenges,we propose a novel data storage solution for 5G industrial Internet collaborative systems.Similar to existing approaches,it provides integrity and confidentiality protection for transmitted data.In terms of security,only authenticated data owners and users can obtain file decryption keys,preventing malicious attackers from data forgery.Regarding access control,decryption is permitted only to authorized data users,safeguarding against unauthorized file access.Furthermore,by introducing an attribute-based encryption mechanism,only data users with specific attributes can decrypt files.In terms of efficiency,our approach utilizes bilinear and modular exponentiation operations solely during the authentication process.For handling substantial data loads,lightweight cryptographic algorithms are employed.Consequently,our solution achieves higher efficiency compared with other known methods.Experimental results demonstrate the feasibility of our approach in real-world applications.
基金Supported by National Natural Science Foundation of China (40901027,No. 41106036)Shandong Natural Science Foundation (2011DQ006)the International Partnership Creative Group, the Chinese Academy of Sciences "Typical Environmental Process and Effects of Coastal Zone Resources"~~
文摘[Objective] The aim was to study the effects of urbanization and industrialization on farmland system in Shandong Peninsula. [Method] In Shandong Peninsula, the effects were studied and analyzed using remote sensing and image interpretation with spatial data analysis and statistic data analysis. [Result] During researching periods in Shandong Peninsula, wasteland area changed from decreasing to increasing; farmland area was declining; orchard and forestry areas were increasing, mainly resulting from political policies and benefits maximization of farmers. Meanwhile, chemical fertilizers and agricultural mechanization are more frequently applied with industrialization and urbanization, leading significant effects on environment, industry and urban. [Conclusion] More policies should be formulated to promote harmonious development of society, economy and environment.
文摘New industrialization in China, different from its past economic development pattern or patterns in developed nations, is the country’s theoretical innovation based on the positive and negative experiences of industrialization at home and worldwide. New industrialization has various novel characteristics, including new sources of efficiency, new factors of production, new organizational forms, and new constraints. In addition, it has certain particularities arising from modernization with Chinese characteristics. This article summarizes the characteristics of new industrialization from the perspectives of people-centered approach, quality-first concept, independent innovation, green low-carbon economics, digital-real integration, and open circulation. There are four systems for promoting new industrialization: A self-sustained scientific and technological system, a high-end advanced manufacturing system, a green low-carbon circular system, and a division of labor system with domestic and international circulation. The Chinese new industrialization proposes the pathway and policy measures considering the new global situation and the requirements of new goals of strengthening organization and leadership, reducing factor cost, accelerating independent technological innovation, smoothing domestic and international circulation, and optimizing competition environment.
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In this paper draw on the innovative concept of investment in the system of agriculture industrialization, examines the status of the industrialization of agriculture in Anhui Province, the industrialization of agriculture investment regime status quo, elaborated on the meaning of investment regimes investment system innovation on innovation and industrialization of agriculture, Anhui should be investment in the industrialization of agriculture system innovation, and promote the development of Anhui Province, rural and agricultural industrialization, specification and guidance, as well as the establishment and improvement investment regime; focuses on the innovative design of the investment regime of the industrialization of agriculture in Anhui Province.
基金Supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(22KJB520012)the Research Project on Higher Education Reform in Jiangsu Province(2023JSJG781)the College Student Innovation and Entrepreneurship Training Program Project(202313571008Z)。
文摘Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.
基金supported by the Scientific Grant Agency of the Ministry of Education,Science,Research and Sport of the Slovak Republic(VEGA)with VEGA 1/0228/24 Project and the Cultural and Educational Grant Agency Ministry of Education,Science,Research and Sport of the Slovak Republic(KEGA)with KEGA 017TUKE-4/2024 ProjectBrazilian Federal Agency for Support and Evaluation of Graduate Education(CAPES),with finance code 001.
文摘Finger-joint lumber is a sustainable building product commercialized as a structural solution for beams,pillars and other thin flat load-bearing elements.This study aims to study finger-joint lumber and its industry to promote this engineered wood product.The first research stage assessed the collection of publications on fingerjoint lumber available globally,in which a structured protocol was developed to prospect studies based on two complementary methodologies:PRISMA 2020 using Scopus and Web of Science databases,and Snowball using both forward and backward models to complete with additional literature.The second research stage assessed finger-joint lumber manufacturers,in which companies were globally prospected using Google search engine and their corporate websites were profoundly analyzed using a structured script to collect information.Literary approaches have provided structural performance and bonding quality of finger-jointing.In the review,we provide a global overview and data regarding the current stage and future directions of finger-joint lumber for industrialized construction.Regarding this structural product,we review the main resources,material preparation and processing,and automated production.Mainly active in Europe and already present in 38 nations across five continents,we survey a finger-joint lumber industry comprising 186 producers controlling 214 manufacturing operations worldwide.The vast majority of this industry has exported linear engineered solutions in different dimensions,certified as to compliance with the origins of their bioresources and the European Union requirements,to markets exposed to 24 languages in order to meet commercial applications such as single-story houses,townhouses,roof structures,and hangars.
基金supported by the National Natural Science Foundation of China(Grant No.42293271)the Alliance of International Science Organizations(Grant No.ANSO-PA-2023-16)。
文摘Global sustainable development cannot be achieved by neglecting rural areas.These regions represent vast territorial spaces beyond urban built-up areas,possessing comparative advantages through their distinctive ecological resources.The transformation of ecological resources into economic value,commonly referred to as ecological industrialization,enhances rural economic vitality and developmental potential.Comprehensive rural revitalization strengthens regional functionality and development resilience,thereby promoting sustainable rural development.Based on human-earth system science,we theorize ecological industrialization as the PGR model,manifesting the transformation path from“poor mountain”to“green mountain”and then to“rich mountain”.It is noteworthy that in regions endowed with beautiful ecological landscapes,the PGR model prioritizes the transformation of“green mountain”to“rich mountain”.The essence of rural revitalization manifests through areal transformations driven by tripartite forces:the rural internal force,urban peripheral force,and urban-rural interaction force.There is a mutually reinforcing relationship between ecological industrialization and rural revitalization,and the implementation of the two can realize the coordinated development of rural functions.In this process,rural areas have realized the transformation from degraded land system to human-earth coupling system.Furthermore,through the examination of Fuping,Liuba,and Sanming as exemplary case studies,we have distilled three distinct modes of ecological industrialization:the circular industry mode,the ecological tourism mode,and the carbon sink trading mode.It is recommended that rural areas prioritize the coordinated implementation of ecological industrialization and rural revitalization in accordance with regional characteristics,so as to better foster rural sustainable development.
