The proliferation of Internet of Things(IoT)systems has resulted in the generation of substantial data,presenting new challenges in reliable storage and trustworthy sharing.Conventional distributed storage systems are...The proliferation of Internet of Things(IoT)systems has resulted in the generation of substantial data,presenting new challenges in reliable storage and trustworthy sharing.Conventional distributed storage systems are hindered by centralized management and lack traceability,while blockchain systems are limited by low capacity and high latency.To address these challenges,the present study investigates the reliable storage and trustworthy sharing of IoT data,and presents a novel system architecture that integrates on-chain and off-chain data manage systems.This architecture,integrating blockchain and distributed storage technologies,provides high-capacity,high-performance,traceable,and verifiable data storage and access.The on-chain system,built on Hyperledger Fabric,manages metadata,verification data,and permission information of the raw data.The off-chain system,implemented using IPFS Cluster,ensures the reliable storage and efficient access to massive files.A collaborative storage server is designed to integrate on-chain and off-chain operation interfaces,facilitating comprehensive data operations.We provide a unified access interface for user-friendly system interaction.Extensive testing validates the system’s reliability and stable performance.The proposed approach significantly enhances storage capacity compared to standalone blockchain systems.Rigorous reliability tests consistently yield positive outcomes.With average upload and download throughputs of roughly 20 and 30 MB/s,respectively,the system’s throughput surpasses the blockchain system by a factor of 4 to 18.展开更多
Purpose:The aim of this study is to analyze the evolution of international research collaboration from 1980 to 2021.The study examines the main global patterns as well as those specific to individual countries,country...Purpose:The aim of this study is to analyze the evolution of international research collaboration from 1980 to 2021.The study examines the main global patterns as well as those specific to individual countries,country groups,and different areas of research.Design/methodology/approach:The study is based on the Web of Science Core collection database.More than 50 million publications are analyzed using co-authorship data.International collaboration is defined as publications having authors affiliated with institutions located in more than one country.Findings:At the global level,the share of publications representing international collaboration has gradually increased from 4.7%in 1980 to 25.7%in 2021.The proportion of such publications within each country is higher and,in 2021,varied from less than 30%to more than 90%.There are notable disparities in the temporal trends,indicating that the process of internationalization has impacted countries in different ways.Several factors such as country size,income level,and geopolitics may explain the variance.Research limitations:Not all international research collaboration results in joint co-authored scientific publications.International co-authorship is a partial indicator of such collaboration.Another limitation is that the applied full counting method does not take into account the number of authors representing in each country in the publication.Practical implications:The study provides global averages,indicators,and concepts that can provide a useful framework of reference for further comparative studies of international research collaboration.Originality/value:Long-term macro-level studies of international collaboration are rare,and as a novelty,this study includes an analysis by the World Bank’s division of countries into four income groups.展开更多
In Thailand, the alteration of weather patterns has resulted in an increase in instances of irregular rainfall, contributing to the occurrence of droughts. The decline of water levels in dams, due to the combined effe...In Thailand, the alteration of weather patterns has resulted in an increase in instances of irregular rainfall, contributing to the occurrence of droughts. The decline of water levels in dams, due to the combined effects of climate change and prolonged droughts, has had a significant impact on agricultural productivity. Drought has a profound effect on the terrestrial biosphere and the atmospheric water cycle and can also contribute to air pollution. Researchers have found a strong correlation between air pollution and drought severity. In response to this pressing issue, the Excellence Center of Space Technology and Research (ECSTAR) at King Mongkut’s Institute of Technology Ladkrabang has joined forces with TeroSpace company to launch an initiative aimed at promoting sustainable growth in Chiang Rai, a province in Thailand known for its rich biodiversity. ECSTAR and TeroSpace’s partnership on the sustainable growth initiative in Thailand’s Chiang Rai province focuses on expanding their collaboration to include international organizations such as the Centre National d’Etudes Spatiales (CNES), which will provide access to satellite imagery and climate and weather information to improve decision-making in various areas of development. CNES is a French organization in charge of space-related activities in France. The collaboration between France and Thailand for this project, in the context of the France-Thailand Year of Innovation 2023, will be crucial for the successful initiation and execution of this research project. The project aims to explore the relationship between air pollution and climate change through the deployment of air quality monitoring devices in designated locations, connected to a global data-sharing network. The results of this research will be valuable to policymakers as they consider the interplay between air pollution and climate change and make efforts to address these challenges.展开更多
Human–robot(HR)collaboration(HRC)is an emerging research field because of the complementary advantages of humans and robots.An HRC framework for robotic assembly based on impedance control is proposed in this paper.I...Human–robot(HR)collaboration(HRC)is an emerging research field because of the complementary advantages of humans and robots.An HRC framework for robotic assembly based on impedance control is proposed in this paper.In the HRC framework,the human is the decision maker,the robot acts as the executor,while the assembly environment provides constraints.The robot is the main executor to perform the assembly action,which has the position control,drag and drop,positive impedance control,and negative impedance control modes.To reveal the characteristics of the HRC framework,the switch condition map of different control modes and the stability analysis of the HR coupled system are discussed.In the end,HRC assembly experiments are conducted,where the HRC assembly task can be accomplished when the assembling tolerance is 0.08 mm or with the interference fit.Experiments show that the HRC assembly has the complementary advantages of humans and robots and is efficient in finishing complex assembly tasks.展开更多
Over the last several years,remote collaboration has been getting more attention in the research community because of the COVID-19 pandemic.In previous studies,researchers have investigated the effect of adding visual...Over the last several years,remote collaboration has been getting more attention in the research community because of the COVID-19 pandemic.In previous studies,researchers have investigated the effect of adding visual communication cues or shared views in collaboration,but there has not been any previous study exploring the influence between them.In this paper,we investigate the influence of view types on the use of visual communication cues.We compared the use of the three visual cues(hand gesture,a pointer with hand gesture,and sketches with hand gesture)across two view types(dependent and independent views),respectively.We conducted a user study,and the results showed that hand gesture and sketches with the hand gesture cueswerewell matchedwith the dependent viewcondition,and using a pointer with the hand gesture cue was suited to the independent view condition.With the dependent view,the hand gesture and sketch cues required less mental effort for collaborative communication,had better usability,provided better message understanding,and increased feeling of co-presence compared to the independent view.Since the dependent view supported the same viewpoint between the remote expert and a local worker,the local worker could easily understand the remote expert’s hand gestures.In contrast,in the independent view case,when they had different viewpoints,it was not easy for the local worker to understand the remote expert’s hand gestures.The sketch cue had a benefit of showing the final position and orientation of the manipulating objects with the dependent view,but this benefit was less obvious in the independent view case(which provided a further view compared to the dependent view)because precise drawing in the sketches was difficult from a distance.On the contrary,a pointer with the hand gesture cue required less mental effort to collaborate,had better usability,provided better message understanding,and an increased feeling of co-presence in the independent view condition than in the dependent view condition.The pointer cue could be used instead of a hand gesture in the independent view condition because the pointer could still show precise pointing information regardless of the view type.展开更多
Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intellig...Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intelligent services to mobile users.However,as the accuracy requirements continue to increase,the components of deep learning models for pedestrian and vehicle detection,such as YOLOv4,become more sophisticated and the computing resources required for model training are increasing dramatically,which in turn leads to significant challenges in achieving effective deployment on resource-constrained edge devices while ensuring the high accuracy performance.For addressing this challenge,a cloud-edge collaboration-based pedestrian and vehicle detection framework is proposed in this paper,which enables sufficient training of models by utilizing the abundant computing resources in the cloud,and then deploying the well-trained models on edge devices,thus reducing the computing resource requirements for model training on edge devices.Furthermore,to reduce the size of the model deployed on edge devices,an automatic pruning method combines the convolution layer and BN layer is proposed to compress the pedestrian and vehicle detection model size.Experimental results show that the framework proposed in this paper is able to deploy the pruned model on a real edge device,Jetson TX2,with 6.72 times higher FPS.Meanwhile,the channel pruning reduces the volume and the number of parameters to 96.77%for the model,and the computing amount is reduced to 81.37%.展开更多
Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accur...Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accurate estimation and prediction of battery health conditions are crucial for battery safety management.In this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven model.Based on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate results.The double exponential decay model is utilized as an empirical model to output highly real-time prediction results.With Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time results.Subsequently,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μs.The proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network.展开更多
To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitme...To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitment,source-network load collaboration,and control of the load demand response.After the constraint functions are linearized,the original problem is decomposed into the main problem and subproblem as a matrix using the strong dual method.The minimum-maximum of the original problem was continuously maximized using the iterative method,and the optimal solution was finally obtained.The constraint conditions expressed by the matrix may reduce the calculation time,and the upper and lower boundaries of the original problem may rapidly converge.The results of the example show that the injected nodes of the wind farms in the power grid should be selected appropriately;otherwise,it is easy to cause excessive accommodation of wind power at some nodes,leading to a surge in reserve costs and the load demand response is continuously optimized to reduce the inverse peak regulation characteristics of wind power.Thus,the most economical optimization scheme for the worst scenario of the output power of the generators is obtained,which proves the economy and reliability of the two-stage robust optimization method.展开更多
With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provi...With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.展开更多
China’s Daya Bay collaboration and the RENO collaboration of South Korea were jointly awarded the 2023 High Energy and Particle Physics Prize of the European Physical Society(EPS)at a ceremony in Hamburg,Germany on A...China’s Daya Bay collaboration and the RENO collaboration of South Korea were jointly awarded the 2023 High Energy and Particle Physics Prize of the European Physical Society(EPS)at a ceremony in Hamburg,Germany on August 21.Prof.WANG Yifang,initiator of the experiment in China and current director of the Institute of High Energy Physics(IHEP)of the Chinese Academy of Sciences(CAS),accepted the award on behalf of the Daya Bay collaboration.展开更多
Response speed is vital for the railway environment monitoring system,especially for the sudden-onset disasters.The edge-cloud collaboration scheme is proved efficient to reduce the latency.However,the data characteri...Response speed is vital for the railway environment monitoring system,especially for the sudden-onset disasters.The edge-cloud collaboration scheme is proved efficient to reduce the latency.However,the data characteristics and communication demand of the tasks in the railway environment monitoring system are all different and changeable,and the latency contribution of each task to the system is discrepant.Hence,two valid latency minimization strategies based on the edge-cloud collaboration scheme is developed in this paper.First,the processing resources are allocated to the tasks based on the priorities,and the tasks are processed parallly with the allocated resources to minimize the system valid latency.Furthermore,considering the differences in the data volume of the tasks,which will induce the waste of the resources for the tasks finished in advance.Thus,the tasks with similar priorities are graded into the same group,and the serial and parallel processing strategies are performed intra-group and inter-group simultaneously.Compared with the other four strategies in four railway monitoring scenarios,the proposed strategies proved latency efficiency to the high-priority tasks,and the system valid latency is reduced synchronously.The performance of the railway environment monitoring system in security and efficiency will be promoted greatly with the proposed scheme and strategies.展开更多
Europe as an important part of the US-led global strategic alliance has been a target for US attempt to include in its strategy as a counterweight against China in the context of intensifying ChinaUS competition and t...Europe as an important part of the US-led global strategic alliance has been a target for US attempt to include in its strategy as a counterweight against China in the context of intensifying ChinaUS competition and the prolonged Russia-Ukraine conflict,so as to form the US global strategic collaboration architecture to contain China through the echoing of the US-European strategic collaboration with the QUAD and the AUKUS painstakingly managed by the US.展开更多
As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from bo...As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.展开更多
Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus t...Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.展开更多
This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the at...This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.展开更多
At present, with the continuous development of technologies such as the Internet, big data, and artificial intelligence, smart campuses in universities are being rapidly constructed. Improving the informatization leve...At present, with the continuous development of technologies such as the Internet, big data, and artificial intelligence, smart campuses in universities are being rapidly constructed. Improving the informatization level of administrative management work is also an important content. The collaborative office work in multiple departments requires more standardized, convenient, intelligent, and secure office systems. In response to this issue, this article analyzes the optimization and construction process of collaborative office systems based on the development of university informatization, summarizes the operational results, and explores the prospects of smart office.展开更多
This paper aims to analyze the present conditions of the social responsibility ecosystem in online audiovisual enterprises in the digital age. It focuses on the governance of social responsibility in these enterprises...This paper aims to analyze the present conditions of the social responsibility ecosystem in online audiovisual enterprises in the digital age. It focuses on the governance of social responsibility in these enterprises and conducts an in-depth analysis of the problems and influencing factors related to the social responsibility aberrations of online audiovisual enterprises. Drawing upon social responsibility theory and collaborative governance theory, this research constructs a social responsibility guidance and governance system guided by the public, supported by the voluntary fulfillment of responsibilities by online audiovisual enterprises, and based on the collaborative participation of diverse stakeholders. It explores and optimizes the implementation pathways of this system, providing theoretical support and practical guidance for promoting the sustainable development of online audiovisual enterprises. Furthermore, it aims to contribute to the creation of a harmonious Internet ecosystem.展开更多
A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer prefe...A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer preferences.Nowadays,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’preferences.On the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested items.However,the cost of these computations increases nonlinearly as the number of items and users increases.To triumph over the issues,a novel expanded stacked autoencoder(ESAE)with Kernel Fuzzy C-Means Clustering(KFCM)technique is proposed with two phases.In the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the ESAE approach and users are clustered using the KFCM approach.In the next phase of online,the top-N recommendation prediction is made by the ESAE approach involving only the most similar user from multiple clusters.Hence the ESAE_KFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation time.An experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the ESAE_KFCM model constantly outperforms conventional RS algorithms on a variety of assessment measures.展开更多
The collaboration of medical care,parenting,and education aims to integrate nursing,midwifery,infant and child care services,and management with speech and hearing rehabilitation technology,among other elements relate...The collaboration of medical care,parenting,and education aims to integrate nursing,midwifery,infant and child care services,and management with speech and hearing rehabilitation technology,among other elements related to the infant care industry chain.This integration targets pediatrics talent training in nine infant care positions,including nursing,infant health care and management,and child rehabilitation,to ensure that the capabilities and quality of professional talents can meet the health care needs of infants and young children.This article briefly explains the background of the“collaboration of medical care,parenting,and education,and integration of industry and education.”It analyzes the necessity of cultivating infant and child care service talents based on the perspective of“collaboration of medical care,parenting,and education,and integration of industry and education.”Based on this perspective,we conducted an in-depth study of the cultivation of professional qualities of infant and child care service talents.展开更多
Under the background of“co-construction,co-governance,and sharing,”the role of the grassroots level is becoming increasingly important.In the past,the governance body was single with blocked information,and the inef...Under the background of“co-construction,co-governance,and sharing,”the role of the grassroots level is becoming increasingly important.In the past,the governance body was single with blocked information,and the inefficient governance mode required gradual transformation.In order to achieve collaborative governance and break through the obstacles in grassroots governance,the key lies in how to play the role of the community,coordinate the relationship between citizens and the community,and allow the community to better play the role of grassroots governance.Under the guidance of the concept of collaborative governance and combined with relevant data,this paper discusses the problems and current situation of community governance in Daqing City,China,explores the path to improve the efficiency of urban community governance,and puts forward relevant constructive suggestions to better realize the role of community in grassroots governance.展开更多
基金This work is supported by the National Key Research and Development Program(No.2022YFB2702101)Shaanxi Key Industrial Province Projects(2021ZDLGY03-02,2021ZDLGY03-08)the National Natural Science Foundation of China under Grants 62272394 and 92152301.
文摘The proliferation of Internet of Things(IoT)systems has resulted in the generation of substantial data,presenting new challenges in reliable storage and trustworthy sharing.Conventional distributed storage systems are hindered by centralized management and lack traceability,while blockchain systems are limited by low capacity and high latency.To address these challenges,the present study investigates the reliable storage and trustworthy sharing of IoT data,and presents a novel system architecture that integrates on-chain and off-chain data manage systems.This architecture,integrating blockchain and distributed storage technologies,provides high-capacity,high-performance,traceable,and verifiable data storage and access.The on-chain system,built on Hyperledger Fabric,manages metadata,verification data,and permission information of the raw data.The off-chain system,implemented using IPFS Cluster,ensures the reliable storage and efficient access to massive files.A collaborative storage server is designed to integrate on-chain and off-chain operation interfaces,facilitating comprehensive data operations.We provide a unified access interface for user-friendly system interaction.Extensive testing validates the system’s reliability and stable performance.The proposed approach significantly enhances storage capacity compared to standalone blockchain systems.Rigorous reliability tests consistently yield positive outcomes.With average upload and download throughputs of roughly 20 and 30 MB/s,respectively,the system’s throughput surpasses the blockchain system by a factor of 4 to 18.
文摘Purpose:The aim of this study is to analyze the evolution of international research collaboration from 1980 to 2021.The study examines the main global patterns as well as those specific to individual countries,country groups,and different areas of research.Design/methodology/approach:The study is based on the Web of Science Core collection database.More than 50 million publications are analyzed using co-authorship data.International collaboration is defined as publications having authors affiliated with institutions located in more than one country.Findings:At the global level,the share of publications representing international collaboration has gradually increased from 4.7%in 1980 to 25.7%in 2021.The proportion of such publications within each country is higher and,in 2021,varied from less than 30%to more than 90%.There are notable disparities in the temporal trends,indicating that the process of internationalization has impacted countries in different ways.Several factors such as country size,income level,and geopolitics may explain the variance.Research limitations:Not all international research collaboration results in joint co-authored scientific publications.International co-authorship is a partial indicator of such collaboration.Another limitation is that the applied full counting method does not take into account the number of authors representing in each country in the publication.Practical implications:The study provides global averages,indicators,and concepts that can provide a useful framework of reference for further comparative studies of international research collaboration.Originality/value:Long-term macro-level studies of international collaboration are rare,and as a novelty,this study includes an analysis by the World Bank’s division of countries into four income groups.
文摘In Thailand, the alteration of weather patterns has resulted in an increase in instances of irregular rainfall, contributing to the occurrence of droughts. The decline of water levels in dams, due to the combined effects of climate change and prolonged droughts, has had a significant impact on agricultural productivity. Drought has a profound effect on the terrestrial biosphere and the atmospheric water cycle and can also contribute to air pollution. Researchers have found a strong correlation between air pollution and drought severity. In response to this pressing issue, the Excellence Center of Space Technology and Research (ECSTAR) at King Mongkut’s Institute of Technology Ladkrabang has joined forces with TeroSpace company to launch an initiative aimed at promoting sustainable growth in Chiang Rai, a province in Thailand known for its rich biodiversity. ECSTAR and TeroSpace’s partnership on the sustainable growth initiative in Thailand’s Chiang Rai province focuses on expanding their collaboration to include international organizations such as the Centre National d’Etudes Spatiales (CNES), which will provide access to satellite imagery and climate and weather information to improve decision-making in various areas of development. CNES is a French organization in charge of space-related activities in France. The collaboration between France and Thailand for this project, in the context of the France-Thailand Year of Innovation 2023, will be crucial for the successful initiation and execution of this research project. The project aims to explore the relationship between air pollution and climate change through the deployment of air quality monitoring devices in designated locations, connected to a global data-sharing network. The results of this research will be valuable to policymakers as they consider the interplay between air pollution and climate change and make efforts to address these challenges.
基金supported in part by the National Natural Science Foundation of China(62293514,52275020,and 91948301)。
文摘Human–robot(HR)collaboration(HRC)is an emerging research field because of the complementary advantages of humans and robots.An HRC framework for robotic assembly based on impedance control is proposed in this paper.In the HRC framework,the human is the decision maker,the robot acts as the executor,while the assembly environment provides constraints.The robot is the main executor to perform the assembly action,which has the position control,drag and drop,positive impedance control,and negative impedance control modes.To reveal the characteristics of the HRC framework,the switch condition map of different control modes and the stability analysis of the HR coupled system are discussed.In the end,HRC assembly experiments are conducted,where the HRC assembly task can be accomplished when the assembling tolerance is 0.08 mm or with the interference fit.Experiments show that the HRC assembly has the complementary advantages of humans and robots and is efficient in finishing complex assembly tasks.
基金Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by Korea government Ministry of Science,ICT(MSIT)(No.2019-0-01343,convergence security core talent training business)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT).(NRF-2020R1A4A1019191).
文摘Over the last several years,remote collaboration has been getting more attention in the research community because of the COVID-19 pandemic.In previous studies,researchers have investigated the effect of adding visual communication cues or shared views in collaboration,but there has not been any previous study exploring the influence between them.In this paper,we investigate the influence of view types on the use of visual communication cues.We compared the use of the three visual cues(hand gesture,a pointer with hand gesture,and sketches with hand gesture)across two view types(dependent and independent views),respectively.We conducted a user study,and the results showed that hand gesture and sketches with the hand gesture cueswerewell matchedwith the dependent viewcondition,and using a pointer with the hand gesture cue was suited to the independent view condition.With the dependent view,the hand gesture and sketch cues required less mental effort for collaborative communication,had better usability,provided better message understanding,and increased feeling of co-presence compared to the independent view.Since the dependent view supported the same viewpoint between the remote expert and a local worker,the local worker could easily understand the remote expert’s hand gestures.In contrast,in the independent view case,when they had different viewpoints,it was not easy for the local worker to understand the remote expert’s hand gestures.The sketch cue had a benefit of showing the final position and orientation of the manipulating objects with the dependent view,but this benefit was less obvious in the independent view case(which provided a further view compared to the dependent view)because precise drawing in the sketches was difficult from a distance.On the contrary,a pointer with the hand gesture cue required less mental effort to collaborate,had better usability,provided better message understanding,and an increased feeling of co-presence in the independent view condition than in the dependent view condition.The pointer cue could be used instead of a hand gesture in the independent view condition because the pointer could still show precise pointing information regardless of the view type.
基金supported by Key-Area Research and Development Program of Guangdong Province(2021B0101420002)the Major Key Project of PCL(PCL2021A09)+3 种基金National Natural Science Foundation of China(62072187)Guangdong Major Project of Basic and Applied Basic Research(2019B030302002)Guangdong Marine Economic Development Special Fund Project(GDNRC[2022]17)Guangzhou Development Zone Science and Technology(2021GH10,2020GH10).
文摘Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intelligent services to mobile users.However,as the accuracy requirements continue to increase,the components of deep learning models for pedestrian and vehicle detection,such as YOLOv4,become more sophisticated and the computing resources required for model training are increasing dramatically,which in turn leads to significant challenges in achieving effective deployment on resource-constrained edge devices while ensuring the high accuracy performance.For addressing this challenge,a cloud-edge collaboration-based pedestrian and vehicle detection framework is proposed in this paper,which enables sufficient training of models by utilizing the abundant computing resources in the cloud,and then deploying the well-trained models on edge devices,thus reducing the computing resource requirements for model training on edge devices.Furthermore,to reduce the size of the model deployed on edge devices,an automatic pruning method combines the convolution layer and BN layer is proposed to compress the pedestrian and vehicle detection model size.Experimental results show that the framework proposed in this paper is able to deploy the pruned model on a real edge device,Jetson TX2,with 6.72 times higher FPS.Meanwhile,the channel pruning reduces the volume and the number of parameters to 96.77%for the model,and the computing amount is reduced to 81.37%.
基金financially supported by the National Natural Science Foundation of China(No.52102470)。
文摘Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accurate estimation and prediction of battery health conditions are crucial for battery safety management.In this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven model.Based on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate results.The double exponential decay model is utilized as an empirical model to output highly real-time prediction results.With Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time results.Subsequently,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μs.The proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network.
基金supported by the Special Research Project on Power Planning of the Guangdong Power Grid Co.,Ltd.
文摘To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitment,source-network load collaboration,and control of the load demand response.After the constraint functions are linearized,the original problem is decomposed into the main problem and subproblem as a matrix using the strong dual method.The minimum-maximum of the original problem was continuously maximized using the iterative method,and the optimal solution was finally obtained.The constraint conditions expressed by the matrix may reduce the calculation time,and the upper and lower boundaries of the original problem may rapidly converge.The results of the example show that the injected nodes of the wind farms in the power grid should be selected appropriately;otherwise,it is easy to cause excessive accommodation of wind power at some nodes,leading to a surge in reserve costs and the load demand response is continuously optimized to reduce the inverse peak regulation characteristics of wind power.Thus,the most economical optimization scheme for the worst scenario of the output power of the generators is obtained,which proves the economy and reliability of the two-stage robust optimization method.
基金supported by the National Natural Science Foundation of China under Grant 52077146.
文摘With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.
文摘China’s Daya Bay collaboration and the RENO collaboration of South Korea were jointly awarded the 2023 High Energy and Particle Physics Prize of the European Physical Society(EPS)at a ceremony in Hamburg,Germany on August 21.Prof.WANG Yifang,initiator of the experiment in China and current director of the Institute of High Energy Physics(IHEP)of the Chinese Academy of Sciences(CAS),accepted the award on behalf of the Daya Bay collaboration.
基金supported by the National Natural Science Foundation of China(No.61903023)the Natural Science Foundation of Bejing Municipality(No.4204110)+1 种基金State Key Laboratory of Rail Traffic Control and Safety(No.RCS2020ZT006,RCS2021ZT006)the Fundamental Research Funds for the Central Universities(No.2020JBM087).
文摘Response speed is vital for the railway environment monitoring system,especially for the sudden-onset disasters.The edge-cloud collaboration scheme is proved efficient to reduce the latency.However,the data characteristics and communication demand of the tasks in the railway environment monitoring system are all different and changeable,and the latency contribution of each task to the system is discrepant.Hence,two valid latency minimization strategies based on the edge-cloud collaboration scheme is developed in this paper.First,the processing resources are allocated to the tasks based on the priorities,and the tasks are processed parallly with the allocated resources to minimize the system valid latency.Furthermore,considering the differences in the data volume of the tasks,which will induce the waste of the resources for the tasks finished in advance.Thus,the tasks with similar priorities are graded into the same group,and the serial and parallel processing strategies are performed intra-group and inter-group simultaneously.Compared with the other four strategies in four railway monitoring scenarios,the proposed strategies proved latency efficiency to the high-priority tasks,and the system valid latency is reduced synchronously.The performance of the railway environment monitoring system in security and efficiency will be promoted greatly with the proposed scheme and strategies.
文摘Europe as an important part of the US-led global strategic alliance has been a target for US attempt to include in its strategy as a counterweight against China in the context of intensifying ChinaUS competition and the prolonged Russia-Ukraine conflict,so as to form the US global strategic collaboration architecture to contain China through the echoing of the US-European strategic collaboration with the QUAD and the AUKUS painstakingly managed by the US.
基金National Natural Science Foundation of China(Grant No.62101138)Shandong Natural Science Foundation(Grant No.ZR2021QD148)+1 种基金Guangdong Natural Science Foundation(Grant No.2022A1515012573)Guangzhou Basic and Applied Basic Research Project(Grant No.202102020701)for providing funds for publishing this paper。
文摘As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.
基金supported in part by the National Key R&D Program of China under Grant 2020YFB1005900the National Natural Science Foundation of China under Grant 62001220+3 种基金the Jiangsu Provincial Key Research and Development Program under Grants BE2022068the Natural Science Foundation of Jiangsu Province under Grants BK20200440the Future Network Scientific Research Fund Project FNSRFP-2021-YB-03the Young Elite Scientist Sponsorship Program,China Association for Science and Technology.
文摘Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.
基金the National Natural Science Foundation of China(Grant No.42174047 and No.42174036)the National Science Foundation Project for Outstanding Youth(No.42104034).
文摘This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.
文摘At present, with the continuous development of technologies such as the Internet, big data, and artificial intelligence, smart campuses in universities are being rapidly constructed. Improving the informatization level of administrative management work is also an important content. The collaborative office work in multiple departments requires more standardized, convenient, intelligent, and secure office systems. In response to this issue, this article analyzes the optimization and construction process of collaborative office systems based on the development of university informatization, summarizes the operational results, and explores the prospects of smart office.
文摘This paper aims to analyze the present conditions of the social responsibility ecosystem in online audiovisual enterprises in the digital age. It focuses on the governance of social responsibility in these enterprises and conducts an in-depth analysis of the problems and influencing factors related to the social responsibility aberrations of online audiovisual enterprises. Drawing upon social responsibility theory and collaborative governance theory, this research constructs a social responsibility guidance and governance system guided by the public, supported by the voluntary fulfillment of responsibilities by online audiovisual enterprises, and based on the collaborative participation of diverse stakeholders. It explores and optimizes the implementation pathways of this system, providing theoretical support and practical guidance for promoting the sustainable development of online audiovisual enterprises. Furthermore, it aims to contribute to the creation of a harmonious Internet ecosystem.
文摘A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer preferences.Nowadays,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’preferences.On the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested items.However,the cost of these computations increases nonlinearly as the number of items and users increases.To triumph over the issues,a novel expanded stacked autoencoder(ESAE)with Kernel Fuzzy C-Means Clustering(KFCM)technique is proposed with two phases.In the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the ESAE approach and users are clustered using the KFCM approach.In the next phase of online,the top-N recommendation prediction is made by the ESAE approach involving only the most similar user from multiple clusters.Hence the ESAE_KFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation time.An experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the ESAE_KFCM model constantly outperforms conventional RS algorithms on a variety of assessment measures.
文摘The collaboration of medical care,parenting,and education aims to integrate nursing,midwifery,infant and child care services,and management with speech and hearing rehabilitation technology,among other elements related to the infant care industry chain.This integration targets pediatrics talent training in nine infant care positions,including nursing,infant health care and management,and child rehabilitation,to ensure that the capabilities and quality of professional talents can meet the health care needs of infants and young children.This article briefly explains the background of the“collaboration of medical care,parenting,and education,and integration of industry and education.”It analyzes the necessity of cultivating infant and child care service talents based on the perspective of“collaboration of medical care,parenting,and education,and integration of industry and education.”Based on this perspective,we conducted an in-depth study of the cultivation of professional qualities of infant and child care service talents.
文摘Under the background of“co-construction,co-governance,and sharing,”the role of the grassroots level is becoming increasingly important.In the past,the governance body was single with blocked information,and the inefficient governance mode required gradual transformation.In order to achieve collaborative governance and break through the obstacles in grassroots governance,the key lies in how to play the role of the community,coordinate the relationship between citizens and the community,and allow the community to better play the role of grassroots governance.Under the guidance of the concept of collaborative governance and combined with relevant data,this paper discusses the problems and current situation of community governance in Daqing City,China,explores the path to improve the efficiency of urban community governance,and puts forward relevant constructive suggestions to better realize the role of community in grassroots governance.
