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
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
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
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
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
In today’s society,the need for talent training is of utmost importance due to rapid development.To achieve high-quality talent training,we need to focus on building a collaborative education mechanism.Practical teac...In today’s society,the need for talent training is of utmost importance due to rapid development.To achieve high-quality talent training,we need to focus on building a collaborative education mechanism.Practical teaching and the second classroom,which serve as important carriers of educational talents,must align their educational goals and complement each other.This article explores the collaborative education mechanism of the second classroom and practical teaching for the ideological and political courses in colleges and universities.It proposes reasonable construction measures to provide some guidelines for teaching work.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
Flexible adaptation to differentiated quality of service(QoS)is quite important for future 6G network with a variety of services.Mobile ad hoc networks(MANETs)are able to provide flexible communication services to use...Flexible adaptation to differentiated quality of service(QoS)is quite important for future 6G network with a variety of services.Mobile ad hoc networks(MANETs)are able to provide flexible communication services to users through self-configuration and rapid deployment.However,the dynamic wireless environment,the limited resources,and complex QoS requirements have presented great challenges for network routing problems.Motivated by the development of artificial intelligence,a deep reinforcement learning-based collaborative routing(DRLCR)algorithm is proposed.Both routing policy and subchannel allocation are considered jointly,aiming at minimizing the end-to-end(E2E)delay and improving the network capacity.After sufficient training by the cluster head node,the Q-network can be synchronized to each member node to select the next hop based on local observation.Moreover,we improve the performance of training by considering historical observations,which can improve the adaptability of routing policies to dynamic environments.Simulation results show that the proposed DRLCR algorithm outperforms other algorithms in terms of resource utilization and E2E delay by optimizing network load to avoid congestion.In addition,the effectiveness of the routing policy in a dynamic environment is verified.展开更多
As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve credibility.Due to the decentralized and trustless natu...As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve credibility.Due to the decentralized and trustless nature of blockchain,the security defense of the blockchain system has become one of the most important measures.This paper comprehensively reviews the research progress of blockchain security threats and collaborative defense,and we first introduce the overview,classification,and threat assessment process of blockchain security threats.Then,we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize the blockchain security evaluation indicators and evaluation methods.Finally,we discuss the challenges of blockchain security and future research directions,such as parallel detection and federated learning.This paper aims to stimulate further research and discussion on blockchain security,providing more reliable security guarantees for the use and development of blockchain technology to face changing threats and challenges through continuous updating and improvement of defense technologies.展开更多
Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep lear...Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep learning approaches for capturing user and product information from a short text.However,such previously used approaches do not fairly and efficiently incorporate users’preferences and product characteristics.The proposed novel Hybrid Deep Collaborative Filtering(HDCF)model combines deep learning capabilities and deep interaction modeling with high performance for True Recommendations.To overcome the cold start problem,the new overall rating is generated by aggregating the Deep Multivariate Rating DMR(Votes,Likes,Stars,and Sentiment scores of reviews)from different external data sources because different sites have different rating scores about the same product that make confusion for the user to make a decision,either product is truly popular or not.The proposed novel HDCF model consists of four major modules such as User Product Attention,Deep Collaborative Filtering,Neural Sentiment Classifier,and Deep Multivariate Rating(UPA-DCF+NSC+DMR)to solve the addressed problems.Experimental results demonstrate that our novel model is outperforming state-of-the-art IMDb,Yelp2013,and Yelp2014 datasets for the true top-n recommendation of products using HDCF to increase the accuracy,confidence,and trust of recommendation services.展开更多
Job shop scheduling(JS)is an important technology for modern manufacturing.Flexible job shop scheduling(FJS)is critical in JS,and it has been widely employed in many industries,including aerospace and energy.FJS enabl...Job shop scheduling(JS)is an important technology for modern manufacturing.Flexible job shop scheduling(FJS)is critical in JS,and it has been widely employed in many industries,including aerospace and energy.FJS enables any machine from a certain set to handle an operation,and this is an NP-hard problem.Furthermore,due to the requirements in real-world cases,multi-objective FJS is increasingly widespread,thus increasing the challenge of solving the FJS problems.As a result,it is necessary to develop a novel method to address this challenge.To achieve this goal,a novel collaborative evolutionary algorithmwith two-population based on Pareto optimality is proposed for FJS,which improves the solutions of FJS by interacting in each generation.In addition,several experimental results have demonstrated that the proposed method is promising and effective for multi-objective FJS,which has discovered some new Pareto solutions in the well-known benchmark problems,and some solutions can dominate the solutions of some other methods.展开更多
Objective Contact precautions,especially the initiation of isolation,are important measures to prevent and control multidrug-resistant organisms(MDROs).However,the implementation in clinical practice remains weak.This...Objective Contact precautions,especially the initiation of isolation,are important measures to prevent and control multidrug-resistant organisms(MDROs).However,the implementation in clinical practice remains weak.This study aimed to analyze the impact of multidisciplinary collaborative intervention on isolation implementation in multidrug-resistant infection,and determine the factors that affect the implementation of isolation measures.Methods A multidisciplinary collaborative intervention related to isolation was conducted at a teaching tertiary hospital in central China on November 1,2018.The information of 1338 patients with MDRO infection and colonization at 10 months before and after the intervention was collected.Then,the issuance of isolation orders was retrospectively analyzed.Univariate analysis and multivariate logistic regression analysis were performed to analyze the factors that affected the isolation implementation.Results The overall issuance rate of isolation orders was 61.21%,which increased from 33.12%to 75.88%(P<0.001)after the implementation of the multidisciplinary collaborative intervention.The intervention(P<0.001,OR=0.166)was a promoting factor for the issuance of isolation orders,in addition to the length of stay(P=0.004,OR=0.991),department(P=0.004),and microorganism(P=0.038).Conclusion The isolation implementation remains far lower than policy standards.Multidisciplinary collaborative interventions can effectively improve the compliance to isolation measures implemented by doctors,thereby promoting the standardized management of MDROs,and providing reference for further improving the quality of hospital infection management.展开更多
BACKGROUND Perioperative nursing can reduce the stress reaction and improve the prognosis of children.AIM To elucidate the influence of multidisciplinary collaborative nursing for enhanced recovery after surgery(ERAS)...BACKGROUND Perioperative nursing can reduce the stress reaction and improve the prognosis of children.AIM To elucidate the influence of multidisciplinary collaborative nursing for enhanced recovery after surgery(ERAS)with family care in perioperative nursing children with an inguinal hernia and its impact on the prognosis.METHODS The data of 100 children with inguinal hernia were retrospectively analyzed.The participants were divided into three groups according to different nursing methods:Groups A(n=38),B(n=32),and C(n=30).Group A received multidisciplinary collaborative ERAS nursing combined with family care nursing;Group B received multidisciplinary collaborative nursing for ERAS;and Group C received routine nursing.The postoperative recovery results of the three groups were compared,including intraoperative blood loss and postoperative feeding time,time of getting out of bed,hospitalization time,and defecation time.Furthermore,the incidence of common complications was also compared between the three groups.RESULTS There was less intraoperative blood loss in Groups A and B than in Group C(P<0.05),and the time of getting out of bed and postoperative hospitalization and defecation times were also decreased in Group C(P<0.05).There was no significant difference in postoperative feeding time among the three groups(P>0.05).Each index had no statistical significance between Groups A and B(P>0.05).The incidence of urinary retention,infection,hematoma,and hernia recurrence in Group A was less than that in Group C(P<0.05).No significant difference was observed in the overall complication rate between Groups A and B and between Groups B and C(P>0.05).CONCLUSION The application of multidisciplinary collaborative nursing combined with family care in the perioperative care of children with an inguinal hernia for ERAS may promote postoperative rehabilitation for children and reduce the incidence of complications.展开更多
Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspe...Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.展开更多
As a resource development model with both economic and ecological functions,the environmental friendliness of marine ranching products meets the environmental needs of consumers.However,the lack of technological innov...As a resource development model with both economic and ecological functions,the environmental friendliness of marine ranching products meets the environmental needs of consumers.However,the lack of technological innovation ability limits the development of marine ranching.Therefore,this research builds a marine ranching collaborative innovation system with multi-agent participation.Evolutionary game theory is used to analyze strategic choices of all parties and the conditions of system equilibrium,and numerical simulation is used to analyze the effect of relevant factors.This paper integrates the benefits from the improvement of environmental friendliness into the payoff matrix,and explains the significance of collaborative innovation to the development of marine ranching from the perspective of ecological environment.The results showed:the participation willingness of marine ranching enterprises is positively related to open innovation subject,while the participation willingness of the other two parties is negatively related to the government;The incentive effect of collaboration is negatively correlated with the government’s will,positively correlated with the other two parties;The incentive effect of government subsidies positively affects the willingness of the three parties to participate.Finally,suggestions are provided for each participant to maintain the strategic choice of marine ranching collaborative innovation system.展开更多
Wireless sensor networks(WSN)are widely used in many situations,but the disordered and random deployment mode will waste a lot of sensor resources.This paper proposes a multi-topology hierarchical collaborative partic...Wireless sensor networks(WSN)are widely used in many situations,but the disordered and random deployment mode will waste a lot of sensor resources.This paper proposes a multi-topology hierarchical collaborative particle swarm optimization(MHCHPSO)to optimize sensor deployment location and improve the coverage of WSN.MHCHPSO divides the population into three types topology:diversity topology for global exploration,fast convergence topology for local development,and collaboration topology for exploration and development.All topologies are optimized in parallel to overcome the precocious convergence of PSO.This paper compares with various heuristic algorithms at CEC 2013,CEC 2015,and CEC 2017.The experimental results show that MHCHPSO outperforms the comparison algorithms.In addition,MHCHPSO is applied to the WSN localization optimization,and the experimental results confirm the optimization ability of MHCHPSO in practical engineering problems.展开更多
Background:Bone microarchitecture is affected by multiple genes,each having a small effect on the external appearance.It is thus challenging to characterize the genes and their specific effect on bone thickness and po...Background:Bone microarchitecture is affected by multiple genes,each having a small effect on the external appearance.It is thus challenging to characterize the genes and their specific effect on bone thickness and porosity.The purpose of this study was to assess the heritability and the genetic variation effect,as well as the sex effect on the calvarial bone thickness(Ca.Th)and calvarial porosity(%PoV)using the Collaborative Cross(CC)mouse population.Methods:In the study we examined the parietal bones of 56 mice from 9 lines of CC mice.Morphometric parameters were evaluated using microcomputed tomography(μCT)and included Ca.Th and%PoV.We then evaluated heritability,genetic versus environmental variance and the sex effect for these parameters.Results:Our morphometric analysis showed that Ca.Th and%PoV are both significantly different among the CC lines with a broad sense heritability of 0.78 and 0.90,respectively.The sex effect within the lines was significant in line IL111 and showed higher values of Ca.Th and%PoV in females compared to males.In line IL19 there was a borderline sex effect in Ca.Th in which males showed higher values than females.Conclusions:These results stress the complexity of sex and genotype interactions controlling Ca.Th and%PoV,as the skeletal sexual dimorphism was dependent on the genetic background.This study also shows that the CC population is a powerful tool for establishing the genetic effect on these traits.展开更多
Navigation is an essential skill for robots.It becomes a cumbersome task for the robot in a human-populated environment,and Industry 5.0 is an emerging trend that focuses on the interaction between humans and robots.R...Navigation is an essential skill for robots.It becomes a cumbersome task for the robot in a human-populated environment,and Industry 5.0 is an emerging trend that focuses on the interaction between humans and robots.Robot behavior in a social setting is the key to human acceptance while ensuring human comfort and safety.With the advancement in robotics technology,the true use cases of robots in the tourism and hospitality industry are expanding in number.There are very few experimental studies focusing on how people perceive the navigation behavior of a delivery robot.A robotic platform named“PI”has been designed,which incorporates proximity and vision sensors.The robot utilizes a real-time object recognition algorithm based on the You Only Look Once(YOLO)algorithm to detect objects and humans during navigation.This study is aimed towards evaluating human experience,for which we conducted a study among 36 participants to explore the perceived social presence,role,and perception of a delivery robot exhibiting different behavior conditions while navigating in a hotel corridor.The participants’responses were collected and compared for different behavior conditions demonstrated by the robot and results show that humans prefer an assistant role of a robot enabled with audio and visual aids exhibiting social behavior.Further,this study can be useful for developers to gain insight into the expected behavior of a delivery robot.展开更多
With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matchi...With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.展开更多
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.
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.
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In today’s society,the need for talent training is of utmost importance due to rapid development.To achieve high-quality talent training,we need to focus on building a collaborative education mechanism.Practical teaching and the second classroom,which serve as important carriers of educational talents,must align their educational goals and complement each other.This article explores the collaborative education mechanism of the second classroom and practical teaching for the ideological and political courses in colleges and universities.It proposes reasonable construction measures to provide some guidelines for teaching work.
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.
基金supported by the 2020 National Key R&D Program"Broadband Communication and New Network"special"6G Network Architecture and Key Technologies"(2020YFB1806700)。
文摘Flexible adaptation to differentiated quality of service(QoS)is quite important for future 6G network with a variety of services.Mobile ad hoc networks(MANETs)are able to provide flexible communication services to users through self-configuration and rapid deployment.However,the dynamic wireless environment,the limited resources,and complex QoS requirements have presented great challenges for network routing problems.Motivated by the development of artificial intelligence,a deep reinforcement learning-based collaborative routing(DRLCR)algorithm is proposed.Both routing policy and subchannel allocation are considered jointly,aiming at minimizing the end-to-end(E2E)delay and improving the network capacity.After sufficient training by the cluster head node,the Q-network can be synchronized to each member node to select the next hop based on local observation.Moreover,we improve the performance of training by considering historical observations,which can improve the adaptability of routing policies to dynamic environments.Simulation results show that the proposed DRLCR algorithm outperforms other algorithms in terms of resource utilization and E2E delay by optimizing network load to avoid congestion.In addition,the effectiveness of the routing policy in a dynamic environment is verified.
基金supported by National Natural Science Foundation of China(Grant Nos.62162022 and 62162024)Young Talents’Science and Technology Innovation Project of Hainan Association for Science and Technology(Grant No.QCXM202007)Hainan Provincial Natural Science Foundation of China(Grant Nos.2019RC098 and 621RC612).
文摘As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve credibility.Due to the decentralized and trustless nature of blockchain,the security defense of the blockchain system has become one of the most important measures.This paper comprehensively reviews the research progress of blockchain security threats and collaborative defense,and we first introduce the overview,classification,and threat assessment process of blockchain security threats.Then,we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize the blockchain security evaluation indicators and evaluation methods.Finally,we discuss the challenges of blockchain security and future research directions,such as parallel detection and federated learning.This paper aims to stimulate further research and discussion on blockchain security,providing more reliable security guarantees for the use and development of blockchain technology to face changing threats and challenges through continuous updating and improvement of defense technologies.
文摘Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep learning approaches for capturing user and product information from a short text.However,such previously used approaches do not fairly and efficiently incorporate users’preferences and product characteristics.The proposed novel Hybrid Deep Collaborative Filtering(HDCF)model combines deep learning capabilities and deep interaction modeling with high performance for True Recommendations.To overcome the cold start problem,the new overall rating is generated by aggregating the Deep Multivariate Rating DMR(Votes,Likes,Stars,and Sentiment scores of reviews)from different external data sources because different sites have different rating scores about the same product that make confusion for the user to make a decision,either product is truly popular or not.The proposed novel HDCF model consists of four major modules such as User Product Attention,Deep Collaborative Filtering,Neural Sentiment Classifier,and Deep Multivariate Rating(UPA-DCF+NSC+DMR)to solve the addressed problems.Experimental results demonstrate that our novel model is outperforming state-of-the-art IMDb,Yelp2013,and Yelp2014 datasets for the true top-n recommendation of products using HDCF to increase the accuracy,confidence,and trust of recommendation services.
基金This research work is the Key R&D Program of Hubei Province under Grant No.2021AAB001National Natural Science Foundation of China under Grant No.U21B2029。
文摘Job shop scheduling(JS)is an important technology for modern manufacturing.Flexible job shop scheduling(FJS)is critical in JS,and it has been widely employed in many industries,including aerospace and energy.FJS enables any machine from a certain set to handle an operation,and this is an NP-hard problem.Furthermore,due to the requirements in real-world cases,multi-objective FJS is increasingly widespread,thus increasing the challenge of solving the FJS problems.As a result,it is necessary to develop a novel method to address this challenge.To achieve this goal,a novel collaborative evolutionary algorithmwith two-population based on Pareto optimality is proposed for FJS,which improves the solutions of FJS by interacting in each generation.In addition,several experimental results have demonstrated that the proposed method is promising and effective for multi-objective FJS,which has discovered some new Pareto solutions in the well-known benchmark problems,and some solutions can dominate the solutions of some other methods.
基金supported by the National Natural Science Foundation of China(No.71473098).
文摘Objective Contact precautions,especially the initiation of isolation,are important measures to prevent and control multidrug-resistant organisms(MDROs).However,the implementation in clinical practice remains weak.This study aimed to analyze the impact of multidisciplinary collaborative intervention on isolation implementation in multidrug-resistant infection,and determine the factors that affect the implementation of isolation measures.Methods A multidisciplinary collaborative intervention related to isolation was conducted at a teaching tertiary hospital in central China on November 1,2018.The information of 1338 patients with MDRO infection and colonization at 10 months before and after the intervention was collected.Then,the issuance of isolation orders was retrospectively analyzed.Univariate analysis and multivariate logistic regression analysis were performed to analyze the factors that affected the isolation implementation.Results The overall issuance rate of isolation orders was 61.21%,which increased from 33.12%to 75.88%(P<0.001)after the implementation of the multidisciplinary collaborative intervention.The intervention(P<0.001,OR=0.166)was a promoting factor for the issuance of isolation orders,in addition to the length of stay(P=0.004,OR=0.991),department(P=0.004),and microorganism(P=0.038).Conclusion The isolation implementation remains far lower than policy standards.Multidisciplinary collaborative interventions can effectively improve the compliance to isolation measures implemented by doctors,thereby promoting the standardized management of MDROs,and providing reference for further improving the quality of hospital infection management.
文摘BACKGROUND Perioperative nursing can reduce the stress reaction and improve the prognosis of children.AIM To elucidate the influence of multidisciplinary collaborative nursing for enhanced recovery after surgery(ERAS)with family care in perioperative nursing children with an inguinal hernia and its impact on the prognosis.METHODS The data of 100 children with inguinal hernia were retrospectively analyzed.The participants were divided into three groups according to different nursing methods:Groups A(n=38),B(n=32),and C(n=30).Group A received multidisciplinary collaborative ERAS nursing combined with family care nursing;Group B received multidisciplinary collaborative nursing for ERAS;and Group C received routine nursing.The postoperative recovery results of the three groups were compared,including intraoperative blood loss and postoperative feeding time,time of getting out of bed,hospitalization time,and defecation time.Furthermore,the incidence of common complications was also compared between the three groups.RESULTS There was less intraoperative blood loss in Groups A and B than in Group C(P<0.05),and the time of getting out of bed and postoperative hospitalization and defecation times were also decreased in Group C(P<0.05).There was no significant difference in postoperative feeding time among the three groups(P>0.05).Each index had no statistical significance between Groups A and B(P>0.05).The incidence of urinary retention,infection,hematoma,and hernia recurrence in Group A was less than that in Group C(P<0.05).No significant difference was observed in the overall complication rate between Groups A and B and between Groups B and C(P>0.05).CONCLUSION The application of multidisciplinary collaborative nursing combined with family care in the perioperative care of children with an inguinal hernia for ERAS may promote postoperative rehabilitation for children and reduce the incidence of complications.
文摘Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.
基金supported by the National Natural Science Foundation of China(Nos.71901199 and 72273135)the Frontier Science Research Support Program,Management College,OUC(No.MCQYZD2302)+3 种基金the China Postdoctoral Science Foundation Funded Project(No.2019M660170)the Postdoctoral Innovation Project of Shandong Province(No.201902019)the Special Program for Rural Revitalization Research of OUC(No.ZX2022002)the‘Youth Innovation Team Program’Team in Colleges and Universities of Shandong Province(No.2022RW011).
文摘As a resource development model with both economic and ecological functions,the environmental friendliness of marine ranching products meets the environmental needs of consumers.However,the lack of technological innovation ability limits the development of marine ranching.Therefore,this research builds a marine ranching collaborative innovation system with multi-agent participation.Evolutionary game theory is used to analyze strategic choices of all parties and the conditions of system equilibrium,and numerical simulation is used to analyze the effect of relevant factors.This paper integrates the benefits from the improvement of environmental friendliness into the payoff matrix,and explains the significance of collaborative innovation to the development of marine ranching from the perspective of ecological environment.The results showed:the participation willingness of marine ranching enterprises is positively related to open innovation subject,while the participation willingness of the other two parties is negatively related to the government;The incentive effect of collaboration is negatively correlated with the government’s will,positively correlated with the other two parties;The incentive effect of government subsidies positively affects the willingness of the three parties to participate.Finally,suggestions are provided for each participant to maintain the strategic choice of marine ranching collaborative innovation system.
基金supported by the National Key Research and Development Program Projects of China(No.2018YFC1504705)the National Natural Science Foundation of China(No.61731015)+1 种基金the Major instrument special project of National Natural Science Foundation of China(No.42027806)the Key Research and Development Program of Shaanxi(No.2022GY-331)。
文摘Wireless sensor networks(WSN)are widely used in many situations,but the disordered and random deployment mode will waste a lot of sensor resources.This paper proposes a multi-topology hierarchical collaborative particle swarm optimization(MHCHPSO)to optimize sensor deployment location and improve the coverage of WSN.MHCHPSO divides the population into three types topology:diversity topology for global exploration,fast convergence topology for local development,and collaboration topology for exploration and development.All topologies are optimized in parallel to overcome the precocious convergence of PSO.This paper compares with various heuristic algorithms at CEC 2013,CEC 2015,and CEC 2017.The experimental results show that MHCHPSO outperforms the comparison algorithms.In addition,MHCHPSO is applied to the WSN localization optimization,and the experimental results confirm the optimization ability of MHCHPSO in practical engineering problems.
文摘Background:Bone microarchitecture is affected by multiple genes,each having a small effect on the external appearance.It is thus challenging to characterize the genes and their specific effect on bone thickness and porosity.The purpose of this study was to assess the heritability and the genetic variation effect,as well as the sex effect on the calvarial bone thickness(Ca.Th)and calvarial porosity(%PoV)using the Collaborative Cross(CC)mouse population.Methods:In the study we examined the parietal bones of 56 mice from 9 lines of CC mice.Morphometric parameters were evaluated using microcomputed tomography(μCT)and included Ca.Th and%PoV.We then evaluated heritability,genetic versus environmental variance and the sex effect for these parameters.Results:Our morphometric analysis showed that Ca.Th and%PoV are both significantly different among the CC lines with a broad sense heritability of 0.78 and 0.90,respectively.The sex effect within the lines was significant in line IL111 and showed higher values of Ca.Th and%PoV in females compared to males.In line IL19 there was a borderline sex effect in Ca.Th in which males showed higher values than females.Conclusions:These results stress the complexity of sex and genotype interactions controlling Ca.Th and%PoV,as the skeletal sexual dimorphism was dependent on the genetic background.This study also shows that the CC population is a powerful tool for establishing the genetic effect on these traits.
基金supported by Taif University Researchers Supporting Projects(TURSP).Under number(TURSP-2020/211),Taif University,Taif,Saudi Arabia.
文摘Navigation is an essential skill for robots.It becomes a cumbersome task for the robot in a human-populated environment,and Industry 5.0 is an emerging trend that focuses on the interaction between humans and robots.Robot behavior in a social setting is the key to human acceptance while ensuring human comfort and safety.With the advancement in robotics technology,the true use cases of robots in the tourism and hospitality industry are expanding in number.There are very few experimental studies focusing on how people perceive the navigation behavior of a delivery robot.A robotic platform named“PI”has been designed,which incorporates proximity and vision sensors.The robot utilizes a real-time object recognition algorithm based on the You Only Look Once(YOLO)algorithm to detect objects and humans during navigation.This study is aimed towards evaluating human experience,for which we conducted a study among 36 participants to explore the perceived social presence,role,and perception of a delivery robot exhibiting different behavior conditions while navigating in a hotel corridor.The participants’responses were collected and compared for different behavior conditions demonstrated by the robot and results show that humans prefer an assistant role of a robot enabled with audio and visual aids exhibiting social behavior.Further,this study can be useful for developers to gain insight into the expected behavior of a delivery robot.
文摘With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.
